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White House Report Lauds Extension of Tax Cuts, AMT Fix

MAR. 1, 2013

White House Report Lauds Extension of Tax Cuts, AMT Fix

DATED MAR. 1, 2013
DOCUMENT ATTRIBUTES
ECONOMIC REPORT OF THE PRESIDENT

 

TRANSMITTED TO THE CONGRESS

 

 

MARCH 2013

 

 

TOGETHER WITH

 

THE ANNUAL REPORT

 

OF THE

 

COUNCIL OF ECONOMIC ADVISERS

 

 

UNITED STATES GOVERNMENT PRINTING OFFICE

 

WASHINGTON: 2013

 

 

                               CONTENTS

 

 

 ECONOMIC REPORT OF THE PRESIDENT

 

 

 ANNUAL REPORT OF THE COUNCIL OF ECONOMIC ADVISERS*

 

 

 CHAPTER 1.     RECOVERING FROM THE PAST AND PREPARING FOR THE FUTURE

 

 

 CHAPTER 2.     THE YEAR IN REVIEW AND THE YEARS AHEAD

 

 

 CHAPTER 3.     FISCAL POLICY

 

 

 CHAPTER 4.     JOBS, WORKERS AND SKILLS

 

 

 CHAPTER 5.     REDUCING COSTS AND IMPROVING THE QUALITY OF HEALTH

 

                CARE

 

 

 CHAPTER 6.     CLIMATE CHANGE AND THE PATH TOWARD SUSTAINABLE ENERGY

 

                SOURCES

 

 

 CHAPTER 7.     INTERNATIONAL TRADE AND COMPETITIVENESS

 

 

 CHAPTER 8.     CHALLENGES AND OPPORTUNITIES IN U.S. AGRICULTURE

 

 

 REFERENCES

 

 

 APPENDIX A     REPORT TO THE PRESIDENT ON THE ACTIVITIES OF THE

 

                COUNCIL OF ECONOMIC ADVISERS DURING 2012

 

 

 APPENDIX B.    STATISTICAL TABLES RELATING TO INCOME, EMPLOYMENT, AND

 

                PRODUCTION

 

 

 * For a detailed table of contents of the Council's Report, see page

 

 11.

 

ECONOMIC REPORT OF THE PRESIDENT

 

 

To the Congress of the United States:

This year's Economic Report of the President describes the progress we have made recovering from the worst economic crisis since the Great Depression. After years of grueling recession, our businesses have created over six million new jobs. As a nation, we now buy more American cars than we have in 5 years, and less foreign oil than we have in 20 years. Our housing market is healing, and consumers, patients, and homeowners enjoy stronger protections than ever before.

But there are still millions of Americans whose hard work and dedication have not yet been rewarded. Our economy is adding jobs, but too many of our fellow citizens still can't find full-time employment. Corporate profits have reached all-time highs, but for more than a decade, wages and incomes for working Americans have barely budged.

Our top priority must be to do everything we can to grow our economy and create good, middle-class jobs. That has to be our North Star. That has to drive every decision we make in Washington. Every day, we should ask ourselves three questions: How do we attract more jobs to our shores? How do we equip our people with the skills needed to do those jobs? And how do we make sure that hard work leads to a decent living?

We can begin by making America a magnet for new jobs and manufacturing. After shedding jobs for more than a decade, our manufacturers have added about half a million new jobs over the past 3 years. We need to accelerate that trend, by launching more manufacturing hubs that transform hard-hit regions of the country into global centers of high-tech jobs and manufacturing. We need to make our tax code more competitive, by ending tax breaks for companies that ship jobs overseas, and rewarding companies that create jobs here at home. And we need to invest in the research and technology that will allow us to harness more of our own energy and put more people back to work repairing our crumbling roads and bridges.

These steps will help entrepreneurs and small business owners expand and create new jobs. But we also need to provide every American with the skills and training they need to fill those jobs. We should start in the earliest years by offering high-quality preschool to every child in America, because we know kids in programs like these do better throughout their academic lives. We should redesign America's high schools to better prepare our students with skills that employers are looking for right now. And because taxpayers can't continue subsidizing the soaring cost of higher education, we should take affordability and value into account when determining which colleges receive certain types of Federal aid.

We also need to reward hard work and declare that no one who works full-time should have to live in poverty by raising the minimum wage so that it's a wage you can live on. And it's time to harness the talents and ingenuity of hardworking immigrants by finally passing commonsense immigration reform -- continuing to strengthen border security, holding employers accountable, establishing a responsible path to earned citizenship, reuniting families, and attracting the highly-skilled entrepreneurs, engineers, and scientists that will help create jobs.

As we continue to grow our economy, we must also take further action to shrink our deficits. We don't have to choose between these two important priorities -- we just have to make smart choices.

Over the last few years, both parties have worked together to reduce the deficit by more than $2.5 trillion, which puts us more than halfway towards the goal of $4 trillion in deficit reduction that economists say we need to stabilize our finances. Now we need to finish the job. But we shouldn't do it by making harsh and arbitrary cuts that jeopardize our military readiness, devastate priorities like education and energy, and cost jobs. That's not how you grow the economy. We shouldn't ask senior citizens and working families to pay down the rest of our deficit while the wealthiest are asked for nothing more. That doesn't grow our middle class.

Most Americans -- Democrats, Republicans, and Independents -- understand that we can't just cut our way to prosperity. That's why I have put forward a balanced approach to deficit reduction that makes responsible reforms to bring down the cost of health care for an aging generation -- the single biggest driver of our long-term debt -- and saves hundreds of billions of dollars by getting rid of tax loopholes and deductions for the well-off and well-connected. And we should finally pursue bipartisan, comprehensive tax reform that encourages job creation and helps bring down the deficit.

The American people don't expect their government to solve every problem. They don't expect those of us in Washington to agree on every issue. But they do expect us to put the Nation's interests before party interests. They do expect us to forge reasonable compromise where we can. Our work will not be easy. But America only moves forward when we do so together -- when we accept certain obligations to one another and to future generations. That's the American story. And that's how we will write the next great chapter -- together.

 

THE WHITE HOUSE

 

MARCH 2013

 

 

THE ANNUAL REPORT

 

OF THE

 

COUNCIL OF ECONOMIC ADVISERS

 

 

LETTER OF TRANSMITTAL

 

 

Council of Economic Advisers

 

Washington, D.C., March 15, 2013

 

 

Mr. President:

The Council of Economic Advisers herewith submits its 2013 Annual Report in accordance of the Employment Act of 1946 as amended by the Full Employment and Balanced Growth Act of 1978.

Sincerely yours,

 

 

Alan B. Krueger

 

Chairman

 

 

Katharine G. Abraham

 

Member

 

 

James H. Stock

 

Member

 

                               CONTENTS

 

 

 CHAPTER 1. RECOVERING FROM THE PAST AND PREPARING FOR THE FUTURE

 

 

      TRACKING THE PROGRESS OF THE RECOVERY

 

 

           Placing the Recovery in Historical Context

 

 

           Making Progress Toward a Sustainable Fiscal Path

 

 

           BUILDING A STRONGER, FAIRER, MORE RESILIENT ECONOMY

 

 

           Strengthening the Foundations of Growth

 

 

           Ensuring Fairness for the Middle Class

 

 

           Making the Economy More Resilient to Future

 

           Challenges

 

 

      CONCLUSION

 

 

 CHAPTER 2. THE YEAR IN REVIEW AND THE YEARS AHEAD

 

 

      AN ECONOMY IN RECOVERY: KEY EVENTS OF 2012

 

 

           European Crisis and the Slowdown in Global Growth

 

 

           Hurricane Sandy and the Drought

 

 

           Monetary Policy

 

 

           Fiscal Policy

 

 

      DEVELOPMENTS IN 2012 AND THE NEAR-TERM OUTLOOK

 

 

           Labor Market Trends

 

 

           Consumption and Saving

 

 

           Business Fixed Investment

 

 

           Business Inventories

 

 

           Government Outlays, Consumption, and Investment

 

 

           State and Local Governments

 

 

           Real Exports and Imports

 

 

           Housing Markets

 

 

           Financial Markets

 

 

           Wage and Price Inflation

 

 

      THE RECOVERY IN HISTORICAL PERSPECTIVE

 

 

           Demographics, Productivity, and Long-Term

 

 

           Economic Growth

 

 

           Reasons for the Slower Cyclical Component

 

 

      OUTLOOK FOR 2013 AND BEYOND

 

 

      CONCLUSION

 

 

 CHAPTER 3. FISCAL POLICY

 

 

      THE FEDERAL BUDGET OUTLOOK

 

 

      FEDERAL INCOME TAX REFORM

 

 

           Tax Expenditures

 

 

           Vertical Equity

 

 

           Efficiency and Simplification

 

 

           Reforming the International Corporate Tax

 

 

      THE STATE AND LOCAL BUDGET OUTLOOK

 

 

           The Cyclicality of State and Local Government

 

           Expenditures

 

 

           Federal Grants to States Through the Recovery Act

 

 

           State and Local Pensions

 

 

 CHAPTER 4. JOBS, WORKERS AND SKILLS

 

 

      DEMOGRAPHIC AND LABOR FORCE TRENDS

 

 

           A Slowdown in Women's Participation Rates

 

 

           Work Schedules and Workplace Flexibility

 

 

      GOVERNMENT AS A PARTNER IN HUMAN CAPITAL AND SKILL FORMATION

 

 

           Expanded Pell Grants

 

 

           Expanded American Opportunity Tax Credit

 

 

           Aggregate Student Loan Debt

 

 

           Income-Based Repayment

 

 

           Federal Loan Consolidation

 

 

           The Growth of For-Profit Colleges

 

 

           Gainful Employment

 

 

           What Is Driving Up Tuition Costs?

 

 

           Government as a Partner in Training

 

 

      IMMIGRATION

 

 

           A Brief History of U.S. Immigration Policy

 

 

           The Economic Benefits of Immigration

 

 

           A Magnet for High-Skilled Immigration

 

 

           Boosting Innovation and Entrepreneurship

 

 

           Conclusion

 

 

 CHAPTER 5. REDUCING COSTS AND IMPROVING THE QUALITY OF HEALTH CARE

 

 

      HEALTH CARE SPENDING

 

 

           Long-Term Spending Growth

 

 

           Medical Productivity

 

 

           Sources of Inefficiency in Health Care Spending

 

 

      EARLY IMPLEMENTATION OF THE AFFORDABLE CARE ACT

 

 

           Economic Benefits of Insurance

 

 

           Expanding Affordable Health Insurance Coverage

 

 

           Consumer Protection

 

 

           Health Care Spending and Quality of Care

 

 

           Medicare Payment Reform

 

 

           Is the Cost Curve Bending?

 

 

 CHAPTER 6. CLIMATE CHANGE AND THE PATH TOWARD SUSTAINABLE

 

            ENERGY SOURCES

 

 

      CONSEQUENCES AND COSTS OF CLIMATE CHANGE

 

 

           The Changing Climate

 

 

           Estimating the Economic Cost of Climate Change: The

 

           Social Cost of Carbon

 

 

           Policy Implications of Scientific and Economic

 

           Uncertainty

 

 

      CARBON EMISSIONS: PROGRESS AND PROJECTIONS

 

 

      POLICY RESPONSES TO THE CHALLENGE OF CLIMATE CHANGE

 

 

           Market-Based Solutions

 

 

           Direct Regulation of Carbon Emissions and the

 

           Vehicle Greenhouse Gas/Corporate Average Fuel Economy

 

           (CAFE) Standards

 

 

           Energy Efficiency

 

 

      ENERGY PRODUCTION IN TRANSITION

 

 

           Oil and Natural Gas

 

 

           Renewable Energy

 

 

           Advanced Technologies and R&D

 

 

      PREPARING FOR CLIMATE CHANGE

 

 

      CONCLUSION

 

 

 CHAPTER 7. INTERNATIONAL TRADE AND COMPETITIVENESS

 

 

      THE WORLD ECONOMY AND U.S. TRADE

 

 

           Growth in World Economies

 

 

           The Euro Crisis

 

 

           Global Imbalances

 

 

      TRADE AND THE MANUFACTURING SECTOR

 

 

           Trade and Productivity

 

 

      GROWTH OF TRADED SERVICES

 

 

      TRADE POLICY

 

 

      BUILDING U.S. COMPETITIVENESS

 

 

           Manufacturing

 

 

           Spillovers Between Manufacturing Production

 

 

           and Innovation

 

 

           Rise of Global Supply Chains

 

 

           Prospects for U.S. Manufacturing

 

 

           Productivity in Services

 

 

      CREATING AN ECONOMY BUILT TO LAST

 

 

           Strengthening Competitiveness: The Manufacturing

 

           Example

 

 

      CONCLUSION

 

 

 CHAPTER 8. CHALLENGES AND OPPORTUNITIES IN U.S. AGRICULTURE

 

 

      THE AGRICULTURAL SECTOR IN 2012

 

 

           Barriers to Entry and Succession Planning in U.S.

 

           Agriculture

 

 

           A Mature Domestic Food Market

 

 

           New Markets in Agriculture

 

 

           Today's Farm Structure

 

 

           Investing in Agricultural Productivity

 

 

           Research and Development Drives Productivity Growth

 

 

           Conservation Practices and the Environment

 

 

           Natural Capital, Conservation, and the Outdoor

 

           Economy

 

 

      GROWING GLOBAL DEMAND FOR FOOD AND AGRICULTURAL COMMODITIES

 

 

           Population Growth and Urbanization

 

 

           Pressure on Agricultural Land and the Environment

 

 

      GLOBAL COMMODITY MARKETS AND PRICE VOLATILITY

 

 

      MEETING THE CHALLENGES AND HARNESSING THE OPPORTUNITIES OF

 

      GLOBAL DEMAND GROWTH

 

 

           Open Trade and Access to Global Food Markets

 

 

           Hired Farm Labor Costs in a Global Economy

 

 

           Improving Risk Management

 

 

           The Dodd-Frank Wall Street Reform and Consumer

 

           Protection Act

 

 

      CONCLUSION

 

 

 REFERENCES

 

 

                              APPENDIXES

 

 

 A.      Report to the President on the Activities of the Council of

 

         Economic Advisers During 2012

 

 

 B.      Statistical Tables Relating to Income, Employment, and

 

         Production

 

 

                                FIGURES

 

 

 1-1.    Monthly Change in Private Nonfarm Payrolls, 2007-2013

 

 

 1-2.    Real Gross Domestic Product and Trends, 1960-2012

 

 

 1-3.    Cumulative Over- and Under-Building of Residential and

 

         Manufactured Homes, 1996-2012

 

 

 1-4.    Real GDP, 2007-2012

 

 

 1-5.    Average Annual Difference Between Growth in Real GDP Per

 

         Capita and Growth in Real Health Expenditures Per Capita,

 

         1965-2012

 

 

 1-6.    Population Growth by Age Group, 1950-2040

 

 

 1-7.    Average Tax Rates for Selected Income Groups Under a Fixed

 

         Income Distribution, 1960-2013

 

 

 2-1.    Real GDP Growth, 2007-2012

 

 

 2-2.    Nonfarm Payroll Employment, 2007-2013

 

 

 2-3.    Private Nonfarm Employment During Recent Recoveries

 

 

 2-4.    Unemployment Rate, 1979-2013

 

 

 2-5.    Initial Unemployment Insurance Claims, 2004-2013

 

 

 2-6.    Consumption and Wealth Relative to Disposable Personal Income

 

         (DPI), 1952-2012

 

 

 2-7.    Business Fixed Investment and Cash Flow, 1990-2012

 

 

 2-8.    Real State and Local Government Purchases During Recoveries

 

 

 2-9.    Real Exports During Recoveries

 

 

 2-10.   Housing Starts, 1960-2012

 

 

 2-11.   Home Prices and Owners' Equivalent Rent, 1975-2012

 

 

 2-12.   Cumulative Over- and Under-Building of Residential and

 

         Manufactured Homes, 1996-2012

 

 

 2-13.   10-Year Treasury Yields, 2004-2013

 

 

 2-14.   Consumer Price Inflation, 2004-2012

 

 

 2-15.   Real GDP During Recoveries

 

 

 2-16.   Productivity Growth and Estimated Trend, 1960-2012

 

 

 2-17.   Employment Percent Growth and Estimated Trend, 1960-2012

 

 

 2-18.   Quarterly Change in Employment and Estimated Trend, 1960-2012

 

 

 2-19.   Real Gross Domestic Product and Trends, 1947-2012

 

 

 3-1.    Average Tax Rates for Selected Income Groups Under a Fixed

 

         Income Distribution, 1960-2013

 

 

 3-2.    Real State and Local Government Gross Investment During

 

         Recoveries

 

 

 3-3.    Federal Receipts and Outlays, 1970-2023

 

 

 3-4.    Federal Budget Deficit, 1970-2023

 

 

 3-5.    Federal Debt Held by the Public, 1970-2023

 

 

 3-6.    Distribution of Benefits of Selected Tax Expenditures, 2013

 

 

 3-7.    Effective Marginal Tax Rates on Wage Income for Selected

 

         Income Groups Under a Fixed Income Distribution, 1960-2013

 

 

 3-8.    Top Marginal Tax Rates, 1960-2013

 

 

 3-9.    Composition of Federal Receipts, 1960-2011

 

 

 3-10.   Individual Income Tax Compliance Costs by Reporting Activity,

 

         2010

 

 

 3-11.   Real Annual Changes in State General Fund Spending, 1981-2012

 

 

 3-12.   Year-to-Year Change in City General Fund Tax Receipts,

 

         2005-2012

 

 

 3-13.   Federal Grants to State and Local Governments by Type,

 

         1960-2012

 

 

 4-1.    Labor Force Participation Rate by Population Group, 1970-2012

 

 

 4-2.    Age-Specific Labor Force Participation Rate by Birth Cohort

 

         for Women, 1926-1992

 

 

 4-3.    Labor Force Participation Rate of Women Aged 25-54, 1991-2011

 

 

 4-4.    Percent of Women Ages 25 Years and Older Working Full-Time,

 

         1991-2009

 

 

 4-5.    Median Weekly Earnings by Education Level, 2012

 

 

 4-6.    Tuition and Fees for Full-Time Undergraduate Students,

 

         1990-2012

 

 

         Private institutions

 

 

         Public institutions

 

 

 4-7.    Compositions of Household Debt Balance, 2003-2012

 

 

 4-8.    Total Postsecondary Enrollment by Type of Institution,

 

         1990-2010

 

 

 4-9.    Average Expenditures per Full-Time-Equivalent Student by

 

         Component, 2000-2010

 

 

         Private institutions

 

 

         Public institutions

 

 

 4-10.   Legal Immigration by Decade, 1820s to 2000s

 

 

 5-1.    GDP and Health Spending, 1980-2011

 

 

 5-2.    Contribution of Population Growth and Aging to Health Care

 

         Spending, 1996-2010

 

 

 5-3.    Cancer Spending per New Cancer Case, 1983-1999

 

 

 5-4.    Life Expectancy after Cancer Diagnosis, 1983-1999

 

 

 5-5.    Acute Care Hospital Readmission Rates, 2007-2012

 

 

 5-6.    Real Annual Growth Rates of National Health Expenditures Per

 

         Capita and Medicare Spending Per Enrollee, 1990-2012

 

 

 5-7.    Relationship Between Change in State Unemployment Rate and

 

         Change in Real Per-Capita Personal Health Spending, 2007-2009

 

 

 5-8.    Projected Medicare Spending as a Share of GDP, 2013-2085

 

 

 6-1.    Illustrative Average Temperature Distribution

 

 

 6-2.    U.S. Energy-Related Carbon Dioxide Emissions, 1973-2040

 

 

 6-3.    Decomposition of CO2 Emission Reductions, 2005-2012

 

 

         6-4. Energy Use per Dollar of GDP, Selected Countries,

 

         1988-2009

 

 

 6-5.    U.S. Energy Intensity, 1950-2010

 

 

 6-6.    Total U.S. Primary Energy Production, 2011

 

 

 6-7.    U.S. Natural Gas Consumption and Production, 2000-2025

 

 

 6-8.    Annual and Cumulative Growth in U.S. Wind Power Capacity,

 

         1998-2011

 

 

 7.1.    Real GDP Growth by Country, 2007-2012

 

 

 7.2.    10-Year Government Bond Yields, 2011-2013

 

 

 7.3.    Current Account Balance by Country, 2000-2011

 

 

 7.4.    U.S. Current Account Balance and its Components, 2000-2012

 

 

 7.5.    Monthly Change in Manufacturing Employment, 1990-2012

 

 

 7.6.    Employment in Export Intensive and Export Nonintensive

 

         Manufacturing Industries, 2011-2012

 

 

 7.7.    Change in Manufacturing Unit Labor Costs, 2003-2011

 

 

 8-1.    Median Income for Farm Households by Farm Type and Income

 

         Type, 2010-2012

 

 

 8-2.    Distribution of Farms by Age of Principal Operator, 2010

 

 

 8-3.    U.S. Real Per Capita Food Expenditures, 1985-2011

 

 

 8-4.    Farm and Nonfarm Productivity, 1948-2009

 

 

 8-5.    Public and Private U.S. Agricultural R&D Spending, 1971-2009

 

 

 8-6.    Population by Region, 1950-2050

 

 

 8-7.    Percentage of Population Residing in Urban Areas, 1950-2050

 

 

 8-8.    Middle-Class Population by Region, 2009-2030

 

 

 8-9.    Corn Yields and Price, 1866-2012

 

 

 8-10.   Government Commodity Payments by Farm Type

 

 

                                TABLES

 

 

 2.1.    Labor Force Participation Rates, 1980-1985 and 2007-2012

 

 

 2.2.    Real GDP Growth During Three Years Following Business Cycle

 

         Trough

 

 

 3.1.    Cyclical Behavior of State and Local Government Expenditures,

 

         1977-2008

 

 

 4-1.    Labor Force Participation Rate of Women Aged 25-54, 1969-2007

 

 

 4-2.    Education Tax Incentives: The American Opportunity Tax

 

         Credit, 2010

 

 

 4-3.    Foreign-Born Persons in Selected Countries

 

 

 4-4.    Distribution of Education, Age, and Employment for Natives

 

         and Foreign Born Individuals, 2010-2012

 

 

 4-5.    Percentage of Foreign-Born College Graduates by Degree and

 

         Occupation, 2010

 

 

 7.1.    Euro Area Selected Economic Indicators

 

 

 8-1.    90 Years of Structural Change in U.S. Agriculture

 

 

 8-2.    Farm Types

 

 

 8-3.    Farm Income and Farm Operator Household Income by USDA Farm

 

         Size Classification, 2010

 

 

                                 BOXES

 

 

 Box 2-1: Effectiveness of Iran Sanctions

 

 

 Box 2-2: Why Is the Labor Share Declining?

 

 

 Box 2-3: Economic Impacts of the American Recovery and Reinvestment

 

          Act

 

 

 Box 2-4: Implications of Demographic Trends for Household Consumption

 

 

 Box 3-1: Estimates of Tax Expenditures in the President's Budget

 

 

 Box 4-1: Minimum Wages and Employment

 

 

 Box 6-1: The Cost of Hurricanes

 

 

 Box 6-2: Handling Uncertainty About Equilibrium Climate Sensitivity

 

 

 Box 7-1: Small Businesses and the NEI

 

 

                              DATA WATCH

 

 

 Data Watch 2-1: Seasonal Adjustment in Light of the Great Recession

 

 

 Data Watch 2-2: The Effect of Statistical Sampling on Laspeyres

 

                 Indexes

 

 

 Data Watch 3-1: Federal Tax Information and Synchronization of

 

                 Interagency Business Data

 

 

 Data Watch 4-1: New Evidence on Access to Paid Leave

 

 

 Data Watch 5-1: Toward Disease-Based Health Care Accounting

 

 

 Data Watch 6-1: Tracking Sources of Emissions: The Greenhouse Gas

 

                 Reporting Program

 

 

 Data Watch 7-1: Implications of Global Value Chains for the

 

                 Measurement of Trade Flows

 

 

 Data Watch 7-2: Measuring Supply Chains

 

 

                         ECONOMICS APPLICATION

 

 

 Economics Application Box 3-1: Marginal Tax Rates and Average Tax

 

                                Rates on Individual Income

 

 

 Economics Application Box 4-1: Baumol's Cost Disease (or Bowen's

 

                                Curse) and the Price of Education

 

 

 Economics Application Box 5-1: Matching in Health Care

 

 

 Economics Application Box 5-2: Economics of Adverse Selection and the

 

                                Benefits of Broad Enrollment

 

 

 Economics Application Box 7-1: Agglomeration Economies and Spillovers

 

                                Across Regions

 

 

 Economics Application Box 8-1: The 2012 Drought

 

 

 Economics Application Box 8-2: The Federal Estate Tax and Farm

 

                                Business Succession Planning

 

CHAPTER 1

 

 

RECOVERING FROM THE

 

PAST AND PREPARING

 

FOR THE FUTURE

 

 

Although economics has long been called "the dismal science," it is more appropriately viewed as a "hopeful science." The right mix of economic policies and leadership can help a country to recover from a deep recession and point to the investments and reforms that will build a stronger, more stable, and more prosperous economy that works for the middle class. Conversely, government dysfunction or misguided fiscal policy can cause self-inflicted wounds to the economy. This year's Economic Report of the President highlights the progress that has been made in recovering from the deepest recession since the Great Depression, together with the policies that the Obama Administration is advancing to address the fundamental imbalances and threats that have built up for decades and that have created severe stress on the middle class and those striving to get into the middle class.

As President Obama embarks on a second term, the U.S. economy unquestionably stands on firmer ground than when he first took office, but more work remains to be done. Our Nation's economic recovery continued to make progress in 2012: payroll employment rose by more than 2 million, the unemployment rate fell to its lowest level in four years, new cars sold at the fastest rate since 2007, and the housing sector showed clear signs of turning a corner for the first time in more than five years. In the near term, sustaining and building upon this progress must be a priority. At the same time, the Obama Administration also remains focused on addressing a number of underlying, structural problems, many of which developed over the course of decades. Some of these problems -- like stagnant middle-class incomes and excessive risk-taking in the financial sector -- played a role in bringing our economy to the brink of collapse in late 2008 and early 2009. Other challenges -- like the dangers of climate change and rising health care costs -- could jeopardize our prosperity and security in the years ahead. Another theme that runs throughout this Report is that demographic changes associated with an aging population are having a profound effect on economic performance in a number of domains, from labor force participation to household consumption, as well as placing increasing pressure on the Federal budget. The Obama Administration is committed to addressing these issues, while also supporting the ongoing recovery, and in turn building an economy that is stronger, fairer and more resilient.

This Report reviews the progress of the ongoing economic recovery during 2012 and highlights the main goals of the President's economic agenda. These goals include strengthening the foundations of economic growth by investing in education, research, and infrastructure, and by fixing a broken immigration system through commonsense immigration reform; ensuring fairness for the middle class by reforming the tax code and health insurance system; and bolstering the economy's resilience to future challenges by addressing the dangers of climate change, moving toward energy independence, pursuing a balanced approach to deficit reduction, adding safeguards to the financial system, opening up new markets for U.S. exports, and equipping American workers to compete in the global economy.

 

Tracking the Progress of the Recovery

 

 

When President Obama first entered office on January 20, 2009, the U.S. economy was in the midst of the worst downturn since the Great Depression. Real gross domestic product (GDP), the total amount of goods and services produced in the country adjusted for inflation, had just contracted at the sharpest rate in any quarter in more than 50 years, shrinking by 8.9 percent at an annual rate. This severe decline in economic output was accompanied by devastating job losses. In the year before President Obama's first inauguration, the U.S. economy lost 4.6 million private sector jobs, including 821,000 in January 2009. As bad as things were at the time, a dark cloud of uncertainty hovered over the economy, and the risk of even further deterioration was still very real. At the end of 2008, the financial system teetered on the brink of collapse and credit for businesses and households had seized up. Home prices were steadily declining, with no bottom in sight, and the fate of the American auto industry hung in the balance, as auto sales in early 2009 plunged to their lowest level in 27 years. A total of $16 trillion in wealth was erased by the financial and housing crisis, causing families to pull back on spending plans, reduce personal debt and increase savings, in turn leading companies to cut back hiring, lay off valued employees, and halt investment plans. In short, the economy was caught in a downward spiral, where consumers were pulling back because they had less income and feared job loss, businesses pulled back and reduced employment even further, and around this vicious cycle went.

Against this backdrop, the Obama Administration acted quickly and decisively to raise aggregate demand, stem the job losses, restore the flow of credit, and put the economy in a position to begin growing once again. The American Recovery and Reinvestment Act of 2009 (the Recovery Act) was the boldest measure of countercyclical fiscal stimulus in U.S. history. The Recovery Act's mix of tax cuts for individuals and businesses, aid to State and local governments, and infrastructure investment was designed to provide the economy with an immediate boost. In addition to the Recovery Act, the Obama Administration worked to stabilize the financial sector through a series of measures including stress tests for banks and rigorous requirements for banks to raise private capital and repay the government for assistance from the Troubled Asset Relief Program. The Making Home Affordable program put in place a number of initiatives that have helped millions of Americans modify or refinance their mortgages and stay in their homes. The Administration also rescued and reformed the auto industry by guiding the successful restructuring of two of America's largest automakers and preserving the critical supply network.

Soon after these steps were taken, the economy reversed course. The contraction in economic output eased in 2009 and GDP began to grow again in the third quarter of that year. The economy has now expanded for 14 consecutive quarters. Similarly, the pace of job losses slowed over the course of 2009, and the monthly change in private employment turned positive in March 2010. In recent recoveries following the end of recessions, job growth has lagged economic growth, as employers either managed to implement ways to raise labor productivity to meet demand or delayed hiring out of caution that demand would not recover. During the current recovery, sustained job growth started 9 months after GDP growth resumed, which is sooner than in the 1991 and 2001 recoveries. As shown in Figure 1-1, private employers have now increased payrolls for 35 consecutive months. The 6.1 million jobs added over this time constitute the best 35-month period of job creation since 1998-2001, more than a decade ago. In addition, some $13.5 trillion of the $16 trillion in lost wealth has been restored due to the rebounding of the equity markets and firming of house prices, although the gains in wealth have not been uniformly shared.

In 2012, the recovery continued to make progress, and the economy and American people showed their resilience in the face of several headwinds. Total nonfarm payroll employment grew by 2.2 million during the year, or roughly 181,000 jobs per month, a bit above the forecast of 167,000 jobs per month that appeared in last year's Economic Report of the President. The unemployment rate fell 0.7 percentage point over the course of the year and reached its lowest level since January 2009. Almost the entire drop in the unemployment rate resulted from increased employment rather than labor force withdrawal. GDP expanded by 1.6 percent during the four quarters of 2012.

 

Figure 1-1

 

Monthly Change in Private Nonfarm Payrolls, 2007-2013

 

 

 

 

Note: Shading denotes recession.

Source: Bureau of Labor Statistics, Current Employment Statistics.

Although 2012 was a year of progress, it was not without challenges. A severe drought in the Midwest subtracted from GDP growth in the second and third quarters. Hurricane Sandy struck in late October, and based on the latest estimates of private property damage, it was the second costliest natural disaster in the United States during the last 40 years, behind only Hurricane Katrina. In addition, the euro area slipped back into recession, reflecting continued uncertainty in financial markets, further deleveraging by households and companies, and sizable fiscal austerity measures undertaken by many European governments. The slowdown among our trading partners in Europe and also in Asia reduced overseas demand for U.S. goods and services. And here in the United States, the threat of scheduled tax increases and automatic spending cuts known as the "fiscal cliff" lingered for most of the year. The economy's performance in 2012 is reviewed in greater detail in Chapter 2. Despite the economy's resilience during the past year, the unemployment rate remains elevated, and more work remains to be done to boost growth and job creation. In 2013, the Administration remains focused on the need to keep moving forward, while once again avoiding the threat of self-inflicted wounds.

 

Figure 1-2

 

Real Gross Domestic Product and Trends, 1960-2012

 

 

 

 

Note: Shading denotes recession. Trend lines represent the average growth rate between successive business-cycle peaks.

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

Placing the Recovery in Historical Context

Chapter 2 also places the recovery in broader historical context. The pattern in recoveries over the last 50 years has been that more recent recoveries tend to be marked by slower growth than the recoveries that preceded them. This tendency is documented in Figure 1-2, which shows real GDP along with trend lines based on the average growth rate between successive business-cycle peaks. The current recovery, so far, is no exception to this pattern. The single largest cause of slower trend GDP growth in recent years is changing demographics, as the rate of overall population growth moderates, the baby boomers move into retirement, and the share of the population that is of prime working age begins to decline. Productivity growth also appears to have slowed down after the 1990s, although it is unclear if the slowdown will continue.

At the same time, however, several of the factors that have restrained growth in recent years are temporary constraints that are unique to the current situation and will likely subside in the years ahead. For instance, a growing body of research has shown that recoveries following financial crises tend to be slower, because of delays in the reemergence of credit and reductions in consumer spending as households pay down debt or rebuild their savings. The Administration expects growth to quicken after households repair their balance sheets and consumers have more money to spend on goods and services. In addition, the housing sector is just now emerging from several depressed years, and much of the overbuilding that took place during the boom years has been offset by underbuilding since 2007. As Figure 1-3 shows, by the Council of Economic Advisers' (CEA) calculations, the U.S. housing market has likely worked off the nationwide cumulative total of excess building that took place in the housing boom years. Consequently, activity in the housing sector is likely to return to more normal levels in the years ahead, although some regions are further ahead in this process than others.

 

Figure 1-3

 

Cumulative Over- and Under-Building of Residential

 

and Manufactured Homes, 1996-2012

 

 

 

 

Note: The 1998 Economic Report of the President projected that 1.6 million new housing units per year would be needed from 1996-2006 to keep pace with demographics. Cumulative over- and under-building is measured relative to this projection.

Source: Census Bureau, New Residential Construction (completions) and Manufactured Homes Survey (placements); CEA (1998); CEA calculations.

Furthermore, despite the Administration's efforts to support State and local governments through the Recovery Act and other measures, employment in this sector has undergone an unprecedented decline. The Obama Administration will continue to look for ways to boost the hiring of teachers, police officers and firefighters, and these efforts should be helped by a broadly improving economy that eases the strain on State and local government finances. Thus, while some of the slower growth experienced in recent years is likely the unavoidable consequence of changing demography, there are still strong reasons to believe that the pace of economic growth will nonetheless pick up.

Making Progress Toward a Sustainable Fiscal Path

During 2012, the Obama Administration continued to pursue a balanced approach to fiscal policy that supports the recovery in the near term while looking to reduce the deficit and stabilize the debt over the medium and long term. The Recovery Act provided substantial support for growth in 2009 and 2010, and the economy benefited in 2011 and 2012 from extended unemployment insurance benefits and a 2 percentage point reduction in the employee contribution to the payroll tax, among other measures. At the same time, the Administration agreed to and Congress enacted $1.4 trillion in discretionary spending cuts, spread over the next decade to ease the impact on an economy that is still healing. Together with the additional revenue from the American Taxpayer Relief Act (ATRA) and interest savings, the deficit has been reduced by more than $2.5 trillion over the next 10 years. Thanks to these actions and steady economic growth, the Federal budget deficit has declined from 10.1 percent of GDP in 2009 to 7.0 percent of GDP in 2012, the largest three-year drop since 1949. The Congressional Budget Office (CBO 2013) projects that the deficit will fall to 5.3 percent of GDP in 2013. The Obama Administration has repeatedly proposed policies to bring the deficit down to below 3 percent of GDP and stabilize the national debt relative to the size of the economy in the 10-year budget window. A further discussion of the Federal budget outlook can be found in Chapter 3.

A comparison of recent economic performance in the United States with that of countries undertaking more abrupt fiscal consolidation underscores the importance of a balanced and responsible approach to return over time to a sustainable Federal budget. Figure 1-4 shows that while GDP in the United States has expanded for 14 consecutive quarters and surpassed its pre-recession peak, the recovery has faltered in places where austerity has been implemented more rapidly. President Obama has put it succinctly: "We cannot just cut our way to prosperity."

The American Taxpayer Relief Act, enacted January 2, 2013, represents an important component of the Obama Administration's approach to reducing the deficit and returning more fairness to the tax code. Before the enactment of ATRA, the Congressional Budget Office (CBO 2012a, 2012b) estimated that if the massive tax hikes and spending cuts originally scheduled to take place in 2013 had been allowed to occur, the full force of these austerity measures, equivalent in dollar terms to roughly 4 percent of GDP, would have caused the unemployment rate to rise by more than one percentage point and likely driven the economy into another recession. The Council of Economic Advisers (CEA 2012) projected that if tax rates rose for middle-class families earning less than $250,000 a year as was planned under then-current law, U.S. consumers would have reined in their spending by nearly $200 billion in 2013. To put this in perspective, this reduction of $200 billion is approximately four times larger than the total amount that 226 million shoppers spent on the post-Thanksgiving "Black Friday" weekend in 2011, or roughly the same amount Americans spent on all the new cars and trucks sold in the United States that year. This would have been a deeply damaging self-inflicted wound to the economy.

 

Figure 1-4

 

Real GDP, 2007-2012

 

 

 

 

Source: U.S. Bureau of Economic Analysis, National Income and Product Accounts; U.K. Office for National Statistics; Statistical Office of the European Communities.

ATRA avoided this massive fiscal retrenchment, securing permanent income tax relief for 98 percent of Americans and 97 percent of small businesses, while also asking wealthier Americans to contribute a bit more to deficit reduction. ATRA reduces the deficit by more than $700 billion over the next 10 years, largely by restoring the top marginal tax rate on upper-income households to the levels that prevailed in the 1990s and taxing these households' capital income at a 20 percent rate instead of 15 percent. At the same time, it locks in lower tax rates for the middle class permanently and extends President Obama's expansions of key tax credits that help working families pay the bills and send their children to college. Other tax credits for business investment and R&D were also extended, as was unemployment insurance for 2 million Americans who are still searching for a job. By avoiding the bulk of the tax increases that would have jeopardized the recovery while also making substantial progress on reducing the deficit, ATRA was a positive step that is representative of the balanced approach that the Administration will continue to pursue.

As this Report goes to press, the U.S. economy is once again confronted with the risk of a self-inflicted wound, in the form of automatic, across-the-board spending cuts known as the sequester. When originally put into place with the Budget Control Act of 2011 (BCA), these cuts were never intended to be policy, but rather to force Congress to reach agreement on a broad, long-term deficit reduction package. In the absence of such an agreement, the cuts went into effect on March 1, 2013, and threaten to slow the economy and cause hundreds of thousands of job losses if not replaced. Private economists suggest the cuts could reduce GDP growth in 2013 by around half a percentage point. This potential reduction in output is sizable, considering that most analysts expect the economy to grow around 2 to 3 percent during the year. Moreover, in the weeks and months ahead, sequestration will begin to disrupt basic functions of government on which Americans depend, from education to emergency first-response to airport security. Already, the Navy has been forced to delay the deployment of an aircraft carrier to the Persian Gulf because of the threat of the cuts. The Administration will continue to call on Congress to replace the across-the-board, indiscriminate BCA sequester with a balanced alternative that closes unfair tax loopholes, reforms entitlements, and cuts unnecessary spending. This type of approach is the best way to support the recovery in the short run, while also making progress toward returning to a sustainable budget in the long run.

While the immediate budgetary concern in 2013 is the need to replace the sequester, it is also important to remain focused on the main driver of our long-term budget challenge: the cost of health care for an aging population. One positive development, with significant implications for the economy and Federal budget if it persists, is the recent slowdown in the growth of health care spending. The rate of growth in nationwide real per capita health care expenditures has been on a downward trend since 2002, with a particularly marked slowdown over the past three years. Since 2010, health care expenditures per capita grew at essentially the same rate as GDP per capita. As shown in Figure 1-5, this development is unusual, because growth in health spending has tended to outpace overall economic growth for most of the last five decades. Although some of the narrowing of this gap can be attributed to the effects of the recession, Chapter 5 presents evidence that structural shifts in the health care sector are underway, spurred on in part by the 2010 Patient Protection and Affordable Care Act (Affordable Care Act). If the recent trends can be sustained, the resulting lower health care costs will have a tremendously positive impact on employers, middle-class families, and importantly, the Federal budget. Indeed, if the growth rate of Medicare spending per beneficiary over the last five years persists into the future, then after 75 years Medicare spending would account for only 3.8 percent of GDP, little changed from its share today, and substantially less than what the Medicare Trustees estimate. This should not be interpreted as a forecast but rather an indication of how sensitive long-term projections are to the assumed rate of growth of Medicare spending per beneficiary.

 

Figure 1-5

 

Average Annual Difference Between Growth in Real GDP Per Capita

 

and Growth in Real Health Expenditures Per Capita, 1965-2012

 

 

 

 

Note: Health expenditures per capita are deflated by the GDP price index.

Source: Bureau of Economic Analysis, National Income and Product Accounts; Centers for Medicare and Medicaid Services, National Health Expenditure Accounts; CEA calculations.

In sum, the U.S. economy has come a long way over the last four years, though more work remains. A staggering total of 8.8 million private sector jobs were destroyed as a result of the Great Recession, but 6.1 million jobs have been gained back. Similarly, $16 trillion in household wealth was lost when the housing bubble burst and the economy went into recession, but now more than $13 trillion -- over 80 percent -- has been regained. And of the estimated $4 trillion in deficit reduction that many budget experts agree is needed over the next 10 years to place the economy on a sustainable fiscal path, more than $2.5 trillion has been achieved. House prices and residential construction are on the rise, the domestic manufacturing sector is showing signs of resurgence after a decade of shedding jobs, and the U.S. auto industry is back on track, selling new cars at an increasing rate. More work remains to be done, but our Nation has come too far now to turn back.

 

Building a Stronger, Fairer, More Resilient Economy

 

 

While continuing to build on the progress in recovering from the recession and increasing job creation in the near term, the Obama Administration has also kept a careful focus on preparing the U.S. economy for a stronger, fairer, more resilient future. Many of the problems that caused the financial crisis and recession built up over decades, and our Nation will not have a durable economy that works for the middle class until these underlying, fundamental issues are addressed. For instance, middle-class incomes stagnated in the 2000s, and many economists have argued that households turned to credit to make up for this weak income growth. Lightly regulated -- or unregulated -- financial companies were all too willing to provide easy credit at nontransparent terms to meet this demand. The borrowing was unsustainable, as evidenced by the bursting of the housing bubble and the fact that outstanding household debt burdens have restrained consumer spending during the course of the recovery.

Part of the weak income growth for middle-class families can be traced to rising health care costs. By one estimate, if health care costs during the 2000s had risen at the same rate as general consumer price inflation -- rather than exceeding it -- the median family of four would have had an additional $5,400 in 2009 to spend on other expenses (Auerbach and Kellermann 2011). Slowing the rise in health care costs is therefore a critical part of ensuring that middle-class families can see their take-home pay start to grow consistently again.

This mix of underlying problems -- stagnant middle-class incomes, excessive reliance on borrowing, and rising health care costs -- motivated two of the Administration's key initiatives during the first term: the Affordable Care Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act. The Affordable Care Act expands insurance coverage and puts in place meaningful reforms that will reduce the cost of medical care, ensuring that families will not be forced into bankruptcy because of an unexpected illness. The Dodd-Frank law puts an end to taxpayer-financed bailouts for big banks, restricts many of the riskiest financial practices that developed in the run-up to the crisis, and creates a new consumer watchdog to increase transparency and fairness for American families.

Strengthening the Foundations of Growth

The economy's long-run growth potential fundamentally depends on the number of workers and the productivity of those workers, which, of course, depends on the productivity of American businesses and the creativity and risk-taking of American entrepreneurs. During the second half of the 20th century, the U.S. economy benefited substantially from favorable demographics. The baby boomers were in their prime working years, and women entered the labor force in record numbers. As the size of the labor force grew more quickly during these years, so too did the economy's potential output. However, as discussed previously, population growth is expected to slow in the years ahead, and the United States is expected to undergo a dramatic demographic transition. Figure 1-6 displays the latest projections from the Census Bureau, showing that overall population growth is estimated to decline from an average of 1.2 percent per year since 1950, to just 0.7 percent per year over the next three decades. Notably, as the baby boomers move into retirement, the only major age group that will grow faster over the next 30 years than it did during the last 60 is persons aged 65 and up. As a result, the share of the population that is of prime working age will fall steadily, and the number of retirees per worker will rise. Consequently, one of the major challenges facing the U.S. economy in the decades ahead is the slowdown in potential output growth that will result from a more slowly growing population and labor force.1

Although the recession caused a decline in the labor force participation rate, it is important to recall that even well before the recession, the labor force participation rate showed signs that it had reached its peak in the late 1990s. This fact largely reflected the aging of the population discussed above and the plateauing of female labor force participation following four decades during which American society was transformed by an increasing number of women in the workforce. So while some discouraged workers are likely to reenter the labor force in the near term as the economy continues to heal, the long-term trend for the labor force participation rate is still likely to be downward. This likelihood was acknowledged in the 2004 Economic Report of the President, which noted, "the long-term trend of rising participation appears to have come to an end. . . . The decline [in the labor force participation rate] may be greater, however, after 2008, which is the year that the first baby boomers (those born in 1946) reach the early-retirement age of 62."

 

Figure 1-6

 

Population Growth by Age Group, 1950-2040

 

Average annual percent change

 

 

 

 

Source: Census Bureau, Annual Estimates of the Resident Population and 2012 National Population Projections; CEA calculations.

In the face of the demographic challenges of an aging population and a more slowly growing workforce, the Administration believes it is imperative to boost the productivity of American workers by investing in education, innovation, research, and infrastructure. One way in particular to enhance the productivity of the workforce is to have a more educated workforce. As discussed in Chapter 4, the value of a college degree -- as measured by the premium paid to college-educated workers -- is significant. Shortly after taking office in 2009, President Obama set the goal that America would once again have the highest proportion of college-educated young people in the world by 2020. Chapter 4 details the steps the Obama Administration has taken to meet that goal, including expanding Pell Grants, establishing the American Opportunity Tax Credit, and reforming the student loan system to help make repayment more manageable for 1.6 million responsible borrowers. More recently, President Obama has called for a new Federal-State partnership that would provide all low- and moderate-income four-year-olds with high-quality preschool.

Commonsense immigration reform is another key aspect of the Administration's efforts to enhance the productivity of the American workforce, create more jobs for workers and more customers for businesses, and ease the looming demographic challenges. With a more slowly growing population and more retirees to support, the time is ripe for America to once again renew its long tradition of welcoming immigrants to our shores. Chapter 4 summarizes the economic case for reforming our immigration system to make the American economy more dynamic. Indeed, immigrants founded more than one in four new businesses in the United States in 2011 (Fairlie 2012). Moreover, commonsense immigration reform that gives undocumented immigrants a pathway to earned citizenship is needed to bring these workers out of the shadows and ensure that employers who hire only legally authorized workers and pay a decent wage are not put at a disadvantage. This type of commonsense reform strengthens the economy as a whole by maintaining competition on a level playing field. Immigrants own more than 2 million American businesses of all sizes and were critical to the creation of many of our largest companies like Yahoo! and Google. To make sure that America has a dynamic, competitive workforce and is the home of the next major innovation, it is essential to move toward an immigration system that is geared to help us grow our economy and strengthen the middle class.

Ensuring Fairness for the Middle Class

As discussed above, the American Taxpayer Relief Act was significant not just because it averted the massive tax increases and automatic spending cuts that were slated to occur at the beginning of 2013, but also because it reversed a decades-long trend of declining tax rates for the wealthiest American households. Figure 1-7 shows the average Federal (individual income plus payroll) tax rate for the top 0.1 percent of earners, as well as for the top 1 percent and the middle 20 percent. Since the mid-1990s, the average tax rate on income earned by the wealthiest Americans has trended down and was close to its historical low for most of the 2000s. Beginning in 2013, however, top earners will contribute a bit more to deficit reduction, reducing pressure to cut key investments in education, research, and infrastructure. Even with the tax changes beginning this year, the average tax rate on these high earners is still well within the lower end of its historical range.

The move toward greater fairness in the tax code is motivated by President Obama's belief that the best way to grow an economy is from the middle out, not from the top down. Over the last 30 years, the wealthiest Americans have seen their share of the nation's income increase substantially. America celebrates success, but Americans also recognize that when the middle class is squeezed and working families struggle to afford the goods and services that businesses are selling, the prosperity of the nation as a whole is jeopardized. ATRA rolls back some of the inequality that has built up since the 1980s and marks the beginning of the return to a tax code that reflects basic principles of fairness and the critical importance of the middle class to the nation's overall economic health. The Administration has proposed to raise additional revenue by closing loopholes for investment fund managers and cutting tax preferences that benefit only high-income households, as well as by making changes to the corporate tax code that would eliminate special breaks for oil and gas companies and corporate jet owners. Chapter 3 provides further detail on how the President's tax and budget policies are informed by the goal of ensuring fairness for the middle class.

 

Figure 1-7

 

(Average Tax Rates for Selected Income Groups)

 

Under a Fixed Income Distribution, 1960-2013

 

 

 

 

Note: Average Federal (individual income plus payroll) tax rates for a 2005 sample of taxpayers after adjusting for growth in the National Average Wage Index.

Source: Internal Revenue Service, Statistics of Income Public Use File; National Bureau of Economic Research, TAXSIM (preliminary for 2012 and 2013); CEA calculations.

In his 2013 State of the Union Address, President Obama emphasized that "our economy is stronger when we reward an honest day's work with honest wages. But today, a full-time worker making the minimum wage earns $14,500 a year. Even with the tax relief we've put in place, a family with two kids that earns the minimum wage still lives below the poverty line." For these reasons, the President proposed raising the Federal minimum wage to $9.00 an hour and indexing it to inflation thereafter. While economists have long debated the effects of the minimum wage on employment, the available evidence suggests that modest increases in the minimum wage raise the incomes of low-wage workers as a group and have little, if any, effect on employment. Doucouliagos and Stanley's (2009) careful meta-analysis of the literature concludes, "with 64 studies containing approximately 1,500 estimates, we have reason to believe that if there is some adverse employment effect from minimum-wage raises, it must be of a small and policy-irrelevant magnitude." Similarly, another literature review by Schmitt (2013) considered the most recent research published since 2000 and found, "The weight of that evidence points to little or no employment response to modest increases in the minimum wage."

In addition to being paid a wage they can live on, working families should also have some protection from the tremendous hardship that could arise in the event of an unforeseen illness or medical condition. There is a fundamental economic rationale for providing this sort of protection. As President Obama said in his second inaugural address, "The commitments we make to each other through Medicare and Medicaid and Social Security, these things do not sap our initiative, they strengthen us. They do not make us a nation of takers; they free us to take the risks that make this country great." The insurance coverage expansion and cost reduction measures contained in the Affordable Care Act are the next major steps toward ensuring that American workers have a fair shot at realizing their full potential. Already, the number of uninsured young people is falling, due to the law's requirement that health insurance plans offer dependent children coverage until age 26. In addition, millions of Americans are now receiving rebates from their health insurers as a result of the law's requirement that insurers use no more than 20 percent of premiums for profits, administrative costs, and marketing. Chapter 5 details these and other important steps that are being taken to improve our Nation's health care system, as well as the major benefits that will result for middle-class workers and families.

The President's top priority remains to make America a magnet for jobs and manufacturing in order to strengthen the middle class and promote economic growth. As discussed in Chapter 7, manufacturing has historically provided Americans with a path to the middle class, especially for less educated Americans. But as foreign competition from companies in China and elsewhere began to emerge, manufacturing work increasingly moved overseas, and millions of American jobs were lost. Manufacturing employment in the United States had been fairly stable at around 18 million jobs from 1965 to 2000, but from 2000 to 2007 -- before the Great Recession -- manufacturing employment dropped precipitously, falling by 3.5 million jobs. Another 2.3 million manufacturing jobs were lost in the recession and its aftermath. Chapter 7 details the Administration's efforts to reverse this trend and bring manufacturing jobs back to the United States. These efforts include supporting new skills training programs for workers, investing in advanced manufacturing R&D to replenish the technology pipeline and strengthen engineering capabilities, providing tax credits for manufacturers that hire more employees in the United States, and encouraging fair trade by expanding America's global market access and leveling the playing field across nations. Many of these initiatives began during President Obama's first term and contributed to the nearly 500,000 manufacturing jobs that have been added over the last 3 years, the best period of job creation in manufacturing since the 1990s. This turnaround in manufacturing would have been inconceivable even just a few years ago, and sustaining this momentum is a key part of the Obama Administration's second-term agenda for the middle class.

Making the Economy More Resilient to Future Challenges

While the Administration works to repair the damage of the Great Recession and build an economy that works for middle-class families, it is critical that we also take steps to ensure that the economy is resilient in the face of gathering challenges. For example, although much progress has been made in moving America toward a clean energy future that does not depend on foreign oil, more work remains to be done. Chapter 6 details the scientific consensus around climate change and the dangerous consequences that could result if greenhouse gas emissions are not reduced. In addition, Chapter 6 discusses the preparatory steps being taken to avoid these harmful outcomes and ensure the economy's resiliency in the face of these risks. The Administration has increased fuel efficiency standards, launched an array of programs to encourage more efficient household energy use, and provided tax credits to companies developing renewable energy sources -- all actions that will reduce greenhouse gas emissions. In 2012, net imports of petroleum products were at a 20-year low, domestic natural gas production was at an all-time high, and the use of renewable sources like wind and solar had more than doubled from 2008. These are positive steps in the right direction, and the Administration aims to continue this progress in the second term.

Chapter 8 presents the challenges and opportunities in the U.S. agricultural sector, as well as the lessons learned from the rapid productivity advances in agriculture that can be built on to raise job creation and output in other areas of the economy. In 2012, America's farmers faced the most severe drought since the 1950s but showed their resilience as net farm income for the year as a whole is estimated to have fallen just 4 percent from the record high level reached in 2011. In the years ahead, America's farmers have an especially important role to play in helping to feed a growing global population. From 2010 to 2050, the world's population is projected to rise by more than 2 billion people, and most of this increase is expected to occur in developing countries. A growing, increasingly urbanized world population will present unique challenges to the agricultural sector, as urban areas rely heavily on a stable and efficient worldwide food chain to provide nutrientdense and diverse foods. At the same time, trade in agricultural commodities will continue to be a global endeavor in which prices respond to supply and demand conditions around the world. Chapter 8 outlines the steps the Administration is taking to build on our Nation's trade surplus in agricultural products and help farmers manage the risk of volatile prices.

 

CONCLUSION

 

 

As President Obama begins his second term, the U.S. economy is undoubtedly in a far stronger position and headed in a much better direction than it was when he first took office in January 2009, but more work remains to be done. 2012 was a year of progress, with private employers adding more than 2 million jobs and the unemployment rate falling to its lowest level in four years. While the worst of the recession is now behind us, many of its aftereffects still linger, as do a number of underlying, structural issues that built up for decades and could threaten our economy's prosperity in the years ahead. As such, the Administration's efforts in the second term will proceed along two critically important and related tracks: recovering from the past and preparing for the future.

The goals of the President's economic agenda described above -- strengthening the foundations of growth, ensuring fairness for the middle class, and making the economy more resilient to future challenges -- are all mutually reinforcing. America built the most prosperous economy on Earth because we recognized that investments in our individual success were inextricably linked to our success as a nation. Today, investments in research and innovation can lead to new technologies that allow for more effective, less expensive health care or cleaner sources of energy. To facilitate these new technological innovations, it is critical to have a vibrant manufacturing sector with advanced engineering capabilities. A growing manufacturing sector can also provide a path to the middle class for many American workers. And when middle-class families see their incomes rise, their increased spending on goods and services supports broad-based, sustainable economic growth -- in other words, an economy that is built to last. This is just one set of examples of the synergies across the various aspects of the President's economic agenda -- many more can be found in the chapters of this Report.

These synergies underlie the economic recovery that began during President Obama's first term and will drive the Administration's work during his second term to continue moving our economy forward.

 

FOOTNOTE TO CHAPTER 1

 

 

1 Although the changing demographics of the United States are likely to have a large effect on the economy and the Federal budget in the years ahead, the challenges are even greater in other advanced countries. According to United Nations projections (UN 2011), in 2040, the ratio of persons aged 65 and older to persons aged 20-64 will be even higher in Canada, France, Germany, Italy, Japan, Korea, and the United Kingdom than it will be in the United States. The Organisation for Economic Co-operation and Development (OECD 2012) has said that the aging of populations across developed countries will be the main contributor to slower potential output growth in OECD countries in the decades ahead.

 

END OF FOOTNOTE TO CHAPTER 1

 

 

CHAPTER 2

 

 

THE YEAR IN REVIEW AND

 

THE YEARS AHEAD

 

 

Following the recession that began in December 2007, the most severe since the Great Depression, the economy is healing and moving in the right direction. By the fourth quarter of 2012, real output was 2.5 percent above the level at its previous business-cycle peak in the fourth quarter of 2007. The economy has added 6.1 million private sector jobs, and 5.5 million jobs overall, since the level of employment hit bottom in February 2010. During the four quarters of 2012, real gross domestic product (GDP) increased at a moderate 1.6 percent rate. Over the 12 months of the year, 2.2 million jobs were added, and the unemployment rate, while still elevated, dropped 0.7 percentage point to 7.8 percent.

The near-term outlook is for further expansion. Consumer spending is rising moderately, as the gradual healing in the labor market lifts income and as households continue to pay off debt and rebuild wealth. A wide array of indicators suggests the housing sector is finally recovering, and the long contraction in the State and local sector appears to be coming to an end. Financial conditions continue to become more supportive; for example, senior loan officers report that banks have become more willing to lend to both small and large businesses.

Although many of the headwinds that have buffeted growth are receding, some remain. Long-term fiscal sustainability requires a path of declining government spending and rising revenue that will exert fiscal drag on the economy. In addition, ongoing congressional deliberations over the appropriate means through which long-term fiscal sustainability will be achieved foster uncertainty that could weigh on consumer and business confidence. Moreover, tepid growth across the global economy -- particularly in Europe and Asia -- may reduce growth in U.S. exports and slow the rebound in domestic manufacturing activity.

This chapter provides an overview of the economic recovery so far, beginning with a review of notable macroeconomic events of 2012. The chapter then turns to a broader discussion of the recovery in historical context. Although the recovery has been slow by historical standards, much -- perhaps two-thirds, according to a recent study by the Congressional Budget Office (CBO 2012d) -- of the slower growth relative to previous postwar recoveries reflects the long-term demographic shifts discussed in Chapter 4 as well as other long-term structural factors. The remaining one-third reflects unique cyclical factors largely related to the financial crisis, including limitations on the ability of households and small businesses to borrow, which led to associated reductions in consumption and investment; the slow recovery of the housing sector as it works off excess inventories of foreclosed and distressed properties; the contraction of State and local government budgets arising, in part, from the drop in assessed house values and property taxes; softening export demand resulting from slower growth in Asia and Europe; and limitations on conventional monetary policy due to the Federal Reserve's lowering of its main policy rate to zero percent (the "zero lower bound").

As severe as the recent recession was, the drop in real GDP in the United States as a result of the financial crisis of 2007-08 was smaller than both the average decline in other global financial crises over the past 40 years and the contraction in the aftermath of the 1929 stock market crash here in the United States. Furthermore, the recovery since June 2009 has been stronger than in most other developed economies. Active government policies helped the economy avoid an even deeper recession and have played an important role in supporting the recovery. These active policies include the American Recovery and Reinvestment Act (the Recovery Act), the temporary payroll tax cut, the extension of unemployment insurance benefits, and both standard and nonstandard monetary policy conducted by the Federal Reserve.

 

AN ECONOMY IN RECOVERY: KEY EVENTS OF 2012

 

 

The past year was another challenging one for an economy in the midst of a recovery from a global financial crisis. Concern over European sovereign debt and the ongoing fiscal consolidation in Europe contributed to a contraction in the European economy during the year, and growth among several of our Asian trading partners also slowed. Natural disasters such as the severe drought in the Midwest and Hurricane Sandy in the Northeast impaired economic output over much of the year. Although the economic sanctions against Iran do not appear responsible (Box 2-1), retail gasoline prices fluctuated widely over the course of 2012, which may have intermittently dampened economic activity. The possibility of tax increases and mandatory spending cuts that had been scheduled to take place at the beginning of 2013 loomed large as the year closed and may have hampered consumer and business sentiment.

Real GDP rose 1.6 percent over the four quarters of 2012, a bit below the pace in 2011 (quarterly figures are shown in Figure 2-1). Growth was uneven (but no more than usual) throughout the course of the year, reflecting, in part, the impact of the drought and Hurricane Sandy, as well as outsized swings in Federal defense outlays and inventory investment. Outside of these factors, business fixed investment and exports slowed notably from 2011. In contrast, personal consumption spending continued to post moderate gains, rising 1.9 percent over the four quarters of 2012, matching the rate of growth recorded in 2011. The fiscal contraction among State and local governments appears to be easing somewhat, and the residential construction sector, which turned a corner in 2011, strengthened further in 2012, growing for seven consecutive quarters for the first time since 2004-05.

The recovery in payroll employment, like that in real output, was uneven. Payrolls expanded briskly at the beginning of the year, but job growth slowed in the spring and early summer before picking up again in the late summer and fall. The fact that the worst months of the crisis occurred during the winter raises the question of whether normal seasonal adjustment procedures contributed volatility to higher frequency indicators, but that does not seem to be the case, as discussed in Data Watch 2-1. The unemployment rate, which fell 0.8 percentage point during 2011, fell another 0.7 percentage point during 2012, reaching 7.8 percent by the end of the year. The drop in the jobless rate during 2012 was concentrated in the first and third quarters of the year, with most -- roughly 90 percent -- of this decline accounted for by employment growth rather than withdrawal from the labor force.

 

Figure 2-1

 

Real GDP Growth, 2007-2012

 

 

 

 

Note: Shading denotes recession.

Source: Bureau of Economic Analysis, National Income and Product Accounts.

 

______________________________________________________________________

 

 

Box 2-1: Effectiveness of Iran Sanctions

 

 

In cooperation with an international coalition, the United States has established strict economic sanctions against the Islamic Republic of Iran, sanctions described by this Administration and others as "comprehensive and biting." The goal of these sanctions is to persuade the Iranian government to abandon its nuclear weapons program. Since President Obama took office, he has steadily increased unilateral and multilateral pressure on Iran because of its inability to meet its international obligations. As a part of that effort, Congress passed and the President signed the Comprehensive Iran Sanctions, Accountability, and Divestment Act of 2010, the National Defense Authorization Act for Fiscal Year 2012, and the Iran Threat Reduction and Syria Human Rights Act of 2012. These laws increased our ability to target the Iranian Central Bank, private banks supporting the Iranian regime, and -- importantly -- the Iranian petroleum sector. In addition to these efforts with Congress, the President has signed Executive Orders imposing additional sanctions against the Iranian energy and petrochemical sectors. These actions received support from members of the international community, including the European Union and our allies in the Middle East. The United States has also worked to establish multilateral sanctions. For example, the United States collaborated with other members of the United Nations Security Council to adopt Resolution 1929, which called on Iran to end its nuclear program and imposed the broadest multilateral sanctions ever faced by the regime.

For Iran, the consequences of the sanctions have been severe. Iranian President Mahmoud Ahmadinejad called these sanctions "the most severe and strictest sanctions ever imposed on a country." The value of Iran's currency, the rial, has dropped substantially in 2012. Governments and private firms from around the world have ended business with, and divested from, Iran, as these actions now carry a heavy price. And perhaps most importantly, oil production in Iran has nosedived (see the figure below). According to the U.S. Energy Information Administration (EIA), Iran's crude oil production, which averaged 3.7 million barrels a day in 2011, dropped to approximately 2.7 million barrels a day by the end of 2012, a decline of about 30 percent. That amounts to billions of dollars in lost revenues for the regime.

The effect of these sanctions on the U.S. economy has been minimal. The sanctions do not appear to have increased the price of oil. As shown in the figure above, while Iranian oil production has dropped, world supply has not. The effects of the sanctions are reviewed regularly; for example, Federal agencies, such as the EIA, watch closely for developments in international energy markets. The President and Congress have structured the implementation of the sanctions to minimize any impact on global energy markets and, by extension, the U.S. economy, and the authorities granted to the executive branch allow us to continue to monitor those effects going forward.

Sanctions do not always prevent or replace war. Indeed, sanctions have sometimes led to war, as shown by Lektzian and Sprecher (2007). Moreover, the fact that Iran's currency has depreciated, its oil production and exports have plunged, and its economy has slowed does not, by itself, fully answer the question: "Are the sanctions working?" The sanctions will have succeeded if and when Iran ends its nuclear program.

Evidence on the effectiveness of sanctions in other settings is mixed. In a widely-cited study, Hufbauer, Shott, and Elliott (1990) find that the rate of success of economic sanctions is low -- about 35 percent. Some argue that even 35 percent is an overestimate (Pape 1997). However, Morgan, Bapat, and Krustev (2009) find that adjusting the sample of sanctions to include threats of sanctions in addition to sanctions actually imposed, and limiting the focus to more recent events, increases the success rate from 35 percent to 45 percent. The success rate is even higher when costs borne by the target are severe or when sanctions are multilateral, both of which are the case with Iran. Moreover, Marinov (2005) finds economic sanctions do tend to destabilize the governments they target, that is, they increase the probability of leadership or regime change.

Iran Oil Production and World Supply, 2009-2013

 

 

 

 

Source: Energy Information Administration.

 

______________________________________________________________________

 

 

European Crisis and the Slowdown in Global Growth

In 2012, the consequences of the European debt crisis continued to affect the world economy. In many advanced economies, fiscal consolidation, vulnerable financial systems, and market uncertainty have suppressed demand, and world economic growth has suffered as a consequence. While these adverse shocks are, for the most part, external to the United States, the globalized nature of world trade and financial markets means that the United States cannot escape their impact. Likewise, the turmoil in European financial markets led U.S. branches of foreign banks to tighten credit standards for commercial and industrial loans.

Hurricane Sandy and the Drought

Natural disasters cause human suffering and physical destruction. From the perspective of economic activity, their widespread disruptions also lead to lost work and output. Historical experience suggests, however, that over time much of this lost production is recouped. After storms, some of the missed work is made up and sizable additional expenditures are required for cleanup, repairs, and rebuilding. Thus, while hurricanes can have a major impact on regional economies, national trends in economic activity typically have not been affected by calamities such as hurricanes and droughts.

Hurricane Sandy is now estimated to have resulted in $35.8 billion in damages to private fixed assets according to the Commerce Department, which would rank it as the second costliest natural disaster in recent U.S. history after adjusting for inflation, though still well behind Hurricane Katrina in 2005. In addition, power outages that affected 8.2 million customers on October 30, and left 930,000 without power a week later, rendered many workers unable to perform their jobs. The storm also disrupted transportation centers such as seaports, airports, and rail lines, as well as refineries and factories, many of which were restored only gradually.

All told, analysts currently estimate that Hurricane Sandy lowered real GDP growth in the fourth quarter by around 0.2 to 0.5 percentage point at an annual rate. Although indicators such as industrial production, vehicle sales, and jobless claims were adversely affected in October or early November, they subsequently improved and rebuilding activity is likely to provide some support to economic growth going forward. The region hit by Sandy has ample spare capacity available to be mobilized for storm recovery efforts: in October 2012, just before the storm hit, the unemployment rate was 0.6 percentage point higher in the five states most directly affected by Hurricane Sandy than in the rest of the country. Construction employment, in particular, had declined in the first 10 months of 2012 across these five states while seeming to have stabilized or expanded elsewhere. Supplemental Federal relief for reconstruction after Sandy, which was enacted in January 2013, should provide needed repairs and reconstruction and thereby support short-term economic growth in the region.

As a result of the severe drought in the Midwest that damaged corn and soybean harvests, farm inventory investment subtracted an average of one-fourth of a percentage point from real GDP growth in the second and third quarters of 2012 (for additional discussion, see Chapter 8). In 2013, the initial estimates of quarterly farm output will be based on the Agriculture Department's initial projection of annual farm output, which in turn will be based on an assumption of normal growing conditions. As a result, farm production, as measured in the National Income and Product Accounts, will probably jump up beginning in first quarter of 2013, bringing with it an associated bump up in estimated GDP growth.

Monetary Policy

In 2012, the Federal Open Market Committee (FOMC) continued to provide substantial policy accommodation and announced several new steps, including for the first time linking its forward guidance for the main policy interest rate to a specific level of the unemployment rate.

Between September 2011 and June 2012, the FOMC conducted the first installment of its Maturity Extension Program, widely known as Operation Twist. As first announced, the Fed said it would purchase "by the end of June 2012, $400 billion of Treasury securities with remaining maturities of 6 years to 30 years and . . . sell an equal amount of Treasury securities with remaining maturities of 3 years or less." According to the FOMC, the objective of this program was to "put downward pressure on longer-term interest rates" and thus provide an additional stimulus for the overall economy. In June 2012, the Committee decided to continue this program at a pace of approximately $45 billion a month, which corresponded to an additional "face value of about $267 billion by the end of December 2012," according to the minutes of the June meeting. Then, in September 2012, the FOMC announced it would further "increase policy accommodation by purchasing additional agency mortgage-backed securities at a pace of $40 billion per month."

 

______________________________________________________________________

 

 

Data Watch 2-1: Seasonal Adjustment in Light

 

of the Great Recession

 

 

For the purposes of economic analysis, researchers are primarily interested in the longer-term direction of a time series and any deviations from that trend. Seasonal fluctuations in the data arising from summer holidays, seasonal shopping, and so forth can obscure these trends and deviations. As a result, most public sources of economic data endeavor to remove normal seasonal patterns from their high-frequency indicators. Unfortunately, this process of seasonally adjusting economic data is fraught with complexity. Seasonal factors cannot be directly observed and must be estimated using various statistical techniques. Moreover, the seasonal patterns for a particular series may not be constant over time. Thus, the accurate estimation of seasonal patterns is a challenge of great importance to the economics community and policymakers.

A number of analysts have argued that the severity of the Great Recession may have distorted several high-frequency economic indicators. The Great Recession, which lasted from December 2007 through June 2009, was particularly acute during the fall of 2008 and the winter of 2009. Real GDP fell more than 7 percent at an annual rate over the fourth quarter of 2008 and the first quarter of 2009, and total nonfarm payroll employment plunged by more than 4 million jobs from September 2008 to March 2009. Given the severity of the downturn during this period, some commentators have hypothesized that the outsized decline in economic activity may have been inadvertently incorporated into the seasonal factors for several key economic indicators. And as a consequence of this statistical bias in the seasonal adjustment process, these observers have raised concerns that the pace of the current recovery has exhibited an abnormal seasonal pattern in which economic activity has appeared not only substantially stronger than it really is during the fall and winter but also correspondingly weaker during the spring and summer.

A few providers of economic data have acknowledged this concern and noted that unusually sharp swings in certain indicators may not be properly accounted for by standard seasonal adjustment techniques. The Federal Reserve reported that the application of default seasonal adjustment procedures to its monthly industrial production data would have artificially raised output in many industries during the first halves of the years 2008 through 2010, if these distortions not been identified in advance and corrected (Federal Reserve Board of Governors 2011). And the Institute for Supply Management concluded that its typical seasonal adjustment procedures did not adequately identify outlier observations during the recent recession. As a result, it introduced more precise criteria for the detection of outliers as part of the seasonal adjustment of its purchasing manager survey data (Institute for Supply Management 2012). Nevertheless, it is important to emphasize that these particular issues pertain to the use of default seasonal adjustment techniques. In general, statistical agencies approach the seasonal adjustment of economic data idiosyncratically based upon the unique characteristics of each individual time series.

Indeed, detailed studies of a wide range of principal economic indicators suggest that the seasonal adjustment techniques that had already been employed by the Bureau of Labor Statistics (BLS) adequately accounted for the effects of the Great Recession. BLS analysts calculated alternative seasonal factors for total nonfarm payroll employment after manually excluding the sharp declines that were recorded during the downturn (Kropf and Hudson 2012). This counterfactual experiment failed to generate meaningful revisions to the actual published estimates of total nonfarm payroll employment since January 2010. In fact, the BLS analysts concluded that the implementation of these counterfactual seasonal factors would have revised total nonfarm payroll employment upward by a mere 24,000 jobs over the second and third quarters of 2011 (in other words, an average of 4,000 jobs a month) and downward by just 19,000 jobs over the fourth quarter of 2011 and the first quarter of 2012 (or an average of roughly 3,000 jobs a month). BLS analysts also thoroughly investigated the seasonal adjustment of the Current Population Survey data over the course of the recovery (Evans and Tiller 2012). This inquiry showed that alternative assumptions regarding seasonal adjustment did not meaningfully affect estimates of the unemployment rate since 2007.

Macroeconomic Advisers (2012) tested the stability of seasonally adjusted nominal GDP by comparing the official estimates to a proxy series that had been constructed using the source data for the national accounts. Contrary to the hypothesis that inaccuracies in the seasonal adjustment process have been artificially suppressing economic activity during the spring and summer months of the current recovery, this analysis found that seasonal factors had not been subtracting as much from GDP growth during the second and third quarters of each calendar year as they had before the downturn. All told, these analyses provide little evidence to support serious concerns over the soundness of seasonally adjusted high-frequency economic variables.

______________________________________________________________________

 

 

The September and June actions together, the Committee said, were intended to increase the Federal Reserve's "holdings of longer-term securities by about $85 billion each month through the end of the year." In December 2012, the Committee announced that it would replace the expiring Maturity Extension Program with a program of purchases of longer-dated Treasuries at a pace of $45 billion a month, thereby further expanding its balance sheet, rather than funding these purchases with the sale of shorter-dated securities, as was the practice under Operation Twist. These purchases, combined with its September 2012 decision to purchase $40 billion a month in agency mortgage-backed securities, kept total purchases of longer-term securities at $85 billion a month.

The nature of the Fed's forward guidance also evolved over the year. The FOMC announced in September 2012 that it would explicitly condition future policy decisions on progress in the labor market and issued additional forward guidance that the Fed's main policy interest rate would likely remain low through mid-2015, an extension from late 2014 as previously announced. In December 2012, the Committee went a step further and announced that it would maintain the "exceptionally low range for the federal funds rate . . . at least as long as the unemployment rate remains above 6 1/2 percent, inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored." The explicit link to numerical values of economic variables replaced the previous reference to a "mid-2015" reference date that had been introduced in September.

In August 2012, during a speech at the annual Federal Reserve Bank of Kansas City Economic Symposium, Federal Reserve Chairman Ben Bernanke assessed the effectiveness of the balance sheet and forward guidance policies that had been implemented in response to the recession. Bernanke (2012a) surveyed research finding that large-scale asset purchases (LSAPs) had significantly lowered yields on long-term Treasury notes, corporate bonds, and mortgage-backed securities; reduced retail mortgage rates; and also boosted stock prices (see for example, Krishnamurthy and Vissing-Jorgenson 2011). One study by Chung and others (2012) used the Federal Reserve Board's FRB/US model of the economy and found that the early phase of the Fed's LSAPs may have raised the level of real GDP by almost 3 percent and increased private payroll employment by more than 2 million jobs, relative to what otherwise would have occurred. Although Chairman Bernanke cautioned against putting too much weight on the estimates of any particular study, he concluded that "a balanced reading of the evidence supports the conclusion that central bank securities purchases have provided meaningful support to the economic recovery while mitigating deflationary risks."

Fiscal Policy

After months of negotiations, in February 2012 Congress extended both the 2 percentage point cut in the payroll tax and the Emergency Unemployment Compensation program through the end of the year. These temporary measures, which were among the Administration's key economic priorities for 2012, had originally been put in place with the passage of the 2010 Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act. The extension through December 2012 provided critical support to American families trying to weather the various headwinds that threatened the recovery over the course of the year.

The economy faced great uncertainty as the end of calendar year 2012 approached. As a result of the confluence of various policies that had been passed in previous years, the economy faced a "fiscal cliff" of across-the-board tax hikes as the Bush-era tax cuts expired, a sharp reduction of the Alternative Minimum Tax (AMT) exemption amounts to the levels that had been in effect in 2001, the imposition of substantial spending cuts through budget sequestration, and the expiration of a number of other tax provisions. In addition, temporary measures to support the economy, including the extension of unemployment insurance benefits and the payroll tax reduction, were also set to expire. As the end-of-year deadline approached, uncertainty in financial markets ticked up, although not as much as during the August 2011 debt ceiling debate. This uncertainty was partly resolved by the passage of the American Taxpayer Relief Act by the House on January 1, 2013, averting what could have been sharply contractionary policies.1

Looking ahead, the American Taxpayer Relief Act -- which permanently extends the middle-class tax cuts, indexes the AMT to inflation, and raises rates on the highest-income taxpayers in order to reduce the deficit relative to the previous policy baseline (see Chapter 3) -- has removed much of the uncertainty about taxes facing the economy.

 

DEVELOPMENTS IN 2012 AND THE NEAR-TERM OUTLOOK

 

 

Labor Market Trends

The labor market continued to heal in 2012. The private sector added 2.2 million jobs, although State and local government employment fell by 32,000, after falling by 286,000 in 2011. Private sector payroll employment has grown in each month since February 2010. Focusing on 12-month changes to abstract from monthly and seasonal volatility, the 12-month change in total nonfarm payroll employment excluding Census hiring has been smooth, hovering around 2 million jobs since the fall of 2011, as shown in Figure 2-2.

Private-sector job growth during the current recovery has been roughly comparable with that in the 1991 recovery and noticeably faster than in the 2001 recovery, as illustrated in Figure 2-3. As is typical, the recovery in hiring since 2009 lagged the recovery in output. Private nonfarm payrolls in the current recovery began growing 9 months after the business-cycle trough. By comparison, payrolls first began expanding consistently 12 months into the 1990-91 recovery, and sustained private-sector job growth in the 2001 recovery did not begin until 21 months after the official end date of the recession. Thus, although the 2007-09 recession lasted longer and led to deeper job losses than did the recessions of 1990-91 and 2001, recovery in the labor market began somewhat sooner.

 

Figure 2-2

 

Nonfarm Payroll Employment, 2007-2013

 

 

 

 

Note: Shading denotes recession. Total excludes temporary decennial Census workers.

Source: Bureau of Labor Statistics, Current Employment Statistics.

 

Figure 2-3

 

Private Nonfarm Employment During Recent Recoveries

 

 

 

 

Source: Bureau of Labor Statistics, Current Employment Statistics; National Bureau of Economic Research; CEA calculations.

Despite continuing improvements in hiring, the unemployment rate remains elevated, reflecting both the deep losses during the recession and the steady but moderate pace of hiring during the recovery. The unemployment rate has receded from its peak of 10.0 percent in October 2009 to 7.8 percent in December 2012, with 0.7 percentage point of that decline during the 12 months of 2012 (Figure 2-4). Layoffs -- as measured by the four-week average of initial claims for unemployment insurance -- fell in 2012 (Figure 2-5), and other indicators of labor market adjustment such as the workweek continued to show improvement. By December 2012, the workweek had increased to 34.4 hours, recovering most of the 0.8 hour lost during the recession.2

Almost all of the decline in the unemployment rate in 2012 reflects growth in employment rather than labor force withdrawal.3 Nevertheless, the recession coincided with a sharp drop in the labor force participation rate, which fell from 66.0 percent in December 2007 to 64.9 percent in February 2010 -- a period when the economy shed jobs at an average rate of 320,000 a month. Since then, labor force participation has continued to decline, reaching 63.6 percent by December 2012.

 

Figure 2-4

 

Unemployment Rate, 1979-2013

 

 

 

 

Note: Shading denotes recession.

Source: Bureau of Labor Statistics, Current Population Survey.

 

Figure 2-5

 

Initial Unemployment Insurance Claims, 2004-2013

 

 

 

 

Note: Shading denotes recession. Four-week moving average.

Source: Department of Labor, Employment and Training Administration.

To what extent can this sharp drop in the labor force participation rate be attributed to the prolonged slack in the labor market? Answering this question requires distinguishing between cyclical movements arising from the prolonged downturn and the demographic trends of an aging, and thus retiring, workforce. To this end, Table 2-1 provides a decomposition of the labor force participation rate into a trend component and a cyclical component over the current business cycle. The trend, or demographic, component from 2007-12 is estimated by extrapolating a linear trend in the labor force participation rate from the 10 years preceding 2007,4 and the cyclical component is computed as the difference between the actual labor force participation rate and this trend.

As can be seen in the bottom half of Table 2-1, the labor force participation rate fell by 2.2 percentage points from 2007-12. Of that drop, 1.2 percentage points are attributed to a declining trend caused primarily by the aging of the workforce, while 1.0 percentage point is cyclical. An analogous calculation for 1980-85 -- the only other postwar period that includes a double-digit unemployment rate -- shows that the labor force participation rate rose by 1.0 percentage point over the twin recessions of the early 1980s. But at that time, trend labor force participation was rising by 2.0 percentage points -- a consequence primarily of the rising participation of women during that period -- so the cyclical component during the early 1980s declined by 0.9 percentage point. Thus, the cyclical component of the change in the labor force participation rate during 2007-12 is close to its value over 1980-85, and so, by this measure, the recession-induced rate of labor force decline differs little from the early 1980s.

Consumption and Saving

Consumer spending, which accounts for approximately 70 percent of GDP, rose moderately in 2012, as credit conditions continued to ease, household liabilities fell relative to income, and the labor market improved. Real household consumption grew 1.9 percent during the four quarters of the year and was supported by an extension of the payroll tax cut, which first went into effect in January 2011 as part of the Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act.

                                   Table 2-1

 

            Labor Force Participation Rates, 1980-1985 and 2007-2012

 

 ______________________________________________________________________________

 

 

                    Labor Force Participation Rate, Percent

 

 ______________________________________________________________________________

 

 

             Year of cycle    (Projection for       After five years

 

 Years       peak (actual)    five years ahead      (actual)

 

 ______________________________________________________________________________

 

 

 1980-1985       63.8              65.7                   64.8

 

 

 2007-2012       65.9              64.6                   63.7

 

 ______________________________________________________________________________

 

 

              Decomposition of Five-Year Change, Percentage Points

 

 ______________________________________________________________________________

 

 

                Total             Trend                    Cycle

 

 ______________________________________________________________________________

 

 

 1980-1985       1.0                2.0                    -0.9

 

 

 2007-2012      -2.2               -1.2                    -1.0

 

 

 ______________________________________________________________________________

 

 

 Note: Numbers may not sum due to rounding. Based on annual averages and

 

 historically adjusted by the CEA for population controls. The projections for

 

 five years ahead are estimated by extrapolating a linear trend in age/gender-

 

 specific labor force participation rates from the 10 years preceding 1980 and

 

 2007, respectively.

 

 

 Source: Bureau of Labor Statistics, Current Population Survey; CEA

 

 calculations.

 

 

Several key developments in 2012 shaped the contours of consumer spending.

Household Income in 2012. Nominal personal income grew 5.0 percent during the four quarters of 2012, a somewhat faster pace of growth than in 2011. Growth in nominal personal income over the course of the year was largely attributable to gains in employee wages, salaries, and benefits. Real disposable personal income, which is personal income less personal taxes and adjusted for price inflation, rose 3.2 percent over the four quarters of 2012, a substantial improvement over the 2011 increase of 0.3 percent. The pattern partly reflects a moderation in inflation mostly due to a drop in energy price inflation. The expiration of the temporary payroll tax cut will subtract about $120 billion from disposable income in 2013.

Household Wealth and Saving in 2012. Households continued to rebuild their balance sheets in the aftermath of the worst economic downturn since the Great Depression. On balance, the wealth-to-income ratio, depicted in Figure 2-6, rose over the first three quarters of 2012 and has improved considerably since the beginning of 2009. Consumption as a share of disposable income tends to fluctuate with the wealth-to-income ratio. As a rule of thumb, a one dollar drop in wealth reduces annual consumer spending by two to five cents. The decline in the wealth-to-income ratio from the first quarter of 2007 to its low point in the first quarter of 2009 was equivalent to roughly 1.7 years of disposable income. Through the third quarter of 2012, this measure regained the equivalent of nearly 0.7 year of disposable income. This simple framework suggests that the household wealth lost during the recession has not yet been recovered and that this loss of wealth has left the level of consumption roughly 2 to 6 percent below what it would have been otherwise. Much of that loss of wealth resulted from the bursting of the housing bubble, and the wealth-to-income ratio now is where it was in the mid-1990s (before the information technology stock price bubble) and early 2000s (before the housing bubble).

 

Figure 2-6

 

Consumption and Wealth Relative to

 

Disposable Personal Income (DPI), 1952-2012

 

 

 

 

Note: Shading denotes recession. Consumption-to-DPI line includes 2012:Q4.

Source: Bureau of Economic Analysis, National Income and Product Accounts; Federal Reserve Board, Z.1; CEA calculations.

The personal saving rate -- expressed in the National Income and Product Accounts as personal saving as a share of disposable personal income -- averaged 3.9 percent in 2012, a bit lower than the rate observed in 2011. The rate of personal saving jumped during the recession as households sharply curtailed spending in response to the crisis, but overall, the saving rate fell modestly over the course of the recovery and is now at the level it was in the early 2000s.

Household Credit and Deleveraging in 2012. Lending standards for consumers, as reported in the Federal Reserve's Senior Loan Officer Opinion Survey, eased for the third consecutive year. Moreover, driven by a surge in nonrevolving lending categories (such as auto and student loans), consumer credit expanded 5.7 percent at an annual rate over the four quarters of 2012. However, because mortgage credit continued to decline, the overall level of household debt decreased 0.6 percent at an annual rate over the first three quarters of 2012. Household debt has declined every year since 2007, as households continue to deleverage.

Although household debt increased in the period before the financial crisis, the extent to which household leverage has restrained consumer spending during the recovery remains unsettled. Traditional models of consumption imply that, absent borrowing constraints, households consume a fraction of their expected lifetime wealth, which implies that the consumption-wealth ratio fluctuates around its mean (Campbell 1987; Lettau and Ludvigson 2003). This theory and its extensions imply that consumption and saving will adjust to maintain appropriate lifetime savings, so for example a loss in housing wealth will cause consumers to increase saving, as they did during and shortly after the recession, to pay down debts and rebuild retirement savings. But consumers, of course, face borrowing constraints and can be locked into mortgage or debt payment streams that might impose additional, direct limitations on consumption. Dynan (2012) and Mian, Rao, and Sufi (2012) provide evidence that these additional effects of the so-called debt overhang from the collapse in housing have further suppressed consumption during the recovery.

Whether one looks at wealth or leverage, household finances have improved substantially in recent years. From the third quarter of 2007 to the first quarter of 2009, household net worth fell by an estimated $16.1 trillion. By the third quarter of 2012, however, households had added $13.5 trillion, recovering more than 80 percent of wealth lost. Households have also made progress in reducing debt burdens. Total household debt stood at 81.4 percent of GDP in the third quarter of 2012, the lowest since 2003 and down from a peak of nearly 98 percent in 2009. Moreover, payments on mortgage and consumer debt took up about 10.6 percent of household disposable income in the third quarter of 2012, the lowest household debt service ratio since 1993.

Effect of Rising Inequality on Consumption. Some of the recent patterns in aggregate consumption behavior -- including the sluggish growth in consumer spending relative to previous recoveries -- may reflect the sharp rise in income inequality over the past 30 years. According to CBO (2012c), after-tax incomes of the top 1 percent of households rose by more than 155 percent from 1979 to 2009, while those of median households increased by less than 33 percent. About one-fifth of this increase in inequality is due to the declining share of income that goes to labor (Box 2-2). As discussed in the 2012 Economic Report of the President, some research suggests that this rise in inequality may have reduced aggregate demand, because the highest income earners typically spend a lower share of their income -- at least over intermediate time horizons -- than do other income groups.

Business Fixed Investment

Real business fixed investment grew 4.6 percent during the four quarters of 2012, after rising 10.2 percent in the four quarters of 2011. Both of its principal components -- equipment and software investment and nonresidential structures investment -- contributed to this slower growth. Investment in equipment and software slowed to 4.6 percent over the four quarters of 2012, down from robust growth of 11.4 percent in 2011. Investment in nonresidential structures increased 4.7 percent, following a 6.9 percent increase in 2011.

Within equipment and software investment, major components such as industrial equipment, transportation equipment, and information-processing equipment all posted notably slower growth in 2012 than in 2011. The relatively stable pace of GDP growth during 2011 and 2012 provided little overall stimulus to equipment investment. The slowing pattern of equipment investment growth may also partially reflect the reduced pace of bonus depreciation, which had been available at a 100 percent rate during 2011 but fell to 50 percent in 2012. (Bonus depreciation encourages investment by allowing firms to write-off equipment purchases immediately, rather than over an extended period). The American Taxpayer Relief Act (ATRA) extended the 50 percent rate through 2013.

Real investment in nonresidential structures grew 4.7 percent during the four quarters of 2012, down from 6.9 percent during 2011. Solid growth in office buildings and electric power plants was partially offset by a decline in petroleum and natural gas drilling, which followed strong growth during the preceding two years.

Despite the slower growth of business investment in 2012, the sector is poised to grow rapidly if demand accelerates because corporations have ample internal funds (Figure 2-7). Corporate profits continued to rise through the first three quarters of 2012, exceeding their pre-recession level, even as a percent of GDP, while corporate dividends remained at roughly pre-recession levels through the first three quarters of the year before spiking in the fourth quarter, before ATRA was passed. As a consequence, corporate cash flow, the sum of undistributed profits and depreciation that represents the internal funds that corporations have available for investment, has remained elevated during the recovery. Cash flow now exceeds investment, an unusual situation insofar as corporations usually have to borrow funds to finance their capital spending plans. A large portion of these investable funds has been channeled to financial investments rather than to new physical capital, as can be seen by the rising level of liquid assets held by nonfinancial corporations. Indeed, as of the third quarter of 2012, nonfinancial corporations held $1.7 trillion of liquid financial assets.

 

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Box 2-2: Why Is the Labor Share Declining?

 

 

The "labor share" is the fraction of income that is paid to workers in wages, bonuses, and other compensation. Income of self-employed workers is also included in some definitions of labor income, as it is in the figure below. The labor share in the United States was remarkably stable in the post-war period until the early 2000s. Since then, it has dropped 5 percentage points. Because capital income is distributed more unequally than labor income, the decline in the labor share accounts for some, but not all, of the rise in inequality. CBO (2011) has estimated that 21 percent of the increase in inequality from 1979 to 2007 was accounted for by shifts between labor and other sources of income, with the remaining 79 percent accounted for by rising inequality within capital, business, or labor income. Nevertheless, the decline in the labor share has adverse implications for government revenues because wages and salaries are taxed at a higher rate than other major income sources.

The decline in the labor share is widespread across industries and across countries. An examination of the United States shows that the labor share has declined since 2000 in every major private industry except construction, although about half of the decline is attributable to manufacturing. Moreover, for 22 other developed economies (weighted by their GDP converted to dollars at current exchange rates), the labor share fell from 72 percent in 1980 to 60 percent in 2005.

Proposed explanations for the declining labor share in the United States and abroad include changes in technology, increasing globalization, changes in market structure, and the declining negotiating power of labor. Changes in technology can affect the share of income going to labor by changing the nature of the labor needed for production. More specifically, much of the investment made by firms over the past two decades has been in information technology, and some economists have suggested that information technology reduces the need for traditional types of skilled labor (Bound and Johnson 1992; Autor, Katz, and Krueger 1998). According to this argument, the labor share has fallen because traditional middle-skill work is being supplanted by computers, and the marginal product of labor has declined.

Increasing globalization also puts pressure on wages, especially wages in the production of tradable goods that can be produced in emerging market countries and some less-developed countries. These pressures on wages can lead to reductions in the labor share. Changes in market structure and in the negotiating power of labor could also lead to a declining labor share. One such change is the decline in unions and collective bargaining agreements in the United States.

These explanations are neither exhaustive nor mutually exclusive (OECD 2012). Overall, these changes have moved the distribution of income towards a winner-take-all society.

Labor Share of Nonfarm Business Income, 1947-2012

 

 

 

 

Note: "Other Developed Countries" refers to the OECD member states. The U.S. labor share includes imputed proprietor's income. The OECD labor share excludes the farm, mining, fuel, and real estate sectors, and is aggregated by the CEA on an annual basis for 22 countries using GDP weights at current exchange rates.

Source: Bureau of Labor Statistics, Productivity and Costs; OECD, Annual Indicators.

 

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Business Inventories

Inventory investment -- measured as the change in inventories from one quarter to the next -- is typically an important contributor to the changes in real GDP during recessions and the early stages of recoveries. During the recession, inventories fell but by less than sales, so the ratio of inventories to sales rose; through the first two years of the recovery, inventories rose less rapidly than sales, and by the end of 2011, the inventory-sales ratio had returned to its level of the mid-2000s. With this inventory cycle behind us, real private nonfarm inventory accumulation in 2012 made only a small, slightly positive contribution to real GDP growth. Looking ahead, inventory investment is expected to make only a minor contribution to growth during 2013.

Government Outlays, Consumption, and Investment

The Federal budget deficit during fiscal year (FY) 2012 -- which ended on September 30, 2012 -- was $1.1 trillion, about $200 billion less than the preceding year. As a share of GDP, the deficit fell to 7.0 percent in FY 2012, down from 8.7 percent in FY 2011.

 

Figure 2-7

 

Labor Share of Nonfarm Business Income, 1947-2012

 

 

 

 

Note: Shading denotes recession. Potential GDP is a CBO estimate. Cash flow, from the National Income and Product Accounts, and liquid assets held by nonfinancial corporations are plotted using three-quarter moving averages. Nonresidential fixed investment line includes 2012:Q4.

Source: Bureau of Economic Analysis, National Income and Product Accounts; Federal Reserve Board, Z.1; Congressional Budget Office.

As measured in the Federal unified budget, Federal receipts rose 6.4 percent in FY 2012 compared with the previous year, reflecting a 3.7 percent increase in individual income tax receipts, a 33.8 percent increase in corporate tax receipts, and a 3.2 percent increase in receipts for social insurance. The $61 billion increase in corporate tax receipts accounted for 42 percent of the rise in overall revenues. Current dollar values of individual income taxes and social insurance and retirement receipts have each risen to 97 percent of their FY 2007 levels, while corporate tax receipts were just 65 percent of their previous high.

Federal outlays declined 1.7 percent in nominal dollars in FY 2012 from FY 2011, falling from 24.1 percent of GDP to 22.8 percent of GDP. The decline in spending during the fiscal year reflected several factors, including reduced outlays on unemployment insurance, Medicaid, and defense. Specifically, fewer individuals received unemployment benefits, a temporary increase in Federal aid to states for Medicaid expired, and the number of U.S. Army personnel stationed in Afghanistan and Iraq was reduced.

During the four quarters of calendar year 2012, the National Income and Product Accounts measure of real Federal expenditures on consumption and gross investment (which does not include Federal transfers to States and individuals) declined 2.8 percent, as a 4.9 percent decline in real defense spending more than offset a 1.5 percent increase in real nondefense spending.

The Federal deficit as a share of GDP fell for the third consecutive fiscal year in 2012. The change in this ratio is one measure of the drag on the economy imposed by fiscal consolidation, and in FY 2012, this drag was 1.7 percentage points (the difference between the deficit-GDP ratio of 8.7 percent in FY 2011 and 7.0 percent in FY 2012). Moreover, the drop in the deficit-to-GDP ratio from 10.1 percent in 2009 to 7.0 percent in 2012 is the largest 3-year decrease since 1949. Looking further ahead, policy changes to be recommended in the FY 2014 Budget will put debt as a share of the economy on a stable path and place the budget in a fiscally sustainable position in the 10-year budget window.

State and Local Governments

Although State and local governments continued to experience fiscal pressure in 2012, the long contraction in the sector finally appears to be coming to an end. State and local consumption and investment (purchases) have shown unprecedented weakness compared with previous recoveries (Figure 2-8). From the end of the recession in mid-2009 to the fourth quarter of 2012, real State and local purchases declined 6.8 percent. By contrast, during the comparable period of each of the six previous recoveries, real State and local purchases posted positive growth, averaging an increase of 10.3 percent over the first three and a half years of the recovery. Nominal State and local government tax receipts increased during the first three quarters of 2012. Federal support from the Recovery Act -- which helped support State and local governments during 2009 and 2010 -- phased out during 2011 and 2012. And while the pace of State and local government job losses eased in 2012, employment in this sector remained 724,000 jobs below its previous peak as of the end of the year, with more than 40 percent of the loss in educational services jobs.

 

Figure 2-8

 

Real State and Local Government Purchases During Recoveries

 

 

 

 

Note: The 1960-2007 average excludes the 1980 recession due to overlap with the 1981-82 recession.

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

On the revenue side, State and local tax receipts rose at an annual rate of 2.6 percent during the first three quarters of 2012, a bit below the pace during 2011. The slow recovery in State and local tax revenue reflects in part the effect of lower house prices on property tax collections. Historically, property taxes have accounted for about 30 percent of State and local government tax receipts and are critical to local governments, but property tax receipts have edged up slowly in the years after the housing bubble burst. Nationwide, property tax receipts have grown just 11.4 percent over the past five years, only slightly faster than inflation, compared with 36.0 percent growth during the preceding five year period from 2002-07. Moreover, State and local governments are still feeling the effect of the drop in house prices: because property value assessments lag behind market valuations, the effect of house prices on property tax receipts operates with a delay of about three years (Lutz 2008). Although policymakers in some states have increased the tax rate on assessed property values to partially offset declines in those values (Lutz, Molloy, and Shan 2011), local governments have still needed to adjust spending to make up for the lost revenue. Despite these difficulties, the recent upturn in house prices suggests that improvement in State and local government finances is on the horizon. In addition, revenues from sales and income taxes -- which make up about 50 to 60 percent of State and local tax receipts -- have also continued to recover, with income tax collections up 7.6 percent during the four quarters of 2012, and sales taxes growing 2.2 percent.

Another factor weighing on State and local government revenues has been the phase-out of the Recovery Act. After rising notably in 2009 and 2010, Federal grants-in-aid to State and local governments plunged $82.1 billion in 2011 before stabilizing during 2012. Both the earlier increase and the recent return to a lower level were largely attributable to the Recovery Act, which was designed to offer temporary support to State and local governments. The portion of Federal grants-in-aid to the States from Recovery Act programs stood at just $17.9 billion in 2012, down from a peak of more than $100 billion in 2010.

Current State and local government expenditures -- which include transfers to individuals as well as government consumption -- rose 2.8 percent over the four quarters of 2012, following a 0.2 percent increase in the previous year. A recent CBO report (CBO 2012b) noted that the weakness in State and local government spending relative to previous recoveries could be attributed roughly equally to three different areas: hiring of employees, purchases of goods and services, and construction spending. Despite continued spending restraint across these major components, the operating position of State and local governments deteriorated to an aggregate deficit of $140 billion by the third quarter of 2012, on pace for a fifth consecutive year of operating deficits for the sector.

State and local government employment fell 32,000 during the 12 months of 2012, a much shallower decline than the 286,000 jobs lost in 2011. Nevertheless, employment in the sector remains well below its peak in 2008. To date, the Administration has taken important steps to help State and local governments maintain critical services in public safety and education. In addition to the grants-in-aid components of the Recovery Act, the Administration established a new fund to support teaching jobs and extended the enhanced Federal matching formula for certain social services and medical insurance expenditures. In 2011, the President proposed additional resources for the teacher job fund as part of the American Jobs Act, which also would have supported the modernization of more than 35,000 schools. Although Congress did not enact this proposal, the President remains committed to supporting educators and first responders in his second term.

Real Exports and Imports

Compared with previous recessions, real exports experienced a sharper-than-usual contraction and rebound during 2007-10. This sharp cyclical decline was partly attributable to the synchronized nature of the 2007-09 contraction and recovery across nearly all countries, a collapse and rebound in commodity prices, and foreign consumers' postponement of purchases of U.S. durable goods, which account for a large share of tradable goods (Baldwin 2009). Now, with the recent slowing of world growth, real exports appear to be reverting to their historical trend (Figure 2-9), growing 1.8 percent during the four quarters of 2012, after rising 4.3 percent in 2011 and 8.8 percent in 2010. As discussed in Chapter 7, the recent slowing in export growth appears to have restrained the pace of U.S. manufacturing activity. Continued export growth will depend, in part, on healthy growth of the world economy and on exchange rates. The value of the dollar has been generally increasing since July 2011, in part reflecting increased international demand for U.S. Treasury bonds in a time of global financial turmoil and rapidly deteriorating global growth. Changes in the terms of trade have contributed to the weakening demand for U.S. goods abroad.

 

Figure 2-9

 

Real Exports During Recoveries

 

 

 

 

Note: The 1960-2007 average excludes the 1980 recession due to overlap with the 1981-82 recession.

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

Real imports grew 0.1 percent during the four quarters of 2012, down from 10.9 percent and 3.5 percent in 2010 and 2011, respectively. A decline in imports of petroleum products offset a moderate rise in imports of nonpetroleum goods. Consistent with Houthakker and Magee (1969), the pattern in real imports parallels, but is sharper than, the general shape of the contraction and rebound in overall U.S. personal consumption spending. Because imports tend to be concentrated more in goods than is overall consumer spending, real imports move more closely with goods consumption -- which is cyclically sensitive -- than with total consumption. In addition, because business equipment investment includes imported capital goods, real imports track this cyclical series as well.

Shrinking exports subtracted from real GDP growth in each quarter of the worst period of the recession from the third quarter of 2008 to the first quarter of 2009, but real exports have added to real GDP in every quarter since, except for in the fourth quarter of 2012.

Housing Markets

Housing activity firmed markedly in 2012 and, although the level of activity remains low by historical standards, the recovery in the sector finally appears to be gaining momentum. On the production side, new housing starts increased to an annual rate of 900,000 units by the fourth quarter of 2012, up from an annual low of 550,000 units in 2009, and 610,000 units in 2011 (Figure 2-10). Demand for housing has also increased, with new and existing home sales reaching their highest levels of the recovery period during 2012. Similarly, inventories of unsold new homes have fallen to their lowest ever recorded level.

Following large declines from 2007 through 2011, housing prices bottomed out in early 2012, and rose 8.3 percent over the 12 months of the year, according to the CoreLogic home price index. Private sector housing experts expect house prices to appreciate at a 3.0 to 3.5 percent annual pace for the next several years. Because households have a choice between renting and owning a home, the price of new homes should increase in tandem with rental costs, at least over long periods of time. As seen in Figure 2-11, house prices increased to a level above parity with rents during the mid-2000s but descended to a level consistent with rents by the end of 2011.

 

Figure 2-10

 

Housing Starts, 1960-2012

 

 

 

 

Note: Shading denotes recession.

Source: Census Bureau, New Residential Construction.

 

Figure 2-11

 

Home Prices and Owners' Equivalent Rent, 1975-2012

 

 

 

 

Note: Shading denotes recession. House prices are measured by the Federal Housing Finance Agency's price index (total index before 1991, purchase-only index after 1991). Owners' equivalent rent is measured by the Personal Consumption Expenditures price index for imputed rent of owner-occupied nonfarm housing (before 1983) and the Consumer Price Index for owners' equivalent rent of residence (1983-present).

Source: Federal Housing Finance Agency, House Price Index; Bureau of Economic Analysis, National Income and Product Accounts; Bureau of Labor Statistics, Consumer Price Index; CEA calculations.

In 1998, the Council of Economic Advisers estimated that the pace of construction of new housing units and mobile homes that would be consistent with projected rates of population and household formation would be 1.64 million units a year over the 10 years from 1996 to 2006. Relative to this 1996 estimate, the subsequent 10 years through 2006 saw a period of tremendous overbuilding that led to an excess supply of 2.6 million housing units by 2007 (Figure 2-12). Since then, the very low levels of new construction effectively allowed the underlying demographics of household formation to catch up to the supply of constructed and manufactured homes nationwide by 2011, with some possible overshooting in 2012.

Although construction, sales, and prices are finally rising, progress has been impaired by the substantial stock of vacant homes and homes still in the foreclosure process; therefore, a recovery in housing starts to the annual pace of roughly 1.76 million units suggested by the demographics of household formation will likely still take several years to achieve (Masnick, McCue, and Belsky 2010). Nevertheless, sustained increases in homebuilding should provide a major impetus to economic growth over the medium term.

Several other factors also appear to be restraining the housing recovery. First, although mortgage rates are at historically low levels, approximately 22 percent of current mortgage holders were underwater (that is, the amount owed on their mortgage exceeded the market value of their home) through the third quarter of 2012, impeding their ability to refinance or sell.

 

Figure 2-12

 

Cumulative Over- and Under-Building of Residential and

 

Manufactured Homes, 1996-2012

 

 

 

 

Source: Census Bureau, New Residential Construction (completions) and Manufactured Homes Survey (placements); CEA (1998); CEA calculations.

Second, although some tightening of lending standards was inevitable in the aftermath of the financial crisis, these standards have not eased by as much as expected this far into the recovery. According to the Federal Reserve Senior Loan Officer Opinion Survey, the net percentage of responding banks that have eased their standards for approving prime residential mortgage loans has been flat since the beginning of 2011, even though demand for prime residential mortgages has increased sharply. According to the April 2012 survey, which included special questions on real estate lending, more than half the lenders reported they were less likely to originate a mortgage to a borrower with a credit score of 680 today than in 2006. All told, the origination of first-lien mortgages to homebuyers now stands at its lowest level since 1995.

As the President emphasized in the State of the Union, moving forward with programs to help homeowners with strong payment histories refinance their homes will provide them with additional liquidity and will spur consumption. In addition, streamlining regulations associated with issuing new mortgages will provide creditworthy potential borrowers the opportunity to purchase homes and will further the recovery of the housing sector.

Financial Markets

Financial market conditions in the United States continued to improve, on net, in 2012, reflecting the ongoing economic recovery and the highly accommodative monetary policies undertaken by the Federal Reserve. The broad, overall improvement in financial conditions is consistent with the performance of the Standard and Poor's (S&P) 500 Composite Index, a measure of U.S. equity prices, which rose 14.4 percent over the 12 months of 2012. Measures of market volatility, such as the Chicago Board Options Exchange Market Volatility Index (also known as the VIX), were also more subdued in 2012 than they were in 2011.

Yields on 10-year Treasury notes averaged 1.7 percent in December 2012, down slightly from 2.0 percent in December 2011. For the year as a whole, the 10-year yield averaged 1.8 percent, the lowest since at least 1953 when the Federal Reserve's constant-maturity series began. Long-term interest rates in the United States were driven even lower than in 2011 by the relative safety of U.S. issues in the presence of concern over sovereign debt issues abroad and by the Federal Reserve System's program to lengthen the maturity of its holdings of U.S. government securities. With these nominal yields falling to historic lows, long-term real interest rates (that is, the nominal yield less expected inflation) also fell. Yields on Treasury Inflation-Protected Securities, an indicator of real rates, averaged negative 0.5 percent in 2012 (Figure 2-13).

Credit standards for commercial and industrial loans, as measured by the Federal Reserve Board's Senior Loan Officer Opinion Survey, have eased since the financial crisis for firms of all sizes, including small firms. Data from the Federal Deposit Insurance Corporation also suggest that the number of loans to small businesses increased in 2012, after having remained depressed through 2011. Nevertheless, the value of small-business commercial and industrial loans remains below its pre-recession level.

Wage and Price Inflation

Core consumer price inflation (the consumer price index excluding the volatile components of food and energy) was stable from 2011 to 2012, rising 1.9 percent in 2012, and down slightly from a 2.2 percent year-earlier increase (Figure 2-14). Twelve-month increases in core consumer prices have fluctuated in the fairly narrow range of 0.6 to 2.3 percent during the past three years. This relative stability is striking, given that standard Phillips curve models of inflation would predict sustained disinflationary pressure over this period because of the considerable slack in labor and product markets.

 

Figure 2-13

 

10-Year Treasury Yields, 2004-2013

 

 

 

 

Note: Real yield based on 10-year inflation-indexed securities.

Source: Federal Reserve Board, H.15.

 

Figure 2-14

 

Consumer Price Inflation, 2004-2012

 

 

 

 

Note: Shading denotes recession.

Source: Bureau of Labor Statistics, Consumer Price Index.

As is usually the case, the overall, or headline, consumer price index, including food and energy prices, fluctuated more in 2012 than did core inflation. Inflation as measured by the overall consumer price index fell from 3.0 percent during the 12 months of 2011 to 1.7 percent in 2012, with the decline stemming from lower rates of food and energy inflation. Energy prices edged up only 0.5 percent during 2012, more than 6 percentage points below their 2011 pace, and food price inflation dropped 2.9 percentage points. Data Watch 2-2 discusses one of the challenges faced by statistical agencies when constructing price indexes based on statistical samples.

 

The Recovery in Historical Perspective

 

 

Following the worst recession since the Great Depression, the recovery that began in the third quarter of 2009 has been a long and difficult one for many Americans. During the recession, 7.5 million jobs were lost, and real GDP fell by 4.7 percent. To date during the subsequent recovery, 4.2 million jobs have been added since June 2009, and real GDP has grown by 7.5 percent. Since the trough in employment in February 2010, the private sector has grown for 35 straight months and added over 6.1 million jobs. Real GDP growth in the United States has exceeded the cumulative growth in the euro area and the United Kingdom (Figure 1-4) as well as in Japan since the fourth quarter of 2007. Nevertheless, U.S. real GDP growth since the end of the recession has been less than the average increase in previous postwar recoveries.

From 1960 to 2007, the U.S. economy had seven recessions, and the average annual rate of growth of real GDP during the 12 quarters following those recessions was 4.2 percent. In contrast, during the 12 quarters following the trough in the second quarter of 2009, the average annual rate of growth of real GDP was 2.2 percent. After three years of recovery, the cumulative growth of real GDP was 6.3 percentage points lower than its average value for the earlier post-1960 recessions. This shortfall is depicted in Figure 2-15, which shows the paths of real GDP for the three most recent business cycles (with cyclical troughs in the first quarter of 1991, the fourth quarter of 2001, and the second quarter of 2009), along with the average path for U.S. business-cycle recoveries from 1960 through 2007. For each of the three most recent cycles, the recovery in real GDP has been slower than the 1960-2007 average. It is worth noting that the most recent recovery has been stronger than the post-2001 recovery if only private demand is considered (that is, excluding government purchases). Still, the fact remains that these three recoveries have been slower than the pre-2007 average.

 

Figure 2-15

 

Real GDP During Recoveries

 

 

 

 

Note: The 1960-2007 average excludes the 1980 recession due to overlap with the 1981-82 recession.

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

The reasons underlying the relatively slow pace of the current recovery have been the subject of considerable research. This research, discussed in more detail below, reaches three main conclusions. First, most -- perhaps two-thirds, using a central estimate across studies -- of the gap between the 12-quarter growth of GDP after the second quarter of 2009 and the average 12-quarter growth following previous troughs is accounted for primarily by changes in the long-term dynamics of the U.S. labor force and economy, mainly long-term demographic shifts. These demographic changes also help explain why the 1991 and 2001 recoveries were slower than the post-1960 average. Second, much of the remaining one-third of the gap can be attributed to the financial crisis dynamics discussed by Reinhart and Rogoff (2009), Reinhart and Reinhart (2010), Hall (2010), Woodford (2010), and others. This research finds that recoveries following financial crises tend to be slow because of delays in the reemergence of credit and reductions in consumer spending as households pay down debt or rebuild their savings, a process referred to as "deleveraging." Third, some unique factors proved to be particularly important impediments to this recovery, as discussed previously: the limited effectiveness of standard monetary policy caused by the zero lower bound on nominal interest rates; the presence of millions of underwater and foreclosed properties, which has impaired the recovery of the housing market; and the contraction in State and local government hiring due to sharply eroded property and sales tax bases. Given the deep and prolonged effects of financial crises, the cyclical component of the current recovery would have lagged even further behind the postwar average were it not for Federal fiscal stimulus -- notably through the Recovery Act (Box 2-3), the temporary payroll tax cut, and extended unemployment insurance benefits -- and for the nonstandard monetary stimulus provided by the Federal Reserve.

 

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Data Watch 2-2: The Effect of Statistical

 

Sampling on Laspeyres Indexes

 

 

The purpose of a price index is to provide a single measure of the overall rate of change in prices for some set of goods and services, for example, all purchases made by consumers. If data on all prices were readily available, the true rate of price increase could be calculated by weighting the relative increases in the prices for every item in the bundle using weights that reflect spending on the items, then combining those weighted price increases to form a price index. Because it is not possible to collect all prices, however, statistical agencies collect a sample of prices and use the sample to construct the price index.

The consequences of using a sample of prices, instead of all prices, can be significant. To be concrete, consider a Laspeyres price index, in which inflation is measured as an arithmetic weighted average of price increases for individual categories of items and the weights are spending shares measured at the beginning of the interval. In practice, each item (for example, apples or a haircut) is sold in an area (such as the Seattle metropolitan region), so the price increase of interest is an item-area price (the increase in the price of apples in Seattle from one month to the next). In reality, there are many item-area prices (one can purchase apples or haircuts at many shops in Seattle), so a sample of item-area prices is taken, and the sampled price increases (the increase in the price of apples at a given store, relative to last month's price at that store) are averaged. Since 1999, the Bureau of Labor Statistics (BLS) has computed this average of the sample of price increases within an item-area using the geometric mean.1

If the number of sampled prices for an item-area is large, the geometric mean of sample price changes will be close to the true item-area price. But collecting many item-area prices is expensive, so in many cases only a small number of item-area prices are collected. When computed using a small sample, the sample geometric mean tends to overstate the true geometric mean. The extent of this overstatement -- the statistical bias arising from using a small sample -- decreases as the number of prices sampled for an item-area increases.

How large is this finite sample bias? As an example, consider a Laspeyres price index constructed using equal weights (that is, an index for which all item-areas have the same consumption shares), with many item-areas and with 10 prices randomly sampled per item-area. Suppose that the true item-area price increase is zero and the standard deviation of the price changes (a measure of the dispersion of the price changes) for sampled goods within each item-area is 10 percentage points. Then the bias is small: The geometric mean index for each item-area overstates the price change by only 0.05 percentage point per period, and under the assumptions made here, this translates into an upward bias of 0.05 percentage point in the overall Laspeyres index. But if only 5 items are sampled per item-area, and the standard deviation of the price changes across stores is a bit larger, say, 15 percentage points, then the bias is larger, and the price change is overstated by 0.23 percentage point per period. If this bias can be calculated (as has been done in the simple example laid out here), a technical correction can be made to the Laspeyres index to eliminate the bias. At a technical level, this bias arises because the Laspeyres index is an arithmetic weighted average of the item-area geometric means. Interestingly, if the geometric means for each item-area are aggregated to a national index using a weighted geometric mean, as with a Törnqvist price index, rather than a weighted arithmetic mean, as with the Laspeyres, the small-sample bias is eliminated, and there is no need for a technical bias correction. For further reading on small-sample bias in index numbers, see McClelland and Reinsdorf (1999) and Bradley (2005).

FOOTNOTE TO DATA WATCH 2-2

 

 

1 The geometric mean of two numbers is the square root of their product. Suppose apple prices are sampled at two stores, one of which held prices constant and the other increased apple prices by 20 percent. Then the arithmetic mean relative price is (1 + 1.2)/2 = 1.10 (an increase of 10 percent), and the geometric mean is (1x1.2)1/2 = 1.095 (an increase of 9.5 percent). The BLS adopted the geometric mean in part because its slightly lower increase captures the effect of shoppers migrating to the store at which apple prices remain constant, so that from the shopper's perspective the overall price increase is in fact less than 10 percent.

 

END OF FOOTNOTE TO DATA WATCH 2-2

 

 

_____________________________________________________________________

 

 

Demographics, Productivity, and Long-Term Economic Growth

A useful starting point for analyzing long-term trends in output is to note that GDP is the product of two terms: real GDP per worker times the number of workers. In turn, GDP per worker is the product of real GDP per hour of labor input -- that is, labor productivity -- times average hours per worker. Although average hours per worker have been declining, the rate of this decline since the mid-1980s has been relatively small. Thus, variation in the long-run growth rate of GDP is, to a first approximation, determined by the long-run growth rate of both productivity and the number of workers.5 The discussion here focuses on the growth of productivity for nonfarm businesses and the growth of overall payroll employment.

 

_____________________________________________________________________

 

 

Box 2-3: Economic Impacts of the American

 

Recovery and Reinvestment Act

 

 

To counter the contraction of aggregate demand in the Great Recession, Congress passed and President Obama signed into law the American Recovery and Reinvestment Act (the Recovery Act) in February 2009. The Recovery Act was a major part of the Federal government's efforts to reinvigorate the economy through direct fiscal stimulus. The Recovery Act authorized an estimated $787 billion for purchases of goods and services by the Federal government, transfers to State and local governments, payments to individuals, and temporary tax reductions for individuals and businesses (based on actual outcomes, the final total exceeded $800 billion).

Numerous studies have examined the success of the Recovery Act in raising employment and stimulating growth. As is the case with policy evaluation generally, the methodological challenge is to compare outcomes from an event that actually happened (implementation of the Recovery Act) to outcomes from a counterfactual event that did not (no Recovery Act). One approach is to use a large macroeconometric model or other statistical techniques to estimate a baseline, non-stimulus forecast that excludes Recovery Act provisions and a stimulus forecast that includes them, and then either compare the two forecasts or compare the actual data to the non-stimulus forecast. Of the studies employing this method, most estimate that the Recovery Act stimulated growth. A Congressional Budget Office study (CBO 2012b) estimated that the Recovery Act boosted the level of GDP by 0.4-1.8 percent in 2009, 0.7-4.1 percent in 2010, 0.4-2.3 percent in 2011, and 0.1-0.8 percent in 2012, with more than 90 percent of the Recovery Act's budgetary impact realized by the end of September 2012. The most recent review by the Council of Economic Advisers (CEA 2013) estimated that the Recovery Act raised the level of GDP as of the third quarter of 2010 by 2.7 percent, which is roughly in the same range estimated by CBO. A report by Blinder and Zandi (2010) estimated that the stimulus raised GDP in 2010 by 3.4 percent. Additional reports by IHS Global Insight and Macroeconomic Advisers provide estimates consistent with these ranges (as reported in CEA 2013). Estimates based on macroeconometric models typically do not include the additional benefits of avoiding very high levels of unemployment, which could be particularly persistent and exhibit so-called hysteresis; see DeLong and Summers (2012) for additional discussion.

A different approach to evaluating the Recovery Act is to use crossstate variation in Recovery Act spending levels to estimate the effects of the spending, and then to extrapolate these effects to the full economy. Wilson (2012) studied state-level variation in Recovery Act spending to determine its employment effect; he estimated that Recovery Act spending created 2 million jobs in its first year and 3.4 million by March 2011, with substantial gains in the construction, manufacturing, education, and health industries. Conley and Dupor (2012) estimated that the spending components of the Act created between 82,000 and 1.5 million jobs. Other papers that use state-level variation to estimate Recovery Act effects on employment include Chodorow-Reich and others (2012), who investigated the employment effects of the Recovery Act's aid to states through increased Federal Medicaid matching funds, and Feyrer and Sacerdote (2011), who considered both total spending and type of spending; both papers found positive employment effects.

The range of estimates of the effect of the Recovery Act is large, and research on this topic is ongoing. Surveying the literature, however, the evidence suggests that the Recovery Act substantially lessened the impact of the Great Recession by increasing employment and output in the years immediately following the crisis.

_____________________________________________________________________

 

 

Figure 2-16 shows quarterly growth of nonfarm business productivity and its cyclically adjusted long-term mean at an annual rate.6 According to this mean, annual trend productivity growth fell from 2.6 percent in 1965 to 1.5 percent in 1985, recovered to 2.3 percent in 2005, and then fell to 2.0 percent as of 2010. Despite the considerable uncertainty and difficulty in distinguishing the trend from cyclical components given the severity of the recent recession, this pattern is in line with others in the academic literature. Gordon (2010) found that trend productivity growth declined from 2.75 percent in 1962 to 1.25 percent in 1979, then rebounded to 2.45 percent by 2002. Fernald (2012) divided the period since 1973 into three regimes of average labor productivity growth: 1.5 percent from 1973 to 1997, 3.6 percent from 1997 to 2003, and 1.6 percent from 2003 to 2012. The very strong productivity growth of the late 1990s and early 2000s evident in Figure 2-16 appears, in part, to have been transitory.

 

Figure 2-16

 

Productivity Growth and Estimated Trend, 1960-2012

 

 

 

 

Note: Shading denotes recession. Trend productivity growth was estimated by a smoothed weighted average over a 15-year moving window.

Source: Bureau of Labor Statistics, Productivity and Costs; CEA calculations.

Figure 2-17 plots the quarterly growth of total payroll employment and its cyclically adjusted long-term mean at an annual rate, and Figure 2-18 plots the quarterly change in employment, measured by the number of jobs; the method for computing the trends in both figures is the same as that used to calculate the trend shown in Figure 2-16. The smoothed mean growth of employment rose from 2.2 percent annually in 1965 to 2.4 percent in 1975 but then declined steadily to 2.0 percent in 1985 and just 0.8 percent in 2005. The trend in the number of jobs added remained high through the 1990s, and in fact more jobs were added in the 1990s than in the 1980s.

The high growth rate of employment in the 1970s reflected the historic surge of women into the U.S. labor force. The trend decline in employment growth since the late 1990s has been largely associated with demographics, in particular the plateauing of female labor force participation during the late-1990s, the steady multi-decade trend decline in male labor force participation, the downward trend in youth labor force participation, and, starting in the 2000s, the entry of the baby-boom generation into retirement. Demographic trends are discussed in more detail in Chapter 4. Indeed, the implications of demographic trends extend beyond the labor force to include, for example, changes in the patterns of consumption as the population ages (Box 2-4).

 

Figure 2-17

 

Employment Percent Growth and Estimated Trend, 1960-2012

 

 

 

 

Note: Shading denotes recession. Trend employment growth was estimated by a smoothed weighted average over a 15-year moving window.

Source: Bureau of Labor Statistics, Current Employment Statistics; CEA calculations.

 

Figure 2-18

 

Quarterly Change in Employment and Estimated Trend, 1960-2012

 

 

 

 

Note: Shading denotes recession. Trend employment growth was estimated by a smoothed weighted average over a 15-year moving window.

Source: Bureau of Labor Statistics, Current Employment Statistics; CEA calculations.

The net effect of the declines in the long-term trends for productivity and employment has been a fairly steady decline in the long-run mean growth rate of GDP over the past 50 years. Indeed, the cyclically adjusted long-term mean growth rate of real GDP fell from 3.7 percent in 1965 to 2.9 percent in 1985 and 2.4 percent in 2005. This steady slowdown is evident in Figure 2-19, in which real GDP is plotted along with trend lines estimated using the quarterly data spanning a full business cycle as dated by the National Bureau of Economic Research (NBER), measured from one business-cycle peak to the next.7 The slopes of these trend lines are less steep over time; in other words, the trend growth of real GDP has been slowing over this period. Indeed, trend growth has slowed enough that, after every post-1960 recession, real GDP has never attained the previous trend growth line that is implied using data from the preceding business cycle. From this perspective, the slower pace of the current recovery is not unusual or unexpected.

In a November 2012 study of the current recovery, CBO decomposed the growth of real GDP in the 12 quarters following a NBER-dated trough into trend growth plus a cyclical component. It attributed about two-thirds of the difference between the growth in real GDP in the current recovery and the average for other recoveries to slow growth in potential GDP. The CBO study estimated potential real GDP growth -- that is, the maximum sustainable rate of growth of real GDP -- using a presumed economy-wide production function in which potential GDP varied with the capital stock.

For comparison purposes, the long-term mean growth rate of GDP is computed here using the methodology of Figures 2-16 and 2-17. The results from this analysis are summarized in Table 2-2. As reported earlier, during the first 12 quarters of recoveries from 1960 through 2007, real GDP grew, on average, at an annual rate of 4.2 percent, whereas during the 12 quarters following the trough in the second quarter of 2009, the annual rate of GDP growth was 2.2 percent, or 2.1 percentage points below the 1960-2007 average. The estimated trend growth rate of real GDP since the second quarter of 2009, however, was 2.1 percent, or 1.1 percentage points below the average trend growth during the 1960-2007 recoveries (3.2 percent). Thus, of the 2.1 percentage points of slower-than-average growth in this recovery, fully 1.1 percentage points, or 53 percent, can be attributed to the overall trend slowdown in real GDP growth over the past 50 years.8

 

Figure 2-19

 

Real Gross Domestic Product and Trends, 1947-2012

 

 

 

 

Note: Shading denotes recession. Trend lines represent the average growth rate between successive business-cycle peaks.

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

The 1991 and 2001 recoveries also exhibited slower than average growth in real GDP (Kliesen 2003; Berger 2011; Bachmann 2011). As can be seen in Table 2-2, the slowdown in trend growth accounted for less than one-fifth of the relatively slower growth in real GDP following the 1991 recession (-0.2 percentage point of the gap of -1.1 percentage points). In contrast, slightly more than one-third of the relatively slower growth following the 2001 recession was attributable to the slowing of long-term real GDP growth (-0.5 percentage point of the gap of -1.3 percentage points).

Stock and Watson (2012) also examined reasons why the current expansion has been slower than previous postwar recoveries. They focused on the first eight quarters of the recovery and estimated that 80 percent of the slower growth in real GDP, relative to the post-1960 average for recoveries, reflected a slowdown in the long-term trend growth rate rather than cyclical factors.

 

_____________________________________________________________________

 

 

Box 2-4: Implications of Demographic Trends

 

for Household Consumption

 

 

The aging of the U.S. population has two implications for patterns of consumption. First, people purchase different things at different ages; for example, younger households spend more on child care services and clothing, while older households spend relatively more on health care. Second, empirical research suggests that families' total amount of spending changes over time as priorities evolve. Because the age distribution of the population will change over the coming decade as the baby boom generation moves into retirement, these changes in household-level consumption will lead to aggregate changes in the types of goods consumed and, potentially, to changes in the fraction of income spent.

One way to forecast how demographic changes will affect consumption is to use data on a sample of households today to estimate average household consumption within spending categories (clothing, health care, and so on), for each subset of the population defined by age, race, sex, and ethnicity of the household head. Then, one can aggregate these averages using the projected future population for each subset to produce an overall estimate for all households. The Council of Economic Advisers undertook this exercise using consumption data from the Consumer Expenditure Survey and demographic projections from the Census Bureau. As the figure below indicates, demographic changes suggest that a greater share of household income will be spent on health care and housing, and a reduced share on education. In percentage terms, however, these changes are likely to be small.

Households' total consumption also varies over their lifetime. In Milton Friedman's (1957) permanent income hypothesis model of consumption, individuals smooth consumption to match their lifetime income, but doing so requires the ability to borrow against future income, as well as considerable planning and discipline. As an empirical matter, on average, household consumption rises as children grow up and then declines as parents enter into retirement (Attanasio et al 1999; Fernandez-Villaverde and Krueger 2007; Bullard and Feigenbaum 2007).1 Consistent with this research, CEA projects that the aging population will lead average household consumption to decline over the next decade, with an implied reduction in the growth rate of consumer spending of perhaps 0.1 percentage point a year, relative to a benchmark in which demographics are held constant.

Many factors other than demographics will also influence future consumer spending. These factors include technological improvements, changes in income and wealth, and changes in the composition of households within demographic groups. In addition, changes in relative prices will affect the composition of spending. For example, if the price of health care increases relative to other areas, and if the demand for health care is insensitive to its price, then the share of spending on health care might be larger than these projections suggest.

Projected Effect of Demographic change on

 

Share of Household Expenditures, 2011-2023

 

 

 

 

Note: Percentage point changes over 12 years, not annualized.

Source: Bureau of Labor Statistics, Consumer Expenditure Survey; Department of Commerce, Census Bureau; CEA calculations.

 

FOOTNOTE TO BOX 2-4

 

 

1 One reason for the decline in consumption upon retirement, at least for some households, is reduced work-related spending such as commuting costs and uniforms, which are counted as consumption expenditures, but such declining work-related expenses do not fully account for this drop.

 

END OF FOOTNOTE TO BOX 2-4

 

 

_____________________________________________________________________

 

 

In summary, these estimates of the share of the relatively slower growth in real GDP during this recovery which is attributable to a slowdown in long-term trends range from 53 percent, shown in Table 2-2, to 80 percent according to Stock and Watson (2012). This fairly wide range of estimates reflects both inherent difficulties in calculating trend growth rates and conceptual differences among these approaches.9 Taken together, however, these studies suggest that most of the relatively slower growth in real GDP during the current recovery -- two-thirds, using the CBO (2012d) estimate, which is also the midpoint of these estimates -- has been attributable to the slowdown in long-term trend growth, which, in turn, has been driven largely by demographic changes in the U.S. workforce.

Reasons for the Slower Cyclical Component

If two-thirds of the slower growth in real GDP during the current recovery relative to growth in previous postwar recessions is attributable to the slowdown in underlying long-term trends, then the remaining one-third can be attributed to cyclical factors that are specific to this recovery. This section summarizes four complementary attempts to quantify those cyclical factors: the 2012 CBO study discussed above, an analysis undertaken here of the sources of forecast errors during the recovery, work done on this question by the Federal Reserve as reported by Bernanke (2012b) and Yellen (2013), and the study by Stock and Watson (2012).

The CBO (2012d) study approaches the question of why the cyclical part of this recovery has been relatively slow by identifying those components of GDP that have exhibited unusually slow growth relative to their cyclical pattern. In decreasing order of importance, CBO found that the cyclical contributions to GDP of State and local government purchases, Federal government purchases (primarily defense spending), residential investment, and consumer spending were all weaker than their respective historical averages during the first 12 quarters of this recovery. In turn, CBO attributed the weakness in these components to several underlying factors. For instance, the CBO study highlighted the extraordinary weakness in housing markets during the current recovery. CBO associated the sharp fall in house prices with reductions in State and local property tax revenues and the persistent glut of vacant and foreclosed homes with the weakness in residential construction. Similarly, CBO noted that, in contrast to previous postwar recoveries, the ability of monetary policy to spur economic activity has been constrained by the zero lower bound on the Federal Reserve's main policy interest rate during this expansion. The CBO analysis also pointed to low consumer confidence and heightened uncertainty as additional factors that have restrained aggregate demand since the second quarter of 2009.

                                   Table 2-2

 

        Real GDP Growth During Three Years Following Business Cycle Trough

 

 ______________________________________________________________________________

 

 

                                             (percent change at an annual rate)

 

                                             __________________________________

 

 

 Business Cycle Trough                       Total         Trend          Cycle

 

 ______________________________________________________________________________

 

 

 1991:Q1                                      3.2           3.0            0.2

 

 2001:Q4                                      2.9           2.7            0.2

 

 2009:Q2                                      2.2           2.1            0.1

 

 Average of 7 recoveries, 1960-2007           4.2           3.2            1.1

 

 ______________________________________________________________________________

 

 

 Difference from Average                     Total         Trend          Cycle

 

 ______________________________________________________________________________

 

 

 1991:Q1                                     -1.1          -0.2           -0.9

 

 2001:Q4                                     -1.3          -0.5           -0.8

 

 2009:Q2                                     -2.1          -1.1           -1.0

 

 ______________________________________________________________________________

 

 

 Note: Trend growth is based on the 15-year moving average smoothed cyclically

 

 adjusted growth rate of real GDP.

 

 

 Source: Bureau of Economic Analysis, National Income and Product Accounts;

 

 National Bureau of Economic Research; CEA calculations.

 

 

A second approach to the question of why the cyclical component of this recovery has been slower than that of the postwar average is to examine whether the expansion has been hindered by unexpected events and forces. Specifically, this approach contrasts the actual, realized values for each component of GDP from the corresponding estimates that were forecast at the start of the recovery. Whereas CBO's approach identifies which components of GDP grew more slowly than their historical average, the approach used here is to identify the components that grew either more slowly or more rapidly than was forecast, thereby identifying the unexpected, or unforecast, sources of the slow growth.

Implementing this method of forecast error analysis requires a quantitative model of the U.S. economy. The one used here is developed and maintained by Macroeconomic Advisers (MA). This model is used to decompose the Administration's economic forecast for the FY 2011 Budget, which was made in November 2009. The MA model uses quarterly data to forecast hundreds of macroeconomic variables. By partitioning the variables into groups, it is possible to see how the forecast errors for each group contributed to the forecast errors for GDP. The variables were divided into five categories: international (foreign GDP, exchange rates, oil prices), fiscal (both Federal and State and local), financial and monetary (financial prices, house prices, monetary indicators, credit flows), housing activity, and other.

That Administration forecast over-predicted output growth by a small amount in 2010 and by larger amounts in 2011 and the first half of 2012; in this sense, the recovery was slower than expected. The forecast error decomposition sheds light on the sources of this unexpectedly slow recovery. During the first part of the recovery, the housing sector was weaker than anticipated, and this unexpected weakness more than accounts for the total GDP forecast error in 2010. Early in the recovery, financial and monetary factors buoyed economic activity relative to the forecast, presumably because the forecast did not fully capture the stimulative effect of nonstandard monetary policy, which was unprecedented and thus difficult to incorporate quantitatively into the forecast. Moving farther out in the forecast, however, the outlook for consumption turned overly optimistic, possibly reflecting an underestimation of the degree of deleveraging as households reduced the amount of new debt they took on and paid down existing debt. This shift in the consumption outlook explains a substantial part of the overall forecast error for both 2011 as well as the first half of 2012. Finally, deteriorating international conditions, largely owing to events unfolding in Europe, added further unanticipated drag in 2011 and especially in the first half of 2012.

These results complement Chairman Bernanke's (2012b) and Vice Chair Yellen's (2013) analyses of the relatively slow growth in the cyclical component of GDP during this recovery. In particular, Chairman Bernanke pointed to unexpected headwinds from the prolonged recovery of the housing sector, the lingering effects of the financial crisis, and the fiscal and financial problems in Europe. Yellen also noted the restraint on consumer spending from the large loss of wealth during the recession. Both emphasized the unexpectedly large declines in the State and local government sector. Indeed, Yellen estimates that, once the drag from the State and local government sector is included, the net fiscal stimulus to the economy was less in the current recovery than it was on average for prior postwar recoveries.

Stock and Watson (2012) also addressed the question of why the cyclical component of the recovery has been slower than the postwar average. In contrast to the two approaches discussed above, Stock and Watson focused on the forecasts of eight-quarter GDP growth from the vantage point of the trough. They found that these forecasts predicted slower-than-average cyclical growth during this expansion. These slow growth forecasts stem from the shocks that produced the recession, which they identify as primarily financial factors (such as borrowing constraints) and uncertainty. Thus, the Stock and Watson analysis is consistent with the Reinhart and Rogoff (2009) view that recoveries following financial recessions typically exhibit slower growth than those following other kinds of recessions. In contrast to Stock and Watson's approach, Hall (2012) used a stylized macroeconomic model to distinguish between the deleveraging effect of cutting back on consumption to rebuild wealth and the liquidity effect of higher borrowing costs, which would arise from tightened lending standards. He concluded that both effects were important during the recession, but that the deleveraging effect was short-lived, whereas the liquidity effect has been more persistent and continues to restrain investment and to contribute to the slow cyclical component of GDP.

Although the CBO analysis, the forecast error decomposition, the analyses by Bernanke and by Yellen, the study by Stock and Watson, and the study by Hall produced different numerical estimates of the causes of the relatively slow recovery, these analyses point to a common understanding of why the cyclical component of the current expansion was slow relative to previous recessions: a financial crisis that led to reductions in the ability of households and small businesses to borrow, spend, and invest; a weak recovery of the housing sector as a result of the excess inventory of vacant, foreclosed, and distressed properties; a decline in State and local spending and employment; monetary policy restrained by the zero lower bound on the Federal Reserve's main policy interest rate; and in more recent stages of the recovery, the detrimental effects of a global slowdown on U.S. economic activity. Against all of these headwinds, the stimulus from Federal fiscal policy actions and aggressive unconventional monetary policy contributed positively to the cyclical component of the recovery.

 

Outlook for 2013 and Beyond

 

 

The Administration's economic forecast was finalized in mid-November 2012, a schedule that is dictated by its role in supporting the Administration's outlook for the FY 2014 Budget, and will be released later this year in conjunction with the Budget.

Consensus-based forecasts -- that is, forecasts that combine multiple, survey-based individual forecasts (e.g., the mean or median) -- typically outperform the constituent individual private forecasters' forecasts of macroeconomic variables such as GDP and the unemployment rate (Clemen 1989; Aiolfi, Capistrán, and Timmerman 2011). Consensus forecasts are thus worth following. In February 2013 the Blue Chip consensus of professional forecasters projected that real GDP would increase 2.4 percent over the four quarters of 2013, faster than the 1.6 percent gain recorded in 2012. The Philadelphia Federal Reserve Bank's Survey of Professional Forecasters (SPF) also projected a 2.4 percent increase in 2013. For 2014, the Blue Chip consensus and the SPF consensus forecast that the economy will continue to strengthen and that year-over-year real GDP growth will increase to a 2.8 percent pace.

Looking further ahead, the Survey of Professional Forecasters expects year-over-year growth will pick up to a 2.9 percent pace in 2015 and a 3.0 percent pace in 2016. With these rates of growth, the unemployment rate, which was 7.8 percent during the fourth quarter of 2012, is projected to edge down slowly to 6.3 percent in 2016.

Importantly, most private sector forecasts reflected in the consensus forecast have not incorporated an effect for the across-the-board budget cuts, known as sequestration, which took effect on March 1.10 These cuts will severely reduce both Federal defense and nondefense discretionary spending, with ripple effects throughout the economy. The Congressional Budget Office (2013) and Macroeconomic Advisers (2013) have estimated that, if sequestration were to remain in effect for the rest of the calendar year, it would reduce real GDP growth by 0.6 percentage point during the four quarters of 2013, relative to its path without the sequester. Moody's Analytics (2013) has estimated a reduction in real GDP growth by 0.5 percentage point.

Additionally, CBO (2013) has estimated that sequestration would lead to the loss of 750,000 lost jobs due to the sequester by the end of 2013 compared with a path without sequestration.11 From this perspective, by the end of this year sequestration would set back the recovery by four to five months at a time when the unemployment rate remains unacceptably high. As President Obama has stated, "The longer these cuts remain in place, the greater the damage to our economy -- a slow grind that will intensify with every passing day."

 

Conclusion

 

 

While much work remains, the economy is healing and moving in the right direction. The permanent extension of middle-class tax cuts and the increase in rates on the highest-income taxpayers through the enactment of the American Taxpayer Relief Act resolved the uncertainty about future tax rates that overshadowed the economy in 2012 and helped move the U.S. budget toward a more sustainable course. Some of the other headwinds that have restrained the economy during the recovery are also easing, most notably in the housing sector. While risks remain, these indicators suggest a continued strengthening of the recovery, which in turn provides an increasingly resilient framework for continued progress toward fiscal sustainability and a more durable economy that works for the broad middle class.

 

FOOTNOTES TO CHAPTER 2

 

 

1 Several studies suggested that going over the full fiscal cliff would likely result in a recession and substantial job losses; see for example CBO (2012a). These studies, including the CBO report, focused on cash flow effects of the fiscal cliff (revenues and spending). A growing body of literature suggests that the uncertainty created by going over the cliff would have further hurt economic activity and employment, although those channels are more difficult to quantify; see for example Bloom (2009).

2 A lengthening of the workweek by 0.1 hour is roughly equivalent, in terms of labor input, to an increase in employment of more than 300,000 jobs.

3 This calculation reflects an adjustment for updated Census Bureau population estimates that were incorporated into the January 2012 Current Population Survey by the Bureau of Labor Statistics (BLS). In accordance with usual practice, the BLS does not revise the official Current Population Survey estimates for earlier months to reflect the updated population values.

4 Specifically, for each gender and age group, labor force participation rates are projected using the previous 10-year trend, and the trend in the overall participation rate over the subsequent period is computed using actual population weights for each group.

5 Because labor productivity is conventionally measured for the nonfarm business sector, there are additional terms that account for the difference between the growth of GDP per hour and nonfarm business output per hour and between nonfarm business hours and total hours.

6 The cyclically adjusted long-term mean, or trend, is estimated using regression methods with a cyclical component, specifically two leads and lags of the CBO's unemployment gap, and a flexible trend component. The flexible trend component is estimated by a smooth weighted average using a two-sided 15-year moving window, which is truncated at the ends of the sample.

7 The cycle starting with the peak in the first quarter of 1980 lasted only six quarters. Because it is not meaningful to estimate trends using only six quarterly observations, the cycles for the first quarter of 1980 and the third quarter of 1981 are merged for the trend estimates in Figure 2-19.

8 This calculation includes the 12 quarters after all troughs, so that the 1980 and 1982 recoveries overlap. Alternatively, if the 12 quarters following the trough in the fourth quarter of 1982 are dropped, 63 percent of the slower than average growth in real GDP is attributable to a slowdown in trend growth. If instead the 12 quarters following the trough in the third quarter of 1980 are dropped, 47 percent of the slower growth in real GDP is attributable to a slowdown in trend growth.

9 In CBO's framework, the increase in long-term unemployment associated with the recession could result in skill deterioration and thereby a decline in potential GDP growth; this general point is also made by Federal Reserve Chairman Ben Bernanke (Bernanke 2012b). Because such declines in potential GDP are an indirect result of the recession, they may be better understood as cyclical rather than long-term trends. The trend estimates in Table 2-2 and in Stock and Watson (2012) are instead based on long-term weighted moving averages; because the resulting estimates are comparable with CBO's, one can infer that this further distinction of a cyclical change in the growth rate of potential GDP is secondary to the long-term demographic and technological trends that drive the growth slowdown.

10 In February, 77 percent of Blue Chip panelists reported that their forecasts did not reflect the effects of full sequestration.

11 The Bipartisan Policy Center (2012) estimates that over two years the effect would be 1 million jobs lost compared with the no-sequestration alternative.

 

END OF FOOTNOTES TO CHAPTER 2

 

 

CHAPTER 3

 

 

FISCAL POLICY

 

 

The American Taxpayer Relief Act of 2012 (ATRA), which was enacted on January 2, 2013, permanently extended the 2001 and 2003 Federal income tax cuts for 98 percent of taxpayers. The tax relief act reflects the approach supported by the President to reduce the Federal budget deficit -- an approach that balances responsible reductions in government spending with new revenues and increased progressivity of the tax code. The new law extended the expansions of several tax credits enacted in the American Recovery and Reinvestment Act of 2009 (the Recovery Act) that have provided economic opportunities through tax relief and college expense assistance to 25 million low- and middle-income students and working families each year. In addition, the new law prevented a substantial cut in Medicare physician payment rates, extended emergency unemployment insurance benefits to protect 2 million workers from losing their benefits in January 2013, and permanently indexed to inflation the exemption amounts for the Alternative Minimum Tax (AMT) to provide tax certainty to tens of millions of middle-class families. The permanent fix to the AMT will protect middle-class families from being subject to a tax designed to ensure that wealthy taxpayers pay their fair share in taxes.

Together with the additional Medicare and investment income taxes for high-income taxpayers in the Affordable Care Act (ACA), ATRA has made the Federal tax system more progressive. Figure 3-1 shows the trends in average Federal individual income and employment tax rates by income class. These average tax rates, defined as the share of taxpayer income paid in taxes, are measured by holding the distribution of taxpayer income constant over time (using the 2005 distribution with incomes adjusted for growth in the National Average Wage Index) to isolate the effects of tax law changes. The tax law changes in 2013 increased the average tax rate for taxpayers in the top 1 percent and the top 0.1 percent of the income distribution by 4.9 and 6.5 percentage points, respectively, while leaving individual income tax rates unchanged for 98 percent of Americans.

 

Figure 3-1

 

Average Tax Rates for Selected Income Groups Under

 

a Fixed Income Distribution, 1960-2013

 

 

 

 

Note: Average Federal (individual income plus payroll) tax rates for a 2005 sample of taxpayers after adjusting for growth in the National Average Wage Index.

Source: Internal Revenue Service, Statistics of Income Public Use File; National Bureau of Economic Research, TAXSIM (preliminary for 2012 and 2013); CEA calculations.

Another recent development in government finance is that the fiscal outlook for State and local governments has improved, although expenditures remain below pre-recession levels and State and local investment spending remains notably low. As shown in Figure 3-2, the continued decline in State and local investment is atypical. In other recoveries, State and local governments' gross real investment was typically flat for several quarters following a business-cycle trough and then increased, but, in this recovery, gross investment has failed to rebound.

This chapter highlights the declining Federal budget deficit since 2009 and the additional work needed to achieve medium- and long-term fiscal health. It then outlines the principles for Federal income tax reform set forth by President Obama in September 2011 and describes specific plans proposed by the Administration to meet these goals. The enactment of ATRA is a step toward achieving these goals, but substantial work remains to make the tax code more equitable and efficient. The chapter also reviews the State and local budget outlook and the Federal Government's role in mitigating the recent recession's effect on government finances at these levels. Finally, the chapter discusses the long-term financial challenge facing State and local governments from the underfunding of pension plans.

 

Figure 3-2

 

Real State and Local Government Gross Investment

 

During Recoveries

 

 

 

 

Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations.

 

The Federal Budget Outlook

 

 

The Obama Administration has taken significant steps to restore the country's fiscal health without disrupting the continuing economic recovery. In fiscal year (FY) 2009, the Federal budget deficit was 10.1 percent of gross domestic product (GDP). This ratio fell 3.1 percentage points to 7.0 percent in 2012, the largest three-year reduction in the deficit since 1949. Under current law, the deficit is projected to fall to 5.3 percent in 2013 (CBO 2013). This decline in the deficit largely reflects the wind-down of Recovery Act spending, the reductions in spending set forth in the Budget Control Act of 2011, new revenues as a result of ATRA, and the improved performance of the economy.

The Congressional Budget Office (CBO) projects that Federal receipts will grow by 11 percent to $2.7 trillion, or 16.9 percent of GDP, in 2013 (Figure 3-3). This is the highest receipts-to-GDP ratio since 2008, but still below the average of 18.3 percent of GDP recorded between 1970 and 2000. As a percent of GDP, outlays are projected to fall from 22.2 percent in 2013 to 21.5 percent in 2017 due in large part to the spending caps put in place by the Budget Control Act as well as reductions in certain mandatory spending as the economy continues to improve. After 2017, outlays will rise, relative to GDP, as interest payments on the national debt increase and as mandatory health and retirement spending grows in accordance with the cost of health care and an aging population. Over the long term, these factors -- rising health costs and changing demographics -- are the primary drivers of fiscal imbalance (CBO 2012).

 

Figure 3-3

 

Federal Receipts and Outlays, 1970-2023

 

 

 

 

Source: OMB (2012b); CBO (2013).

The Administration's goal of stabilizing the debt-to-GDP ratio requires reducing the deficit to 3 percent of GDP or lower. Increases in revenues and decreases in outlays in recent years have brought the Federal budget deficit -- the gap between outlays and receipts -- closer to that target (Figure 3-4). CBO projects that, under current law, deficits will continue to shrink over the next few years, falling below 3 percent of GDP by 2015, but will then increase steadily to 3.8 percent of GDP by 2022. Under current law, publicly held Federal debt is projected to reach 77 percent of GDP in 2023 (Figure 3-5).

Although enacted legislation and overall economic improvements will help reduce the budget deficit, other structural changes will be needed to achieve fiscal sustainability. The President has put forward a balanced deficit-reduction plan to achieve approximately $1.8 trillion in savings through a combination of reductions in discretionary spending, savings in entitlement programs, and new revenue raised by reforming tax expenditures and closing tax loopholes. When added to the more than $2.5 trillion in deficit reduction the President already signed into law, the total deficit reduction would amount to more than $4 trillion over ten years, a goal set by the President to stabilize the debt-to-GDP ratio and to put the country on a sustainable fiscal path over the next decade.

 

Figure 3-4

 

Federal Budget Deficit, 1970-2023

 

 

 

 

Source: OMB (2012b); CBO (2013).

 

Figure 3-5

 

Federal Debt Held by the Public, 1970-2023

 

 

 

 

Source: OMB (2012b); CBO (2013).

 

Federal Income Tax Reform

 

 

A fair, simple, and efficient tax code lays the foundation for job creation, economic growth, and an equitable society. Recognizing the crucial role tax reform can play in deficit reduction and economic growth, President Obama set forth a list of principles in September 2011 for comprehensive tax reform. These principles include lowering tax rates, cutting inefficient and unfair tax breaks, observing the "Buffett Rule" to enhance tax fairness, reducing the deficit, and increasing job creation and growth in the United States (OMB 2011).

Because revenue must be raised to finance essential services provided by the government, sound tax policy attempts to raise revenue fairly and efficiently. A number of notions of fairness can help guide tax policy: "horizontal equity" demands equal treatment of equals; the ability-to-pay principle prescribes that a taxpayer's burden should be related to her ability to pay; the benefit principle suggests that a taxpayer's burden should be related to the benefits she receives from government services. Such notions of fairness are often incomplete, and sometimes they are in conflict with each other. Still, these principles can serve as useful guides.

Fairness, however, must be balanced with efficiency. High tax rates, combined with a complex tax system and a narrow tax base (that is, with many deductions, exclusions, or exemptions), provide incentives for taxpayers to shift income between the individual and corporate tax bases, retime income, and alter behavior in other ways to reduce tax liability (Saez, Slemrod, and Giertz 2012). In addition, although tax subsidies could encourage socially beneficial activity or correct market failures, when there are no externalities or other market failures, tax provisions that favor one activity over another can lead to an inefficient allocation of resources.

A key feature of the tax code is the schedule of statutory tax rates on marginal income. To achieve myriad tax, economic, and social policy goals, the tax code also contains a dizzying web of deductions, exemptions, exclusions, credits, and special treatment of certain income. The fact that taxpayers modify their behavior to reap the benefits of special tax provisions is bittersweet. On one hand, it means that well-thought-out tax provisions that are designed to encourage a particular activity are working. On the other hand, a taxpayer determined to avoid liability can engage in tax avoidance and thereby expend socially unproductive resources navigating the jungle of tax provisions.1

Tax Expenditures

The tax code contains numerous special tax provisions, referred to as "tax expenditures," which lead the tax system to deviate from taxing economic income (Box 3-1). Economic income generally follows the Haig-Simons definition of comprehensive income as consumption plus changes in net worth. Relative to a tax structure built on a comprehensive income measure, tax expenditures erode the tax base, causing the government to forgo revenue, but they provide important tax benefits to individuals and families. How such benefits are distributed over the income distribution varies widely across tax provisions. To assess the distributional effects of a given tax expenditure, the Treasury Department estimated the tax benefits of each major individual income tax expenditure under 2013 income tax law for taxpayers in different income classes.

As illustrated in Figure 3-6, the Earned Income Tax Credit (EITC) and the Child Tax Credit (including the refundable portion) provide substantial benefits to taxpayers in the lowest income quintile but have little impact on the after-tax income of taxpayers in the top three income quintiles. By contrast, the bottom two income quintiles receive almost no benefits from tax expenditures like the charitable giving deduction and deductions for State and local taxes. Almost all of those tax benefits accrue to taxpayers in the top two income quintiles. Middle and upper-middle income taxpayers benefit the most from the exclusion of employer-provided health insurance, whereas taxpayers in the bottom quintile and those in the top percentile of the income distribution receive relatively little benefit from the exclusion.

Because the tax value of deductions and exclusions increases with taxpayers' marginal tax rates, these tax expenditures provide larger benefits to high-income taxpayers than to low- and middle-income taxpayers for a given amount of deductions or exclusions. (For various measures of tax rates, see Economics Application Box 3-1.) In particular, an additional dollar of deductions or exclusions reduces taxable income by $1 and consequently reduces the liability of taxpayers in the 39.6-percent bracket and 25-percent bracket, respectively, by 39.6 cents and 25 cents. In an effort to improve tax fairness, improve efficiency, and reduce the deficit, the President has proposed to reduce the tax value of selected tax expenditures to 28 percent for high-income taxpayers, a level comparable to the tax value provided by the tax code for middle-income taxpayers.

 

_____________________________________________________________________

 

 

Box 3-1: Estimates of Tax Expenditures

 

in the President's Budget

 

 

Tax expenditures, commonly viewed as government spending through the tax code, are defined in the Congressional Budget Act of 1974 as "revenue losses attributable to provisions of the Federal tax laws which allow a special exclusion, exemption, or deduction from gross income or which provide a special credit, a preferential rate of tax, or a deferral of tax liability."

Each year the Treasury Department estimates the value of tax expenditures in terms of the Federal income tax loss and reports the estimates in the annual Budget of the United States Government.1 Table 17-1 of the President's fiscal year 2013 Budget lists 173 corporate and individual income tax expenditures in the tax code. Tax expenditures take many different forms:

  • Exclusions and exemptions allow specific types or sources of income -- such as compensation received as medical insurance or interest from municipal bonds -- to be excluded or exempt from income for tax purposes.

  • Deductions permit taxpayers to deduct certain types of expenses from income to calculate the taxable base. Examples include itemized deductions (which include deductions for home mortgage interest, charitable giving, State and local taxes, and medical expenses) and "above-the-line" deductions (which include deductions for student loan interest, self-employed retirement and health insurance contributions, and educators' out-of-pocket expenses).

  • Tax credits reduce tax liability by the amount of the credit. When the amount of a tax credit exceeds tax liability before the credit is applied, the credit will erase the tax liability, and, if the credit is refundable, the government will pay the filer the excess amount. In the Federal Budget, the portion of a refundable credit that reduces tax liability is treated as a revenue loss, and the portion that exceeds tax liability is treated as an outlay.

  • Special rates apply a lower tax rate to specific sources of income than the rate applied to ordinary income. For example, long-term capital gains and qualified dividends are taxed at lower rates than ordinary income.

  • Deferrals permit taxpayers to delay including certain income in the taxable base. Such tax expenditures include accelerated depreciation or immediate expensing of business investment as well as tax incentives for retirement saving.

 

Table 17-3 of the FY 2013 Budget ranks tax expenditures by projected revenue effect. The 10 largest tax expenditures by the projected revenue effect for 2013-2017 are:2
  • Exclusion of employer contributions for medical insurance premiums and medical care ($1,012 billion)

  • Deductibility of mortgage interest on owner-occupied homes ($606 billion)

  • 401(k)-type plans ($429 billion)

  • Accelerated depreciation of machinery and equipment ($375 billion)

  • Exclusion of net imputed rental income on owner-occupied housing ($337 billion)

  • Special rates for capital gains ($321 billion)

  • Defined benefit pension plans ($298 billion)

  • Deductibility of State and local taxes other than on owner-occupied homes ($295 billion)

  • Deductibility of charitable contributions, other than education and health ($239 billion)

  • Exclusion of interest on public purpose State and local bonds ($228 billion).

FOOTNOTES TO BOX 3-1

 

 

1 The Joint Committee on Taxation also annually publishes a list of tax expenditures. Tax expenditure estimates do not equal the amount of revenue that would be generated if the expenditure were eliminated for two reasons: first, eliminating a tax expenditure would result in behavioral effects that could offset the revenue gain; second, removing multiple tax expenditures simultaneously creates interaction effects that depend on the particular expenditures.

2 The estimates do not include effects on Federal outlays. Refundable tax credits, such as the Earned Income Tax Credit and the Child Tax Credit, can carry significant outlay effects.

 

END OF FOOTNOTES TO BOX 3-1

 

 

_____________________________________________________________________

 

 

The preferential rate on capital gains and dividends gives rise to tax benefits because these sources of income are taxed at a lower rate than ordinary income.2 Of the selected tax expenditures in Figure 3-6, the benefits of the preferential tax rate on capital gains and dividends are most skewed to the upper end of the income distribution. The underlying tax data for Figure 3-6 suggest that taxpayers in the top 0.1 percent of the income distribution receive 41 percent of the total positive capital gains realizations and qualified dividends. Because of this unequal distribution of capital gains realizations and qualified dividends, the preferential rate provides substantially more benefit to the top 0.1 percent of taxpayers than to taxpayers in any other income class.

 

Figure 3-6

 

Distribution of Benefits of Selected Tax Expenditures, 2013

 

 

 

 

Note: Estimates are the percentage reduction in after-tax cash income (2013 income levels)under current law, including ATRA) from eliminating each tax expenditure. Families with negative incomes are excluded from the lowest income class.

Source: Department of the Treasury, Office of Tax Analysis calculations.

Vertical Equity

Vertical equity holds that individuals who have a greater ability to pay should contribute more in taxes than those who are less able to pay (for a discussion of tax fairness, see Economics Application Box 3-1). The President has called one specific formulation of this idea, the Buffett Rule, a basic principle of tax fairness. The Buffett Rule states that no household making over $1 million should pay a smaller share of income in taxes than middle-class families pay. Several studies have shown that the current tax system violates the Buffett Rule; many high-income families pay a smaller share of income in Federal taxes than do middle-income families (Hungerford 2011; CEA 2012; Cronin, DeFilippes, and Lin 2012). Thus, implementing the Buffett Rule, or adopting the rule as a guiding principle for tax reform, would improve tax fairness.

While the current Federal tax system is progressive, its progressivity has significantly declined since the 1960s. Figure 3-1 above shows that average tax rates for middle-income taxpayers rose slightly in the 1960s and the 1970s and then remained relatively stable since the 1980s. By contrast, Federal tax burdens for the wealthiest taxpayers have dropped dramatically since 1960 as a result of changes in tax laws. The share of income the top 0.1 percent paid in Federal individual income and employment taxes fell to 24.1 percent in 2012, about half of what this group paid in 1960.

 

_____________________________________________________________________

 

 

Economics Application Box 3-1: Marginal Tax Rates and

 

Average Tax Rates on Individual Income

 

 

Marginal and average tax rates are two tax rates commonly used to describe a tax system and to measure the fraction of income people pay in taxes. A statutory marginal tax rate for an income tax is the tax rate specified by law and applied to one additional dollar of taxable income. A tax system may consist of multiple statutory rates, with each applying to a range of taxable income to form a tax bracket. A taxpayer's statutory marginal tax rate thus depends on the tax bracket in which her taxable income falls. An effective marginal tax rate is the fraction of an additional dollar of income a taxpayer actually pays to the government. The effective marginal tax rate is determined by the statutory rate as well as by other tax provisions, such as phase-ins or phase-outs of tax credits. An average, or effective, tax rate is the fraction of a taxpayer's total income that is owed as tax liability. The share of total income paid in taxes indicates the tax burden faced by a taxpayer.

One criterion for evaluating tax systems is fairness. Economics provides useful tools to help evaluate a tax system's fairness. Two important concepts are horizontal and vertical equity. Horizontal equity means equal treatment of equals, which is commonly interpreted as equal treatment of those with an equal ability to pay; vertical equity holds that those who have a greater ability to pay should contribute more in taxes than those who are less able to pay. To evaluate vertical equity, a tax can be classified as being proportional, regressive, or progressive. A tax is proportional if average tax rates are equal for taxpayers at all income levels. A tax is regressive if average tax rates fall with income, and a tax is progressive if average tax rates increase with income. Under a progressive tax system, high-income taxpayers face a larger tax burden than low-income taxpayers. This notion is long ingrained in economics. In fact, endorsing progressive taxes, Adam Smith wrote in The Wealth of Nations that "it is not very unreasonable that the rich should contribute to the public expense, not only in proportion to their revenue, but something more than in that proportion."

_____________________________________________________________________

 

 

Figure 3-7 depicts the trends in effective marginal tax rates on wage income. As shown, effective marginal tax rates faced by middle-income taxpayers have been relatively constant during the past five decades, in contrast with the dramatic decline in the effective marginal tax rates faced by the top 1 percent or 0.1 percent of taxpayers. In other words, taxpayers at the top of the income distribution have always faced higher marginal tax rates on wage income than middle-income taxpayers, but the spread between their marginal tax rates has narrowed significantly since 1960. Before ATRA was enacted, the top effective marginal rate on wage income was close to its lowest level in the past five decades; there was only a short period in the late 1980s and early 1990s when the top effective marginal tax rate was lower than the rate in 2012.

 

Figure 3-7

 

Effective Marginal Tax Rates on Wage Income for Selected Income

 

Groups Under a Fixed Income Distribution, 1960-2013

 

 

 

 

Note: Average effective marginal Federal (individual income) tax rates on wage income for a 2005 sample of taxpayers after adjusting for growth in the National Average Wage Index.

Source: Internal Revenue Service, Statistics of Income Public Use File; National Bureau of Economic Research, TAXSIM (preliminary for 2012 and 2013); CEA calculations.

As noted, the preferential rate on long-term capital gains is particularly regressive, and evidence suggests that capital gains realizations have become more concentrated over time. The portion of total capital gains realized by the 0.1 percent of taxpayers who reported the most capital gains income increased from 25 percent in 1987 to over 40 percent in 2010 (Lurie and Pearce 2012). Relative to the increased income concentration, the top effective marginal tax rate on long-term capital gains declined during the period (Figure 3-8). The rate ranged between 20 percent and 30 percent from the 1980s to the early 2000s, fell to 16 percent in 2003, and fell further to 15 percent in 2010 because of the scheduled elimination of the phase-out of itemized deductions under the 2001 tax cut. The rate rose to 25 percent in 2013.

In addition to individual income and employment taxes, the Federal Government collects corporate income taxes and estate taxes. Piketty and Saez (2007) examined the combined effect on vertical equity of Federal individual, employment, corporate, and estate taxes from 1960 to 2004. They argued that corporate and estate taxes substantially contributed to a more progressive tax system in 1960 than in 2004. Because the wealthiest taxpayers own a disproportionately large share of the nation's capital income and wealth, they bear the largest burden of the corporate income and estate taxes.3 The Federal Government, however, has shifted away from relying on these two Federal taxes as revenue sources, leaving taxpayers at the top of the income distribution with a much lower tax burden in 2004 than in 1960. As shown in Figure 3-9, corporate tax revenues as a percent of total Federal receipts declined from 23.2 percent in 1960 to 10.1 percent in 2004. The share for estate and gift taxes declined modestly from 1.7 percent in 1960 to 1.3 percent in 2004 (OMB 2012b).

 

Percent Figure 3-8

 

Top Marginal Tax Rates, 1960-2013

 

 

 

 

Note: The top rate on qualified dividends is equal to the top rate on ordinary income until 2003; thereafter, it is equal to the top rate on long-term capital gains. The top marginal rates on long-term gains calculated by Treasury include the effects of the Alternative Minimum Tax (AMT) and the phase-out of itemized deductions.

Source: Internal Revenue Service, Statistics of Income; Department of the Treasury, Office of Tax Analysis; CEA calculations.

Efficiency and Simplification

From the current point of a complex tax code with many special provisions, simultaneously eliminating special provisions and lowering tax rates could make the tax code both simpler and more efficient. Cutting unfair and inefficient tax breaks and simplifying the tax system with lower tax rates are among the principles the President set forth for tax reform. High tax rates, coupled with a narrow tax base, cause taxpayers to adopt economically inefficient behavior. When examining the efficiency gains from tax reform, it is important to identify the behavioral margins that are in response to changes in tax policy and the resulting economic effects. In theory, lowering tax rates can lead to an increase in labor supply (or a decrease in labor supply if the income effect dominates the substitution effect), but evidence suggests that, when tax rates change, labor supply effects are small compared with tax avoidance effects (Saez, Slemrod, and Giertz 2012). One such effect occurs when investors delay realizing capital gains and hold onto assets only to avoid capital gains tax. Despite this inefficient "lock-in" effect, negative associations between top individual income tax rates on capital gains and private saving, investment, or changes in real GDP are not supported by U.S. experience (Hungerford 2012; Burman 2012).

When taxpayers make decisions in response to special provisions in the tax code, they engage in more of the tax-preferred activity than they would otherwise, thereby steering resources away from other more productive uses.4 One major unfair and inefficient tax break is the tax treatment of partners' profits interests, also known as carried interests, in an investment partnership. Carried interests, despite being derived from performance of labor services, receive capital gains treatment. This preferential tax treatment provided for income derived from performing a specific activity induces a behavioral distortion and is economically inefficient. To improve fairness and efficiency of the tax code, the Administration has proposed to tax carried interests as ordinary income and subject that income to self-employment taxes.

In addition, the Administration has proposed to improve the tax code's efficiency by closing business loopholes and broadening the business tax base. For example, corporations currently use life insurance as a form of tax shelter because of its favorable tax treatment. Investment returns on life insurance products are allowed to accumulate tax free until policies are cashed in. As a result, businesses can take interest deductions for investment-oriented life insurance policies that cover their officers and employees before any gain is realized -- and taxed -- on the policies. The Administration's recent Budget would close this loophole and encourage businesses to make more efficient investment decisions by limiting the interest deductions allocable to investment in certain life insurance policies.

 

Figure 3-9

 

Composition of Federal Receipts, 1960-2011

 

 

 

 

Note: Other includes excise taxes, estate taxes, customs duties, and other receipts.

Source: OMB (2012b).

The President has also proposed making the Federal subsidy for State and local governments' borrowing costs more efficient by extending Build America Bonds (BABs), in which the Federal Government makes direct payments to State and local governments. Traditional tax-exempt bonds provide a Federal subsidy through a Federal tax exemption to investors for interest income received from the bonds. One study finds that as much as 20 percent of the tax revenue the Federal Government forgoes from tax-exempt bonds accrues to investors, leaving only 80 percent of the subsidy to benefit State and local governments (CBO/JCT 2009).

Complexity is another source of inefficiency in the tax code because it increases the amount of time and money taxpayers spend to comply with the law and creates opportunities for them to engage in the unproductive activity of tax avoidance. It is estimated that complying with the Federal income tax cost businesses at least $100 billion for tax year 2009 (Contos et al., forthcoming) and individuals over $50 billion for tax year 2010,5 with the total costs amounting to approximately 1 percent of GDP. Estimating the time and monetary costs incurred by taxpayers for preparing individual income tax returns, an analysis by the Internal Revenue Service (IRS) shows sources of individual income tax compliance costs by reporting activity (Figure 3-10).6 More than half -- 55 percent -- of compliance costs arise from keeping track of and reporting income, and the remaining compliance costs arise mostly from calculations for tax deductions and credits. Thus, tax simplification -- such as having fewer deductions and credits or streamlining income reporting -- has the potential to reduce compliance burdens. Tax simplification could also enhance taxpayer compliance by reducing the opportunities for tax evasion and decreasing inadvertent taxpayer errors in calculating tax liabilities (Kopczuk 2006).7

Reforming the International Corporate Tax

The international provisions of the corporate tax code create opportunities for U.S. companies to reduce their taxes by locating their operations and profits abroad. The tax system is subject to gaming, as corporations manipulate complex tax rules to minimize taxes and, in some cases, shift profit that is attributable to activity performed in the United States or elsewhere to low-tax jurisdictions.

The current U.S. tax system subjects foreign subsidiaries of U.S.-based multinationals to taxes on their overseas income while allowing a tax credit for foreign taxes paid. However, corporations often do not need to pay taxes to the Federal Government on that income until they repatriate it to the United States, a rule called deferral (because it defers taxation of the income). Many companies reinvest, rather than repatriate, a significant portion of their income overseas and, as a result, may never face U.S. taxes on much of that income. The U.S. tax system is often described as "worldwide" because it taxes U.S. companies on profits earned abroad. For many companies, however, opportunities for deferral can make it effectively much closer to a territorial system -- a system in which taxes are never paid on foreign income. By contrast, although most other developed countries have taken a territorial approach, some countries, including Japan and the United Kingdom, have implemented tax "triggers" that effectively apply worldwide taxation if a multinational is operating in a low-tax country.

U.S. multinational corporations have a significant opportunity to reduce overall taxes paid by shifting profits to low-tax jurisdictions -- either by moving their operations and jobs there or by relying on accounting tools and transfer pricing principles to shift profits. Studies show that U.S. multinationals' decisions about the choice of where to invest are sensitive to effective tax rates in foreign jurisdictions (OECD 2008). Evidence also suggests that U.S. firms' reported profits in a foreign country increase when the country's tax rate declines relative to the U.S. rate, after taking into account other factors that would have influenced the level of income earned by U.S. firms in that foreign country (Clausing 2009; Grubert 2012).

 

Figure 3-10

 

Individual Income Tax Compliance Costs by Reporting Activity, 2010

 

 

 

 

Note: Tax year 2010. The cost of reporting the self-employment tax deduction is included in Other taxes.

Source: Internal Revenue Service, Office of Research, Analysis, and Statistics calculations.

The incentive to shift profits to low-tax jurisdictions can lead to inefficient over-investment abroad and under-investment in the United States. It can also erode the U.S. tax base, requiring higher tax rates on income that remains taxable in the United States to collect the same amount of revenue. Finally, the international tax system is very complex, which not only burdens companies with complicated accounting and tax requirements but also benefits companies that avoid paying taxes by manipulating intricate rules.

Business tax reform should be a foundation to maximize investment, growth, and jobs in the United States. It should properly balance the need to reduce tax incentives for U.S. companies to locate overseas with the need for them to be able to compete overseas; some overseas investments and operations are necessary to serve and expand into foreign markets in ways that benefit U.S. jobs and economic growth. The President has proposed to protect the U.S. tax base, strengthen the international corporate tax system, and encourage domestic investment by establishing a new minimum tax on income earned by subsidiaries of U.S. corporations operating abroad (White House/Treasury 2012). That requirement would stop the tax system from rewarding companies for moving profits offshore. Thus, foreign income in a low-tax jurisdiction would be subject to immediate U.S. taxation up to the minimum tax rate, with a foreign tax credit allowed for income taxes on that income paid to the host country. At the same time, this minimum tax would be designed to keep U.S. companies on a level playing field with competitors when engaged in activities that, by necessity, must occur in a foreign country.

 

_____________________________________________________________________

 

 

Data Watch 3-1: Federal Tax Information and

 

Synchronization of Interagency Business Data

 

 

Each year, the Internal Revenue Service (IRS) collects tax data from hundreds of millions of taxpayers. During fiscal year 2011, more than 200 million individual income, employment, corporate income, and estate tax returns and 1.8 billion third-party information returns, such as W-2 and 1099 forms, were filed with the IRS (IRS 2012). Successful tax administration builds on taxpayers' willingness to share personal information with the tax authority and voluntarily comply with tax law (Greenia and Mazur 2006). To ensure taxpayer confidence in the tax system, the tax code contains provisions to safeguard taxpayer confidentiality by requiring each access to Federal tax information (FTI) to be authorized by law.

Under current law, access to FTI is authorized within the IRS for tax administration purposes; in other limited cases, disclosures of FTI are allowed only for specified information to specific parties for specific tasks. When considering whether to amend the law to authorize a disclosure of FTI, Congress should evaluate several factors, including the potential benefits resulting from the data usage and the risk of compromising taxpayer confidentiality or affecting their willingness to voluntarily comply with tax law.

Tax law currently authorizes disclosure of business FTI for government statistical use. It authorizes disclosure of business FTI -- either for corporate or noncorporate businesses -- to the Census Bureau but permits disclosure of business FTI to the Bureau of Economic Analysis (BEA) only for corporate businesses. Another Federal statistical agency, the Bureau of Labor Statistics (BLS), currently does not have access to any business FTI. The Census Bureau uses business FTI to construct its business list, and therefore many Census data products are considered to be "comingled" with tax information (Pilot 2011). Because of the access limits on BEA and BLS, the Census Bureau cannot share many of its products with these two agencies, a situation that prevents the three Federal statistical agencies from synchronizing their business data.

Business data are the fundamental elements for measuring national and local economic activity. National and local statistics on income, output, productivity, payroll, and employment are all based on business data collected by these Federal statistical agencies. Policymakers and businesses rely on these statistics to guide their decision-making. Thus, improving the accuracy, consistency, and reliability of national and local economic statistics can yield tremendous benefits because policy formation and business decision-making will be based on better quality economic statistics. Greater synchronization of interagency business data could advance the quality of economic statistics. For example, BLS and the Census Bureau currently have different coverage and classifications in their business data. BEA's National Income and Product Accounts (NIPA) produce two measures of national economic activity: gross domestic product (GDP, which uses Census Bureau data as its primary source data) and gross domestic income (GDI, part of which uses BLS data).

The two measures of national economic activity differ in part because of discrepancies in the underlying business data. Allowing Federal statistical agencies to share and coordinate business data would help to reconcile these discrepancies and thereby result in a better measurement of economic activity.

_____________________________________________________________________

 

 

The State and Local Budget Outlook

 

 

State and local government expenditures have continued to rebound from the challenges created by the Great Recession, although many State and local governments have yet to return to their pre-recession spending and investment levels. State general fund spending grew by 1.6 percent in real terms in FY 2012, after a small 0.6 percent drop in FY 2011 (NASBO 2012a). In the two previous fiscal years, State general fund spending shrunk dramatically, falling by 2.6 percent in FY 2009 and 8.0 percent in FY 2010 (Figure 3-11); the real gain since 1979 has averaged 1.6 percent a year.

As local economic conditions have rebounded, fiscal distress faced by States has abated, although challenges remain. One such indicator of fiscal distress is the need to institute midyear budget cuts in response to lower-than-expected revenues or higher-than-expected outlays. In FY 2012, just 8 States made midyear budget cuts ($1.7 billion total), down from 23 States in FY 2011 ($7.8 billion), 39 States in FY 2010 ($18.3 billion), and 41 States in FY 2009 ($31.3 billion).

 

Figure 3-11

 

Real Annual Changes in State General Fund Spending, 1981-2012

 

 

 

 

Note: Changes are adjusted for inflation using the state and local government implicit price deflator.

Source: NASBO (2012a).

Like State spending, local government expenditures fell sharply during the recession. Constrained by lower revenues, cities cut back on spending more than they have in 25 years (National League of Cities 2012). General fund expenditures dropped at least 4 percent in both FY 2010 and FY 2011, almost twice as much as they did following the recession in FY 2001. Asked how they plan to change expenditures in FY 2012, local government budget officers most often said they would reduce the size of the municipal workforce, followed by delays or cancellations of capital infrastructure projects. The National League of Cities projected that expenditures will finally increase in FY 2012, but only by 0.3 percent, because local government revenues have yet to grow since the recession (National League of Cities 2012).

On the revenue side, State general fund tax revenues are poised to increase by $26.1 billion in FY 2013 after increasing by $16.6 billion in FY 2012. In nominal terms, general fund revenues are set to surpass prerecession levels for the first time in FY 2013. The reason for this jump several years after the onset of the national recovery is that State revenues follow a cyclical pattern with macroeconomic growth but often do so with a lag.

Local government tax receipts were also decimated by the recession and have yet to rebound. A projected decrease in city general fund revenues for FY 2012 will mark the sixth consecutive year of year-over-year decreases in revenues, and city budget officers will continue to face lingering challenges. Each of the primary tax streams used by local governments -- property taxes, sales taxes, and income taxes -- was affected by the economic downturn. Sales tax revenues dropped sharply and first, as consumers cut back on purchases. In 2011 and 2012, however, city sales tax receipts started to rebound, with sales tax revenues increasing year-over-year in both years (Figure 3-12). Because home values fell, cities -- many of which rely heavily on property taxes -- faced another area of shrinking revenue. The decline in property tax collections came with a lag, however, probably because of the time needed for lower prices to translate into lower assessed values. Property tax receipts fell in 2010 and 2011 and will continue to pose challenges for strapped local governments. Home prices have started to recover, but slowly. Finally, local governments also face lower income tax receipts as unemployment challenges persist.

The Cyclicality of State and Local Government Expenditures

Particular types of State and local government spending are more sensitive to cyclical factors than others. For example, when economic conditions deteriorate, spending on "automatic stabilizers" -- programs like Medicaid that provide means-tested benefits -- increases. While automatic stabilizers are widely recognized as being countercyclical, less attention has been paid to the cyclical behavior of public investment spending. One study by the Government Accountability Office (GAO 2011) examined trends in State and local government spending across the business cycle and found that capital expenditures -- primarily spending on land, buildings, and equipment -- are more procyclical than other types of spending (Table 3-1). The GAO found that spending on health and public welfare is countercyclical, while current expenditures on elementary and secondary education, current expenditures on highways, and capital outlays are the most procyclical categories of State and local government spending. The GAO noted that trends in capital outlays and current expenditures tend to lag the business cycle by one to two years, although there is substantial variation in the lag for current expenditures by type.

 

Figure 3-12

 

Year-to-Year Change in City General Fund Tax Receipts, 2005-2012

 

 

 

 

Source: National League of Cities (2012).

Private economists have reached similar conclusions. Echoing the GAO finding, Wang, Hou, and Duncombe (2007) studied the determinants of capital spending, noting that capital expenditures tend to be more procyclical than current expenditures. The authors cited evidence that States' and municipalities' financing decisions are affected by the business cycle, but the study did not draw conclusions about the impact of the business cycle on the level of capital spending. Similarly, McGranahan (1999) found that capital spending is more procyclical than current expenditures. On average, McGranahan found that each percentage point increase in the unemployment rate leads to a $6.94 fall in per capita capital outlays (average per capita spending is $239.85); this drop is split evenly between construction spending ($3.57) and other capital outlays ($3.37). Moreover, McGranahan found that even though State operating budgets do not include capital expenditures, States tend to reduce budgetary pressure by reducing capital spending during downturns. Hines, Hoynes, and Krueger (2001) found that all components of State and local government spending are procyclical, with capital spending (on highways, parks, and recreation, for example) generally more procyclical than current spending (on health and education, for example).

Bureau of Economic Analysis (BEA) data on State and local expenditures show that the most recent recession was somewhat atypical, with gross investment failing to rebound as in other recoveries (see Figure 3-2 above). Ideally, State and local governments would increase investment spending during recessions, both as a means of employing capital and labor, thereby helping to drive the economy out of the recession, and also as a mechanism for strengthening the economy in the future. Moreover, lower labor costs during recessions make capital projects relatively cheap, meaning that investment during recessions can provide taxpayers with a higher return on investment; historically low interest rates in recent years have further lowered the cost of capital projects. Greater investment by State and local governments in the most recent recession would have both contributed to the recovery and built a stronger economy in future years at a relatively low cost.

                                   Table 3-1

 

     Cyclical Behavior of State and Local Government Expenditures, 1977-2008

 

 ______________________________________________________________________________

 

 

 Expenditure function         Correlation with GDP        Cyclical behavior

 

 ______________________________________________________________________________

 

 

 General expenditures                 0.34                   Procyclical

 

 

      Capital outlays                 0.50                   Procyclical

 

 

 Current expenditures                 0.23                   Procyclical

 

 

      Elementary and

 

      secondary education             0.60                   Procyclical

 

 

      Higher education                0.29                   Procyclical

 

 

      Health and hospitals           -0.36                   Countercyclical

 

 

      Highways                        0.53                   Procyclical

 

 

      Police and corrections          0.38                   Procyclical

 

 

      Public welfare                 -0.31                   Countercyclical

 

 

      All other current

 

      expenditures                    0.40                   Procyclical

 

 ______________________________________________________________________________

 

 

 Source: GAO (2011).

 

 

Despite the downturn in investment spending relative to past recessions, the procyclical nature of State and local fiscal policy means that Federal policies can prove particularly effective at mitigating the economic effects of a downturn. State and local governments serve a vital role in providing services to their residents, and the Federal Government contributes to that role by aiding State and local governments through grants, loans, and implicit support through the tax system.

Federal grants-in-aid -- which include both cash grants and grants in-kind -- have been expanding over time.8 In constant dollars (FY 2005), Federal grants to State and local governments increased from $45.3 billion in 1960 to an estimated $504.4 billion in 2012 (Figure 3-13). The composition of Federal grants to State and local governments has changed dramatically as well. In 1960, 35.3 percent of Federal grants were for payments to individuals, 47.3 percent were for physical capital, and 17.4 percent were for other uses. As projected, in 2012, the share of grants for payments to individuals grew to 60.2 percent, while the share for physical capital fell to 15.7 percent, and the share for other uses grew to 24.1 percent. Thus, over the past five decades, the share of Federal grants for physical capital has plummeted while the share devoted to individual payments has skyrocketed.

 

Figure 3-13

 

Federal Grants to State and Local Governments by Type, 1960-2012

 

 

 

 

Note: Grants that are both payments for individuals and capital investment are shown under capital investment. Figures for FY 2012 are estimates.

Source: OMB (2012a).

Federal Grants to States Through the Recovery Act

The Federal Government used the existing grants structure to provide swift fiscal relief during the recent recession -- a time when states faced severe and unforeseen economic conditions. It did so through the Recovery Act, which provided enhanced grant funding in the areas of education, Medicaid, transportation, energy, water, and other programs.9 Most provisions of the Recovery Act expired in 2010, but some were extended in August 2010 by Public Law 111-226, an act providing education and Medicaid assistance to the States. The temporary fiscal relief provided by the Recovery Act accounts for most of the $141.1 billion increase in Federal outlays for grants-in-aid to States from 2008 to 2010. In 2011, Federal grant outlays were $606.8 billion; this was a $1.6 billion decrease from 2010, reflecting the expiration of the temporary increase in the Federal share of State Medicaid costs and other provisions of the Recovery Act. Grant outlays for 2012 are estimated to increase by $5.7 billion to $612.4 billion.

However, outlays from grants funded through annual appropriations are estimated to decrease by $24.9 billion in 2012 from the previous year and to decrease again by $20.5 billion in 2013. These decreases reflect the winding down of discretionary grant spending on Recovery Act programs such as the State Fiscal Stabilization Fund as well as the enactment of caps on discretionary spending in the Budget Control Act of 2011, which constrains appropriations of new discretionary budget authority, including appropriations for grants.

By transferring aid to State and local governments, the Recovery Act helped stabilize programs that would have been cut and kept States and localities from having to institute tax increases. Had the Recovery Act not provided grants-in-aid to State and local governments, these governments would have been forced either to make deeper cuts in funding for important public programs, including critical education and health programs (and the associated jobs to support those programs), or to raise taxes to compensate for the shortfall. Either option would have been detrimental to the economic recovery. The billions of dollars provided to State and local governments were one of the reasons the Recovery Act was able to dampen the recession and put the country on a faster track to recovery.

State and Local Pensions

State and local pension plans are an important part of the nation's retirement security framework, promising future retirement benefits to 14.5 million workers employed by State and local governments in 2011 (Census Bureau 2012). About 19 percent of total employer contributions to employee retirement plans were made through State and local pension plans, and approximately 28 percent of all plan assets were accounted for by State and local pensions (CBO 2011). Pension plan contributions make up a significant component of the compensation provided to State and local government workers, including police officers, firefighters, and teachers.

Most State and local plans are defined benefit plans, which provide workers with a designated benefit based on years of service and final salary.10 For example, a worker covered by a defined benefit plan might earn benefits equal to 2 percent of wages (often measured over the last several years of employment) multiplied by years of work and adjusted for inflation. The structure of defined benefit plans means that employer liability grows as workers earn wages and increase their tenure with State and local governments; this liability can also grow with inflation because the value of a defined benefit plan is often indexed to the cost of living. From this perspective, defined benefit plans can be viewed as a form of deferred compensation, with workers reaching retirement age being owed compensation earned earlier in their career.

Defined benefit programs offer workers a steady stream of income for life, thus providing insurance against outliving assets and investment risk. One drawback to these plans, however, is the problem of underfunding, which presents a serious long-term fiscal challenge for State and local governments. Underfunding arises when the accumulated contributions in State and local government pension accounts are insufficient to cover the expected liabilities owed to public sector workers. The Pew Center on the States estimated that the public pension programs of State and local governments were underfunded by $757 billion in FY 2010, carrying $3.07 trillion in liabilities and $2.31 trillion in assets (Pew Center on the States 2012). Another study showed that the ratio of State and local pension fund assets to liabilities declined from 103 percent in 2000 to 75 percent in 2011, due in large part to market trends and the specific accounting rules adopted by most plans to value assets (Munnell et al. 2012a). While aggregate funding levels have decreased over the past decade, funding adequacy varies considerably from state to state.

Alternative approaches to calculating pension funding suggest even lower levels of funding adequacy. Unlike private pension systems, which are governed by Federal law and regulations, no Federal rules apply to State and local plans in determining plan liabilities and required contributions. Most States and local pension plans adhere to guidelines drafted by the Governmental Accounting Standards Board (GASB) to report funding adequacy, but the board does not have enforcement authority, nor can it require States and localities to adopt specific funding policies. Until June 2012, GASB standards allowed plans to use discount rates based on the expected rates of return -- typically around 8 percent -- to determine pension liabilities. Under this approach, pension underfunding was about $700 billion at the end of 2009 (CBO 2011), consistent with the Pew Center's estimate. In sharp contrast, CBO found that a broader measure of liabilities that uses the fair value discount rate, an approach often applied in corporate accounting, produces an underfunding estimate of $2 trillion to $3 trillion.

Low levels of funding threaten the welfare of both taxpayers and State and local government employees. One concern is that underfunded pensions will dominate State and local government budgets in upcoming decades, as an increasingly high share of revenue may be needed to provide retired government workers with promised benefits. If taxpayers must devote higher revenue to paying promised benefits to retired workers, less funding may be available for key programs like elementary education, health care, and infrastructure development. From another perspective, underfunded pensions may also pose a risk to government employees, who may see their benefits challenged as a means of achieving cuts in government spending.

Increased transparency in the budget process is a key step toward improving the adequacy of State and local pension funding. One important strategy often proposed to increase transparency is for State and local governments to adopt discount rates for liabilities that accurately portray the magnitude of their promised obligations. Critics of the old GASB discount rate argued that the high discount rate of around 8 percent ignored the role of asset risks in calculating the present value of future promised benefits. Economists often argue that pension liabilities should be discounted by the riskless rate of return because the payments to retired workers will be made with certainty (Novy-Marx and Rauh 2011).11

Under the new discount method approved by GASB, plans will project the portion of pension liabilities that are backed by underlying plan assets (that is, the funded portion) and the portion of liabilities that need to be covered by other resources (that is, the unfunded portion). The new standards allow States and localities to use a roughly 8 percent discount rate for funded liabilities but require the use of a riskless discount rate for pension liabilities that are unfunded (NASBO 2012b). With the new GASB standards, the estimated funding ratio of State and local pension plans would have been 57 percent in 2010, markedly lower than the 76 percent estimated under the previous method (Munnell et al. 2012b).12 Once State and local pension underfunding is better understood through heightened reporting transparency, State and local governments might be more willing to undertake difficult financial decisions and pension reforms to shore up their pension plans.

 

FOOTNOTES TO CHAPTER 3

 

 

1 Behavior that reduces tax remittances without altering real investment, savings, or labor decisions is called tax avoidance when it is legal and tax evasion when it is illegal.

2 One argument for the preferential rate is that corporations already pay income taxes so individual income taxes on capital gains and dividends result in double taxation. However, evidence shows that not all of the long-term capital gains are attributable to corporate stocks or mutual funds, and therefore some capital gains are never taxed at the corporate level (Wilson and Liddell 2010; Burman 2012).

3 Piketty and Saez (2007) assume the burden of the corporate income tax falls on owners of capital income. Several tax policy groups, including the Treasury Department's Office of Tax Analysis, the Congressional Budget Office, and the Tax Policy Center, assume in their current tax models that the majority of the corporate tax burden -- about 80 percent -- is borne by capital income, whereas the remainder is borne by labor. Cronin et al. (2013) provide details of the different corporate tax incidence assumptions.

4 If the tax-preferred activity is underconsumed or underproduced because of market failures or externalities, then a favorable treatment could increase quantity and result in more efficient allocations of resources.

5 The IRS estimates of the business and individual income tax compliance costs include out-of-pocket costs and the monetized burden associated with the time spent on preparing the returns.

6 Under current law, the IRS is authorized access to Federal tax information for tax administration purposes. Certain Federal agencies have limited access to tax data for governmental statistical use. See Data Watch 3-1.

7 For example, studies have shown that complexity may have affected EITC compliance and kept eligible taxpayers from claiming the tax credit (Holtzblatt and McCubbin 2004; Kopczuk and Pop-Eleches 2007).

8 Federal grants generally fall into one of two broad categories: categorical grants or block grants. In addition, these grants may have characteristics of one or more other types of grants: formula grants, project grants, and matching grants. Categorical grants have a narrowly defined purpose and may be awarded on a formula basis or as a project grant.

9 In addition to grant funding to States, the Recovery Act created Build America Bonds, which provided State and local governments a lower-cost borrowing tool to finance public capital projects. Authority to issue Build America Bonds expired at the end of 2010.

10 Defined benefit plans are fundamentally different from defined contribution plans, which allow workers to contribute to an individual retirement account and often offer some form of an employer match. Defined contribution plans do not provide workers with a designated retirement benefit; rather, the individual account balance grows with new contributions and investment returns.

11 In a sample of 77 municipal plans, the discount rate ranged from 7.5 percent to 10.0 percent, with a median of 8.0 percent (Novy-Marx and Rauh 2011).

12 This rate change incorporates the effects of the new discount method and other pension accounting reforms approved by GASB.

 

END OF FOOTNOTES TO CHAPTER 3

 

 

CHAPTER 4

 

 

JOBS, WORKERS AND SKILLS

 

 

The future of the American economy depends critically on our workers and their skills, especially in today's global economy. For the past three decades, American workers have faced a challenging job market. Computers and robots now perform routine tasks, reducing demand for workers in many industries and occupations. In addition, advances in communication technology and low transportation costs have enabled many production jobs to be performed in lower-wage countries abroad. The United States needs to invest in the skills of its workforce to engage effectively in the global competition for good jobs, especially in high-end manufacturing. The Nation also needs to produce and attract highly skilled workers who lead innovation, entrepreneurship, and growth.

Aside from the "skills" challenge, the United States, like many other advanced economies, also faces a "demographic" challenge. Rising longevity and lower birth rates have increased the average age of the population and reduced population growth. Even though the United States is in a relatively strong position compared to many other developed nations in this regard, the latest Census estimates project that the prime working-age population, defined as individuals aged 25-54, will continue to decline as a share of the total population, falling from 40.5 percent in 2012 to 37.9 percent by 2040. By affecting the size of the labor force as well as the ratio of retirees to the working-age population, ongoing demographic changes have a direct impact on the long-run growth of the economy.

This chapter begins by describing the demographic and labor force trends that pose challenges in the near future. It next turns to education and the steps the President has taken to ensure that all Americans have access to the education and training they need to succeed in the changing labor market. The chapter ends with an overview of immigration and its potential to help address both of the challenges ahead -- the need for more workers and the need for a more skilled, innovative, and entrepreneurial workforce. Commonsense immigration reform can be a key contributor to future economic growth and job creation.

 

_____________________________________________________________________

 

 

Box 4-1: Minimum Wages and Employment

 

 

In his State of the Union address, delivered on February 12, 2013, President Obama called on Congress to raise the Federal minimum wage from $7.25 to $9.00 in stages by the end of 2015 and index it to inflation thereafter. His guiding principle was that in the wealthiest nation in the world, no one who works full-time should have to live in poverty. By way of example, President Obama noted that a full-time worker making the minimum wage earns $14,500 a year. Even with the tax relief for lower-income workers that exists in current law, a family with two children and one minimum wage income still lives below the poverty line. Raising the minimum wage to $9.00 would raise the wages of approximately 15 million workers. In addition to making America a magnet for jobs and equipping workers with the skills they need, ensuring that hard work leads to a decent living is a cornerstone of the President's vision to build a stronger economy.

Economists have long studied how the minimum wage affects employment and the economy. A comprehensive survey article written in 1982 concluded that a 10 percent increase in the minimum wage lowers teen employment by 1 to 3 percent. While this reflected the opinion of most economists at the time, the consensus view among economists has since shifted as more evidence has accumulated. Indeed, by the early 1990s time-series estimates of the effect of the minimum wage on teenage employment were turning up statistically insignificant effects (Wellington 1991). The 1999 Economic Report of the President concluded that "modest increases in the minimum wage have had very little or no effect on employment."

The shift in consensus reflects two decades worth of studies that have made some methodological advances in the field. Since the 1990s, after the shift in the time-series evidence, economists have used differences across states in the level and timing of changes to minimum wage laws to study the effect of the minimum wage on employment of low wage workers (Card 1992). This approach arguably produces more robust estimates than the previous time-series approach of relating changes in nationwide teenage employment to movements in the federal minimum wage because it allows researchers to do a better job of controlling for other factors, such as underlying economy-wide trends, that might also affect low-wage employment. A further refinement of the state-level analysis is to focus more specifically on comparisons of adjacent states, which has the advantage that underlying economic trends are more likely to have had similar effects on nearby states (Card and Krueger 1994). A particularly compelling recent study takes this approach a step further by comparing all contiguous county-pairs in the United States that are located on the opposite side of a state border (Arindrajit Dube, T. William Lester, and Michael Reich 2011). The authors show that workers benefited in states that increased their minimum wage, such as California, Rhode Island, New York, Vermont, and Washington, relative to similar workers across the state borders. The study concluded, "For cross-state contiguous counties, we find strong earnings effects and no employment effects of minimum wage increases."

A meta-analysis by Doucouliagos and Stanley (2009) of 64 studies on the minimum wage published between 1972 and 2007, encompassing over 1,000 estimates, finds that most estimates are concentrated around zero, indicating no detectable effect (see figure). The authors conclude that the available research finds "no evidence of a meaningful adverse employment effect" of the minimum wage.

Estimates of the Effect of Minimum Wage

 

on Employment by Statistical Precision

 

 

 

 

Note: "SE" refers to the standard error.

Source: Doucouliagos and Stanley (2009); data provided by John Schmitt.

 

_____________________________________________________________________

 

 

Demographic and Labor Force Trends

 

 

The U.S. adult civilian non-institutional population stood at 237.8 million in 2010 and is projected to reach 263.0 million by 2020, growing at a projected annual rate of 1.0 percent, down from 1.1 percent in the 2000s and 1.2 percent in the 1990s. Further, the share of older Americans is projected to grow over the 2010-20 period, with the number of individuals aged 55 and older increasing 2.6 percent a year, while the number of 16-24 year olds remains roughly constant and the size of the working-age population grows by just 0.3 percent a year (Toossi 2012). These population projections reflect the aging of the baby-boom generation born between 1946 and 1964. Because older men and women are considerably less likely to participate in the labor force than younger individuals, these demographic trends imply that the fraction of the population in the labor force will fall. This trend has already begun.

After increasing at a steady clip for two and half decades starting in the mid-1960s, labor force participation exhibited slower growth during the 1990s and began to fall during the 2000s. The overall labor force participation rate (LFPR), which peaked at 67.1 percent in 2000, fell to 63.7 percent in 2012. Approximately half of this decline can be attributed to the aging of the population and the retirement of the oldest members of the baby-boom generation together with long-term declines in labor force participation among several of the groups shown in Figure 4-1 not related to cyclical factors (see Table 2-1 in Chapter 2).

As the figure illustrates, participation rates have fallen for all major demographic groups since 2000 with the exception of men and women aged 55 and older. The LFPR for younger men and women fell in the 2000s, although the decline for men is a continuation of a long-term trend, whereas the gradual decline for women in the 2001-07 recovery is a new development that reverses a long period of rising participation. The labor force participation rate for 16-24 year olds has dropped precipitously since 2000 after trending down since 1980.

Recent studies suggest two different explanations for the declining trend among teens and young adults. On the one hand, the increasing monetary return to educational attainment has made it more likely that young people enroll in school rather than become employed. One recent study found that while about two-thirds of the decline in participation among teens stems from an increasing share of teens enrolled in school, an additional portion is due to declining participation among those enrolled in school (Aaronson, Park, and Sullivan 2007). To the extent that young people are forgoing work for education, the decline in their labor force participation is less of a concern because they are acquiring skills that will raise their productivity when they do enter or return to work. Less optimistically, other researchers have argued that competition for low-wage jobs has been a major cause of the decline in the teen LFPR, with low-skilled adults now filling jobs that teenagers used to take (Smith 2011).

 

Figure 4-1

 

Labor Force Participation Rate by Population Group, 1970-2012

 

 

 

 

Source: Bureau of Labor Statistics, Current Population Survey, Annual Social and Economic Supplement; CEA calculations.

On the other end of the age spectrum, older workers have increased their labor force participation. Researchers have identified rising education levels and the growth of white-collar and service jobs as important explanations. Other plausible explanations that have not yet been investigated fully are improved health and reductions in the value of retirement savings (Blau and Goodstein 2010; Maestas and Zissimopoulos 2010).

The labor force participation of working-age men has declined steadily since the 1970s. One likely factor behind this trend is that real wages have declined for less skilled men. Since the early 1970s, the average real wage has fallen about 25 percent for high school dropouts and about 15 percent for high school graduates with no further education (Acemoglu and Autor 2011).

The pattern for women has been different. During the 1970s and 1980s, the economy benefited greatly as married women entered the labor force and increased potential and actual gross domestic product (GDP). As Figure 4-1 above illustrates, the growth in female labor force participation abated in the early 2000s. Different forces appear to be at work for different groups of women. Gains in employment for less educated women during the 1990s were encouraged by policy changes (for example, the Earned Income Tax Credit and welfare reform) and by strong economic growth that was not sustained in the early 2000s. Highly educated women, particularly mothers, have pulled back from the pattern of large increases in labor force participation observed in the 1970s and 1980s. Lack of hours flexibility and the challenges inherent in balancing career and family appear to be important factors for these women.

A Slowdown in Women's Participation Rates

Table 4-1 reports participation rates of working-age women in selected years that correspond to peak years of the business cycle and thus allow a focus on long-term trends. From 1969 to 1989, the labor force participation rate of working-age women increased 24.5 percentage points. The most dramatic changes in participation have occurred among married women, and more starkly, among married mothers. The LFPR among married mothers increased an astounding 31.4 percentage points from 1969 to 1999. Growth among all working-age women was slower during the 1990s, but the LFPR for working-age women increased another 4 percentage points to 77 percent in 1999. As the table shows, however, since 1999, the participation rate for these women has declined, falling to 75.6 percent by 2007.

Figure 4-2, which compares the participation rates of women born in different periods, provides insight into the rise and subsequent stagnation of participation among married mothers. Among women born between 1936 and 1945, labor force participation is moderately high at younger ages, drops during the peak child-bearing years, exhibits a subsequent reprise in mid-life, and finally declines as retirement approaches. The curve tends to rise across successive generations of women, indicating higher participation rates for each successive cohort, and the dip associated with child-bearing ages has largely disappeared. The rise in participation, however, appears to have stopped with the most recent generation. Given this pattern across birth cohorts, it is difficult to be optimistic about future increases in the labor supply of prime-age women. New birth cohorts work no more than the immediately preceding cohort at the same ages, and it is therefore unlikely they will work more at later ages. The gains during the 1970s and 1980s achieved from the increased participation of married mothers appear to have come to a standstill and perhaps even partially reversed.

What has brought about this change? One candidate explanation -- that labor market prospects have declined for women in the 2000s -- cannot be the whole story, since participation has fallen even among groups for whom average wages have risen. For example, according to one recent investigation, the average weekly wage of women aged 25-39 with a college degree increased 2.4 percent from 1999 to 2007, after adjusting for inflation, even as the share of this group who are employed fell 3.0 percentage points (Moffitt 2012).

                                   Table 4-1

 

         Labor Force Participation Rate of Women Aged 25-54, 1969-2007

 

 ______________________________________________________________________________

 

 

                                                           Percent

 

                                               ________________________________

 

 

                                               1969   1979   1989   1999   2007

 

 ______________________________________________________________________________

 

 

 Prime-Age Women                               48.8   62.1   73.3   77.0   75.6

 

 

   Marital Status

 

     All married                               43.5   57.4   70.2   74.1   73.3

 

     Widowed/divorced                          69.6   73.4   78.4   81.6   79.0

 

     Never married                             80.5   80.8   81.8   82.6   79.9

 

 

   Marital status and presence of children

 

     Married mothers                           40.8   54.4   67.8   72.2   71.6

 

     Widowed/divorced mothers                  65.5   70.9   76.1   82.5   81.2

 

     Never-married mothers                     50.4   57.6   64.0   78.4   75.4

 

 

   Race

 

     White                                     47.6   61.6   73.3   76.9   75.6

 

     Black                                     58.7   66.5   74.1   79.6   77.8

 

     Other                                     49.1   62.3   69.5   71.4   72.1

 

 

   Education

 

     High school dropouts                      45.0   48.7   51.3   56.1   53.2

 

     High school graduates                     49.8   62.7   73.4   75.2   73.2

 

     Some college                              48.2   66.9   78.3   80.2   79.1

 

     College graduates                         58.2   74.9   83.4   84.3   81.8

 

 ______________________________________________________________________________

 

 

 Source: Bureau of Labor Statistics, Current Population Survey; CEA

 

 calculations.

 

Figure 4-2

 

Age-Specific Labor Force Participation Rate

 

by Birth Cohort for Women, 1926-1992

 

 

 

 

Source: Bureau of Labor Statistics, Current Population Survey, Annual Social and Economic Supplement; CEA calculations.

The one subgroup of women most likely to have been affected by declining labor market prospects is never-married mothers, a population that tends to have lower levels of education and correspondingly lower wages. As Table 4-1 illustrates, the labor force participation of these women rose dramatically from 64.0 percent in 1989 to 78.4 percent in 1999. One factor contributing to this increase was the 1996 welfare reform act, which replaced the welfare entitlements embodied in the old Aid for Families with Dependent Children with more temporary and conditional assistance under the Temporary Assistance to Needy Families program (Blank 2002; Moffitt 2003; Grogger 2003). Another important factor was the expansion of the Earned Income Tax Credit (EITC) in 1986, 1990, and 1993, which made work more attractive and encouraged the entry of low-wage workers into the labor force (Eissa and Liebman 1996; Meyer and Rosenbaum 2001). The impacts of these program and tax changes were amplified by the strong labor market of the second half of the 1990s, a situation that was not sustained as labor markets weakened in the 2000s. The further expansion of the EITC under the Recovery Act and the American Taxpayer Relief Act, and increasing and indexing the minimum wage as proposed by President Obama, would be expected to encourage greater labor force participation for this group in the future.

Work Schedules and Workplace Flexibility

Recent studies that examine the career trajectories of highly educated women in business and law provide some perspective on the challenges women face as they attempt to balance career and family. One study followed a cohort of University of Chicago graduates who had earned a master's in business administration (Bertrand, Goldin, and Katz 2010). While male and female graduates started their careers with similar earnings, 17 percent of the women were not working at all 10 years later, compared with only 1 percent of the men. In addition, only 62 percent of female graduates were working year-round full-time 10 years after graduation, compared with more than 92 percent of the men. The lower levels of work among these career-minded women generally were associated with motherhood, suggesting that work-family balance issues played a role.

One way that women (and others with family responsibilities) may achieve greater flexibility for juggling these competing demands is to work part time rather than full time during some periods. Traditionally, however, given that part-time jobs tended to pay lower wages, the fact that women were more likely to be in part-time work was thought to be a major impediment to women gaining equal pay (Blank and Burtless 1990; Manning and Petrongolo 2008; Bardasi and Gornick 2008). In some cases, however, offering part-time work -- and greater hours flexibility more generally -- may be seen by employers as a way to attract highly qualified workers, especially highly qualified women who might otherwise choose not to work.

Other advanced economies appear to be offering a different mix of work schedules and employment opportunities. Figure 4-3 shows a comparison of labor force participation rates for women, 25-54 years old, in selected advanced economies. While participation rates in France, Germany, and the United Kingdom were slightly below the U.S. rate in 1991, they were higher than the U.S. rate by 2011. Much of the rapid rise in the European participation rates for working-age women has come from increases in part-time work. In contrast, women in the United States are more likely either to work full-time -- defined as 35 hours or more a week -- or not to work at all. Figure 4-4 shows that, among the selected countries, U.S. women are still the most likely to work full-time.

The labor force participation rate and average hours worked among those who do participate can be used to calculate average hours worked per woman across countries. In 2005-09, women worked an average of 26.8 hours a week in the United States, more than the average of 26.4 hours per capita in France, 24.4 in the United Kingdom, 22.3 in Germany, and 20.2 in the Netherlands. The U.S. average, however, was down from 27.4 hours a week in 1995-99, while women's hours worked had risen in all the other countries.

A recent study by Blau and Kahn (2013) noted that in 1990, the United States ranked 6th among 22 developed countries in women's labor force participation, but by 2010 the United States had fallen to the 17th position. Blau and Kahn found that the increased prevalence of "family-friendly policies" -- parental leave as well as part-time work entitlements -- in other developed countries can account for up to 29 percent of the decline in U.S. women's LFPR relative to other countries. Among the countries shown in Figure 4-3, the greatest change in labor force participation for prime-age women occurred in the Netherlands, where the rate rose by nearly 20 percentage points between 1991 and 2011. During this period, the Netherlands instituted laws that mandate equal pay per working hour regardless of total weekly hours worked. These requirements were accompanied by other laws that establish employees' right to request changes in their weekly working hours or request parental leave on a part-time basis (OECD 2012a). As Data Watch 4-1 highlights, the United States lags behind in the availability of both paid and unpaid leave.

One question is whether rising labor force participation comes at a cost. In particular, women in other developed countries could be accepting lower wages in exchange for being able to work part-time or having access to other forms of workplace flexibility. Contrary to this notion, however, gender wage gaps are actually smaller in other developed countries than in the United States. For example, in 2010, the female-to-male hourly wage ratio was 77.7 percent in Germany, 78.7 percent in the United Kingdom, 81.9 percent in the Netherlands, 84.4 percent in France, and 84.4 percent in Sweden. In all of these countries, part-time work and other types of workplace flexibility, such as paid parental leave, are more available than in the United States, where the female-to-male hourly wage ratio was 75.0 percent. Part of what lies behind this phenomenon is that the wage distribution is more compressed in these other countries (Blau and Kahn 2003). Although women in the United States and France are at similar percentile positions of the overall wage distribution relative to their male counterparts, for example, wage compression translates into a much smaller gender wage gap between the average working man and woman in France compared to the United States. Comparisons across countries also suggest, however, that it is not inherently the case that greater flexibility implies lower wages.

 

Figure 4-3

 

Labor Force Participation Rate of Women Aged 25-54, 1991-2011

 

 

 

 

Note: Workers on leave are considered employed. The participation rates in the KILM data are harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies, as well as for other country-specific factors such as military service requirements.

Source: International Labour Organization, Key Indicators of the Labor Market (KILM).

 

Figure 4-4

 

Percent of Women Ages 25 Years and Older

 

Working Full-Time, 1991-2009

 

 

 

 

Note: Full-time is defined as 35 hours per week or more. Workers on leave are considered employed. The participation rates in the KILM data are harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies, as well as for other country-specific factors such as military service requirements.

Source: International Labour Organization, Key Indiciators of the Labor Market (KILM).

Other recent work comparing wages and hours flexibility across occupations also challenges the notion that hours flexibility necessarily comes at a cost. Goldin and Katz (2012) provide an illustrative case study of the pharmacist occupation, where consolidation brought about by scale economies led to the rise of large retail giants. The new market structure made it possible for two part-time pharmacists to substitute for one full-time pharmacist, creating a much more flexible work environment for women. Notably, part-time pharmacists earn no less per hour than full-time pharmacists in contrast to other occupations employing female college graduates where working part-time is associated with wages as much as 20 percent lower. Among women aged 35-39 with pharmacy degrees, only 12 percent were not in the labor force, compared with 18 percent among other college graduates. The study also found that only 11 percent of women with active pharmacy licenses ever had a spell out of the workforce. Given this pattern of continuous participation, female pharmacists are likely to work more over their lifetimes than other women who start working long hours but drop out altogether mid-career as they face the often stark choice between work and family.

To be sure, not all occupations can easily accommodate flexible hours. There is some evidence, however, that even in fields such as medicine, where part-time work is rare, jobs may be evolving to accommodate more flexible schedules (Goldin and Katz 2011). More flexible schedules also seem to be gaining acceptance in the business community (CEA 2010). As more businesses adopt these practices, the cost to any one firm of their adoption will be lowered. An individual employer may be less likely to offer flexible work schedules when other firms have not adopted the same practice out of the fear that it will attract less committed workers. This situation is similar to health insurance, where before enactment of the Affordable Care Act, a firm might not have offered health insurance in an environment where employer-provided health insurance was rare out of the fear that it would attract the least healthy workers. If all firms engage in the practice, the risk to any one firm is lowered.

Such developments may well provide a boost to the economy. Women received a majority of both bachelor's degrees (57 percent) and master's degrees (60 percent) awarded in 2010. Educational attainment commands a high return in an increasingly knowledge-based economy. It is in society's collective interest to encourage women to make full use of these educational investments by remaining in the labor market where the return to their job-related skills can be realized.

 

______________________________________________________________________

 

 

Data Watch 4-1: New Evidence on Access to Paid Leave

 

 

The traditional family today is vastly different than it was decades ago. In contrast to 1975, when just 43 percent of women with children were working, nearly two-thirds of women with children were at work in 2010. The juggling of work and family is not a challenge for women alone. Among married households with children, 60 percent had two working parents. In addition, Americans are getting older. With an aging population, working families will face growing challenges in providing eldercare in the years to come. Access to paid leave and scheduling flexibility can help families deal with these challenges.

Each of the President's Budgets since FY 2011 has proposed money for a State Paid Leave Fund at the Department of Labor that would provide competitive grants to help cover start-up costs for states that choose to launch their own paid leave programs. The value to families of paid leave is illustrated by California's experience with its Paid Family Leave (PFL) program. Since 2004, employed individuals in California have been able to take up to six weeks of paid leave to spend time with a newborn or a newly adopted child or to care for a seriously ill relative. During this time, workers receive payments through the State Disability Insurance system for up to 55 percent of their earnings. A recent study found that the California program more than doubled the overall use of maternity leave, increasing it from around three to six or seven weeks for the typical new mother, with especially large growth among less advantaged mothers, while also raising the hours and wage incomes of employed mothers in the affected group by 6 to 9 percent (Rossin-Slater, Ruhm, and Waldfogel 2011).

The President's FY 2011 Budget included funding to add a module to the American Time Use Survey (ATUS) asking workers about the leave policies at their place of work. The module had questions on leave access, leave use, and unmet need for leave. Because the ATUS is linked to the Current Population Survey, rich data are available on the characteristics of people surveyed. The ATUS survey also provides much-needed information on workers' ability to adjust their schedules or location or to work from home, as well as other dimensions of workplace flexibility that can help in balancing work and family obligations.

This new survey indicates that a large fraction of American workers still lacks access to paid leave, including paid sick leave and paid family leave for the birth of a child. In addition, only 53 percent of the workers reported that they had the ability to adjust their schedule or work location. Previous studies using the National Compensation Survey have shown large disparities in access to paid leave by level of earnings. The new data confirm these findings and, in addition, document large disparities in access to paid leave and scheduling adjustments across education groups and between Hispanics and non-Hispanics (see table). Those in the top quartile of earnings are 1.7 times as likely to have access to paid leave as workers in the bottom quartile (83 percent vs. 50 percent). College-educated workers are about twice as likely to have access to paid leave as workers without a high school degree (72 percent vs. 35 percent). Only 43 percent of Hispanics have access to paid leave, compared with 61 percent of non-Hispanics. Although a large and roughly similar share of workers in most groups has access to unpaid leave, that is a poor substitute for paid leave that can be taken when the need arises.

 

           Access to Leave by Selected Characteristics, 2011

 

 ______________________________________________________________________

 

 

                                              Percent

 

                            ___________________________________________

 

 

                                                           Access to

 

                                             Access to     schedule

 

                              Access to      unpaid        adjustment

 

                              paid leave     leave         or location

 

 ______________________________________________________________________

 

 

 Total                           59.0           76.6           55.9

 

   Gender

 

     Male                        60.3           75.4           55.5

 

     Female                      57.5           77.9           56.3

 

   Race/Ethnicity

 

     White only                  58.9           76.9           56.6

 

     Black only                  60.6           76.7           49.8

 

     Asian only                  62.2           72.1           59.8

 

     Hispanic                    43.0           71.2           48.2

 

     Non-Hispanic                61.4           77.4           57.1

 

   Education

 

     Less than high school       34.9           70.4           37.6

 

     High school                 61.1           75.8           48.2

 

     Some college                66.4           78.2           55.8

 

     Bachelor's or higher        71.6           75.3           60.5

 

   Weekly Earnings

 

     $0-$540                     50.1           78.0           47.2

 

     $541-$830                   77.1           78.9           48.8

 

     $831-$1,230                 81.3           74.9           51.4

 

     $1,230+                     82.7           75.4           59.9

 

 ______________________________________________________________________

 

 

 Notes: Education breakdown is only for individuals age 25 and over.

 

 Each earnings range represents approximately 25 percent of full-time

 

 wage and salary workers (except self-employed incorporated workers)

 

 who held only one job.

 

 

 Source: Bureau of Labor Statistics, American Time Use Survey, Leave

 

 Module; CEA calculations.

 

______________________________________________________________________

 

 

Government as a Partner in Human Capital and Skill Formation

Overwhelming evidence shows that the average return to obtaining a college education is large. In 2011, the median weekly earnings of individuals with a bachelor's degree was $1,053, compared with $638 for individuals with only a high school diploma -- a 65 percent premium for the college graduate. A bachelor's degree is also the gateway to other advanced degrees that command even higher earnings premiums (Figure 4-5). The premium for college and beyond has been rising since 1980 and has continued to increase, albeit at a slower rate than in the 1980s (Acemoglu and Autor 2011). Because the number of college graduates also has been increasing over this time, the rising premium is a signal that the economy is demanding still more college graduates.

From a national perspective, an educated workforce is vital. The productivity of a nation's labor force is a key input into future economic growth, and the most direct prescription for increasing labor productivity is investment in skills. The United States has historically been a leader among developed countries in the share of its population with postsecondary education (referred to by the Organisation for Economic Co-operation and Development as "tertiary" education). That standing has fallen over the past generation, with the United States now ranked 14th among a set of 34 industrialized nations in the share of 25-34 year olds with such education (OECD 2012b). While other measures can be used to assess a nation's ability to educate its workforce -- including measures of educational quality, test scores, and how well people with skills are matched to jobs that can make use of them -- the fall in the U.S. postsecondary education ranking is a reminder that we have more to do to provide America's workers with the skills to compete in today's economy.

 

Figure 4-5

 

Median Weekly Earnings by Education Level, 2012

 

 

 

 

Note: Data are for full-time wage and salary workers, 25 years and older.

Source: Bureau of Labor Statistics, Current Population Survey.

Early learning and the quality of education from kindergarten through high school (K-12) are key determinants of successfully completing a college degree. Study after study finds that early life conditions have persistent and large effects on later life outcomes such as high school graduation rates, employment, and earnings (Cunha and Heckman 2008; Cunha, Heckman, and Schennach 2010; Almond and Currie 2011). In his State of the Union address delivered to Congress on February 12, 2013, President Obama proposed to work with states to make high-quality preschool available to every single child in America. Four years ago, the President launched the Race to the Top competition, which has proven to be successful in convincing states to develop smarter curricula and higher standards for grades K-12. In his 2013 State of the Union address, the President announced a new challenge to high schools to partner with colleges and employers to better equip students with the problem-solving and math skills that are in demand in today's high-tech economy.

President Obama wants to make the United States the leader in postsecondary attainment. In his address to Congress on February 24, 2009, he set 2020 as the year by which the Nation would once again have the highest proportion in the world of young people graduating from college. The U.S. Department of Education projects that the share of college graduates will need to increase by 50 percent to achieve this goal. That means 8 million more young adults will need to earn associate degrees, bachelor's degrees, and meaningful postsecondary certificates by 2020. To achieve this ambitious goal, the higher education system must undertake far-reaching reforms to improve college readiness, widen access, ensure quality, promote affordability and value, and accelerate completion. Colleges and universities in every state have a vital role and a unique opportunity to help America again lead the world in college attainment.

Giving America's workers the skills to compete for good jobs will require the necessary resources to educate millions of additional students. Unfortunately, State and local government support for higher education -- traditionally the cornerstone of public higher education funding -- has been falling for at least a decade. From 2000 to 2010, State appropriations for public four-year institutions fell from $8,029 to $6,388 per full-time student, while appropriations for public community colleges fell from $7,095 to $5,712 (in 2010 dollars).1 This sharp drop in State support has left postsecondary institutions in need of alternative revenue sources, including additional tuition dollars. In fact, in 2010, for the first time ever, public research and master's institutions received more revenue from tuition than from State appropriations. While State appropriations fell only 0.4 percent in 2012, the effects of budget cuts stemming from the economic downturn are expected to last for some time.

Sticker tuition is the price of tuition advertised by the individual colleges. Net tuition is the price students actually pay after deducting Federal, State, and private aid, as well as various discounts offered by the institutions themselves. Between 2000 and 2012, sticker tuition increased from $4,860 to $8,370 (in 2012 dollars) per full-time student at public institutions, an increase of $3,510, and from $21,310 to $28,280 at private institutions, an increase of $6,970 (Figure 4-6). Net tuition per full-time student has increased much less than sticker tuition, going up $1,260 at public institutions and $820 at private institutions over this period. The relatively modest increase in the net cost of attending college resulted in large part from Federal policies aimed at reducing the price of education. President Obama has worked to expand these Federal programs. Expanded Pell Grants made college more affordable for 9.4 million low-income students in 2011 (2.4 million more than in 2009), and the establishment of the American Opportunity Tax Credit (AOTC) has lowered the cost of attending college for millions more.

 

Figure 4-6

 

Tuition and Fees for Full-Time Undergraduate Students, 1990-2012

 

 

a. Private institutions

 

 

 

 

b. Public institutions

 

 

 

 

Source: The College Board, Annual Survey of Colleges, Trends in Student Aid (2012).

Expanded Pell Grants

Pell Grants are the foundation of the Nation's efforts to make college affordable for students from lower- and middle-income families. Pell Grants help more than 9 million Americans a year pay for college, but the purchasing power of these grants has diminished over time. Recognizing the importance of the Pell Grant program to so many people, President Obama worked aggressively to increase the maximum award. The Health Care and Education Reconciliation Act, signed into law in 2010, raised the maximum grant from $5,550 for the 2012-13 academic year to $5,975 in 2017-18. The Act invests approximately $40 billion a year in Pell Grants to ensure that all eligible students receive an award and that these awards will be increased in future years to keep pace with inflation. These steps, together with the funding provided in the American Recovery and Reinvestment Act of 2009 (the Recovery Act) and President Obama's first two Budgets, more than doubled the total amount of funding available for Pell Grant awards.

President Obama also took steps to stabilize Pell Grant funding. In the past, the budgeting process for Pell Grants often led to funding shortfalls, as Pell Grant funding is subject to the annual appropriations process rather than financed through mandatory funding. The appropriations bill that funds Pell Grants for the upcoming academic year is passed almost a full year before the funds become available, and thus the funding is established before it can be clear what the program will cost. The recent shortfall was expected to be particularly severe because of the large number of students qualifying for the award. The Act covered the expected funding shortfall and much of the recent growth in Pell costs, putting the program on a sounder footing going forward. The Act increased investments in Pell Grants by reforming existing student loan programs to deliver loans directly to students instead of subsidizing banks through the more costly Federal Family Educational Loan program. Direct student loans are more efficient and affordable for taxpayers, and the reform allowed more than $60 billion to be reinvested in Pell Grants and other programs that support and sustain college access, while cutting billions from the national deficit (CBO 2010).

Expanded American Opportunity Tax Credit

Tax credits for higher education expenses were substantially expanded by President Obama in the Recovery Act. Before 2009, taxpayers could claim either the Lifetime Learning Credit or the Hope Scholarship Credit toward higher education expenses. The Recovery Act established the American Opportunity Tax Credit, an expanded version of the Hope Credit. The AOTC offers a larger maximum benefit, makes more middle-income taxpayers eligible, and is partially refundable. These provisions substantially enlarged both the pool of taxpayers eligible for education tax credits and the amount of money available to qualifying taxpayers.2

In 2010, the AOTC was one of the most widely used education tax incentives, with 11.9 million taxpayers (8.3 percent of all taxpayers) claiming the credit (Table 4-2). The AOTC benefits totaled $12.3 billion, likely making the credit more important to college affordability than all other education deductions and credits combined. The benefits of the AOTC were spread throughout the income distribution with low- and middle-income families receiving substantial benefits. Seventy-nine percent of the beneficiaries had household incomes below $100,000, and 13.1 percent of beneficiaries had household incomes below $25,000. The refundable aspect of the AOTC was particularly beneficial to low-income households. In 2010, AOTC benefits claimed as refundable credits were worth a total of $6.0 billion to American households, with those benefits flowing overwhelmingly to households with incomes under $50,000. The majority of beneficiaries of the refundable portion of the AOTC -- 63.6 percent -- had household incomes under $25,000. In recent budget negotiations, the Administration achieved an agreement with Congress to extend the AOTC for an additional five years. If the AOTC program had been allowed to expire, 11 million college students and their families would have seen tax increases averaging $1,100. President Obama has called on Congress to make this tax credit permanent so that families can plan ahead and count on this credit for all four years of college.

Aggregate Student Loan Debt

While net tuition has risen considerably less than sticker tuition, for some low- and middle-income families, even the rise in net tuition may have put a quality education out of reach; for other students, the rise in college costs has led to substantially higher levels of borrowing. Aggregate student debt has grown steadily, from $241 billion in the first quarter of 2003 to $966 billion in the fourth quarter of 2012 (in dollars not adjusted for inflation). In contrast, after increasing earlier in the 2000s, aggregate amounts of other types of consumer debt, including mortgages, home equity loans, and credit card and auto debt, have fallen since the financial crisis (Figure 4-7).3 In fact, more student loan debt is now outstanding than either credit card debt or auto loan debt; only the mortgage debt category is larger. This rise in aggregate student loan debt, coupled with an increase in the share of student borrowers in delinquency status, has focused growing attention on student borrowing.

                               Table 4-2

 

   Education Tax Incentives: The American Opportunity Tax Credit, 2010

 

 ______________________________________________________________________

 

 

                                                 Percent of

 

                                    Amount       income       Percent

 

                                    (thousands   class        of total

 

 Income Class            Returns    of dollars)  benefitting  benefit

 

 ______________________________________________________________________

 

 

 $0 to $24,999          2,829,111    1,605,855        4.8        13.1

 

 $25,000 to $49,999     3,628,972    3,579,601       10.5        29.2

 

 $50,000 to $99,999     3,628,533    4,500,639       11.8        36.7

 

 $100,000 to $199,999   1,776,318    2,582,592       12.4        21.0

 

 $200,000 or more           4,122        3,385        0.1         0.0

 

 All returns, total    11,867,055   12,272,073        8.3       100.0

 

 ______________________________________________________________________

 

 

 Source: Internal Revenue Service, Statistics of Income.

 

 

The rise in aggregate student debt -- apparent even after adjusting the figures to account for inflation -- has been driven partly by increased enrollment in postsecondary education (Figure 4-8). Between 1990 and 2012, the number of students attending college increased from 13.8 million to 21.0 million. From this perspective, the rise in aggregate student debt is partly the result of increased investment in human capital, which can be expected to lead to higher wages in the future and to a more prosperous standard of living for the cohorts who have been entering the labor market. The rise in aggregate student debt also reflects increases in the share of students who take out student loans and increases in the amount they borrow. Total borrowing has fallen in the aftermath of the financial crisis, and some of the increase in student debt may reflect families taking out student loans rather than home equity lines of credit to pay for college, but concern has been expressed about the increase in student debt.

Among students who received a bachelor's degree from a four-year public college between academic years 1999-2000 and 2010-11, the share who took out student loans rose from 54 percent to 57 percent. More importantly, the average loan amount rose by 16.1 percent, from $20,500 to $23,800 (in constant 2011 dollars). Sharply rising student loan debt not only threatens the financial stability of recent graduates but also may serve as a disincentive for younger students who are deciding whether to invest in their future and obtain a college degree. To help protect taxpayers, borrowers, and the broader economy against the threat of rising student loan delinquencies, the Administration has advanced several polices designed to make it easier for students to pay back their education loans and to hold schools accountable for poor student debt outcomes after graduation.

 

Figure 4-7

 

Compositions of Household Debt Balance, 2003-2012

 

 

 

 

Source: Federal Reserve Bank of New York, Quarterly Report on Household Debt and Credit.

 

Figure 4-8

 

Total Postsecondary Enrollment by Type of Institution, 1990-2010

 

 

 

 

Source: Department of Education, National Center for Education Statistics, Digest of Education Statistics (2011).

Income-Based Repayment

Since 2009, responsible former students have been able to enroll in an Income-Based Repayment (IBR) plan to cap student loan payments. In October 2011, the Administration announced a new "Pay As You Earn" option that will reduce monthly payments for about 1.6 million current college students and borrowers; eligible borrowers include those holding any type of Federal student loan, such as Stafford, PLUS, and consolidation loans (nonfederal loans and loans in default are not eligible). Starting in 2012, the new IBR option has allowed eligible students to cap their annual loan payments at 10 percent of their discretionary income. The amount that an eligible student borrower is required to pay each month is based on adjusted gross income (AGI) and family size. Specifically, the maximum monthly payment equals 15 percent of the difference between AGI and 150 percent of the poverty threshold for a given family size, divided by 12. Eligible borrowers never have to pay more than the maximum monthly threshold; if a borrower's monthly payments are higher than this threshold, they may apply to have their monthly payments lowered. Ultimately, IBR helps responsible student loan borrowers continue to make payments on their student loans at a manageable rate. As of November 2012, the Department of Education estimated that approximately 1.37 million borrowers are participating in the IBR program.

Federal Loan Consolidation

The Administration also took important steps to allow student borrowers to better manage their debt by consolidating their Federal student loans. Starting in January 2012, an estimated 6 million current students and recent college graduates were eligible to consolidate their loans as a Direct Loan, and by so doing, reduce their interest rates. Before this policy change, approximately 5.8 million borrowers had both a Direct Loan and a Federal Family Education Loan. These loans require separate payments making borrowers more likely to default. By consolidating these loans, borrowers could achieve the convenience of a single payment to a single lender. Borrowers who took advantage of this consolidation option also received up to a 0.5 percentage point reduction in their interest rate on some of their loans, which means lower monthly payments that may save each borrower hundreds of dollars in interest over the life of the loan.

The Growth of For-Profit Colleges

Although they still account for only a small fraction of all postsecondary education students, for-profit colleges are the fastest-growing type of postsecondary school. They offer both an opportunity and a challenge for America's system of higher education. For-profit colleges have been shown to be flexible and innovative in meeting the needs of many postsecondary students, especially those who seek a nontraditional education or who require flexible arrangements for receiving their education, such as on-line and evening courses. Many for-profit colleges respond quickly to the changing needs of employers, and they can play an important role in helping more Americans earn college degrees. However, the experiences of some students at for-profit schools have been a cause for concern.

For-profit colleges have shown mixed outcomes with respect to completion rates relative to other types of institutions. For-profit completion rates in one- and two-year programs tend to be higher than completion rates for similar programs at other schools, but completion rates in for-profit bachelor programs are significantly lower. Low graduation rates not only waste taxpayer funds devoted to subsidizing the cost of education but can lead to prolonged financial hardship for students who borrow to finance their education but do not gain a college diploma to add to their earning potential.

Students at for-profit schools are about twice as likely as other students to be idle -- not working or enrolled in school -- six years following matriculation. In 2009, 23.6 percent of enrollees at for-profit schools were idle six years later, compared with just 10.6 percent of matriculating students at four-year public and nonprofit private schools, and 13.3 percent of matriculating students at two-year public and nonprofit private schools. As a result, the average annual earnings of for-profit graduates are about $2,000 less relative to their counterparts at other types of schools, after accounting for differences in student characteristics (Deming, Goldin, and Katz 2012). Yet another study that uses detailed data to take account of differences in student characteristics found large and significant earnings benefits from obtaining an associate degree from public and nonprofit institutions but not from for-profit institutions (Lang and Weinstein 2012).

Given the higher tuition costs at many for-profit institutions, students at these schools also leave with substantially higher debt than their counterparts at public and nonprofit schools. In 2007-08, 53 percent of bachelor's degree recipients at some for-profit four-year schools had accumulated more than $30,500 in debt, compared with 24 percent of graduates at private nonprofit schools and just 12 percent of public school graduates (Baum and Steele 2010). Default on student loans is a much more serious problem at for-profit schools. For fiscal year 2009, the three-year "cohort default rate," which measures the percentage of borrowers who enter repayment with student loans and default over a three-year period, was 22.7 percent among for-profit students, compared with just 7.5 percent for private nonprofits and 11 percent for public institutions (Department of Education 2012).

Gainful Employment

In 2010 and 2011, the Obama Administration issued a broad set of rules to strengthen occupational higher education programs at for-profit, nonprofit, and public institutions by protecting students from aggressive or misleading recruiting practices, providing consumers with better information about the effectiveness of such education and training programs, and ensuring that only eligible students or programs receive aid. One notable provision in this set of regulatory reforms was the "gainful employment" rule, which made occupational programs ineligible for Federal aid if they failed to meet a set of tests related to students' financial situations after graduation. While many occupational and for-profit institutions have pioneered new ways to reach adult students, offer online education, and meet the needs of employers, some programs have left students with large debts and poor employment prospects. Specifically, the rule stated that programs could become ineligible for financial aid if fewer than 35 percent of graduates were actively repaying their student loans; graduates were spending in excess of 30 percent of their discretionary income on student loan payments; and graduates were spending more than 12 percent of their total income on student loan payments. The gainful employment provisions were intended to align institutional incentives with the interests of students, by conditioning eligibility to receive Federal aid on student outcomes. In June 2012, a Federal judge vacated the key provisions of the gainful employment rule on the grounds that there was no factual basis for the rule's 35 percent repayment standard and that the better-grounded debt-to-income ratio standards were so intertwined with the repayment standard as to invalidate the whole rule. The Department of Education has appealed a portion of the judge's decision, asking that schools continue to be required to report information about their students' loan repayment rates and debt-to-income ratio to the Department even if this information is not used to determine eligibility for Federal funds. The Obama Administration remains committed to the principles of accountability and transparency in the use of taxpayer funds in occupational higher education programs and will continue efforts to provide students with good information about the quality and value of such programs.

What Is Driving Up Tuition Costs?

One often-posed explanation for the increase in tuition costs is that colleges require skilled labor inputs -- highly educated instructors -- and as education premiums rise, so do the costs of these skilled labor inputs. This explanation -- an example of the Baumol's cost disease (Economics Application Box 4-1) -- may be a contributing factor at private colleges but is unlikely to be the major part of the story at public institutions. Over the period 2000-10, average full-time faculty salaries increased 2 percent at public four-year colleges and actually fell at community colleges. Instructional spending as a share of total costs has been falling at public colleges as institutions seek to cut costs by substituting non-tenured and adjunct faculty for full-time tenure-track faculty. Evidence is mixed on whether this compositional shift has hurt learning outcomes with some arguing that graduation rates have suffered while others find no measurable changes. But, faculty salaries have not driven up costs.

So, what is driving up tuition costs? A recent survey article by economist Ronald Ehrenberg suggests that no single answer fits across all institutional types. Different types of institutions -- private and public universities engaged in research, private and public institutions largely devoted to teaching, and public community colleges specializing in two-year instructional programs -- are subject to different market forces and cost pressures (Ehrenberg 2012).

One driver of costs for many colleges is increased competition for students. The higher education market has been transformed from a statebased model where a majority of students attend local state universities to a more national -- even international -- market where students search over a large set of options. In this competitive environment, many institutions seek to position themselves as unique by offering an attractive mix of amenities. Published rankings likely contribute to this spending race because expenditures per student and average faculty salaries are often inputs into the rankings. Private research institutions, including the elite private universities, are in the best position to compete in this environment. These universities seek to have the most appealing facilities and the most renowned research faculty, and so at these types of institutions, the rise in tuition reflects rising average expenditure per student. At private research institutions, average spending per full-time equivalent (FTE) student on "education and related" items increased by more than $10,000, from $42,449 in 2000 to $52,710 in 2010, all measured in 2010 dollars. Spending increases have been fairly evenly spread across categories such as instructional expenditures (faculty salaries and benefits), research (grants and contracts as well as matching funds), student services (admissions, registrar, and counseling services), and academic support (libraries and academic computing) (Figure 4-9a). While these increases may look like rising labor costs, spending on physical plant -- "operation and maintenance costs" -- has also increased. An important factor for private institutions is "tuition discounting," or the share of each tuition dollar that is returned to students in the form of need-based or merit grant aid. Tuition discounting at these institutions is substantial and increased from 28.6 percent in 2000 to 33.1 percent in 2008. The ability to offer tuition discounts essentially allows institutions to price discriminate in order to obtain a diverse mix of students.

 

______________________________________________________________________

 

 

Economics Application Box 4-1: Baumol's Cost Disease

 

(or Bowen's Curse) and the Price of Education

 

 

In the 1960s, economists William Baumol and William Bowen developed the notion, known as "Baumol's cost disease," that in certain labor-intensive industries -- the example they chose was the performing arts -- there is less opportunity for productivity gains to reduce labor costs. The number of musicians needed to perform Beethoven's Ninth Symphony is the same today as it was decades ago, but the number of workers needed to produce a single car has fallen considerably. Because markets dictate that wages remain comparable across industries for equally skilled workers, the relative price of products and services in sectors where productivity is stagnant will rise over time. Baumol's cost disease has been cited as a partial explanation for the long-term growth in education costs. Compensation for higher-education faculty and administrators has been rising over time, even though productivity in education has changed very little.

Whether and to what extent Baumol's cost disease plays a role in the continued rise in higher education cost is a topic of much debate. Regardless of its importance as a possible explanatory factor, improved technology and productivity growth offers a potential solution to growth in the cost of college, opening up potential new ways to deliver education. One such innovation is massive open online courses, or MOOCs, that can accommodate tens of thousands of students in a single class. Another promising innovation is courses delivered through a hybrid of online lectures and in-person tutoring. One study that used randomized trials found no significant difference in learning outcomes between traditional face-to-face statistics courses and hybrid online statistics courses, yet costs were lower in the hybrid course. Another study, also using a randomized design, found a slight advantage for live economics lectures over online lectures in the case where all ancillary materials such as web-based assignments and availability of tutors were comparable. The relatively small advantage demonstrated by live lectures, however, suggests there is room for considerable cost saving with relatively little reduction in learning outcomes (Bowen et al. 2012; Figlio, Rush, and Lin 2010).

______________________________________________________________________

 

 

In contrast, at public institutions, where most students enroll, average spending per student has not risen nearly as much, and tuition increases largely reflect institutions' attempts to compensate for declining State support (Figure 4-9b). At public community colleges, the average level of State and local appropriations per FTE student to these institutions fell from $7,095 in 2000 to $5,712 in 2010. Other public institutions lie somewhere between these two extremes, with public research institutions looking more like private research institutions, and public master's- and bachelor's-degree-granting institutions that are more oriented toward teaching looking more like community colleges. Average expenditure per FTE student at public research institutions increased from $24,178 in 2000 to $26,971 in 2010. Public research institutions shifted resources away from instructional spending by substituting non-tenured and part-time faculty for full-time, tenured faculty. Meanwhile institutional spending to support research activities increased, likely reflecting the attempt to gather new funding sources such as Federal and private research grants as State and local appropriations decreased. To compete with private universities for faculty who can attract Federal and private grants, public institutions often provide "start-up" research funds and build expensive lab facilities.

The Administration is committed to keeping college affordable for middle-class families. The Department of Education has released a College Scorecard to provide transparency for families as they evaluate their options for their higher education. The Department, along with the Consumer Financial Protection Bureau, has also designed a College Shopping Sheet to help families and students understand exactly how much money they will owe at each of the schools to which they have been accepted. President Obama has proposed a Race to the Top: College Affordability and Completion challenge to reward States that increase the number of college graduates while containing the costs of tuition. The President has also called on Congress to work with him to hold colleges accountable by considering value, affordability, and student outcomes in making determinations about which colleges and universities receive access to Federal student aid.

 

Figure 4-9

 

Average Expenditures per Full-Time-Equivalent Student

 

by Component, 2000-2010

 

 

a. Private institutions

 

 

 

 

b. Public institutions

 

 

 

 

Source: Integrated Postsecondary Education Data System, Delta Cost Project.

Government as a Partner in Training

As part of the Administration's efforts to prepare workers for America's 21st century economy, meet the needs of local employers, and achieve President Obama's goal of ensuring that every American worker has the opportunity to secure at least one year of postsecondary education, the Department of Labor, along with the Department of Education, launched the Trade Adjustment Assistance Community College and Career Training (TAACCCT) grant program. This $2 billion initiative expands the capacity of community colleges to provide training and credentials to local workers needed for high-wage, high-skill employment in industries like advanced manufacturing, biotechnology, information technology, and other emerging fields. To date, the Department of Labor has awarded 45 grants to colleges across the nation to develop curricula for advanced manufacturing. For example, the Department of Labor funded the National STEM Consortium, led by Anne Arundel Community College in Maryland. This collaboration of 10 leading community colleges in nine states organized to develop nationally portable, certificate-level programs in science, technology, engineering, and mathematics and is also building a national model of multi-college cooperation in the design and delivery of high-quality, labor-market-driven occupational programs. Spokane Community College, in partnership with 11 other community colleges, worked with aerospace employers including Boeing to design an advanced curriculum in aerospace maintenance and manufacturing. The consortium known as Air Washington has been recognized by the Boeing Company for this curriculum development and for its ongoing assistance to the Boeing Academic Alignment Team. This effort includes the development of a pre-employment program to offer training in basic aerospace-related skills to adult learners, a web-based curriculum component on English as a second language, and assessments of prior learning, particularly for active military or veterans, to evaluate credit and classroom advancements based on military experiences and training. The programs funded by TAACCCT are establishing a national repository of high-quality technical curricula and related materials that can be made available at no charge to community colleges around the country.

Several existing U.S. training consortia provide successful models. Among those worth noting are Project QUEST and the Wisconsin Regional Training Partnership. Project QUEST is a training program in San Antonio aimed at the working poor with high school diplomas. The program works with firms (many of which are hospitals) in the city to identify job openings and the skills required to fill them. The firms then make a good-faith pledge to hire program graduates into jobs that meet living-wage standards and may redesign their jobs to create advancement ladders. The training is provided by local community colleges and typically lasts a year and a half. The program, which offers modest financial support and extensive counseling to the trainees, is organized and managed by a nonprofit closely linked to a community-based organization. More than 2,000 people have participated in QUEST. An evaluation found that those who completed the program saw their earnings rise by an average of $5,000 a year (Kochan, Finegold, and Osterman 2012). The Wisconsin Regional Training Partnership was established by unions and firms in Milwaukee in the 1990s and does training for manufacturing and construction. A study with random assignment of participants to treatment and control groups found significant increases in employment and incomes for program participants compared with nonparticipants (Holzer 2011).

Key features of these successful programs are the involvement of industry and worker-focused organizations, along with a commitment to continually evaluate what works and what does not, and a willingness to make adjustments. The involvement of employer groups ensures that the training is relevant; the involvement of worker-focused organizations ensures that workers share in the gains of their improved productivity. Together, the groups can work together to upgrade jobs, rather than taking current job duties and career paths as given. In some cases, as in the Wisconsin program, upgrading has meant calling on other agencies (in that case, the federally funded Manufacturing Extension Program) to help firms upgrade their management, operations, and information-technology practices so that they offer a greater return to skill (Maguire et al. 2010). The programs also have used a variety of tools (focus groups with employers, unions, and workers but also randomized controlled trials) to evaluate their programs, adjusting if necessary based on the results.

 

Immigration

 

 

We are a nation of immigrants and their descendants. Now, more than ever, the economic and social benefits of immigration loom large. Immigrants increase the size of the population and thus of the labor force and customer base, making an important contribution to economic growth. In 2010, there were nearly 40 million foreign-born people in the United States, representing 13 percent of the population and 16 percent of the workforce. As the United States faces the prospect of a slow-growing population, immigrants are likely to play an increasingly important role in the American economy. Immigrants work in diverse industries and occupations. While they represent 16 percent of the workforce, they account for more than 20 percent of workers in agriculture, construction, food services, and information technology. They are agricultural laborers, domestic workers, and cabdrivers as well as health care workers, computer software engineers, and medical scientists (Singer 2012). This diversity promotes economic growth as immigrants and natives often specialize in different tasks and occupations.

In addition, many highly skilled workers in the STEM fields are immigrants, and research has shown that these workers contribute importantly to innovation and growth. Many immigrants start businesses and create jobs for American workers. The United States has a distinct advantage compared with other developed nations in that flexible labor markets and robust returns to skills encourage the in-migration of these highly qualified workers. Our open society also allows immigrants to integrate better than in other countries, and we benefit from their vitality and creativity. Commonsense immigration reform can honor America's historical legacy of welcoming those willing to work hard for a better life, while also promoting its national and economic interests.

A Brief History of U.S. Immigration Policy

International migration flows from developing to developed countries are on the rise across the world. According to the latest United Nations estimates, more than 200 million people, or 3.1 percent of the world's population, live in a country that is not their original country of birth. Table 4-3 shows immigrants as a share of total population in selected advanced economies. In addition to the historical immigrant-receiving countries such as Australia, Canada, New Zealand, and the United States, the European Union, Scandinavian countries, and even Russia now have substantial foreign-born populations.4

Between 2001 and 2010, 10.5 million foreign-born individuals received legal-resident status (green cards) in the United States. While this is a large number, Figure 4-10 illustrates that the flow of legal immigrants is only now surpassing levels attained at the turn of the 20th century, when the population was much smaller but immigration was virtually unrestricted. The figure also shows that immigrant inflows, as a share of the total population, are far below the levels reached in the 19th century. In reaction to the large inflows in the early 1900s, particularly from Eastern and Southern Europe, Congress enacted a national quota system in 1921. The 1965 amendments to the Immigration and Nationality Act repealed the national quota system and made family reunification a priority. Under current law, immediate relatives of U.S. citizens -- spouses, minor children, and parents -- are not subject to annual numerical limits. For other family members including siblings and adult children of U.S. citizens and spouses and minor children of legal permanent residents, a numerical cap of 226,000 applies. Over the 10-year period from 2002 to 2011, an average of 469,777 immediate relatives of U.S. citizens and an average of 207,927 other family members obtained permanent residency status annually (DHS 2011). As a result of numerical limits and processing backlogs, applications in the "other family member" category have long waiting times. The longest waiting periods are for applications from countries such as China, India, Mexico, and the Philippines; under the law, no more than 7 percent of total family-sponsored visas can be allotted to any single country.

                               Table 4-3

 

              Foreign-Born Persons in Selected Countries

 

 ______________________________________________________________________

 

 

                                    Percent of Total Population

 

                           ___________________________________________

 

 

         Country                   1990                    2010

 

 _____________________________________________________________________

 

 

      New Zealand                  15.5                    22.4

 

      Australia                    21.0                    21.9

 

      Canada                       16.2                    21.3

 

      Spain                         2.1                    14.1

 

      Sweden                        9.1                    14.1

 

      United States                 9.1                    13.5

 

      Germany                       7.5                    13.1

 

      France                       10.4                    10.7

 

      United Kingdom                6.5                    10.4

 

      Russia                        7.8                     8.7

 

      Japan                         0.9                     1.7

 

 _____________________________________________________________________

 

 

 Source: United Nations, Department of Economic and Social Affairs,

 

 Population Division, Trends in International Migrant Stock (2008).

 

 

Foreign workers also come to the United States through employment-based green cards. A maximum of 140,000 employment-based slots for permanent residency are available each year, although the actual cap varies since unused visas in the family program are carried over to the employment system. On average over 2002-11, 157,181 employment visas were issued annually (DHS 2011). Employment-based green cards typically require the worker to have at least a college degree or documented evidence of special skills; only 10,000 employment-based green cards are available to workers without formal education or skill requirements. Individuals can obtain employment-based green cards for making large direct investments in job-creating enterprises, although this category is limited to approximately 10,000 visas.

 

Figure 4-10

 

Legal Immigration by Decade, 1820s to 2000s

 

 

 

 

Source: Department of Homeland Security, Yearbook of Immigration Statistics (2011); Department of Commerce, Census Bureau.

Foreign-born individuals are also allowed to reside and work in the United States on a temporary basis through several temporary immigrant visa programs. For example, individuals are admitted to work in the agricultural industry (H-2A visas) and other seasonal industries (H-2B visas) for short durations on specific jobs with specific employers. These visas help alleviate peak seasonal demands in certain sectors of the economy but cannot be used to employ less-skilled workers for longer durations. H-1B visas permit temporary employment for skilled professionals who are sponsored by a U.S. employer, typically in science, computer, or engineering occupations. A worker can remain in H-1B status for up to six years. Current law permits 65,000 new H-1B issuances a year, although up to 20,000 individuals who either hold advanced degrees from U.S. universities or are going to work for institutions of higher education or government research organizations are exempt from the cap. Applications for the H-1B visa are accepted starting in April for the following fiscal year. The application window closes when the annual cap is met. Demand for H-1B visas slowed during the recent recession but has picked up again, pointing to increasing demand for workers in the rapidly growing STEM occupations. One study published by the Department of Commerce found that employment in STEM occupations increased 7.9 percent from 2000 to 2010 while employment in non-STEM jobs grew just 2.6 percent over the same period. Moreover, STEM jobs are projected to grow by 17.0 percent from 2008 to 2018 (Langdon et al. 2011). In 2010, 151,710 foreign graduate students were enrolled in U.S. postsecondary institutions in STEM fields (NSF/NIH 2010). Allowing this population -- already here and educated in the United States -- to stay by increasing the number of visas available will ultimately position the Nation well in the global competition for new ideas, new businesses, and jobs of the future.

In part because of the limited pathways for less skilled workers to obtain legal status, an estimated 11.5 million foreign-born individuals in the United States are undocumented (Hoefer, Rytina, and Baker 2012). Bipartisan support for strengthened immigration enforcement has resulted in a well-resourced and modernized enforcement system. While effective, the fiscal burden of this system is also substantial. The Border Patrol has doubled in size over the past seven years to 21,370 agents in FY 2012. Spending for the two main immigration agencies -- U.S. Customs and Border Protection and U.S. Immigration and Customs Enforcement -- surpassed $17.9 billion in FY 2012, an amount that is higher than all other spending on criminal Federal law enforcement agencies (Meissner et al. 2013). Workplace enforcement, which could alleviate some of the fiscal burdens of border enforcement, has not kept pace. Effective workplace enforcement would entail enabling employers to quickly and accurately verify employees' eligibility by using an electronic employment verification system (E-Verify), and also holding those employers accountable who deliberately break the law by hiring unauthorized workers or violating labor laws.

The Department of Homeland Security estimates that of the 11.5 million unauthorized immigrant population residing in the United States in 2011, approximately 1.3 million were under 18 years of age (Hoefer, Rytina, and Baker 2012). Undocumented young people who were brought to the country as children have no clear path to future legal status that would enable them to further their education and find gainful employment outside of the shadow economy. Various versions of legislation to address the undocumented student population, often referred to as the DREAM Act, have been introduced in recent congressional sessions. The latest effort in 2010 passed the House but failed to pass the Senate. In June 2012, the Secretary of Homeland Security announced and implemented a new process, known as "Deferred Action for Childhood Arrivals," which provides work-status eligibility and relief from deportation for unauthorized immigrants who are no more than 30 years old and who arrived in the United States before age 16. While a smaller number are currently eligible to petition, up to 1.7 million young people could potentially benefit from this program once they reach the requisite age (Passel and Lopez 2012).

Foreign-born workers in the United States tend to be concentrated at both the low and the high end of the educational spectrum. Table 4-4 shows that 29.1 percent of the foreign-born have less than a high school degree. On the other hand, 10.9 percent have a master's degree or higher, a share on a par with that of the native-born. The table also shows that the foreign-born are more likely to be of working age, with 67.2 percent of the foreign-born aged 25-54 years old compared with 55.9 percent of the native population. The table also shows that foreign-born men are much more likely to be employed than native-born men.

Other countries that receive large numbers of immigrants, such as Australia and Canada, admit a majority of their immigrants based on employment skills. Australian work visas are most commonly granted to highly skilled workers. Candidates are assessed against a system that grants points for certain standards of education. In Canada, almost two-thirds of visas are issued to economic immigrants, primarily skilled workers and their dependents. Skilled workers are selected on factors such as education, English or French language abilities, and work experience. In contrast, the United States has a more "outcome"-based approach to granting visas. For example, employment visas are awarded to persons with extraordinary ability (EB-1), outstanding professors and researchers (EB-2), and skilled and unskilled workers with job offers from a U.S. employer (EB-3). While some may argue that Canada and Australia might do a better job of attracting skilled immigrants than the United States because of their point-based systems, a recent study using detailed data compares the United States with Australia and finds that, by and large, the two countries attract similar immigrants. Skill premiums and geographic proximity, rather than the specific details of the admission criteria, play the predominant role in determining the quality of employment-based immigrants (Jasso and Rosenzweig 2008).

                               Table 4-4

 

          Distribution of Education, Age, and Employment For

 

            Natives and Foreign Born Individuals, 2010-2012

 

 ______________________________________________________________________

 

 

                                         Native          Foreign Born

 

 ______________________________________________________________________

 

 

 Education Attainment (Age 25+)

 

 

   Less than high school                   9.3                29.1

 

   High school, no college                31.7                26.0

 

   Some college or associates             28.2                16.2

 

   Bachelor's                             19.9                17.8

 

   Master's or higher                     10.9                10.9

 

 

 Age Group

 

 

   16-19                                   0.6                 0.3

 

   19-24                                   6.9                 5.0

 

   25-54                                  55.9                67.2

 

   55-64                                  17.5                13.6

 

   65+                                    19.1                13.9

 

 

 Work Status

 

 

   Employed                               60.3                62.4

 

 

    Men                                   64.7                73.8

 

    Women                                 56.2                51.2

 

 ______________________________________________________________________

 

 

 Note: Sample limited to individuals 16 and over who are not enrolled

 

 in school.

 

 

 Source: Bureau of Labor Statistics, Current Population Survey, Annual

 

 Social and Economic Supplement; CEA calculations.

 

 

Since enactment of the Immigration and Nationality Act of 1965, family reunification has been a cornerstone of U.S. immigration policy. Debate continues on whether the United States should maintain this family-based system or move more toward an occupation- and skills-based system. While the question is often posed as a stark choice between two systems, in reality the two visa categories -- family and employment -- complement each other in important ways. In choosing a country to move to, skilled prospective immigrants envision a better life not only for themselves but for their families. Using data arranged by year of arrival and country of origin, one study found a positive correlation between the fraction of immigrants arriving on sibling preference and mean education levels of the immigrants. The data seem to support the notion that highly educated immigrants who arrive based on employment and occupational preference categories then sponsor their siblings who are also highly educated (Duleep and Regets 1996). As proposals are made to increase skill-based immigration, it is important to keep in mind that a welcoming policy toward the family is an important factor in attracting skilled workers to live and invest in the United States.

The Economic Benefits of Immigration

Conventional theory suggests that the destination country as a whole gains from immigration, though these gains may be uneven across groups. Immigrants add to the labor force and increase the economy's total output. The gains accrue to natives whose productivity is enhanced by immigrant workers -- often referred to as complementary factors -- as well as to capital owners. A major study published by the National Research Council in 1997 estimated the size of the "immigrant surplus" to be on the order of $14 billion in 1996 dollars, or 0.2 percent of GDP. Given the size of today's economy, this translates into $31.4 billion in 2012 dollars, even without accounting for growth in the share of the population that is foreign born.

There are additional reasons to think the above calculations may understate the full economic benefit of immigration. For one, the calculations do not take into account the fact that capital owners may boost investment in response to the increased number of workers, which may induce further economic growth. For another, the simple approach assumes a negative impact on the average wages of native workers that has been difficult to establish empirically. The same National Research Council study concluded that the body of empirical evidence pointed to a very small negative impact from immigration on wages of competing native workers -- on the order of 1-2 percent and often statistically insignificant.5 In fact, to the extent that new immigrants crowd out existing workers, research shows that those most adversely affected are recent immigrants (Lalonde and Topel 1991; Ottaviano and Peri 2012). A new immigrant with limited English skills, for example, will likely compete closely with other recent immigrants with poor English ability in jobs that do not require institutional, technical, or advanced language skills, thereby lowering the recent immigrants' wages.

Recent studies suggest, in fact, that the skills and talents that immigrants and natives bring to the labor market may not be substitutes for each other. Low-skilled immigrants may enhance the productivity of high-skilled natives. Even within skill groups, the various talents that immigrants and native workers bring to the labor market may complement each other rather than compete. The intuition behind the gains to both natives and immigrants in this case would follow from the principle of comparative advantage. For example, an immigrant worker may be an extraordinary computer programmer but have limited English skills. Rather than filling the programming job with a native worker who is not as skilled in this particular task, the employer might assign the native worker to tasks that use communication and English language skills. Some of these ideas are pursued in recent work by Giovanni Peri and co-authors (Peri and Sparber 2009; Ottaviano and Peri 2012). Other research also by Giovanni Peri compares states with differing levels of immigration and finds that immigration raises productivity by promoting efficient task specialization (Peri 2012).

Another question regards the impact of immigration on the public finances of the host country. Immigrants contribute positively to government finances by paying taxes but add to costs by using publicly provided goods and services such as roads, police, and schools. The 1997 National Research Council study estimated that, over the long run, a typical immigrant and his or her descendants would contribute about $80,000 more in taxes (in 1996 dollars) than they would receive in terms of public goods and services. This would translate into nearly $120,000 in 2012 dollars. This positive fiscal impact is attributable to several factors: most immigrants arrive at young ages; their descendants are expected to have higher incomes; immigrants help to pay for public goods such as national defense that do not entail congestion costs; and the 1996 Personal Responsibility and Work Opportunity Reconciliation Act prohibited new immigrants from receiving public benefits for five years after arrival.

A recent Congressional Budget Office study also found that allowing undocumented immigrants a pathway to citizenship is likely to help the Federal budget. The study estimates that, had a pathway been established, Federal revenues would have increased by $48.3 billion while Federal outlays would have increased by $22.7 billion over the 2008-12 period, leading to a surplus of $25.6 billion. The revenue increase stems largely from greater receipts of Social Security payroll taxes, while the increase in outlays would be in the form of refundable income tax credits and Medicaid. This calculation does not take into account possible increases in Federal discretionary spending. There may be also additional expenditures at the State and local level on education and healthcare, which are harder to forecast (CBO 2007).

Another important economic benefit of providing a pathway to earned citizenship is that, by bringing immigrant workers out of the shadows, they will be able to obtain above-ground jobs, advance in their careers, and contribute more fully to the economy. Moreover, with a pathway to earned citizenship, immigrant workers and their employers will invest more in their skills, raising the benefit to the economy even further. Legalizing this population will also benefit U.S.-born citizens as they need no longer compete with workers who may work at below market wages due to their unauthorized status.

A Magnet for High-Skilled Immigration

A growing area of study is how high-skilled immigrants -- particularly those in the STEM fields -- contribute to innovation and growth. Based on the 2010 National Survey of College Graduates conducted by the National Science Foundation, immigrants represent 13.6 percent of all employed college graduates, but they account for 50 percent of PhDs working in math and computer science occupations, and 57.3 percent of PhDs in engineering occupations (Table 4-5). About two-thirds of these foreign-born PhDs hold U.S. degrees, suggesting that many of them either immigrated as children or came to attend U.S. universities and stayed.

Interestingly, one study found that 26 percent of all U.S.-based Nobel laureates over the past 50 years were foreign born. The same study also found that in the EU-12 countries, immigrants made up slightly less that 5 percent of total population and accounted for about 4 percent of those holding masters' and PhDs, in contrast to the United States (Wasmer et al. 2007).6

                                     Table 4-5

 

                  Percentage of Foreign-Born College Graduates

 

                          by Degree and Occupation, 2010

 

 _____________________________________________________________________________

 

 

                                            Bach-              Profes-  Doc-

 

                                     All    elor's  Master's   sional   torate

 

 _____________________________________________________________________________

 

 

 Total                               13.6    11.8     15.3      12.9      32.2

 

  All sciences                       28.6    20.3     38.1      50.7      44.2

 

   Math/computer sciences            29.2    21.8     42.4      30.5      50.0

 

   Life and related sciences         28.8    14.5     27.3      59.4      44.2

 

   Physical and related sciences     23.9    12.2     21.3      49.6      38.8

 

  Engineering                        24.1    16.2     33.3      44.4      57.3

 

 _____________________________________________________________________________

 

 

 Source: National Science Foundation/National Center for Science and

 

 Engineering Statistics, National Survey of College Graduates (2010).

 

 

These statistics support the view that the United States continues to be a magnet for highly skilled immigrants. Two factors likely play a role. First, the United States has flexible labor markets that are able to integrate immigrants relatively quickly. Second, the skill premium is high in the United States, and individuals with exceptional ability and willingness to work hard can thrive. These factors have enabled the Nation to benefit from large inflows of highly skilled workers.

Boosting Innovation and Entrepreneurship

In addition to the benefits already covered, recent studies have shown that immigrants promote productivity and innovation, directly and also indirectly through positive spillover effects on native researchers and scientists. Gauthier-Loiselle and Hunt (2010) found that immigrants patent at two to three times the rate of U.S.-born citizens. The study also found that immigrants further boost innovation in the economy by having positive spillovers on the native rate of innovation. Another study found that raising the number of skilled information-technology workers -- as has been done by raising the cap on H-1B visas -- spurs innovative activity in states that more heavily employ these workers (Kerr and Lincoln 2009).

Studies also have found that immigrants are not only exceptional workers and innovators but also highly entrepreneurial. One study found that 25 percent of venture capital companies between 1991 and 2006 were started by immigrants (Anderson and Platzer 2006). Another found that immigrants started 25 percent of engineering and technology companies founded between 1995 and 2005 (Wadhwa et al. 2007). Even outside the high-tech sector, one study found that immigrants are more likely than natives to start a company with more than 10 workers (Fairlie 2012). Immigrants are 30 percent more likely to form new businesses than U.S.-born citizens. A study by Partnership for a New American Economy found that more than 40 percent of Fortune 500 companies were founded by immigrants or their children. The study also found that these companies are responsible for many jobs here and abroad -- employing more than 10 million people worldwide -- and that they generate annual revenues of $4.2 trillion.

While there is clearly room for further study, these studies generally provide little systematic evidence that increases in the supply of foreign scientists and engineers discourage natives from entering these fields or from engaging in innovative activity. For example, Gauthier-Loiselle and Hunt found that the inflow of high-skilled immigrant science and engineering workers into a state did not decrease the number of patents originated by native science and engineering workers in the state. Borjas (2007) also found that, on the whole, rising enrollment of foreign graduate students did not discourage native enrollment in science and engineering programs, although there were some disparate impacts across groups.

President Obama has supported a recent initiative to graduate 1 million more college graduates with STEM degrees. At the same time, all evidence points to the fact the United States is extraordinarily successful at attracting highly skilled workers from other countries. Sensible immigration policy would entail taking advantage of this unique situation and allowing more high-skilled immigration. The lack of clear evidence of crowding out bolsters confidence that these are not two conflicting policy goals.

Conclusion

With slowing population growth and aging of the workforce, America needs more workers. The Nation also needs to invest in the education, skills, and training of its citizens so they can fill the jobs of the future. Over the past four years, President Obama has taken an aggressive stance toward combating the rising cost of college. The expansion of the Federal Pell Grant program and the American Opportunity Tax Credit has made college more affordable for millions of students and families. Challenges still remain, including the continuing rise of tuition and levels of student debt. In his recent State of the Union address, President Obama called upon colleges to join in the effort to keep costs down. He proposed using metrics such as value, affordability, and student outcomes in distributing Federal campusbased aid. He also announced a new Race to the Top program for College Affordability and Completion, which will reward states who are willing to change their higher education policies and practices to contain tuition costs and ease students' progress toward a college degree.

With the potential to address both the need for workers and the need for skills, the gains from commonsense immigration reform loom large. Immigration can boost the economy by adding workers and making our labor force younger and more dynamic. Offering a path to citizenship to more than 11 million currently undocumented residents will further expand the economy as this group invests in education, finds gainful employment, and pays taxes. Border enforcement has proven to be effective, but it is a drain on our public finances. Smart enforcement that balances border security with crackdowns on worksite fraud will not only have higher returns going forward, but it will also save taxpayers money. America has historically been a magnet for capable and hard-working immigrants who seek opportunities and a better life. Many of these immigrants are innovators and entrepreneurs. The smart policy ahead is to leverage America's unique advantage for future prosperity and growth.

Smart policy also involves making sure that all Americans benefit from economic growth. In his 2013 State of the Union address, President Obama reiterated his commitment that an honest day's work is rewarded with decent pay, enough to feel secure and support a family. A Federal minimum wage that keeps up with the cost of living, policies that strengthen workers' ability to bargain for decent wages and safe working conditions, and tax policies such as refundable credits that allow lower-income families to invest in their children's education, are important pieces of the foundation upon which an economy that works for the middle class is built.

 

FOOTNOTES TO CHAPTER 4

 

 

1 States provide substantially less appropriations to private institutions on a per-student basis. State funding for private institutions was more stable over this period. For example, state appropriations per full-time student rose from $513 to $523 at private research institutions and fell from $537 to $288 at private master's institutions. (College Board 2010). See: http://chronicle.com/article/State-Spending-on-Higher/136745/

2 The AOTC is available to taxpayers with income below $90,000 ($180,000 if married), offering a maximum credit amount of $2,500 per student for the first four years of postsecondary education; students must be enrolled at least part-time and be pursuing a degree to be eligible. The AOTC is 40 percent refundable, meaning that taxpayers with no tax liability can claim up to $1,000 toward higher education expenses.

3 Aggregate mortgage debt peaked in 2008:Q3, home equity debt peaked in 2009:Q1, and auto debt, credit card debt, and other debt peaked in 2008:Q4.

4 The list does not include countries in the Middle East, such as Israel, Jordan, Kuwait, Qatar, and United Arab Emirates that have substantial guest-worker programs and foreign-born populations who generally make up 40 percent or more of the total population.

5 NRC (1997), chapter 5. Also see Card (1990), Friedberg and Hunt (1995), Card (2009), Cortes (2008). See Borjas (2003) and Borjas, Grogger, and Hanson (2011) for the opposing view.

6 According to the study, the data for Nobel Laureates were found at the official website of the Nobel Foundation: http://nobelprize.org/nobel/.

 

END OF FOOTNOTES TO CHAPTER 4

 

 

CHAPTER 5

 

 

REDUCING COSTS AND IMPROVING THE QUALITY OF HEALTH CARE

 

 

In March 2010, the President signed into law the Affordable Care Act. Provisions of the Act have already helped millions of young adults obtain health insurance coverage and have made preventive services more affordable for most Americans. When fully implemented, the law will expand coverage to an estimated 27 million previously uninsured Americans and ensure the availability of affordable comprehensive coverage through traditional employer-sponsored insurance and new health insurance marketplaces or exchanges. There are signs that the Affordable Care Act has started to slow the growth of costs and improve the quality of care through pay-for-performance programs, strengthened primary care and care coordination, and pioneering Medicare payment reforms. These provisions, as well as others in the Affordable Care Act, will help to bend the cost curve downward while laying the foundation for moving the health care system toward higher quality and more efficient care.

 

HEALTH CARE SPENDING

 

 

Health care spending has increased dramatically over the past half century, both in absolute terms and as a share of gross domestic product (GDP) (Figure 5-1). Spending in the U.S. health care sector totaled $2.7 trillion in 2011, up by a factor of 3.9 from the $698.3 billion (in 2011 dollars) spent in 1980. Health care spending in 2011 accounted for 17.9 percent of GDP -- almost twice its share in 1980.

Some of the increase in health care spending is attributable to demographic changes. Of the real increase in spending on prescription drugs, office-based visits, hospitalizations, and all other personal care from 1996 to 2010, for example, 11.5 percent can be accounted for by the changing age structure of the population and 22.8 percent can be accounted for by increases in the size of the population (Figure 5-2).1 The effects of population aging will become a more important driver of higher spending in coming years; by 2030, one in five Americans will be over age 65, compared with only one in eight today, and per capita medical costs in a given year are approximately three times greater for those 65 and over than for younger individuals. The majority of the increase in health care spending, historically, has come from increases in the amount spent per person over and above any effects attributable purely to population aging and population growth, reflecting increases in the use of medical services driven at least in part by the development of new technologies and increases in unit costs that exceed the overall rate of inflation.

 

Figure 5-1

 

GDP and Health Spending, 1980-2011

 

 

 

 

Source: Centers for Medicare and Medicaid Services, National Health Expenditure Accounts; Bureau of Economic Analysis, National Income and Product Accounts; CEA calculations.

 

Figure 5-2

 

Contribution of Population Growth and Aging

 

to Health Care Spending, 1996-2010

 

 

 

 

Source: Department of Health and Human Services, Agency for Healthcare Research and Quality, Medical Expenditure Panel Survey; CEA calculations.

Long-Term Spending Growth

Why has health care spending risen so much, even after taking into account changes in the size and age mix of the population? A likely piece of the story is that long-term growth in health care wages has not been accompanied by corresponding labor-saving technological progress. The theory of "cost disease" as developed by Baumol and Bowen (1966) notes that labor-saving technological progress has led to significant increases in labor productivity and hence wage growth in some important parts of the economy (such as the manufacturing sector). To compete for workers, labor-intensive sectors such as health care, education, and the performing arts also must raise their wages. According to the theory, productivity growth has been slower in these sectors. The result, the argument concludes, is an increase in the relative cost of output in these labor-intensive sectors, as higher costs are passed on to consumers in the form of higher prices.

Consistent with this theory, Nordhaus (2006) found that labor-intensive sectors generally experienced rising relative prices between 1948 and 2001. Nordhaus also found that shifts in labor from sectors that experienced labor-saving technological progress to sectors that remained relatively labor-intensive lowered overall productivity growth, as the share of labor-intensive sectors in overall output rose over the second half of the 20th century.

The cost-disease diagnosis assumes that, in labor-intensive sectors, it is difficult to reduce the amount of labor required to produce a given set of outputs. The health care sector, however, has experienced substantial technological progress, as new pharmaceutical therapies, diagnostic and medical devices, and surgical procedures have been introduced, allowing many conditions to be treated more effectively than in the past.

While some of these innovations have been labor-saving (some pharmaceuticals, for example), most others are complementary to expensive specialist labor (such as imaging and advances in surgical procedures). Consequently, technological change in medicine has caused the cost per treatment to rise, even as improvements in clinical effectiveness have led to increases in medical productivity. Technological change in medicine has contributed to long-term increases in spending. A recent study found that a quarter to a half of the rise in health care spending since 1960 can be explained by technological change in the health care system (Smith, Newhouse, and Freeland 2009). And rather than satisfying a relatively fixed demand for health care at lower cost, the development of many of these new technologies has contributed to an increase in the demand for health care services.

For some researchers, the importance of technological change for health care spending points to increases in demand as an additional explanation to the cost disease theory for why health care spending has increased disproportionately with income. If health care is a "super-normal good" -- a good associated with an elasticity of consumption with respect to income that is greater than one -- then as incomes rise by a certain percentage, consumption of health care rises by a greater percentage. Hall and Jones (2007) argue that this can happen if, after achieving a certain level of consumption, individuals prefer to spend additional income on life-extending health care (which allows for consumption in the extended years of life) rather than on extra consumption now. Consequently, as incomes rise, people choose to spend ever more on health care over other goods.

The disproportionate effect of income on the demand for health care may also operate through larger institutional mechanisms. Consistent with this idea, Smith, Newhouse, and Freeland (2009) find that income growth affects health care spending growth primarily through the actions of governments and employers on behalf of large insurance pools, suggesting a key role for payment reform in affecting medical spending growth.

These factors are not only a U.S. phenomenon. Indeed, while the United States has higher levels of health care spending than other members of the Organisation for Economic Co-operation and Development (OECD), the annual real rate of growth in health care spending per capita in the United States between 1960 and 2010 was not too different from elsewhere, averaging 4.13 percent compared with 3.62 percent in the other OECD countries, adjusted for purchasing power parity. In more recent years, health care spending has continued to grow at similar annual real rates -- 3.10 percent in the United States and 3.30 percent in the other OECD countries between 2000 and 2010, somewhat below the long-term rates of spending growth observed since 1960.

Medical Productivity

Productivity growth in health care largely has taken the form of improvements in the quality of care, with developments in new procedures and care practices contributing to increased survival, decreased morbidity, reduction in pain, and less onerous treatment administration in many cases.

A full accounting of medical productivity growth should reflect changes not only in cost per service but also in health outcomes. However, medical productivity is often hard to measure because health outcomes are hard to measure. Recent studies comparing increases in life expectancy to increases in treatment costs over time suggest that productivity growth in the health care sector has been enormous. For example, Cutler and McClellan (2001) found that the value of increased survival rates and decreased morbidity rates as a result of improved treatment of heart attacks, low-birth-weight infants, and depression over the past few decades has far exceeded the increased spending on these conditions over the period. Using a similar methodology, Philipson et al. (2012) found that survival gains across all cancer patients in the United States between 1983 and 1999 cost on average only $8,670 per life-year gained. Estimates of the value of a statistical life-year, based on compensating wage differentials that measure the implied trade-off between wages and increased risk of fatality, are typically multiples higher (Viscusi and Aldy 2003). Therefore, even if some piece of the apparent gain in longevity results from earlier diagnosis, the introduction of these cancer therapies represents an enormous improvement in productivity. Faster growth in spending on cancer treatment in the United States than in Europe over this period is sometimes mistakenly taken to indicate the inefficiency of U.S. medical care, but it is also the case that the improvement in life expectancy for cancer patients was greater in the United States than in Europe. From 1983 to 1999, U.S. spending per cancer patient rose by $16,700 (in 2010 dollars) more than European spending per cancer patient (Figure 5-3), and U.S. cancer patient life expectancy rose by 0.4 years more than European cancer patient life expectancy (Figure 5-4), implying a cost per extra life year saved of approximately $42,000. Given the consensus in the literature that the value of additional life-years is much higher, the additional U.S. spending has been a good value.

 

Figure 5-3

 

Cancer Spending per New Cancer Case, 1983-1999

 

 

 

 

Source: Philipson et al. (2012), updated data provided by the authors.

 

Figure 5-4

 

Life Expectancy after Cancer Diagnosis, 1983-1999

 

 

 

 

Note: European countries included are Finland, France, Germany, Iceland, Norway, Slovakia, Slovenia, Sweden, Scotland, and Wales.

Source: Philipson et al. (2012), updated data provided by the authors; Surveillance, Epidemiology and End Results (SEER); European Cancer Registry (EUROCARE).

Murphy and Topel (2006) directly estimate the aggregate monetary value of increases in longevity, finding that, if valued in the national accounts, increases in life expectancy since 1970 would have added $3.2 trillion a year to national wealth. While a different set of assumptions about the statistical value of a life year, the elasticity of intertemporal substitution, and the value individuals place on non-working hours lowers the aggregate valuation of the observed longevity increase, the order of magnitude of the estimated valuation nonetheless suggests an enormous return to the increase in health care spending over this period.

In general, estimating how much the productivity of health care has grown is a difficult task. Changes in health outcomes, morbidity rates, and patient convenience are hard to measure, hard to attribute to the use of specific technologies, and hard to value. Furthermore, limitations in available data mean that spending often cannot be disaggregated to the treatment of specific diseases or patients. Given these difficulties, it is widely agreed that aggregate measures of the output of the health care sector do a poor job of capturing the effects of productivity growth. Developing better methods to measure real output and productivity growth in health care is an important area of ongoing research (Data Watch 5-1).

Sources of Inefficiency in Health Care Spending

Although growth in overall medical productivity has been large, not all increases in medical spending are productive. Cutler and McClellan (2001) showed that improved treatment of heart attacks produced significant increases in patient longevity between 1984 and 1998. By contrast, Skinner, Staiger, and Fisher (2006) found little improvement in survival rates among heart attack patients between 1996 and 2002 despite significant growth in treatment costs. The latter study also found that the regions with the largest increases in spending also experienced the smallest gains in survival. Geographic variation in practice patterns and health outcomes implies that more than 20 percent of Medicare spending on heart attack treatment produces little health value (Skinner, Fisher, and Wennberg 2005). The case of heart attack treatment points to more general inefficiencies in the allocation of spending within the health care system.

Among the many possible sources of spending inefficiencies, several stand out as key sources of waste. First, the fragmentation of the delivery system contributes to a failure to provide patients with necessary care. That in turn can lead to complications and readmissions, particularly for the chronically ill for whom care coordination is most essential for health.

 

______________________________________________________________________

 

 

Data Watch 5-1: Toward Disease-Based Health Care Accounting

 

 

Existing national data on health expenditures generally are organized by the type of medical care that individuals purchase (such as doctor visits or drugs). For addressing questions related to the productivity of health care, however, data on health care spending by disease would be far more useful.

Switching to disease-based accounting poses a challenge because patients often suffer from more than one disease at once, making it difficult to allocate spending to specific diseases. Three conceptual approaches to allocating spending across disease have been suggested: tracking each encounter with the health care system; tracking disease "episodes"; or identifying all conditions a person has and using regression analysis to allocate spending to diseases. All three approaches have advantages and limitations, and a consensus has not yet developed on which one is preferable. Whichever approach is adopted, the universe of conditions will need to be categorized into a set of disease groups, at an appropriate level of detail, to which medical costs then can be assigned for analysis.

The Medical Expenditure Panel Survey (MEPS) is a nationally representative survey that provides information on most health spending, although it fails to capture spending on behalf of institutionalized patients and active duty military. The MEPS sample is too small, however, to represent rare conditions. Although not comprehensive in their coverage, data on health care claims provide another valuable -- and potentially much more detailed -- source of information on health care spending. In addition to data on spending, data on health outcomes that can be linked to the disease-based spending data also are needed.

Important progress has been made toward developing diseasebased health care data. The Bureau of Economic Analysis is working on a health care satellite account that will provide disease-based measures of household medical expenditures. These estimates will be based on private insurance claims data, Federal data on Medicare and Medicaid spending, and data from MEPS on the uninsured. Simultaneously, the Bureau of Labor Statistics is developing disease-based price indexes that account for shifts in treatment patterns. These indexes will be useful to the Bureau of Economic Analysis for decomposing spending into changes in prices versus changes in quantities.

The Affordable Care Act has significantly increased funding for research on patient-centered outcomes, and data will be available to qualified entities to evaluate the performance of providers and suppliers with respect to quality, efficiency, effectiveness, and resource use. Under the President's Open Data initiative, the Department of Health and Human Services has launched a Health Data Initiative to promote the availability of Medicare and Medicaid data, where appropriate, to researchers and entrepreneurs. Paralleling these initiatives, the Health Care Cost Institute, a nonprofit organization, has developed a claims database to be made available to researchers to foster a better understanding of what drives health care costs. These administrative data on claims hold the potential for further progress on understanding the drivers of health care spending increases and identifying high value medical care.

______________________________________________________________________

 

 

Second, lack of care coordination also contributes to duplicate care and overtreatment, a source of waste exacerbated by payment systems that compensate physicians based on the number of services provided (see Economic Applications Box 5-1). Overuse of expensive medical technologies is particularly costly, and some research suggests that a significant portion of coronary artery bypass graft surgery, angioplasty, hysterectomy, cataract surgery, and angiography is of questionable or low medical value (Goldman and McGlynn 2005).

Third, the failure of providers to adopt widely recognized best medical practices also contributes to waste. These failures include lack of adherence to established preventive care practices and patient safety systems, as well as widespread failure to adopt best treatment practices. In cases where the best medical practice is both clinically more effective and lower in cost -- for example, the use of beta blockers in the treatment of acute myocardial infarction (Skinner and Staiger 2005, 2009) -- failure to follow these practices results in worse clinical outcomes and higher readmissions and contributes to wasteful spending.

Finally, payment fraud also adds to system waste, not only through inappropriate payments but also through the administrative burden on honest providers who must adhere to the regulatory requirements of unavoidable but burdensome fraud detection systems.

Taken together, fragmentation of care, overtreatment, failures of care delivery, and payment fraud have been estimated to account for between 13 and 26 percent of national health expenditures in 2011 (Berwick and Hackbarth 2012). The magnitude of this waste offers an equally large opportunity for spending reductions and improvement in quality of care -- an opportunity that underpins many of the provisions of the Affordable Care Act.

 

______________________________________________________________________

 

 

Economics Application Box 5-1: Matching in Health Care

 

 

Traditional economic analysis focuses on markets in which prices and quantities adjust so that in principle, supply equals demand. In some markets, however, prices do not exist and cannot be used to allocate resources. Gale and Shapley (1962) made early theoretical contributions to our understanding of how markets can be designed to allocate resources efficiently in the absence of prices. Taking the "marriage market" as an example, Gale and Shapley studied how, in the absence of prices, these markets can produce stable matches -- matches where no alternative pairing would make both individuals in any match better off. These principles were extended by Roth, who applied them to the practical design of market institutions -- for example, the market for medical students in residency programs (Roth 1984), and the assignment of students to public high schools in New York City and Boston (Abdulkadiroglu, Pathak, and Roth 2005). For these pioneering contributions, Shapley and Roth were awarded the 2012 Nobel Prize in Economic Sciences.

The market for live kidney transplants is yet another market where prices do not determine allocation. Paying for organs is a felony under the 1984 National Organ Transplant Act. Patients can receive a kidney from a compatible donor or are placed on a waiting list for a cadaveric kidney. Currently, nearly 95,000 patients in the United States are waiting for a kidney transplant. Dialysis for these patients costs approximately $60,000 a year, for a total of $30 billion a year, or 6.7 percent of total Medicare spending, the single most expensive component of Medicare. In 2011, there were about 11,000 transplants of deceased donor kidneys and only 5,770 transplants from living donors; in the same year, more than 4,700 patients died while waiting for a kidney transplant.

Many patients have willing potential donors. However, immunological incompatibility greatly limits the number of transplants using live kidneys, which are preferred to cadaverous kidneys for their tissue quality and greater longevity. Patients receiving a live kidney transplant are estimated to live 10-15 years longer than they would on dialysis.

Increasing exchanges between incompatible patient-donor pairs would greatly expand the opportunity for dialysis patients to receive a living donor kidney, and increase the quality of matches. In paired kidney exchanges, a donated kidney from one (immunologically incompatible) patient-donor pair is transplanted in the patient of a second patient-donor pair, and vice versa. The potential for improving the number of live kidney transplants is greater with "chains" -- exchanges involving many donor-recipient pairs. The 2007 amendment to the National Organ Transplant Act clarified that kidney paired donations (KPD) do not constitute "valuable consideration" (that is, financial compensation), thereby paving the way for the creation of KPD exchanges.

The economic principles of stable matches developed by Shapley and Roth can be applied to KPD exchanges. Whereas the concept of stability in the medical residency setting, for example, is based on the mutual preferences of medical students and residency programs, stability in a kidney exchange is primarily based on obtaining the best matches along immunological criteria. Using these principles, transplant centers have established KPD programs, as have nonprofit organizations such as the New England Program for Kidney Exchange, founded by Roth and colleagues. Congress also established a national KPD pilot program, operated under the Organ Procurement and Transplantation Network (OPTN) as a nonprofit under Federal contract.

In 2011, the separate pilot KPD programs, including OPTN, resulted in 430 transplants -- a promising start to paired kidney exchanges, but nevertheless representing only a fraction of the potential number of possible transplants.

Computer models suggest that many more transplants could be achieved each year if there were a nationwide pool of all eligible donors and recipients. A larger pool of eligible donor-recipient pairs also could potentially increase the quality of matches. A living kidney transplant (and all subsequent care) saves money over dialysis after roughly two years. On average, Medicare would save $60,000 a year for every patient who receives a living kidney transplant rather than continuing to receive dialysis, all while increasing the life expectancy of a kidney recipient by 10-15 years, again relative to dialysis treatment.

______________________________________________________________________

 

 

EARLY IMPLEMENTATION OF THE AFFORDABLE CARE ACT

 

 

The Affordable Care Act includes a series of provisions that will transform the Nation's health care system. By expanding coverage, the health reform law stabilizes insurance markets and makes health insurance affordable. The Affordable Care Act also includes important provisions that are aimed at reducing inefficient spending, promoting competition, and improving the quality of medical care.

Economic Benefits of Insurance

Insurance provides important economic benefits to covered households. It covers unforeseen medical expenditures, allowing individuals to receive necessary medical treatment without suffering potentially crippling financial consequences.

The 2008 Medicaid expansion in Oregon provided a unique setting in which to study the effects of health insurance on health and financial security. Because access to the Oregon Medicaid coverage expansion was offered through a lottery, the benefits of insurance could be estimated without the usual statistical concerns that purchasers of insurance differ from non-purchasers in ways related to health and financial outcomes. Finkelstein et al. (2011) found that, after one year of Medicaid coverage, previously uninsured adults in Oregon were 10 percent less likely to report having depression and 25 percent more likely to report their health as good, very good, or excellent. They also experienced lower financial strain because of medical expenses, including lower out-of-pocket expenditures, lower debt on medical bills, and lower rates of refused medical treatment because of medical debt, than individuals who were not randomly assigned to Medicaid coverage.

The benefits of having insurance coverage are large. A recent study (CBO 2012a) estimated that the insurance value of Medicaid to enrollees in the lowest quintile of income earners is equivalent to 11 percent of their before-tax income, defined by the CBO as market income plus cash transfers. As a comparison, real average before-tax incomes in the lowest quintile rose 15 percent between 1995 and 2009, while real incomes in the highest quintile rose 24 percent. Hence, the value of Medicaid is roughly comparable to the additional income that would have kept average income in the lowest quintile growing at the same rate as average income in the highest quintile.

Expanding Affordable Health Insurance Coverage

The Affordable Care Act is projected to increase the number of insured individuals in the United States by 14 million in 2014 and by 27 million in 2022 (CBO 2012b). The requirement that health insurance plans offer dependent coverage to children up to age 26 went into effect in 2010. Sommers (2012) found that this provision resulted in more than 3 million uninsured young adults gaining health insurance between September of 2010 and December of 2011.

Looking ahead to 2022, the Congressional Budget Office (CBO 2012b) projects that the Affordable Care Act will lead to an additional 12 million people being insured through Medicaid and the Children's Health Insurance Program (CHIP), with the remainder of the estimated 27 million newly insured individuals covered through employer-based insurance, the Affordable Insurance exchanges, or the Small Business Health Options Program (SHOP) exchanges (Economics Application Box 5-2). The law likely will cause some firms that currently do not offer health benefits to begin doing so, and some workers who are currently uninsured will take up employer coverage that is already offered. At the same time, the new options created by the Affordable Care Act may make employer-sponsored insurance (ESI) coverage less attractive for some employers. The net effects on the prevalence of employer-sponsored coverage, however, are likely to be small.

 

______________________________________________________________________

 

 

Economics Applications Box 5-2: Economics of Adverse

 

Selection and the Benefits of Broad Enrollment

 

 

In health insurance markets, adverse selection occurs when relatively unhealthy individuals are more likely than healthy individuals to purchase health insurance coverage at a given price. Insurers understand this tendency and attempt to set premiums to reflect average expected expenditures in a plan. The selection of relatively unhealthy enrollees into coverage raises average expected expenditures, resulting in higher premiums and more adverse selection into coverage.

Adverse selection explains why offered premiums in the individual and small group health insurance markets often are too high for most healthy people compared with the health costs they actuarially can be expected to incur, meaning that they either pay too much for coverage or choose to go uninsured rather than pay the high premiums. In some cases, insurance markets subject to extreme adverse selection may disappear completely (Cutler and Reber 1998).

Encouraging broad participation in health insurance coverage helps tremendously to solve the market failure associated with adverse selection. For example, adverse selection is virtually nonexistent in the large group employer sponsored insurance (ESI) market. Take-up rates in this market are very high, thanks both to the tax advantages associated with ESI and to the fact that employers typically pay a portion of premiums, which makes ESI a good deal for the vast majority of employees. While employer contributions are offset by lower wages in equilibrium (Gruber 1994; Baicker and Chandra 2005), employees who decline coverage rarely recoup the employer contribution on the margin. The large enrollment in many ESI plans means that a small number of high expenditure enrollees does not dramatically affect premiums for a large risk pool. This prevents adverse selection from taking root and reinforces broad enrollment through premium stabilization and affordability.

Similarly, the Affordable Care Act encourages broad enrollment through the widespread accessibility of health insurance exchanges, the individual responsibility requirement related to the purchase of health insurance, and the financial assistance offered to lower-income earners to purchase private plans on an insurance exchange. Other provisions of the Affordable Care Act raise consumer awareness and foster consumer choice through information campaigns, standardization, and consumer search tools, similar to those implemented in the successful rollouts of the Medicare Advantage and Medicare Part D prescription drug programs. As in ESI, broad enrollment in the exchanges is expected to foster premium stability and affordability and to reduce the incidence of cost-shifting from uncompensated care to the insured.

______________________________________________________________________

 

 

Based on microsimulations of firms' optimizing behavior, analysts have estimated effects of the Affordable Care Act on the number of individuals with ESI coverage ranging from a 1.8 percent decline (CBO 2012b) to a 2.9 percent increase (Eibner et al. 2011). Other estimates fall with this narrow range (Buettgens, Garrett, and Holahan 2010; Lewin Group 2010; Foster 2010) and are consistent with the small positive effects of health reform on ESI coverage observed in Massachusetts, where similar statewide health insurance reforms were legislated in 2006 (Long, Stockley, and Yemane 2009).

Consumer Protection

The Affordable Care Act also establishes numerous consumer protections related to the purchase of private health insurance, some of which are already in effect. Starting in 2014, individual and group health plans will not be allowed to deny or limit coverage on the basis of an individual's health status. And within certain limits, premiums will be allowed to vary by age, geography, family size, and smoking status, but not by individual health status, gender, or other factors.

The Affordable Care Act also requires that double-digit increases in insurance premiums be reviewed by States or the Department of Health and Human Services, with insurance companies needing to provide justification for any such premium increases. Plans may be excluded from an insurance exchange based on premium increases that are not justified. Further, since the beginning of 2011, most insurers have been allowed to retain no more than 20 percent of consumers' premiums for profits, marketing, and other administrative costs. Overhead and administrative costs in excess of this limit are to be rebated to consumers (or in the case of employer-sponsored insurance, to employers, who must pass a share of these rebates to their employees as cash, improved benefits, or lower premiums, with the share depending on the proportion of the total health plan premium paid by the employees). As of August 2012, an estimated 12.8 million Americans had received rebates totaling $1.1 billion from insurers as a result of this 80/20 medical loss ratio rule.

Health Care Spending and Quality of Care

The Affordable Care Act includes a series of provisions designed to reduce spending while improving the quality of care in the health care system. Reducing excessive payments to Medicare Advantage plans, strengthening antifraud efforts, and initiating reforms to Medicare provider payment systems, among other policies, are expected to extend the life of the Medicare Trust Fund by an additional eight years. These reforms complement numerous other provisions that improve health care quality while lowering costs.

The Hospital Value-Based Purchasing Program went into effect in October 2012. The program rewards more than 3,500 hospitals for providing high-quality care and reduces payments for hospitals demonstrating poor performance. Similar pay-for-performance programs in Medicare Advantage and the end-stage renal disease prospective payment system encourage higher-quality care and more efficient care delivery. Additionally, pay-for-reporting initiatives in which providers are rewarded for reporting procedures and outcomes have been launched in virtually every Medicare payment category, and mark the first step toward value-based purchasing.

The Partnership for Patients program is a public-private partnership that aims to reduce hospital complications and improve care transitions in more than 3,700 hospitals and partnering community-based clinical organizations. By stopping millions of preventable injuries and complications in patient care, this nationwide initiative has set as its goal saving 60,000 lives and up to $35 billion in spending, including up to $10 billion in Medicare spending, over the three years following its launch. Data provided by the Centers for Medicare and Medicaid Services (CMS) show that since the Partnership for Patients program was introduced in 2011, the hospital readmission rate within Medicare has fallen to 17.8 percent, down from an average of about 19 percent that had prevailed from 2007 through 2010 (CMS 2013) (Figure 5-5). The data also show that the declines were larger in hospitals participating in Partnership for Patients.

The Affordable Care Act builds on the investments made in the Recovery Act to encourage the use of health information technology. By making it easier for physicians, hospitals, and other providers to assess patients' medical status and provide care, electronic medical records may help eliminate redundant and costly procedures. More than 186,000 health care professionals (about one-third of eligible providers) and 3,500 hospitals (about two-thirds of eligible hospitals) have already qualified for incentive payments for the meaningful use of electronic health records authorized by the Recovery Act.

The Affordable Care Act also launched extensive efforts to prevent and detect fraudulent payments under Medicare, Medicaid, and the Children's Health Insurance Program. An important goal of the Administration's efforts has been to prevent fraudulent payments before they are made rather than chasing them afterward, but there also are ongoing efforts to recover fraudulent payments if they occur. Antifraud efforts have recovered a record-high $14.9 billion over the last four years.

 

Figure 5-5

 

Acute Care Hospital Readmission Rates, 2007-2012

 

 

 

 

Source: Center for Medicare and Medicaid Services, Office of Enterprise Management.

Medicare Payment Reform

Traditional fee-for-service Medicare reimburses physicians for each service provided, creating incentives for overutilization. Spending inefficiencies are exacerbated by fragmentation across providers, who historically have had few incentives to coordinate care. Likewise, the prospective payment system (PPS) for Part A hospital services, which is designed to control costs by paying hospitals a prospective amount per diagnostic-related group (DRG) episode, is not immune to waste. While the DRG-based PPS encourages more efficient care and reductions in length of stay compared with cost-based reimbursement (Sloan et al. 1988; Seshamani, et al. 2006), it also can encourage a reduction in necessary care, leading to negative short-term health effects and readmissions (Cutler 1995; Encinosa and Bernard 2005; Seshamani, et al. 2006). Further, the inpatient PPS also can be susceptible to "upcoding," whereby providers code patients as being sicker than they are to raise the risk-adjusted prospective payments (Cutler 1995; Carter et al. 2002; Dafny 2005).

To curb these inefficiencies, the Affordable Care Act has established initiatives that lay a foundation for reforming care delivery and physician payment. At their core, these initiatives are designed to foster greater coordination of care across providers, while simultaneously aligning financial incentives to encourage provider organizations to deliver higher-quality, more efficient medical care. Each initiative builds on a core of clinical and patient engagement quality measures to ensure that cost savings are derived from more efficient delivery of care and not reduced patient access or care quality.

One such initiative is the Medicare Shared Savings Program (MSSP). Under this program, providers deliver care through accountable care organizations (ACOs), contractual organizations of primary care physicians, nurses, and specialists responsible for providing care to at least 5,000 beneficiaries. The Federal Government shares any savings generated for those beneficiaries, relative to benchmarks, with ACOs that meet rigorous quality standards, giving the ACOs incentives to invest in delivery practices, infrastructure, and organizational changes that help deliver higher-quality care for lower costs. Currently, more than 4 million beneficiaries receive care from more than 250 ACOs participating in the MSSP and other CMS projects, with ACO participation and covered beneficiaries continuing to increase as the program expands.

The Affordable Care Act also created the Center for Medicare and Medicaid Innovation, which is charged with identifying, testing, and ultimately expanding new and effective systems of delivering and paying for care. The CMS Innovation Center is authorized to invest up to $10 billion in initiatives that have the potential to reduce program expenditures while preserving or enhancing quality of care furnished to individuals under Medicare, Medicaid, and the Children's Health Insurance Program. Initiatives within the CMS Innovation Center include shared savings models, as well as bundled payments to hospitals and post-acute-care providers.

The Innovation Center's Pioneer ACO program is a more aggressive version of the MSSP and is open to organizations that have had success with risk-based payment arrangements. Pioneer ACOs may keep a greater share of Medicare savings than ACOs in the MSSP but are also at greater risk for losses if spending benchmarks are not met. Successful Pioneer ACOs are also eligible to move to a population-based payment arrangement whereby they assume greater financial risks and rewards for a predetermined set of patients. This greater risk-reward profile further encourages investments in care coordination and best practice delivery reforms. Pioneer ACOs must also develop similar outcomes-based payment arrangements with other payers, extending payment innovations to the commercial market and maximizing the impact of the program's incentives.

Currently, roughly 860,000 beneficiaries are enrolled in 32 Pioneer ACOs. The Pioneer program is just entering its second year, so it is too early for any comprehensive assessment, but Pioneer ACOs do seem to be making substantial investments in infrastructure and care processes. Infrastructure investments include health information technology adoption and improved data analytic capabilities, which enable providers to identify opportunities for improvements in care processes and the quality of care. For example, the potential savings associated with early identification and treatment of patients with high propensity for developing a chronic disease have led some Pioneer ACOs to make organizational changes that place greater focus on primary care and disease management. CMS is supporting Pioneer ACOs by providing privacy-protected patient information to promote care coordination, hosting collaborative learning networks, and offering other technical assistance.

Care coordination is also central to the Comprehensive Primary Care (CPC) initiative. Primary care is critical to promoting overall health and reducing medical spending. Yet because any one insurer accounts for only a fraction of a provider's business, insurers underinvest in primary care systems that would improve care coordination. Through the CPC initiative, Medicare partners with State and commercial insurers to promote community-wide investments in the delivery of coordinated primary care. Simultaneously, through direct financial payments or shared Medicare savings, the CPC initiative rewards high-quality providers who reduce health care costs through investments in care coordination. At the end of 2012, about 500 primary care practices were participating in the CPC initiative, representing 2,343 providers serving approximately 314,000 Medicare beneficiaries.

The CMS Innovation Center has introduced bundled payments as a model for hospital payment and delivery reform. A bundled payment is a fixed payment for a comprehensive set of hospital and/or post-acute services, including services associated with readmissions. Moving from individual payments for different services to a bundled payment for a set of services across providers and care settings encourages integration and coordination of care that will raise care quality and reduce readmissions. Variants on bundled payments are being demonstrated, differing in the scope of services included in the bundle, and whether payment is retrospective (based on shared Medicare savings) or prospective, which intensifies the financial risk and return to investing in changes to the efficiency and quality of care. Currently, 467 health care organizations across 46 states are engaged in the bundled payment initiative.

Is the Cost Curve Bending?

The real rate of health expenditure growth has declined or remained constant in every year between 2002 and 2011. For each of the three years 2009, 2010 and 2011, National Health Expenditure data show the real rate of annual growth in overall health spending was between 3.0 and 3.1 percent, the lowest rates since reporting began in 1960.

Additionally, the National Health Expenditure data show that growth in Medicare spending fell from an average of 8.6 percent a year between 2000 and 2005 to an average of 6.7 percent a year between 2006 and 2010. Notably, over a third -- 2.5 percentage points -- of the 2006-2010 growth was attributable to increases in Medicare enrollment. With the exception of a spike in 2006, the year Medicare Part D was introduced, the growth rate of Medicare spending per enrollee -- a measure of health care spending intensity -- has been on a downward trend since 2001, with a particularly significant slowdown over the past three years (see Figure 5-6). Projections suggest the growth rate of Medicare spending per beneficiary will decline even further. While Medicare enrollment is expected to increase 3 percent a year over the next decade (CMS 2012), the rate of growth in spending per enrollee is projected to be approximately the same as the rate of growth in GDP per capita, according to the CBO and Office of the Actuary at CMS (Kronick and Po 2013). Similarly, the rate of growth in spending per Medicaid enrollee is projected to be near the rate of growth in GDP per capita. In the commercial health insurance market, per enrollee spending growth also has declined in recent years, the proximate cause being a slowdown in the growth rate of per-enrollee use of medical services (HCCI 2012).

 

Figure 5-6

 

Real Annual Growth Rates of National Health Expenditures

 

Per Capita and Medicare Spending Per Enrollee, 1990-2012

 

 

 

 

Note: Estimates for 2012 are projected.

Source: Center for Medicare and Medical Services, National Health Expenditure Accounts; CEA calculations.

There are several potential causes of the recent declines in the growth rate of spending per enrollee. One factor is the recent recession, in which job losses have caused the loss of insurance coverage. However, the recession explains only a small fraction of the declines in spending growth rates since the start of the recession. The slowdown in the growth rate of per-capita health expenditures began before the recession took hold, and has continued through the economic recovery and into 2012.

As expected, changes in real per-capita total health care spending at the state level are negatively correlated with changes in unemployment in the state between 2007 and 2009 (Figure 5-7). If the relationship in Figure 5-7 holds at the national level, then the increase in the national unemployment rate between 2007 and 2011 of 4.3 percentage points was associated with a $199 decline in spending per-capita (in 2007 dollars), or 2.6 percent of per-capita health care spending in 2007. This accounts for only 18 percent of the slowdown in spending growth since the start of the recession in 2007 and an even smaller proportion of the slowdown in spending growth since 2002, when the growth rate in real per-capita total health care spending began to decline.2

Structural changes in the health care market offer another explanation for the decline in per-enrollee spending growth. One possibility is that hospitals and provider groups have increasingly sought to improve efficiency -- through adopting more high value medical practices and performing fewer low value procedures -- in response to evidence showing their potential for cost savings and quality improvements (Fisher and Skinner, 2010). At the same time, formulary changes that encourage substitution away from branded to generic drugs, and changes in insurance design that increase patient cost sharing for both services and pharmaceuticals, also may explain a portion of the declines in spending growth per enrollee over the past decade. For example, the sharp slowdown in the growth rate of medical imaging since 2006 likely was due to a confluence of reforms including prior authorization, increased cost sharing and reduced reimbursements (Lee and Levy 2012). Notably, Lee and Levy found that a large fraction of the declines involved imaging identified as having unproven medical value. Similarly, payment reforms and regulations are thought to have contributed to long-run declines in Medicare spending growth rates (White 2008).

Early responses to the Affordable Care Act may have contributed to the decline in per enrollee spending since 2010 (Kronick and Po 2013). Relevant provisions of the law include provisions intended to foster coordinated care, improve primary care, reduce preventable health complications during hospitalizations, and promote the adoption of health information technology.

The decline in the hospital readmission rate, coinciding with the introduction of the Partnership for Patients program in 2011, also may point to early effects of the Affordable Care Act on spending. The Act's Medicare hospital readmissions reduction program, introduced in October 2012, should reinforce these effects. Likewise, infrastructure investments and care process changes, either funded directly by the Affordable Care Act or stimulated through the Affordable Care Act's payment reform, are other possible sources for the recent declines in spending growth.

 

Figure 5-7

 

Relationship Between Change in State Unemployment Rate and

 

Change in Real Per-Capita Personal Health Spending, 2007-2009

 

 

 

 

Source: Centers for Medicare and Medicaid Services, National Health Expenditure Accounts; Bureau of Labor Statistics, Current Population Survey; CEA calculations.

In addition, spending declines may reflect early changes in medical care delivery made in anticipation of impending Medicare payment reform. The Affordable Care Act moves providers towards savings-based payment models in Medicare that encourage improved coordination of care. Hospitals seeking new ways to reduce costs and increase bargaining power with suppliers and insurers may respond by consolidating their operations. Recent years have seen a continued consolidation and integration of physicians into provider networks.

The long-run growth rate of per-capita spending has significant implications for the budget. Medicare spending represented 3.7 percent of GDP in 2011 (Medicare Trustees 2012). Under current law, including cost control measures of the Affordable Care Act and the Sustainable Growth Rate-mandated physician payment cut, CMS projects that Medicare spending will rise to represent 6.7 percent of GDP in 75 years, with long-term nominal per-beneficiary spending growing at a rate on average equal to 4.3 percent per year (Medicare Trustees 2012). However, nominal growth rates of per-beneficiary Medicare spending have been declining since 2001, and over the past five years have averaged 3.6 percent. At least some of the recent decline in Medicare spending growth appears to be structural, implying that the low spending growth rates from the past few years may persist.3 If the per-beneficiary growth rate of Medicare spending were to remain 3.6 percent per year, then after 75 years Medicare spending would account for only 3.8 percent of GDP, little changed from its share today, and substantially less than what the Medicare Trustees estimate. (Figure 5-8). This should not be interpreted as a forecast but rather an indication of how sensitive long-term projections are to the assumed rate of growth of Medicare spending per beneficiary. In this hypothetical scenario where per-beneficiary Medicare spending grows at a rate equal to the one observed over the past five years, Medicare spending as a share of GDP would be much lower than what current long-term projections suggest.

 

Figure 5-8

 

Projected Medicare Spending as a Share of GDP, 2013-2085

 

 

 

 

Source: Medicare Trustees (2012); Social Security Trustees (2012); CEA calculations.

The causes for the recent and projected declines in the growth rate of medical spending and utilization, and their relationship to the major quality-improving and cost-saving provisions of the Affordable Care Act, remain an important area for future research. Enacted provisions of the health reform law appear to be having positive effects on care coordination, hospital outcomes and spending. And payment reforms that better align payment with cost and provide incentives for efficiency such as shared savings and bundled payment programs hold potential to improve to care quality and reduce medical spending.

 

FOOTNOTES TO CHAPTER 5

 

 

1 Total annual spending on prescription drugs, office-based visits, hospitalizations and other personal care between 1996 and 2010 was estimated using the Medical Expenditure Panel Survey (MEPS). To estimate the effect of changes in the age distribution between 1996 and 2010 on spending, age-specific spending levels and total U.S. population were held constant at 1996 levels, but the proportion of the population within each age group was allowed to reflect the 2010 age distribution. To estimate the effect of population growth between 1996 and 2010 on spending, total spending increases were calculated holding age-specific spending levels constant at 1996 levels, but allowing both the age distribution and total population to reflect their 2010 values. Then, the estimated spending increases due to changes in the age distribution were subtracted from this figure.

2 Between 2001 and 2006, real per-capital spending grew by 21.5 percent. Between 2006 and 2011, real per-capital spending grew by 7.1 percent, where the 14.4 percentage point difference in spending growth captures the slowdown in spending growth. The 2.6 percent decline in total health care spending between 2007 and 2011 attributable to the recession accounts for approximately (2.6/14.4)*100 = 18 percent of the slowdown in spending growth since the start of the recession.

3 Regression analysis shows a flat and insignificant relationship between state-level 2007-09 changes in per-beneficiary Medicare spending and changes in unemployment, suggesting that little if any of the recent declines in per-beneficiary Medicare spending growth is related to regional cyclical factors.

 

END OF FOOTNOTES TO CHAPTER 5

 

 

CHAPTER 6

 

 

CLIMATE CHANGE AND THE PATH TOWARD SUSTAINABLE ENERGY SOURCES

 

 

The Administration is committed to a comprehensive energy strategy that supports economic and job growth, bolsters energy security, positions the United States to lead the world in clean energy, and addresses the global challenge of climate change. Finding a responsible path that balances the economic benefits of low-cost energy, the social and environmental costs associated with energy production, and our duty to future generations is a central challenge of energy and environmental policy.

The most significant long-term pollution challenge facing America and the world is the anthropogenic emissions of greenhouse gases. The scientific consensus, as reflected in the 2009 assessment by the U.S. Global Change Research Program (USGCRP) on behalf of the National Science and Technology Council, is that anthropogenic emissions of greenhouse gases are causing changes in the climate that include rising average national and global temperatures, warming oceans, rising average sea levels, more extreme heat waves and storms, and extinctions of species and loss of biodiversity. A multitude of other impacts have been observed in every region of the country and virtually all economic sectors.

As part of the United Nations Climate Change Conferences in Copenhagen and Cancún, the United States pledged to cut its carbon dioxide (CO2) and other human-induced greenhouse gas emissions in the range of 17 percent below 2005 levels by 2020, and to meet its long-term goal of reducing emissions by 83 percent by 2050. Approximately 87 percent of U.S. anthropogenic emissions of all greenhouse gases (primarily CO2 and methane) are energy-related, and fossil-fuel combustion accounts for approximately 94 percent of U.S. CO2 emissions (EPA 2010a).

Climate change is often described in terms of changes in background conditions that unfold over decades, but extreme events superimposed on, and possibly amplified by, those background changes can cause severe damage. For example, storm surges superimposed on higher sea levels will cause greater flooding, heat waves superimposed on already warmer temperatures will cause greater damage to crops, and a warmer atmosphere amplifies the potential for both droughts and floods.

From an economist's perspective, greenhouse gas emissions impose costs on others who are not involved in the transaction resulting in the emissions; that is, greenhouse gas emissions generate a negative externality. Appropriate policies to address this negative externality would internalize the externality, so that the price of emissions reflects their true cost, or would seek technological solutions that would similarly reduce the externality. Such policies encourage energy efficiency and clean energy production. In addition, prudence mandates that the Nation prepare now for the consequences of climate change.

 

CONSEQUENCES AND COSTS OF CLIMATE CHANGE

 

 

The clear scientific consensus is that anthropogenic greenhouse gas emissions are causing our climate to change. These changes include increasing temperatures, rising sea levels, changing weather patterns, and increasingly severe heat waves, with negative consequences for human health, property, and ecosystems.1

The Changing Climate

Projections using a wide variety of climate models paint a broadly similar picture of how global temperatures can be expected to rise in response to emissions -- a picture that is also consistent with observed temperature changes (Rohling et al. 2012). Likely temperature paths, from a comparison of models by the USGCRP (2009), predict that the average global temperature under a low-emissions scenario will increase by approximately 4°F by the end of this century; under the medium and high emissions scenarios, end-of-century increases are 7°F and 8°F, respectively. Some regions are projected to experience greater temperature increases than others. The Arctic has warmed by almost twice the global average in recent decades, in part because warming melts snow and ice, leading to less reflected sunlight, which causes yet more warming (Arctic Monitoring and Assessment Programme 2011).

Warming temperatures raise sea levels because of expanding ocean water, melting mountain glaciers and ice caps, and partial melting of the Greenland and continental Antarctic ice sheets. Since 1880, the global sea level has risen about 20 centimeters, more than half of which has occurred since 1950. Projections by the National Oceanographic and Atmospheric Administration show sea levels rising over the 21st century by 19 to 200 centimeters (NOAA 2012).

Increasingly common extreme events, such as heat waves, droughts, floods, and storms, pose some of the most significant risks of climate change. In its assessment of the current scientific literature, the IPCC (2012) concluded that increases in greenhouse gases will almost certainly increase the frequency and magnitude of hot daily temperature extremes during the 21st century, while episodes of cold extremes will decrease. In addition, the length, frequency, and intensity of heat waves are very likely to increase over most land areas, and droughts may intensify (Hansen, Sato, and Ruedy 2012; Rhines and Huybers 2013). In fact, an increase in the mean temperature implies more very hot days and fewer very cold days, even if the variability of daily temperatures around the mean remains unchanged. This phenomenon -- a disproportionate increase in previously extreme temperatures as the mean temperature increases -- is illustrated in Figure 6-1, which displays a shift in a hypothetical distribution of possible daily temperatures. The implications of Figure 6-1 accord with observed changes over the past decades and centuries as well as with climate model simulations. For example, according to the USGCRP estimates, under a high-emissions scenario, areas of the Southeast and Southwest that currently experience an average of 60 days a year with a high temperature above 90°F will experience 150 or more such days by the end of the century.

Patterns of precipitation and storms are also likely to change, although the nature of these changes currently is more uncertain than those for temperature. Northern areas of the United States are projected to become wetter, especially in the winter and spring; southern areas, especially the Southwest, are projected to become drier. Moreover, heavy precipitation events will likely be more frequent: downpours that currently occur about once every 20 years are projected to occur every 4 to 15 years by 2100, depending on location. The strongest cold-season storms are projected to become stronger, more frequent, and more costly. For more on the costs of storms, see Box 6-1.

Estimating the Economic Cost of Climate Change: The Social Cost of Carbon

Because greenhouse gas emissions cause climate change, policies to reduce climate change must focus on reducing anthropogenic greenhouse gas emissions. An important step in informing a policy response is knowing precisely where carbon emissions are coming from, and that is the purpose of the Environmental Protection Agency (EPA) Greenhouse Gas Reporting Program discussed in Data Watch 6-1.

Another critical step in formulating policy responses to climate change is to estimate the economic costs induced by emitting an additional, or marginal, ton of CO2. This cost -- which covers health, property damage, agricultural impacts, the value of ecosystem services, and other welfare costs of climate change -- is often referred to as the "social cost of carbon" (SCC). Having a range for the SCC provides a benchmark that policymakers and the public can use to assess the net benefits of emissions reductions stemming from a proposed policy. Although various studies, notably Stern (2006), have estimated the cost of climate change, until recently the Federal Government did not generate its own unique set of estimates of the SCC.

 

Figure 6-1

 

Illustrative Average Temperature Distribution

 

 

 

 

Source: CEA illustration.

 

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Box 6-1: The Cost of Hurricanes

 

 

Hurricanes draw energy from the temperature difference between the surface ocean and mid-level atmosphere. Although no one hurricane or storm can be attributed to global warming, there is some expectation that warming surface waters will increase the maximum intensity of hurricanes, and a trend toward increasing hurricane intensity has been observed in the North Atlantic over the past three decades (Kossin et al. 2007). As the figure shows, insured losses from storms have also been increasing over the past 20 years, a trend that is driven by losses from recent large hurricanes. Because many of the losses from hurricanes are uninsured, total costs can substantially exceed insured costs.

Development near vulnerable coasts, increasing intensity of storms, and rising sea levels point toward hurricane winds, precipitation, and storm surges that are increasingly destructive. In fact, several studies project substantial increases in hurricane-related costs because of climate change.1 It is difficult to isolate the contribution of climate change to the historical increase in hurricane costs. Nonetheless, from the perspective of social cost, the relevant facts are that the total cost is increasing, and that storm costs will increase with coastal development and could well also increase in response to greater storm severity.

Total Insured Market Losses Caused by All Storm Types, 1985-2012

 

 

 

 

FOOTNOTE TO BOX 6-1

 

 

1 Mendelsohn et al. (2012); Nordhaus (2010); Pielke (2007); Narita et al. (2009).

 

END OF FOOTNOTE TO BOX 6-1

 

 

Note: Years with the 12 costliest hurricanes in U.S. history are labeled.

Source: Munich Reinsurance Company (2012).

______________________________________________________________________

 

 

In 2010, a Federal interagency working group, led by the Council of Economic Advisers and the Office of Management and Budget, produced a white paper that outlined a methodology for estimating the SCC and provided numeric estimates (White House 2010). The SCC calculation estimates the cost of a small, or marginal, increase in global emissions. This process was the first Federal Government effort to consistently calculate the social benefits of reducing CO2 emissions for use in policy assessment. To date, the 2010 interagency SCC values have been used to evaluate at least 17 rules at various stages in the rulemaking process by the EPA, the Department of Transportation (DOT), and the Department of Energy (DOE).

 

______________________________________________________________________

 

 

Data Watch 6-1: Tracking Sources of Emissions:

 

The Greenhouse Gas Reporting Program

 

 

In October 2009, the Environmental Protection Agency (EPA) launched its Greenhouse Gas Reporting Program, an ambitious effort to collect and make publicly available facility-level data on greenhouse gas emissions across the United States. Today, experts and non-experts alike can view, explore, and download comprehensive information on greenhouse gas emissions using the EPA's convenient online data tool. The program is a leap forward for greenhouse gas data collection and the first of its kind in its scale and "bottom-up" approach. It will be an important piece of administrative infrastructure for any future effort to regulate or price greenhouse gas emissions.

Since 1990, the EPA has reported estimates of greenhouse gas emissions in its annual Inventory of U.S. Greenhouse Gas Emissions and Sinks, in compliance with the U.S. commitment under the United Nations Framework Convention on Climate Change. These estimates, however, are mostly "top-down," in that the EPA estimates national emissions using aggregate data on fuel production, imports and exports, and inventories. In 2008, Congress instructed the agency to begin to collect facility-level data, and the EPA developed the Greenhouse Gas Reporting Program to augment the data collected through the National Greenhouse Gas Inventory. The first wave of data, which covers emissions in 2010, was made publicly available in January 2012. More than 6,000 facilities -- refineries, power plants, chemical plants, landfills, and more -- were required to report their emissions, which amounted to 3.2 billion tons of carbon dioxide equivalent (CO2e) that year alone.1 The EPA will release data on 2011 emissions in early 2013.

The EPA provides its database of facility-level greenhouse gas emissions online (http://ghgdata.epa.gov), and visitors can view data by sector or geography or both. The site's rich interface and powerful maps software permits easy spatial analysis of emissions, and built-in charts help users glean useful information from what might otherwise be an unwieldy dataset. Although the Greenhouse Gas Reporting Program is an important step forward for greenhouse gas data collection, there are a few limitations: only facilities that emit more than 25,000 tons of greenhouse gases (measured in CO2e) a year are required to report (although some sectors are "all in," meaning even emitters below the 25,000-ton threshold report for the first three to five years), and the program does not cover emissions from agriculture or land use.

FOOTNOTE TO BOX 6-1

 

 

1http://www.epa.gov/ghgreporting/ghgdata/reported/index.html

 

END OF FOOTNOTE TO BOX 6-1

 

 

______________________________________________________________________

 

 

To estimate the SCC, the working group used three different peer-reviewed models from the academic literature of the economic costs of climate change and tackled some key issues in computing those costs. One issue is the choice of the discount rate used to compute the present value of future costs: because many of the costs occur in the distant future, the SCC is sensitive to the weight placed on the welfare of future generations. Another issue is how to handle some of the uncertainty surrounding climate projections. Box 6-2 explains how the working group dealt with uncertainty about the equilibrium climate sensitivity, which serves as a proxy for the climate system's response to greenhouse gas emissions.

The working group report provided four values for the social cost of emitting a ton of CO2 in 2011: $5, $22, $36, and $67, in 2007 dollars. The first three estimates, which average the cost of carbon across various models and scenarios, differ depending on the rate at which future costs and benefits are discounted (5, 3, and 2.5 percent, respectively). The fourth value, $67, comes from focusing on the worst 5 percent of modeled outcomes, discounted at 3 percent. All four values rise over time because the marginal damages increase as atmospheric CO2 concentrations rise.

The SCC study acknowledged that these estimates, while a substantial step forward, need refinement, for example by a more complete treatment of some damage categories. A detailed discussion of the methodology can be found in Greenstone, Kopits, and Wolverton (2013). The interagency working group has committed to update its estimates of the SCC as the literature evolves and as new scientific and economic evidence become available.

Policy Implications of Scientific and Economic Uncertainty

As a general matter, policy decisions must commonly be made in the presence of uncertainty. A standard approach for cost estimation or policy evaluation in the presence of uncertainty is to consider different scenarios and to compute a weighted average (expected value) over those scenarios. But in some cases it is difficult to quantify this uncertainty. In particular, some of the unknowns about climate change concern extreme scenarios that are far outside recorded human experience. Although such events are therefore difficult to quantify, the possibility of very severe outcomes can and should inform policy.

 

______________________________________________________________________

 

 

Box 6-2: Handling Uncertainty About

 

Equilibrium Climate Sensitivity

 

 

The 2010 Federal study on the social cost of carbon (SCC) used three integrated economic-geophysical models to estimate the cost of climate change: the DICE model, the PAGE5 model, and the FUND model.1 The costs estimated by each model are sensitive to climatic, economic, and emissions parameters. A key input parameter for each model is the equilibrium climate sensitivity, defined as the increase in the long-term annual global-average surface temperature increase associated with a doubling of atmospheric carbon dioxide (CO2) concentration relative to pre-industrial levels.
Estimates of Uncertainty About Equilibrium Climate Sensitivity

 

 

 

 

Source: IPCC (2007); Roe and Baker (2007).

 

The Intergovernmental Panel on Climate Change (IPCC 2012) suggests a range for the equilibrium climate sensitivity of 2-4.5°C (3.2-7.2°F), but the scientific uncertainty extends outside this range. The figure shows distributions of possible values of this parameter arising from different studies; each line in the figure corresponds to a given study, and the higher the line, the greater the chances (according to that study) of the corresponding value of the equilibrium climate sensitivity.

Although the distributions from different studies differ, each holds open the possibility that the value of this parameter might be very large.

This range of uncertainty over the equilibrium climate sensitivity matters for estimating the economic costs of carbon emissions: a higher value implies a more amplified response of temperature to carbon emissions, which would be associated with greater human consequences. To handle this uncertainty, the task force adopted a standard approach used by economists, which is to compute a weighted average -- technically, an expected value -- where the weighting reflects the uncertainty in the scientific literature. Specifically, simulations were run for many values of the equilibrium climate sensitivity drawn randomly from an assumed probability distribution and the results were averaged, producing the expected value for the SCC. The resulting SCC estimate incorporates the uncertainty in the equilibrium climate sensitivity.

FOOTNOTE TO BOX 6-2

 

 

1 The DICE model was developed by William Nordhaus, David Popp, Zili Yang, Joseph Boyer, and colleagues. The PAGE model was developed by Chris Hope with John Anderson, Paul Wenman, and Erica Plambeck. The FUND model was developed by David Anthoff and Richard Tol.

 

END OF FOOTNOTE TO BOX 6-2

 

 

______________________________________________________________________

 

 

One principle of policy design under uncertainty is that the policy should be able to adapt as more is learned and the uncertainty is resolved; another is that a policy should be robust to uncertainty.2 A robust policy aims to give acceptable outcomes no matter what happens, within a given range of possible outcomes. As applied to climate change, this idea of robust policy in the face of uncertainty leads to policies that avoid worst-case outcomes. Such an approach has been advocated by Weitzman (2009, 2011), who argues that, when considering the expected damages of unmitigated global climate change, it is important to consider low probability but potentially catastrophic impacts that could occur. By focusing on avoiding the most costly climate outcomes, a climate change policy that is robust to scientific uncertainty would be more aggressive than a policy that simply focuses on quantifiable uncertainty or a consensus temperature path. If future scientific knowledge were to determine that the worst outcomes could be ruled out, then a robust policy could be adjusted. Thus, although uncertainty complicates the task of computing costs, it is not in itself a reason for inaction or delay.

 

CARBON EMISSIONS: PROGRESS AND PROJECTIONS

 

 

The past five years have seen a remarkable turnaround in U.S. emissions of carbon dioxide. As can be seen in Figure 6-2, from the early 1980s through the mid-2000s, energy-related CO2 emissions increased from approximately 4,500 million metric tons (MMT) to a peak of just over 6,000 MMT in 2007. Since 2007, however, emissions have fallen sharply to approximately 5,500 MMT in 2011, the most recent year for which there is complete data. Indeed, as shown in the figure, this reduction in emissions makes significant progress toward achieving the Copenhagen Accord target of a 17 percent reduction in greenhouse gas emissions below 2005 levels by 2020.3

A natural question is what set of new events or initiatives led to the sharp reduction in emissions. There are a number of candidate explanations: reductions in the carbon content of energy, most notably the substitution of natural gas and renewables for coal; improvements in economy-wide energy efficiency; and unexpectedly low energy demand because of the recession. To estimate the contribution of these factors to the decline in emissions, one needs to posit a counterfactual path for these three variables, that is, for the carbon content of energy (CO2 per British thermal unit, or Btu), energy use per dollar of gross domestic product (Btu/GDP), and GDP. Given a counterfactual, or baseline, path for these variables, one can decompose the decline in carbon emissions to a decline in the carbon content of energy, an accelerated improvement in energy efficiency, or a shortfall of GDP, relative to the baseline path.4 Because the question focuses on the role of new developments, a natural approach is for the baseline to be a business-as-usual projection from a given starting point. For the purpose of this exercise, the starting point is taken to be the 2005 values of the carbon content of energy, energy efficiency, and GDP; the business-as-usual projections are made either by using historical published forecasts or by extrapolating historical trends.

The results of this decomposition estimate that actual 2012 carbon emissions are approximately 17 percent below the "business as usual" baseline. As shown in Figure 6-3, of this reduction, 52 percent was due to the recession (the shortfall of GDP, relative to trend growth), 40 percent came from cleaner energy (fuel switching), and 8 percent came from accelerated improvements in energy efficiency, relative to trend. Of the cleaner energy improvements, most (approximately two-thirds) came from reductions in emissions from burning coal. Reductions in emissions from petroleum combustion also made important contributions (approximately one-third), as these high-carbon content fuels were replaced by lower carbon-content natural gas and clean renewable energy sources, notably wind and biofuels. The contribution from energy efficiency stems from efficiency improvements over the 2005-12 period that were faster than projected; in particular, the Energy Information Administration (EIA 2005) forecast a reduction in the energy content of GDP of 1.6 percent per year, but energy efficiency improved by more than this forecast.5

 

Figure 6-2

 

U.S. Energy-Related Carbon Dioxide Emissions, 1973-2040

 

 

 

 

Note: Shading denotes recession.

Source: EIA (2012b).

As the economy improves, GDP will rise, and the weakness of the economy in 2007-09 will no longer restrain energy consumption. Thus if the recent reductions in emissions are to be continued, a greater share will need to be borne by fuel switching into natural gas and into zero-emissions renewables, and by accelerating improvement in economy-wide energy efficiency.

 

Figure 6-3

 

Decomposition of CO2 Emission Reductions, 2005-2012

 

 

 

 

Source: Bureau of Economic Analysis, National Income and Product Accounts; EIA (2013); CEA calculations.

 

POLICY RESPONSE TO THE CHALLENGE

 

OF CLIMATE CHANGE

 

 

As a general matter, government intervention may be warranted if an individual's action produces a negative externality; that is, if the action imposes costs on another person and those costs are not borne by the person taking the action. As with many environmental problems, the impacts of pollution are broadly shared by society, and individuals emitting pollution do not bear the full, direct costs of their individual action (or reap the full benefits individually of reducing pollution). In the case of anthropogenic emissions of greenhouse gases, the costs of climate change are borne by others, including future generations, and those costs are not reflected in the price of greenhouse gas emissions. This market failure is also present in reverse: an entrepreneur with a clever idea for reducing greenhouse gas emissions, such as a novel energy conservation technology, cannot recoup the full benefit of her innovation because there is no way she can charge those who will benefit from the abatement of those emissions.

This diagnosis of the market failure underlying climate change clarifies the need for government to protect future generations that will be affected by today's emissions. Responding to the challenge of climate change leads to a multipronged approach to policy. Four such responses are implementing market-based solutions; technology-based regulation of greenhouse gas emissions; supporting the transition of the U.S. energy sector to technologies, such as renewables and energy efficiency, that reduce our overall carbon footprint; and taking actions now to prepare for those impacts that are by now unavoidable.

Market-Based Solutions

In his 2013 State of the Union Address, President Obama urged Congress to pursue a bipartisan, market-based solution to climate change. Market-based solutions to greenhouse gas emissions provide economic incentives so that the cost of polluting reflects the economic harm caused to others by that pollution. In this sense, market-based solutions are said to "internalize" the externality caused by the pollution. Under the standard assumptions of economic theory, market-based solutions to pollution are economically efficient because those who create the externality can choose the least costly and disruptive way to reduce their emissions. Under market-based solutions, the effective price of the activity producing the negative externality is adjusted so that it reflects the cost of that externality. There are various ways that market-based solutions can be implemented, one of which is a cap-and-trade system like the one Senators McCain and Lieberman worked on.6

Another example of a market-based solution is a Clean Energy Standard that would require electric utilities to obtain an increasing share of delivered electricity from clean sources but would allow them to meet the standard by trading clean-energy credits. By allowing trading in credits, electric utilities that produce renewable energy at relatively low cost can sell credits to those for which renewable production would be high-cost. Thus the total cost across all utilities of meeting the standard is reduced, relative to the cost were each utility required to meet the standard without tradable credits. In this way, a market for clean energy credits harnesses private-sector incentives to minimize the cost of generating electricity from clean energy sources.7

Direct Regulation of Carbon Emissions and the Vehicle Greenhouse Gas/Corporate Average Fuel Economy (CAFE) Standards

Another way to address the externality of carbon emissions is by direct regulation. In 2007, the Supreme Court ruled in Massachusetts v. EPA that it is incumbent upon the EPA to determine whether greenhouse gases pose a risk to public health or welfare and, if so, to regulate greenhouse gas emissions under the Clean Air Act. In 2012, the U.S. Court of Appeals for the District of Columbia Circuit upheld the EPA's authority to regulate greenhouse gas emissions.

The Administration's corporate average fuel economy (CAFE) and greenhouse gas regulations, released in 2012 jointly by the EPA and the DOT, require automakers to increase the fuel economy of passenger cars and light trucks so that they are estimated to achieve 54.5 miles per gallon by 2025, approximately doubling the previous mileage standards.8 The new fuel economy standards are expected to save more than 2 million barrels of oil a day by 2025 -- more than we import from any country other than Canada -- and to reduce consumer expenditures on gasoline. The standards are projected to reduce annual CO2 emissions by over 6 billion metric tons over the life of the program, roughly equivalent to the emissions from the United States in 2010 (White House 2011a).

The new fuel economy standards help to correct the externality that the cost of carbon emissions is not accounted for in the price of gasoline. The standards also provide a clear signal to the thousands of firms in the auto supply chain that investments in fuel-saving innovation will pay off. These innovations range from large (batteries for electric cars) to small (lighter-weight bolts), and often require suppliers to coordinate with each other. For example, use of innovative high-strength steels can reduce the overall weight of a vehicle, but only if firms making automotive parts and those making tooling for the parts each invest in new production processes (Helper, Krueger, and Wial 2012). The new standards ensure demand for fuel-saving innovations and thus provide an incentive for such investments.

Energy Efficiency

An important way to reduce greenhouse gas emissions is to use energy more efficiently, that is, to use less energy to provide a given service outcome. For example, weatherizing a home improves efficiency by requiring less energy to maintain a given inside temperature. Using less energy, in turn, reduces greenhouse gas emissions.

The Administration has made energy efficiency initiatives an important component of its energy plan.9 These initiatives include major research investments to improve the efficiency of building designs and components such as lighting, heating, and air conditioning, along with smart building controls. Other important initiatives include the weatherization of more than 1 million homes across the country, the President's Better Buildings Challenge with $2 billion in private-sector commitments to energy efficiency retrofits, new standards for residential and commercial appliances, and the Rural Energy for America Program. The Administration has also introduced a variety of programs to help consumers learn about developments in energy efficiency; one such example is the Home Energy Score, a new voluntary program from the DOE to help homeowners make cost-effective decisions about energy improvements. Additionally, as part of a broader manufacturing strategy, the Administration has partnered with manufacturing companies representing more than 1,400 plants that plan to make investments that will improve energy efficiency by 25 percent over 10 years.

An overall measure of economy-wide energy use is the amount of energy needed to generate a dollar's worth of goods and services ("energy intensity"). As is shown in Figure 6-4, the energy intensity of the U.S. economy has fallen steadily over the past quarter century, with an annual average rate of decline of 1.7 percent from 1990 through 2011. However, U.S. energy intensity is still one-third higher than that of Germany and Japan, in part because Germany and Japan have automobiles and building codes that are more energy efficient, as well as smaller homes set more densely.10

One reason for the decline in the energy intensity of the U.S. economy is the increasing importance of services as a share of U.S. GDP. Manufacturing is more energy-intensive than is the production of services, and for decades the share of U.S. GDP derived from services has been growing while the share derived from manufacturing has been declining. This shift from manufacturing to services therefore has reduced the energy intensity of the U.S. economy.

To control for changes in the energy-GDP ratio driven by changes in the sectoral composition of output, the DOE developed an "Economy-wide Energy Intensity Index." This index estimates the amount of energy needed to produce a basket of goods in one year, relative to the previous year. As indicated in Figure 6-5, between 1985 and 2010, the DOE Energy Intensity Index fell by 14 percent. In contrast, the energy-GDP ratio fell by 33 percent. Thus, while much of the decline in energy usage per dollar of GDP has come from improvements in energy efficiency, much of it has also come from factors other than improved efficiency such as shifts in the composition of output.

 

Figure 6-4

 

Energy Use per Dollar of GDP, Selected Countries, 1988-2009

 

 

 

 

Source: Energy Information Administration, International Energy Statistics.

 

Figure 6-5

 

U.S. Energy Intensity, 1950-2010

 

 

 

 

Note: "Energy" is the amount of energy consumed (measured in Btu) compared to 1985 levels. "Energy/GDP" is energy consumed divided by GDP, compared to 1985 levels. The energy intensity index is available starting in 1970.

Source: Department of Energy, Office of Energy Efficiency and Renewable Energy, Energy Intensity Indicators: Trend Data.

The energy intensity index measures the energy footprint of U.S. production, not of U.S. consumption. This distinction arises because energy intensity includes energy used to produce exported goods and services (which are not consumed domestically) and excludes energy used to produce imports. To estimate the CO2 intensity of consumption, as opposed to the CO2 intensity of production, one needs to adjust U.S. CO2 emissions for the difference of foreign emissions in the production of imports less domestic emissions in the production of exports.

Technical developments that use less energy to provide a service, such as maintaining a room at a comfortable temperature, can both reduce energy consumption and improve consumer welfare. Because technical improvements in energy efficiency reduce the energy cost of the service, consumers are better off, and because the price of the service declines, they might use more of it. For example, weatherizing a home might tempt the homeowner to bump up the thermostat a couple of degrees. This consumer response of using more of the newly efficient service is known as the rebound effect. The magnitude of the rebound effect depends on the particular service, more specifically on the elasticity of demand for the service. Viewed solely through the lens of CO2 reduction -- a lens that is appropriate because CO2 emissions are under-priced -- the rebound effect suggests that government efforts on energy efficiency should emphasize services with inelastic demand, so that price changes do not substantially alter service consumption and actual energy savings approach the technically feasible energy savings.

One such example is the services derived from automobiles. In the context of the vehicle greenhouse gas-CAFE standard discussed earlier, the EPA assumes a rebound effect of about 10 percent11, that is, consumers will drive about 10 percent more than if the efficiency of their vehicles had not increased (EPA 2010b). In their reviews of the rebound effect, Greening, Greene, and Difiglio (2000) and Gillingham et al. (2013) suggest more generally that the rebound effect tends to range between 10 percent and 30 percent. Although much has been written on the rebound effect, the base of original research is limited, and more research is needed concerning the rebound effect (and the associated price elasticities) empirically, both in the short and long run.

 

ENERGY PRODUCTION IN TRANSITION

 

 

The United States is in a period of swift and profound change in the way that energy is produced and consumed. Thanks to recent advances in technology, more of the country's domestic oil and gas resources are now accessible. As a result, U.S. oil production has climbed to the highest level in 15 years and natural gas production reached an all-time high. This increase in domestic oil production enhances energy security, and increased natural gas production has substituted for coal, which reduces CO2 emissions per unit of energy produced. At the same time, the Obama Administration has taken historic steps to promote greater energy efficiency and the deployment of renewable energy across the U.S. economy. In the past five years, the United States has more than doubled non-hydroelectric renewable electricity generation. The Administration is working to continue these trends through a comprehensive "all of the above" approach to energy policy that takes advantage of all domestic energy resources, while also igniting the innovation needed to lead the world in clean energy.

The transformation of the U.S. energy sector to one with a smaller carbon footprint is central to climate change policy. As Figure 6-6 shows, approximately 77 percent of U.S. energy production in 2011 came from burning fossil fuels, and the remaining 23 percent was approximately evenly split between nuclear and renewables. In broad terms, the share of natural gas (the fossil fuel with the lowest carbon content) and the share of renewables have been expanding, displacing the share of coal (the fossil fuel with the highest carbon content).

Oil and Natural Gas

New developments in exploration and production techniques and technology have made the extraction of new sources of oil and natural gas economically viable, resulting in a U.S. production boom. Figure 6-7 shows the changing consumption and production trends of natural gas in the United States, along with the U.S. share of global production since 2000. As a result of the developments in shale gas production, total U.S. natural gas production rose 27 percent, from 18.1 trillion cubic feet in 2005 to 23.0 trillion cubic feet in 2011, and well-head prices fell 46 percent, from $7.33 per thousand cubic feet to $3.95 per thousand cubic feet. In 2011, for the first time in 30 years, energy production from dry natural gas exceeded energy production from coal.

The benefits of increased production of natural gas are observed throughout the U.S. economy. In recent years, low energy costs have become a competitive advantage to the U.S. industrial sector. Additionally, low prices for byproducts of natural gas such as methane, ethane, and propane spur growth in agriculture, petrochemical manufacturing, and other industries that use these byproducts.

 

Figure 6-6

 

Total U.S. Primary Energy Production, 2011

 

 

 

 

Note: Natural gas includes natural gas plant liquids.

Source: EIA (2012a).

 

Figure 6-7

 

U.S. Natural Gas Consumption and Production, 2000-2025

 

 

 

 

Source: EIA (2012b).

In the power sector, burning natural gas produces nitrogen oxides, carbon dioxide, and other pollutants, but in lower quantities than burning coal or oil. The life-cycle emissions of greenhouse gases from a combined-cycle natural gas plant is roughly half that of a typical coal-fired power plant per kilowatt hour (Logan et al. 2012). On the other hand, methane, a primary component of natural gas and a greenhouse gas, can be emitted from natural gas systems into the atmosphere through production processes, component leaks, losses in transportation, or incomplete combustion. Measuring fugitive methane emissions from the U.S. natural gas supply chain and, more generally, understanding the potential impacts of natural gas development on water quality, air quality, ecosystems, and induced seismicity, are critical to understanding the impact on the environment of the increasing use of natural gas.

Renewable Energy

In the long run, large reductions in carbon emissions require large increases in energy production from zero-emissions sources, especially renewable energy. In the beginning of his Administration, President Obama set a goal of doubling U.S. renewable energy generation capacity from wind, solar, and geothermal sources by 2012. This ambitious goal has been achieved, thanks both to the Administration's historic investments in clean energy technologies and to decades of government-funded research and development (R&D) aimed at driving costs down to the point where renewable energy is competitive with traditional fossil-fuel energy.

Since 2008, the most significant increase in renewable energy production has been in wind energy. The dramatic increase in wind generating capacity is shown in Figure 6-8. In 2011, wind power constituted more than 30 percent of new additions to U.S. electric generating capacity: close to 6.8 gigawatts of new wind generating capacity was installed in the United States, representing an investment of $14 billion. Wind energy supplies 20 percent of electricity consumption in some states, including Iowa and South Dakota. As a nation, the United States accounts for 20 percent of total global wind power generation and 16 percent of global installed capacity. In 2012, wind power provided more than 3 percent of the nation's electricity generation (EIA 2013b).

The Administration also continues a strong commitment to the development and promotion of solar energy. An important aim is bringing the cost of solar photovoltaics down closer to grid parity with traditional, fossil sources of energy, including natural gas. The Administration's support for solar energy has included more than $13 billion since September 2009 through DOE programs for solar-related projects, including applied R&D, demonstrations, and the DOE clean energy loan guarantee program. In 2011, the DOE launched an ambitious new effort, the Sunshot Initiative, aimed at reducing the installed costs of solar energy systems of all sizes (residential, commercial, and utility) by an additional 75 percent by the end of the decade.

 

Figure 6-8

 

Annual and Cumulative Growth in U.S. Wind

 

Power Capacity, 1998-2011

 

 

 

 

Note: Orange bars are annual additions to capacity and blue bars are total installed capacity at the outset of the year.

Source: DOE (2012b).

Solar photovoltaic capacity is growing rapidly, with current installed capacity estimated to be approximately 4 gigawatts.12 The Interstate Renewable Energy Council estimates that grid-connected photovoltaic capacity increased more than tenfold between 2007 and 2011.

President Obama has set a goal of once again doubling generation from wind, solar, and geothermal sources by 2020, and has called on Congress to make the renewable energy Production Tax Credit permanent and refundable, as part of comprehensive corporate tax reform, providing incentives and certainty for investments in clean energy.13

Advanced Technologies and R&D

The Federal Government also has an important role to play in R&D involving frontier fossil-fuel technologies. Notably, the Administration has invested nearly $6 billion in clean coal technology R&D -- the largest such investment in U.S. history -- and this strategy has attracted more than $10 billion in additional private sector capital investment. Clean coal technology involves removing CO2 from flue gases released from burning coal, then preventing its escape into the atmosphere by injecting it underground, a process known as carbon capture and sequestration. The recovered CO2 can potentially be used to recover hard-to-reach oil reserves, partially offsetting the carbon capture costs. Another clean coal technology in the R&D stage is hydrogen production from coal, in which the highly concentrated CO2 stream is captured and sequestered. Advanced technologies also have the potential to make natural gas burn even cleaner by capturing and storing CO2 emissions, and the government has a role to play in encouraging research into these technologies.

Federal research efforts on zero- and reduced-emissions energy sources extend into other domains as well, including research toward shifting cars and trucks to nonpetroleum fuels.

 

PREPARING FOR CLIMATE CHANGE

 

 

The policies discussed so far aim to reduce emissions of greenhouse gases and thereby to stem future costs of climate change. But the climate has not yet fully adjusted to current levels of greenhouse gases, and ongoing anthropogenic emissions will continue to increase greenhouse gas concentrations because CO2 remains in the atmosphere for centuries. Thus, while it is important for all countries to sharply reduce CO2 emissions to limit the extent of further climate change, even with the most concerted international efforts additional climate change is inevitable. We therefore face a world with an unavoidably changing climate for which we need to prepare.

Policies to prepare for climate change occur at many scales. At the local level, preparing for climate change can entail changing building codes to make structures more storm- and flood-resistant and investing in stronger community planning and response. More substantially, destructive effects of coastal storms can be partially dissipated by restoring natural storm barriers such as tidal wetlands, sand dunes, and coastal barrier landforms.

National policies to prepare for climate change range from providing information about likely changes in local climates and weather patterns, to supporting further research on and monitoring of climate change and its consequences, to providing proper incentives for individuals to prepare for climate change. For example, federal insurance programs, such as the Agriculture Department's crop insurance program and the Federal Emergency Management Agency's flood insurance program, provide insurance either with a subsidy or where there is no private market (that is, the price a private insurer would charge would exceed what a purchaser would be willing to pay). Revisiting federal insurance subsidies could encourage practices that could be increasingly important in the face of accelerating climate changes, such as farmers planting drought-resistant varietals or homeowners building or renovating away from flood plains.

Preparing for climate change will also entail larger-scale infrastructure investments. Some of these investments involve maintaining existing infrastructure. For example, a 2007 investigation by the American Society of Civil Engineers reported that chronic underfunding of the New Orleans hurricane protection system was one of the principal causes of the levee failures after Hurricane Katrina, a storm that inflicted over $110 billion of damages.

Other investments involve enhancing or extending existing infrastructure. For example, the electric power grid can be made more resilient to increasingly severe storms and rising sea levels by using smart grid technology, which pinpoints outage locations and helps to isolate outages, reducing the risk of widespread power shutdowns. The Recovery Act provided the single largest smart grid investment in U.S. history ($4.5 billion matched by an additional $5.5 billion from the private sector), funding both the Smart Grid Investment Grant and Smart Grid Demonstration programs, among others, to spur the Nation's transition to a smarter, stronger, more efficient, and more reliable electricity system (White House 2011b).

 

CONCLUSION

 

 

The scientific consensus is that the anthropogenic emission of greenhouse gases is causing climate change. The results can be seen already in higher temperatures and extreme weather, and these are but precursors of what lies ahead. Although greenhouse gas emissions and climate change are global problems, the United States is in a unique position to tackle these challenges and to provide global leadership.

The Nation has made substantial progress toward the Administration's ambitious short-term Copenhagen targets for reducing emissions of carbon dioxide, but much difficult work lies ahead. Undertaking this work, which reflects the Administration's commitment to future generations, entails many policy steps that are economically justified by the negative externalities imposed by greenhouse gas emissions. Policies to reduce emissions of greenhouse gases include market-based policies; encouraging energy efficiency; direct regulation; encouraging fuel switching to reduced-emissions fuels; and supporting the development and widespread adoption of zero-emissions energy sources such as wind and solar. And, as the country reduces emissions along this path, it also needs to prepare for the climate change that is occurring and will continue to occur. Together these policies pave the way toward a sustainable energy future.

 

FOOTNOTES TO CHAPTER 6

 

 

1 The scientific consensus on the effects of greenhouse gas emissions on climate is summarized in reports by the USGCRP (2009) and the International Panel on Climate Change (IPCC 2012). The draft Third National Climate Assessment report, prepared by the National Climate Assessment Development Advisory Committee, was issued for public comment in January 2013.

2 An important early paper on policymaking under uncertainty is Brainard (1967). Recent work in economics on robust policy in the face of model uncertainty includes Hansen and Sargent (2001, 2007), Giannoni (2002), Onatski and Stock (2002), and Funke and Paetz (2011).

3 United Nations Framework Convention on Climate Change, Appendix I, http://unfccc.int/meetings/copenhagen_dec_2009/items/5264.php.

4 Specifically, CO2 emissions are the product of (CO2/Btu)x(Btu/GDP)xGDP, where CO2 represents U.S. CO2 emissions in a given year, Btu represents energy consumption in that year, and GDP is that year's GDP. Taking logarithms of this expression, and then subtracting the baseline from the actual values, gives a decomposition of the CO2 reduction into contributions from clean energy, energy efficiency, and the recession.

5 Houser and Mohan (forthcoming) undertake a similar decomposition. They use different assumptions for the baseline, including somewhat stronger post-2005 GDP growth in the "business as usual" case than is assumed here, and as a result attribute slightly more of the post-2005 reduction in CO2 emissions to slower economic growth.

6 For a more detailed discussion of cap-and-trade, see the 2010 Economic Report of the President, chapter 9.

7 For further discussion of a Clean Energy Standard, see the 2012 Economic Report of the President, chapter 6.

8 Because the standards regulate greenhouse gas emissions, they can be met in part in ways that do not improve fuel economy. In particular, if improvements are made by reducing leakage of greenhouse gases in auto air conditioners, or by replacing refrigerants with non-greenhouse gases, then the goal of reducing greenhouse gas emissions is achieved without improving fleet fuel economy.

9 http://www.whitehouse.gov/sites/default/files/email-files/the_blueprint_for_a_secure_energy_future_oneyear_progress_report.pdf

10 In neither Germany nor Japan is the lower energy intensity due to having less manufacturing than the United States. In fact, manufacturing (an energy-intensive sector) is almost twice as high as a share of GDP in Germany as it is in the United States.

11 The EPA rebound estimate draws on the literature, for example, Small and Van Dender (2007).

12 The Interstate Renewable Energy Council (IREC), the Solar Energy Industries Association (SEIA), and the National Renewable Energy Lab (NREL).

13http://www.whitehouse.gov/sites/default/files/uploads/sotu_2013_blueprint_embargo.pdf.

 

END OF FOOTNOTES TO CHAPTER 6

 

 

CHAPTER 7

 

 

INTERNATIONAL TRADE AND COMPETITIVENESS

 

 

The United States is more closely linked with other nations through trade, investment, and financial flows than ever before. For example, total trade in goods and services as a share of gross domestic product (GDP) was approximately 31 percent in 2012, compared with 26 percent in 2000 and 11 percent in 1970. International linkages are also reaching more deeply than ever before into the organization of industries and firms. U.S. companies are increasingly part of global supply chains, in which firms buy inputs from subcontractors located in many countries. These linkages bring both challenges and opportunities for the U.S. economy and for government policy. Macroeconomic shocks and policies halfway around the world have direct effects on growth, employment, and national balance sheets here at home, just as shocks and policies in the United States affect economies across the globe.

Significant opportunities are available for U.S. firms to expand exports and create jobs, for resources to be allocated to their most productive uses, for innovation to flourish, and for consumers to enjoy higher incomes, lower prices, and expanded choice. These opportunities, however, have been accompanied by job displacement, downward wage pressures, and other adjustment costs. Government policy plays an important role in providing infrastructure and incentives that reduce these adjustment costs, promote the creation of middle-class jobs, and foster innovative ecosystems in the private sector. Administration policies in both trade and competitiveness seek to create a fair, firm foundation for the long-term prosperity of the United States and its trading partners.

 

THE WORLD ECONOMY AND U.S. TRADE

 

 

Fiscal consolidation, weak financial systems, and market uncertainty have adversely affected demand in many advanced economies, and world economic growth has suffered. In 2012, there were a number of shocks to global growth, including the impact of financial stresses in Europe that reached a peak in mid-summer. Given the globalized nature of world trade and finance, the United States cannot fully escape the impact of development in other nations.

Growth in World Economies

Unlike the U.S. economy, which has sustained positive economic growth for the past three years, several of the nation's major trading partners have slipped into economic contraction. In 2012, the euro area fell into recession once again, as severe austerity measures put in place to combat the region's debt crisis impeded growth. The International Monetary Fund (IMF) estimates that in 2012, the euro area economy contracted 0.4 percent, compared with growth of 2.0 percent in 2010 and 1.4 percent in 2011. While Japan was temporarily able to recover from the harsh economic slowdown resulting from the earthquake and tsunami that struck the country in early 2011, slower global demand and the phase-out of reconstruction spending brought the third largest economy in the world back into recession.

With the euro area, Japan, and the United States accounting for almost half of global GDP, slower average growth in these economies was sufficient to lower growth at the global level. Emerging market economies have relied on import demand from these large, high income economies to sustain high growth for over a decade. As import demand has weakened, particularly from Japan and Europe, economic growth in emerging markets has decelerated as well (Figure 7-1). For example, in 2012:Q2, real GDP in China grew approximately 5.65 percent at an annual rate, the lowest quarterly GDP growth China has recorded since the beginning of the global slowdown in 2008.

The Euro Crisis

After financial tensions reached a peak in mid-2012, steps were taken by both the governments of Europe and the central bank to reassure markets of the integrity of the euro area and to begin the process of reforms. In the summer of 2012, the European Central Bank announced it stood ready to stabilize the bond markets of any member state in a reform program, while governments launched the European Stability Mechanism (ESM), a joint fund to provide direct loans to governments that replaces the temporary European Financial Stability Fund (EFSF). These firewalls against financial contagion have helped restore confidence, allowing Ireland and Portugal to begin their return to financial markets. In Greece, meanwhile, European governments made important concessions in a redesigned program that reduces Greek borrowing costs and supports continued reforms.

 

Figure 7-1

 

Real GDP Growth by Country, 2007-2012

 

 

 

 

Note: Data through 2012:Q4 for all but emerging markets, for which data is available only for 2012:Q3.

Source: Country sources; U.S. Department of Commerce, Bureau of Economic Analysis; Cabinet Office of Japan; Statistical Office of the European Communities; CEA calculations.

The combined impact of these measures produced noticeable results. Bond yields in vulnerable countries fell dramatically to more sustainable levels; in the week of the announcement of the bond buying plan, Spanish 10-year bond yields declined from 6.9 percent to 5.6 percent, and Italian 10-year bond yields fell from 5.8 percent to 5.0 percent (Figure 7-2).

Meanwhile, European authorities have taken important measures to ensure that their banks have access to liquidity and hold adequate capital. The authorities have also committed to launching a banking union with a single supervisor and a European facility to recapitalize banks in troubled countries where the governments are already facing problems managing their debts. Uncertainty remains about access to a capital backstop as well as about prospects for euro area institutions for common resolution and deposit guarantees.

Finally, while the global recovery is clearly underway, European nations are still facing challenges. The euro area reentered recession in 2012, and the IMF in January forecast a further contraction of 0.2 percent in 2013 with continuing declines in output in Italy and Spain. Unemployment in the euro area is hitting record highs, with 2012 unemployment rates in Greece and Spain in excess of 23 percent (Table 7-1). Sustained fiscal consolidation and the deleveraging in the banking and business sectors in the euro area continue to act as headwinds to growth. Even as European leaders continue to undertake structural reforms aimed at increasing competitiveness over the medium term, markets remain sensitive to growth and reform prospects in large economies, including countries like France, Italy and Spain. Meanwhile, a number of countries with stronger budget positions, including Germany and the Netherlands, are running significant balance of payments surpluses and thus are not an important source of demand for the European recovery. More broadly, the euro area's combined trade surplus, after adjusting for the effect of commodity prices, is rising quite rapidly, contributing to global imbalances. Weaker European economies are closing their trade deficits as imports decline with fiscal consolidation and contracting domestic demand, and Germany's current account surplus has risen back to its pre-crisis level of 6 percent thanks to the strong performance of German exports around the world.

 

Figure 7-2

 

10-Year Government Bond Yields, 2011-2013

 

 

 

 

Source: Bloomberg.

While we are making progress on increasing U.S. exports, these also depend on expansion in overseas markets. Europe is a significant destination for American exports, accounting for more than 20 percent of U.S. goods exports and almost 40 percent of U.S. service exports. Europe is also the leading foreign source of investment in America, accounting for more than 70 percent of all foreign direct investment in the United States in 2011. Global and U.S. economic performance will depend, in part, on continuing progress to resolve Europe's challenges.

                                   Table 7-1

 

                     Euro Area Selected Economic Indicators

 

 ______________________________________________________________________________

 

 

                            Greece        Spain        Italy         Germany

 

                        _____________  ____________ ____________   ____________

 

 

                        2009    2012   2009   2012  2009    2012   2009    2012

 

 ______________________________________________________________________________

 

 

 GDP growth (percent)   -3.3   -6.0    -3.7   -1.4  -5.5    -2.1   -5.1     0.9

 

 

 Unemployment rate

 

 (percent)               9.5   23.8   18.0    25.1   7.8    10.6    7.8     5.5

 

 

 Current account

 

 balance (percent

 

 of GDP)               -11.2   -2.9   -4.8    -0.8  -2.0    -1.5    5.9     6.4

 

 

 Primary budget

 

 balance (percent

 

 of GDP)              -10.4    -1.7   -9.9    -4.5  -1.0     2.6   -0.9     1.4

 

 

 General government

 

 debt (percent

 

 of GDP)              128.9  170.7    53.9   90.7  116.0    126.3  74.7    83.0

 

 

 ______________________________________________________________________________

 

 

 Source: IMF (2012); European Commission Statistical Office.

 

 

Global Imbalances

"Global rebalancing" has been one of the Administration's major international economic policy goals for the past four years. In June 2012, the G-20 nations reiterated their support for this goal, calling upon countries with current account deficits to boost national savings, consistent with evolving economic conditions, and for countries with large current account surpluses to strengthen domestic demand and move toward greater exchange rate flexibility.

A country's current account consists predominantly of the difference between its exports and its imports of goods and services (other factors include net income on overseas assets and unilateral transfers such as foreign aid and remittances). A current account deficit occurs when a country's absorption (the sum of domestic consumption, investment and government spending) exceeds its production. In this case, it must either borrow from abroad or sell foreign assets. Current account deficits in certain countries correspond to current account surpluses in others. A current account deficit may indicate that a country offers sound investment opportunities, or it may be caused by investment bubbles or fiscal deficits. Large and persistent current account surpluses can occur when governments intervene in financial markets to prevent market-driven adjustments in interest rates and exchange rates from taking place. While large current account imbalances may not directly cause financial crises, they often indicate underlying dynamics that are unsustainable and thus have historically been important precursors to financial crises (Reinhart and Rogoff 2011).

Before the 2008 crisis, the United States was running a large current account deficit financed by surpluses from creditor nations such as China and Japan, a situation that Federal Reserve Chairman Ben Bernanke referred to as the "global saving glut" (Bernanke 2005). In China, for example, low levels of social insurance and policies designed to encourage excessive saving by firms contributed to large surpluses (Obstfeld 2012). From 2000 to 2007, the U.S. deficit ballooned to more than 5 percent of GDP, while current account surpluses in China, Germany, and Japan grew to 10, 7, and 5 percent of GDP, respectively. Current account deficits in Europe's periphery reached alarming levels. The surplus countries came to rely on unsustainable growth in net exports to drive their economies. The deficit countries relied on unsustainable growth in household consumption, construction of residential real estate, and government budget deficits for economic growth.

The crisis of 2008 brought about a distinct change in global imbalances: the U.S. current account deficit shrank to 3 percent of GDP in 2009, while current account surpluses in China and Japan dropped as well (Figure 7-3). The Administration, along with the wider international community, continues to press for a more balanced approach to growth in the world. Greater reliance on consumption, and less on exports and investment, will provide those countries with large current account surpluses with a more sustainable source of growth over the long run. The members of the G-20 have committed to moving more quickly to market-determined exchange rate systems and exchange rates that reflect underlying fundamentals.

 

TRADE AND THE MANUFACTURING SECTOR

 

 

Although the Nation's current account balance has improved substantially since its record deficit level of $800.6 billion in 2006, much of this improvement is due to growing surpluses of trade in services and income on investments, while the trade deficit in goods appears to have increased since the recovery from the recession began in the third quarter of 2009 (Figure 7-4). However, the increase in the goods deficit conceals the fact that from 2010 to 2012, exports of manufactures grew at a faster rate (22.0 percent) than imports (19.3 percent). The goods deficit has widened only because manufacturing imports began the period at a much higher level.

U.S. trade in manufactures, both imports and exports, has grown rapidly in recent decades primarily as a result of reductions in trade costs, the rapid growth of emerging markets, and the increasing international specialization of supply chains. Technological improvements in transportation and communication have lowered trade costs, as have reductions of tariffs and other trade barriers both at home and abroad. Emerging markets, particularly China, have grown at an impressive pace in the past decade and have moved aggressively into manufacturing. In the past 10 years, China's share of world manufacturing exports has grown from 5 percent to over 15 percent. Finally, improvements in information technology (IT) have led to the emergence of global value chains, in which tasks and components involved in production are allocated across countries to take advantage of differences in costs, skills, technology, or proximity to the market (Data Watch 7-1). As a result, trade in intermediate goods and services has grown rapidly. The effects of these forces on the U.S. economy have been profound.

 

Figure 7-3

 

Current Account Balance by Country, 2000-2011

 

 

 

 

Note: Germany and Japan current account data available through 2012, U.S., U.K., and China data only available through 2011.

Source: Deutsche Bundesbank; Bank of Japan; United Kingdom Office for National Statistics; U.S. Department of Commerce, Bureau of Economic Analysis; Chinese State Administration of Foreign Exchange.

 

Figure 7-4

 

U.S. Current Account Balance and its Components, 2000-2012

 

 

 

 

Note: Shading denotes recession.

Source: U.S. Department of Commerce, Bureau of Economic Analysis.

Trade and Productivity

Greater openness of world markets enhances the productivity of U.S. industries and firms. Research finds that the U.S. industries experiencing the largest declines in tariffs have exhibited some of the strongest productivity gains. Bernard, Jensen, and Schott (2006) find that falling trade costs led individual U.S. manufacturing plants that already export to increase their shipments abroad, high-productivity nonexporters to become more likely to export, and low-productivity plants to become more likely to exit the domestic market. Together, these effects result in a reallocation of economic activity toward high-productivity firms, thereby raising overall industry productivity. Studies of numerous other countries show similar gains in industry productivity through trade-induced reallocation across firms.

Evidence also shows that decreases in industry-level trade costs lead to within-firm productivity growth. Lileeva and Trefler (2010), for example, found that the Canada-U.S. Free Trade Agreement caused increases in labor productivity, product innovation, and adoption rates for advanced manufacturing technologies among Canadian exporters. Pierce (2011) showed that U.S. tariffs lower the productivity of U.S. firms, in part by slowing the rate at which older, less-productive production lines are phased out in favor of new product lines. Several other studies have found that trade liberalization increases research and development (R&D) and technology upgrading.

Firm productivity and exports also can be enhanced when trade liberalization lowers the cost, and expands the variety, of imported intermediate inputs.1 Although much of the evidence for this channel comes from studies of middle- and low-income countries, Amiti and Wei (2009) found that imports of service inputs, such as telecommunications, insurance, finance, computing, and other business services, have a significant positive effect on manufacturing productivity in the United States. In a similar vein, Francois and Woerz (2008) showed that, across advanced economies, increased import penetration in producer services results in better export performance, particularly by skill- and technology-intensive industries.

 

GROWTH OF TRADED SERVICES

 

 

The United States is currently the world's largest services exporter. In 2011, U.S. exports of private services exceeded $600 billion, and sales through foreign affiliates exceeded $1 trillion. Taken together, international sales of services by U.S. companies are on the order of $1.7 trillion a year, an amount equal to approximately 11 percent of U.S. GDP. Services trade accounts for approximately 30 percent of U.S. exports and 15 percent of U.S. imports. A study by the Organisation for Economic Co-operation and Development and the World Trade Organization (WTO), however, estimated that nearly 60 percent of the value of U.S. exports can be attributed to the service sector. This estimate takes into account both direct services exports, as measured in official trade statistics, and indirect services exports embodied as intermediate inputs in goods exports. The main traded service categories are "other private services" (which includes items such as business, professional, and technical services, insurance services, and financial services), royalties and license fees, and private travel.

Falling costs of travel, communication, and information technology have increased the opportunities for trade in services. Over the past 10 years, services imports and exports both almost doubled. Much of the growth was accounted for by increased trade in business services, especially digitally enabled services, defined by the Bureau of Economic Analysis (BEA) as those for which digital information and communications technologies (ICT) significantly facilitate cross-border trade. According to the BEA, from 1998 to 2010, exports of all ICT-enabled services grew at an annual rate of 9 percent to reach 61 percent of total U.S. services exports, up from 45 percent in 1998. Imports of ICT-enabled services grew at an annual rate of 10 percent, rising to 56 percent of U.S. services imports, from 34 percent. Increases in business, professional, and technical services contributed most to the overall increase in ICT-enabled services trade. The private services surplus was $162 billion in 2010; of this, $116 billion resulted from a trade surplus in ICT-enabled services.

Some estimates suggest that about 70 percent of employment in business services is in industries potentially subject to international competition (Jensen 2009). There is a widespread concern that, as business services become more tradable over time, these jobs will be lost to import competition from low-wage, labor-abundant countries. However, given the abundance of capital and highly skilled workers in the United States, the most successful U.S. export industries tend to be those that employ capital and skilled labor most intensively. In the services sector, the largest export industries -- integrated record production and distribution, software publishers, web search portals, satellite telecommunications, and motion picture and video production -- also pay the highest wages (Jensen 2011). The fact that the United States has consistently maintained a positive trade balance in services, and high-skill business services in particular, suggests that the world is willing to pay for the high-quality, skill-intensive services that the United States provides.

 

______________________________________________________________________

 

 

Data Watch 7-1: Implications of Global Value

 

Chains for the Measurement of Trade Flows

 

 

While international trade and foreign direct investment have been growing rapidly for decades, recent advances in information technology along with improving industrial capabilities in emerging markets have made it profitable to segment production processes and relocate them throughout the world, creating global value chains. This shift has made it increasingly difficult to interpret international trade statistics. In the past, it was safe to assume that most if not all of the value of a traded product was created in the country that exported it. Thus, a country's industrial capabilities could be judged by the content of exports, trade rules could be tied to gross levels of trade in specific products, and exports could be directly related to domestic job creation. With the rise of global value chains, however, one can no longer be sure how much of the value of a product or service is added in the country that declares it as an export. For example, in 2009, between one-third to one-half of the total value of exports of transport parts and equipment from most major producing countries originated in a different country. Similar patterns emerge in the electronics sector: in China and Japan, the world's largest exporters of electronic goods in 2009, the foreign content of electronics exports was about 40 percent. In Mexico, the share was over 60 percent (OECD 2013).

Official trade statistics are measured in gross terms -- the amount the importer pays the exporter for the good. That approach is appropriate for adding up a country's balance of payments made to, and received from, the rest of the world. To determine how much value an exporter adds to a good or service traded internationally, however, one must subtract the value of intermediate inputs supplied by other countries, including the country importing it. Removing these intermediate flows from exports gives a measure of "value-added" trade.

Measuring value-added trade reveals a number of surprising facts. For example, according to Koopman et al. (2010), in 2004 about 8 percent of total gross U.S. imports was U.S. value added in the form of U.S. intermediate inputs used in foreign production. About 25 percent of the value of U.S. gross exports was made up of imported intermediate inputs; however, about half the value of those inputs originated in the United States, so only about 13 percent of U.S. gross exports were not U.S. value added. By contrast, about 37 percent of China's exports were value added somewhere else. Johnson and Noguera (2012) estimate that, while still large, the U.S.-China imbalance is approximately 40 percent smaller when measured on a value-added basis, and the U.S.-Japan imbalance is approximately 33 percent higher. They also show that domestic value added in gross exports for the world as a whole has fallen dramatically in recent years, indicating the rise of global value chains.

The Organisation for Economic Co-operation and Development and the World Trade Organization recently released a new data set containing estimates of value-added trade for 40 countries and 18 industries for 2005, 2008, and 2009 (OECD 2013). Future releases will see an expansion in the number of countries, industries, and time periods, dating back to 1995. This effort represents a substantial improvement in the availability of information about global value chains.

______________________________________________________________________

 

 

Despite America's apparent comparative advantage in tradable highskill, high-wage business services, export activity on the part of these firms faces significant impediments. About 25 percent of manufacturing plants export; in business services, only about 5 percent of businesses export (Jensen 2009). While differences in language and culture may pose greater barriers to trade in services than in manufactures, services also are differentially affected by an array of government-imposed impediments, such as restrictions on foreign ownership and partnership arrangements; nationality, residency, or local presence requirements for service providers; licensing and accreditation requirements; and limitations on the scope of activities. Hufbauer, Schott, and Wong (2010) have estimated that the aggregate level of barriers to services imports in emerging markets such as China, India, and Indonesia is equivalent to a tariff on these imports of more than 60 percent. After decades of liberalization through trade agreements, tariffs in that range are relatively rare for goods. Recent research also has found that restrictions on foreign acquisitions, discrimination in licensing, restrictions on the repatriation of earnings, and inadequate legal recourse all have a significant negative effect on investment inflows into services sectors (Borchert, Gootiiz, and Mattoo 2012). The Administration has undertaken several important initiatives to address these impediments, discussed further below.

 

TRADE POLICY

 

 

World trade collapsed in 2009; the recovery, while substantial, is being held back by slow global growth. In response, in his 2010 State of the Union address, the President launched the National Export Initiative (NEI), an Administration-wide effort to double U.S. exports in support of up to 2 million additional American jobs by the end of 2014. Under the NEI, the Administration continues to focus on improving trade advocacy and export promotion efforts, removing or reducing barriers to U.S. exports of goods and services, increasing access to credit, robustly enforcing trade rules, and pursuing policies at the global level to promote strong, sustainable, and balanced growth. In 2012, U.S. exports of goods and services amounted to $2.2 trillion, an all-time record, despite challenging global economic conditions.

Longer-term trends affecting trade include the rapid growth in emerging markets and the rise of global value chains. The growth of emerging markets makes them the most likely source of future U.S. export growth. The International Monetary Fund estimates that developing countries will account for more than three-quarters of the economic growth of all U.S. trading partners in the next five years. It is vital, therefore, that the United States secure from these countries more open and transparent market access for U.S. firms. In addition, because of their growing involvement in global value chains, U.S. firms are increasingly exposed to policies and barriers behind the borders, not just at the borders, of countries around the world. Countries vary widely in their use of subsidies, export taxes, support for state-owned enterprises, financial market restrictions, ownership restrictions on foreign direct investment, government procurement, and enforcement of intellectual property rights, to name a few.

To address these challenges, the United States has pursued a robust program of enforcement of existing rules through WTO dispute settlement and a negotiating strategy for new agreements aimed at securing deep commitments with like-minded countries on a broad array of trade-related measures. The overriding goal of these latter initiatives, whether multilateral, plurilateral or bilateral, is to open markets and set standards for conduct that eventually shape the standards adopted by the global trading system. The United States continues to adhere strongly to the precept that trade liberalization at the multilateral level holds the highest potential for securing wide-ranging market-opening outcomes. The United States will continue to complement its multilateral approaches with discussions at the plurilateral and bilateral levels to build consensus for, and commitments to, market-opening agreements critical to the growth of trade-supported jobs.

 

_____________________________________________________________________

 

 

Box 7-1: Small Businesses and the NEI

 

 

Small businesses, defined by the Small Business Administration as independent businesses having 500 or fewer employees, account for more than half of nonfarm private GDP. These 27.5 million businesses, many of them family-owned companies, are a key part of the U.S. economy. However, they are far less likely to export or to use inputs from abroad than are larger firms. In a world of imperfect financial markets, the costs of financing export operations pose an especially high barrier for smaller firms, because they are more likely to need external financing to undertake export transactions. Small businesses also can find it more difficult to learn about foreign markets and to overcome foreign trade barriers and unfair trade practices compared with larger firms.

Through the NEI, the Obama Administration is committed to helping small businesses overcome such barriers to exporting. The NEI calls for a national outreach campaign both to identify small businesses that may be able to increase their exports and to raise awareness generally among the nation's small businesses about export opportunities. The NEI provides training and other technical assistance to help small businesses prepare to become exporters, sets up pilot programs to match small businesses with export intermediaries, and outlines several measures to support small businesses once they begin to export to new markets. Thanks in part to the efforts of the NEI, a record of nearly 287,000 U.S. small and medium-size enterprises (SME) exported in 2010 (98 percent of all exporters), a total increase of more than 16,600 SMEs over 2009. The goal is to increase the national base of SME exporters by 50,000 by 2017.

_____________________________________________________________________

 

 

In 2012, market-opening trade agreements with Korea, Colombia, and Panama entered into force. The United States is currently negotiating with 10 partners in the Trans-Pacific Partnership to tackle 21st-century trade issues in the Asia-Pacific region. In January 2013, the President announced plans to negotiate toward an international services agreement with an initial group of 20 trading partners, aimed at removing impediments to global services trade. In February, the Administration announced its intention to launch negotiations for a comprehensive Transatlantic Trade and Investment Partnership with the 27-member European Union, aimed at expanding what is already the world's largest economic relationship, accounting for one-third of total goods and services trade and nearly half of global economic output.

In the WTO, the United States is advocating new approaches that can offer opportunities for agreements on issues that have been part of the Doha Development Agenda, such as trade facilitation, and in areas that are outside the Doha agenda, such as expansion of the Information Technology Agreement. The United States also welcomed Russia's membership in the WTO, a membership that will provide significant commercial opportunities for U.S. exporters.

Finally, the Administration aims to address potential disruptions that trade can cause to domestic labor markets. The Federal Government's Trade Adjustment Assistance (TAA) program is designed to assist workers whose jobs have been lost to import competition or threatened by trade-related circumstances. The program provides financial, job training, and relocation assistance to newly unemployed workers displaced by trade, with the goal of making it easier for these workers to develop new skills and then enter more vibrant sectors of the economy. In fiscal year 2012, the TAA program certified 1,131 petitions that permitted more than 81,000 workers to participate in the program.

 

Building U.S. Competitiveness

 

 

The Nation must construct an economy based on a solid foundation of educating, innovating, and building better infrastructure, a foundation that can be strengthened in both manufacturing and in services. A hallmark of the Administration's policies is the recognition that there are many spillovers within and between economic sectors and regions. Thus, wellchosen policies reinforce each other both to increase competitiveness and to provide more middle-class jobs. For example, grants that assist workers and firms that invest in apprenticeships benefit other firms in their industry and region that can draw on a pool of skilled labor. Because of the myriad benefits that arise from having a broad base of innovative workers, economic growth and fairness go hand in hand. That is, Administration policies are built around the idea that the country does best when everyone does their fair share and plays by the same rules.

Manufacturing

While manufacturing employment has declined as a share of the workforce for the past 50 years, the absolute number of manufacturing jobs was relatively constant at about 18 million from 1965 until 2000. However, starting in 2000, manufacturing employment dropped precipitously. The United States lost 3.5 million manufacturing jobs in the 7 years before the Great Recession and then lost another 2.3 million during the recession.

This job loss has serious implications for the economy. First, the decline in manufacturing employment significantly reduced the number of middle-class jobs, especially for less educated workers. Wages and salaries in manufacturing are 7 percent higher than in the rest of the economy, and total hourly compensation (which includes the value of benefits such as health care and pensions) is 13 percent higher. After controlling for factors such as education, age, gender, race, union status, and location, the compensation premium for manufacturing rises above 14 percent. A 2012 Department of Commerce study comparing manufacturing workers to those in other private industries finds similar results (ESA 2012). Workers of all education levels and occupations in manufacturing -- from assemblers to design engineers -- earn more than their peers in other industries, showing manufacturing's value in maintaining a strong American middle class. Second, growing evidence shows that manufacturing production has positive spillover impacts on other parts of the economy. Spillovers occur when one company's activities benefit other businesses even though the latter did not pay for them (Economic Application Box 7-1). As discussed below, the loss of manufacturing activity has reduced these benefits.

Spillovers Between Manufacturing Production and Innovation

The argument is sometimes made that loss of U.S. production jobs is part of an efficient global division of labor in which the United States focuses on higher-end innovative activity and cedes lower-skill production activity to other countries. However, this argument does not always hold.

First, production need not be a low-skill activity. Some of our main competitors in manufacturing employ more highly skilled production workers and pay significantly higher wages than do companies in the United States. Countries such as Germany and Denmark compete through business and government support for "high-road" production practices, in which workers participate in innovation as well as production. The higher wages paid to these highly-skilled workers are offset by their higher productivity (Helper, Krueger, and Wial 2012).

Despite its private and social benefits, however, companies do not always adopt the high-road strategy because successful implementation requires them to adopt a whole suite of interrelated practices. For example, a study of U.S. valve producers found that more-efficient firms adopted advanced information technology, while simultaneously changing their product strategy (to produce more customized valves), their operations strategy (using their new IT capability to reduce setup times, run times, and inspection times), and human resource policies (employing workers with more problem-solving skills and using more teamwork). The success of changes in one area depended on success in other areas. For example, customizing products was not profitable without reductions in the time required to change over to making a new product, something made possible both by improved IT capabilities and the improved use of this capability by the empowered workers. Conversely, the IT and training investments often did not pay off in firms that did not customize their products (Bartel, Ichniowski, and Shaw 2007).

 

_____________________________________________________________________

 

 

Economics Application Box 7-1: Agglomeration

 

Economies and Spillovers Across Regions

 

 

Businesses are not spread out evenly across space but tend to clump together, or "agglomerate." As explained in Alfred Marshall's Principles of Economics (1890), firms group together because proximity allows them to share workers, ideas, and other inputs more easily. Numerous studies have found that establishments located near other establishments, whether in related industries (a cluster) or in diverse industries (urbanization), tend to be more productive (Rosenthal and Strange 2003).

A cluster is a geographically concentrated ecosystem of customers, suppliers, trade associations, and labor unions that do business with one another. These groups have collective capabilities. Like the common pasture in medieval English villages on which the livestock owned by many residents grazed, this "industrial commons" allows firms, particularly small firms, to nourish their technological capability using shared assets. These common resources help to accelerate innovation and commercialization. For example, firms located near each other can share equipment needed for testing, and can more easily meet face-to-face, which improves knowledge-sharing and trust-building. Service firms (such as those in the Los Angeles film industry) -- not just manufacturers -- benefit from agglomeration.

In some cases, both the grouping of firms and the higher productivity may be the result of a third factor. For example, several firms may each decide to locate near a natural harbor; their lower transport costs may increase their productivity, but at least initially there may be little benefit due to the proximity of other firms. Still, research suggests that the entry of a large factory to a community tends to increase the productivity of surrounding firms (Greenstone, Hornbeck, and Moretti 2010). Other research indicates that the benefits of R&D investment are primarily local, suggesting that ideas -- and by extension productivity -- are improved in geographically concentrated industries. Jaffe (1989) uses data from patent citations to show that inventors disproportionately build on the work of nearby scientists. Branstetter (2001) argues that the benefits of R&D appear to be primarily confined to the borders of the investing country.

Because the benefits of a shared asset spill over to help even firms that did not contribute to paying for it, and because profit-maximizing firms will not value this benefit to other firms in making their plans, market forces are unlikely to provide enough investment in shared assets. A case thus can be made for government to subsidize such activity. For example, government support for key local assets such as a university or apprenticeship program may help a cluster to develop through improved access to specialized R&D and skilled workers. Other successful clusters have emerged from a mix of firm- and government-led actions such as the cluster of computer and technology companies in Silicon Valley.

Once lost, these ecosystems can be hard to recreate. For any single firm, the decision to move production elsewhere may make economic sense. But that decision affects suppliers and the local talent pool, making it easier for the next firm to leave and harder for the next firm considering coming there to say yes. Conversely, new industries can build on foundations left by older clusters. For example, Optimus, a Pittsburgh biofuels startup, uses a 100-year-old union training program to reduce the costs of training technicians to service its innovative equipment -- and to demonstrate its product. Supported by the new federal Workforce Innovation Fund, a partnership of startups, unions, and Carnegie Mellon University is creating apprenticeship programs that build on this model of shared training and product demonstration assets.

_____________________________________________________________________

 

 

Second, there may be spillovers from production to innovation. Thus, while Moretti (2012) shows that the positive wage spillovers associated with innovation jobs are greater than those associated with manufacturing jobs, it may not be possible to keep the innovation jobs in the long run if production jobs are lost. For example, when production in consumer electronics migrated to Asia decades ago, the United States lost the potential to compete for follow-on innovations and subsequent production in flat-panel displays, LED lighting, and advanced batteries (Pisano and Shih 2012). Making products exposes engineers to the problems and the capabilities of existing technology, generating ideas both for improving processes and for applying a given technology to new markets. Losing this exposure makes it harder to come up with innovative ideas.2

Even when American firms do maintain a technological edge, their operations may be less profitable than if they were part of a vibrant industrial commons. E-ink, a Massachusetts firm now owned by its Taiwanese business partner, designed the electronic "ink" that represents the Kindle's key innovative element. Because the firm was located so far away from its Asian suppliers, its engineers were not able to interact on a daily basis with other firms in the supply chain that were inventing new products, making it hard for the firm to find new markets for its inks. The situation is similar throughout the rest of the LCD flat-panel-display industry. Harvard Business School Professor Willy Shih estimates that, because the United States has offshored much of its production capacity in this industry, U.S. firms capture only about 24 percent of the profits from U.S. Kindle sales (Pisano and Shih 2012).

Rise of Global Supply Chains

In recent decades, the structure of manufacturing has changed dramatically. Instead of vertically-integrated firms that obtain most of their inputs from within national borders, lead firms now purchase many inputs from outside suppliers around the world. Most manufacturing production today occurs in layers of specialized, smaller firms that provide components for final assembly and sale by large lead firms or original equipment manufacturers (OEMs). For example, CEA calculations estimate that in the United States in 1988, there were fewer than two employees in firms making automotive parts for every automaker employee. By 2010, parts companies had four employees for every automaker employee (Data Watch 7-2).

Because of this vertical dis-integration, almost all large U.S. manufacturers now depend on their suppliers for well over half their value-added. In most cases, these suppliers are shared with other firms. This arrangement has some advantages -- for example, it may create opportunities for crossfertilization. But shared supply chains also have a weakness in that firms' incentives to invest in their suppliers are reduced. If an OEM helps its supplier develop a new technology, the supplier's other customers -- often the OEM's rivals -- will enjoy these improvements without having contributed. As a result, OEMs have less incentive to make such investments and may be more inclined to shift costs and risks down the supply chain to smaller suppliers. These practices, called "free-riding" by economists, improve the larger firms' financial performance in the short run but may weaken the entire supply chain in the long run.

 

_____________________________________________________________________

 

 

Data Watch 7-2: Measuring Supply Chains

 

 

The potential collapse of General Motors and Chrysler in December 2008 underscored the importance of understanding the operation of supply chains. Because the large auto manufacturers all relied on a common set of suppliers, a failure of any of the major players could have threatened the viability of the entire industry.

Measuring the size of this supply chain presents a statistical challenge. U.S. government statistical agencies assign each worksite in the United States to a single industry on the basis of its primary activity. Two North American Industrial Classification System (NAICS) codes are commonly used for reporting sales and employment in the auto industry -- NAICS 3363 (motor vehicle parts manufacturing) and NAICS 3362 (motor vehicle body manufacturing) -- but these codes do not capture all workplaces involved in the auto supply chain. First, many firms that make auto parts are not classified as serving the automotive market, but rather by the materials or the technology they use, such as "plastics product manufacturing" or "forging and stamping." Similarly, the NAICS codes do not link tooling producers to their customer industry. Second, the worksites that focus on nonproduction activities such as research or management are not categorized with the industry they serve; rather, they are grouped together in "Professional, Scientific, and Technical Services." In addition, contract workers in auto parts plants are assigned to the temporary help industry, rather than to motor vehicle parts production.

Using survey data for late 2010, the Council of Economic Advisers has estimated the number of jobs in the auto supply chain based on a more inclusive definition that includes all of this activity. While the conventional definition of auto parts showed employment of 553, 860 for this period, the CEA estimate was more than 1 million. The high degree of interdependence in the auto industry made the 2008 financial crisis particularly perilous, because contagion from financial troubles at one firm in the industry easily could have spread to others. The CEA's larger estimates of the size of the auto supply sector imply this risk was greater than previously realized.

_____________________________________________________________________

 

 

Prospects for U.S. Manufacturing

The U.S. economy gained nearly 500,000 manufacturing jobs between January 2010 and January 2013, after losing more than 5 million manufacturing jobs in the previous decade (Figure 7-5). These job gains represent not just a cyclical recovery but also potentially the start of a longer-term trend toward the "in-sourcing" of manufacturing. About three-quarters of the increase in U.S. manufacturing shipments since the end of the recession is due to an increase in domestic demand and inventory restocking; the other quarter comes from an increase in exports. Because of the extensive spillover benefits associated with a vibrant manufacturing sector, this recovery has positive implications for long-term growth of the economy as a whole.

 

Figure 7-5

 

Monthly Change in Manufacturing Employment, 1990-2012

 

 

 

 

Note: Shading denotes recession.

Source: Bureau of Labor Statistics, Current Employment Statistics; CEA calculations.

Since early 2012, diminished impetus from several key drivers of growth, as described in Chapter 2, has challenged the growth of U.S. manufacturing. First and most important, export growth has begun to slow, reflecting the slower pace of global growth. Second, after surging during the past few years, demand by domestic business for new capital equipment appears to have slowed. Third, firms finally appear to have replenished their inventories to levels more consistent with demand after heavily depleting stockpiles during the recession.

As noted above, "export-intensive" industries have played a large role in the recovery of manufacturing since the end of the recession. From April 2011 through February 2012, industries that export at least 20 percent of their shipments accounted for 57 percent of manufacturing output and 51 percent of manufacturing employment. During this period, manufacturing production and hiring rose faster in these industries than in others. Since February 2012, however, manufacturing production and hiring has slowed, with nearly two-thirds of the slowdown in output and 90 percent of the slowdown in hiring occurring in export-intensive industries (Figure 7-6).

 

Figure 7-6

 

Employment in Export Intensive and Export Nonintensive

 

Manufacturing Industries, 2011-2012

 

 

 

 

Note: Export-intensive manufacturing industries are three-digit NAICS industries in which exports as a share of total shipments exceeded 19.9 percent, the average for the manufacturing sector as a whole in 2011. Export-intensive industries accounted for about 57 percent of manufacturing output in 2011.

Source: Federal Reserve Board, G.17; CEA calculations.

Other trends, however, suggest a brightening outlook for manufacturing. The continued recovery in the housing sector should lead to greater demand for construction supplies, and the order backlog for commercial aircraft is substantial. In addition, although production of nondurable goods like food and beverage products, plastics and rubber, and chemicals has lagged that of durable goods so far during the recovery, it should accelerate as consumer and business demand becomes more broad-based. Indeed, with capacity utilization now close to its historical average, and weekly work hours elevated above it, even a moderate rise in demand could quickly translate into a pickup in production, hiring, and investment.

Prospects for In-sourcing. Several recent reports have concluded that manufacturers increasingly view the United States as a favorable production location.3 Factors cited for this change include trends in unit labor costs, expansion of domestic energy resources such as wind and natural gas, and greater recognition of the "hidden costs" of moving production abroad.

Over the past decade, U.S. unit labor costs -- the cost of labor required to produce one unit of output -- have grown much more slowly than in other developed nations (Figure 7-7). U.S. hourly compensation in manufacturing has grown somewhat over the past decade, but rapid productivity growth has reduced the cost of producing a unit of manufactured output in the United States. Meanwhile, when measured in U.S. dollars, the cost of manufacturing a unit of output in key trading partners has risen, in some cases substantially.

Several recent studies by management consultants argue that these trends create the potential for a "manufacturing renaissance" in the United States and estimate that the result could be 1 million or more new manufacturing jobs by 2015 (Boston Consulting Group 2012; Inch and Dutta 2012; Simchi-Levi et al. 2011). A key assumption of most of these analyses is that U.S. manufacturing wages continue to be stagnant. Thus, while these trends provide favorable tailwinds for U.S. manufacturing, they will not by themselves lead to sustainable prosperity. In contrast, the "high road" model discussed above also yields favorably low unit labor costs -- but does so by increasing productivity, rather than by reducing wages.

Reassessing the Costs of Moving Production Abroad. Based on their experience during the past decade, American firms now have a greater understanding of the magnitudes of hard-to-measure costs attributable to the risks and complexities of operating far from home. Initially, "many manufacturers who had offshored their operations likely did so without a complete understanding of the 'total costs,' and thus, the total cost of offshoring was considerably higher than initially thought," according to a study of 287 manufacturers conducted by Accenture (Ferreira and Heilala 2011).

Compared with operating in the United States, setting up a supply chain in China and learning to communicate with suppliers requires many long trips and much time of top executives -- time that could be spent on introducing new products or processes at home. There is also greater risk from a long supply chain, because shipping prices and delivery times can vary enormously. In addition, U.S. companies are coming to value more highly the advantages that come from having production, innovation, and design close together. For example, Intel manufactures its most advanced chips in the United States, near where they are designed (Helper, Krueger, and Wial 2012).

To take another example, Sleek Audio, a start-up manufacturer with innovative headphone technology, initially went to China for all of its production. After years of flying several times a year to China, and an incident in which millions of dollars of product had to be scrapped because of poor quality, the owners moved manufacturing to the United States. They began to work with a local manufacturer with experience in making precision products for the military, Dynamic Innovation, located within 10 minutes of Sleek Audio in Florida. In the course of redesigning the product for more automated U.S. production, the firms dramatically improved product quality, replacing hand-welded plastic panels with robot-welded aluminum ones that also significantly improved sound quality (winning an award from the Consumer Electronics Association). The price was higher in the United States, but the improved product features and ability to customize design more than offset this cost (Prasso 2011; Koerner 2011; Hackel 2011).

 

Figure 7-7

 

Change in Manufacturing Unit Labor Costs, 2003-2011

 

 

 

 

Note: Average annual percent change for China represents 2003-2009 data. The BLS does not track manufacturing unit labor costs for China, and many economists have expressed concern over the reliability of recent Chinese economic statistics (Wan 2013).

Source: Bureau of Labor Statistics, International Comparisons of Manufacturing Productivity and Unit Labor Costs; Ceglowski and Golub (2011).

Numerous other collaborations that bring together different forms of expertise are keeping jobs in the United States. Many of these collaborations bring together shopfloor workers with a concrete understanding of plant conditions and engineers with deep technical knowledge. For example, management and members of the machinists' union at an Ashland, Kentucky chemical plant have worked together for two decades to improve both product quality and working conditions (Davidson 2013).

Productivity in Services

The service sector encompasses widely varied activities, ranging from house cleaning to data entry to investment advice. Despite this diversity, some common trends can be observed -- trends similar in many respects to those seen in manufacturing.

As noted, many services are becoming increasingly globalized; as in manufacturing, there is also less vertical integration. In the hotel industry, for example, it is now common for a lead firm such as Marriott to create and advertise an overall brand, while the day-to-day oversight of the workforce is handled by a separate hotel operating company, and staffing may be organized by a temporary-services firm (Weil 2011).

As in manufacturing, there are wide variations in performance across firms within individual service industries. In retail trade, for example, in the late 1980s and 1990s, Wal-Mart's real value-added per worker was more than 40 percent higher than that of other general merchandise retailers (Johnson 2002). Trucks with on-board computers had 13 percent higher capacity utilization than trucks without them (Hubbard 2003). Much of the productivity improvement realized by high-productivity service firms has been associated with investments in information technology (Bosworth and Triplett 2007). Obtaining these performance improvements often involves investing simultaneously in information technology and in complementary organizational changes, as in the valve case described earlier. For example, retailers who can quickly integrate data on consumers' purchases with their systems for replenishing inventory are more productive than those who cannot (Wailgum 2007; Zhu 2004).

Finally, although the use of IT and other innovations in services has led to large productivity gains, the benefits of these gains have not been evenly shared. Although IT adoption has led to increased pay and autonomy for workers who interpret information, such as financial advisers, it has led to reduced employment and pay for jobs that can be described in rules that a computer can follow -- jobs such as routine claims processing that require moderate skills and that once paid middle-class wages (Levy and Murnane 2005).

 

Creating An Economy Built To Last

 

 

A hallmark of the Administration's policies to reverse the middle-class jobs deficit is leveraging positive spillovers to raise labor demand and productivity, and to create new industries and products, while equipping American workers with the tools they need to succeed in a modern economy. The President's blueprint for creating an economy built to last aims to promote synergies within local areas and among companies that add to growth in investment and good jobs.

The following discussion uses manufacturing as an example to illustrate these policies, but their usefulness is not limited to manufacturing. For example, the U.S. Department of Agriculture has for decades helped an industry made up largely of small producers remain internationally competitive, by providing an integrated set of services with large spillover benefits to farmers and rural communities: land-grant universities for research and training; cooperative extension agents that help to diffuse practices shown by this research to be effective; access to capital (in part through the department's own credit agencies); and programs that help farmers set up cooperatives to achieve economies of scale in purchasing and marketing.

Strengthening Competitiveness: The Manufacturing Example

A competitive U.S. manufacturing sector is a key to the Administration's vision of a U.S. economy that is innovative and competitive and that provides good jobs. Rising costs abroad coupled with sustained domestic productivity gains make the United States an increasingly attractive location for investment. But good policy is also needed to fully capture the benefits of this underlying trend and encourage investment in middle-class jobs in the United States. The view that a strong "industrial commons" is important for competitiveness, but also subject to market failure, suggests that government policy should promote the creation of, and access to, these shared resources. Thus, the Administration's policies work to promote the type of manufacturing that builds innovative capability and raises living standards.

The Administration's proposals help in several ways to strengthen these types of manufacturing. First, general policies to improve productivity and wages (such as the policies to support education, health care, and a clean environment discussed in other chapters of this Report) are essential to building long-term economic competitiveness.

Second, the Administration has made trade policy a priority. These policies have particular importance in manufacturing. Some argue that much of the steep manufacturing employment decline in the early 2000s was caused by a sharp rise in imports from emerging nations, especially China (Autor, Dorn, and Hanson, forthcoming; Pierce and Schott 2012). In some cases, producers exporting from these nations have benefited from policies that gave them an unfair advantage relative to manufacturers in the United States. In response to these policies, the Obama Administration, in addition to pursuing the broader trade policies discussed earlier in the chapter, launched an Interagency Trade Enforcement Center charged with protecting American companies from unfair trade competition.

Third, the Administration has championed tax credits to reduce the costs of socially beneficial actions (such as R&D). These policies aim to reward firms for providing lasting social benefits. In contrast, a "smoke stack-chasing" approach tries to lure individual firms to a particular location using tax abatements and other incentives. In general, these subsidies are awarded to firms for undertaking activity that would have occurred anyway; the subsidy simply influences the location of the activity. Thus these individual incentives generally do not lead to net investment (Chirinko and Wilson 2008). State and local governments provide more than $80 billion a year on such incentives, including $25 billion to manufacturers (Story 2012).

Finally, the Administration has championed sector-specific policies that use the convening power of government to promote coordination and investment. Productive ecosystems that promote innovation and good jobs require strong partnerships among industry stakeholders, including business, government, unions, trade associations, and universities. A sectoral approach to encouraging the development of such ecosystems (in manufacturing and in other industries) can help to build simultaneously both the demand for and the supply of shared assets, such as trained workers, competent customers engaged in innovation, suppliers of components, and standards for equipment design. The supply-chain analysis above suggests that policy may be needed to address two key issues: free-rider problems that lead to underinvestment and information barriers that hinder coordination among stakeholders in a supply chain.

The Administration's flagship manufacturing initiative is a $1 billion National Network for Manufacturing Innovation fund that will create up to 15 institutes to help ensure that new technology bridges the gaps from invention to product development to manufacturing at scale. Leveraging the assets of a particular region, each institute will bring together universities, companies, and government to co-invest in the development of new technologies that spill over to provide general benefits to a region's manufacturing base, rather than just a single company. Institutes will build workforce skills and business capabilities in large and small companies. A pilot center, the National Additive Manufacturing Innovation Institute, opened last year in Youngstown, Ohio. The universities and firms participating in the institute matched the initial $30 million in federal funding with $40 million of their own.

As discussed, many firms have been slow to adopt even well-known improved practices and thus lack the capability to participate in such innovative endeavors. To help these firms upgrade their operations, the Administration has proposed increased funding for the Manufacturing Extension Partnership program, which provides a range of business services to small manufacturers.

The Administration also has proposed initiatives to replenish the technology pipeline, by increasing funding for advanced manufacturing R&D. Despite tightening budgets, the Administration has emphasized the importance of funding industrially relevant, advanced manufacturing technologies such as advanced materials, smart manufacturing, and robotics.

 

Conclusion

 

 

The United States economy benefits from being closely linked with other nations through trade, investment, and financial flows. The Nation's economic recovery and long-run growth prospects depend in large part on U.S. businesses being able to compete in an open, fair and growing world economy. The Federal government is determined to do its part to facilitate this outcome. Sound macroeconomic policies that aim at strong, balanced, and sustainable growth are but one element. Another is a trade policy aimed at the maintenance of open, competitive markets, compliance with WTO obligations, and leadership in the multilateral trading system. The United States pursues a policy that supports jobs through trade, enforces trade rules, bolsters international trade relationships, and partners with developing countries to fight poverty and expand opportunities.

Creating and maintaining a competitive industry or region requires continuous investment by firms, workers, and communities. These investments are often more productive if others are also investing. In a number of cases (especially in manufacturing), investments in these productive ecosystems were allowed to lapse, affecting both competitiveness and job quality. Administration policy has helped to reverse these lapses, leading to domestic economic growth and increased exports.

Many of the policies discussed in connection with manufacturing also benefit consumers and workers in the services sector, such as policies that promote access to education. In addition, sector-specific policies for services are discussed in other chapters of this Report. For example, as discussed in Chapter 5, the administration has convened the Partnership for Patients, which brings together hospitals and clinics in a community to work to reduce errors in patient care.

While much remains to be done, these policies have laid a foundation for competitiveness and prosperity for both the United States and its trading partners.

 

FOOTNOTES TO CHAPTER 7

 

 

1 Houseman et al. (2011) concluded that the decline in input prices associated with shifts to lower-cost producers may not be fully captured by statistical agencies, and as a result the data may suggest that manufacturers are producing more goods with fewer inputs, when in fact the real value of those inputs has simply been understated. After attempting to correct for this so-called "offshoring bias," the authors concluded that average annual manufacturing productivity growth would be between 6 percent and 14 percent lower, and value-added growth would be 7 percent to 18 percent lower than official estimates between 1997 and 2007.

2 The U.S. auto industry could have ended up on this path, but as a result of the Administration's rescue of General Motors and Chrysler, and investments in innovation, the industry is growing and healthy.

3 Academic literature often refers to this phenomenon of work returning to the United States from abroad as "on-shoring."

 

END OF FOOTNOTES TO CHAPTER 7

 

 

CHAPTER 8

 

 

CHALLENGES AND OPPORTUNITIES IN U.S. AGRICULTURE

 

 

U.S. agriculture fared better during the Great Recession than many other sectors and remains a bright spot in the U.S. economy. Despite an extensive and severe drought in 2012, net farm income is forecast to total $112.8 billion, only 4.3 percent below the previous year's record of $117.9 billion (USDA 2013a). Strong demand for agricultural products and below-average crop yields pushed up crops prices, and along with significant crop insurance indemnity payments, helped to make the 2012 income figure the second-highest since 1974 after adjusting for inflation. (See Economics Application Box 8-1 on the 2012 drought).

The strength of the U.S. agricultural sector is due in part to the demand for American agricultural exports. The value of agricultural exports has steadily risen and now accounts for a projected 31 percent of gross farm cash income. Exports reached a near record level of $135.8 billion in 2012 and are projected to reach $142 billion in 2013 (USDA 2012a).

Increasing demand from abroad created by rising incomes and a growing middle class will present opportunities for U.S. agriculture. The world population is expected to reach more than 9.2 billion by 2050, with growth coming primarily in developing countries, most of which are net importers of food products. The convergence of population growth and rapid urbanization, especially in developing regions of the world, will likely result in growing demand for food as well as changing dietary patterns.

Trade in agricultural commodities is a global endeavor, and the U.S. agricultural sector is subject to significant price volatility at the commodity level. Because of its high degree of integration with the international marketplace, U.S. agriculture is vulnerable to price volatility induced by other countries' agricultural policies -- import and export restrictions -- and growing conditions. Further, while the effects of climate change on livestock and crop production systems are expected to be mixed in the next 25 years, over the long term, continued changes are expected to have generally detrimental effects on most crops and livestock.

 

_____________________________________________________________________

 

 

Economics Application Box 8-1: The 2012 Drought

 

 

A drought in the summer of 2012 across much of the United States caused significant crop losses and some livestock liquidation. About 80 percent of agricultural land experienced low rainfall and high temperatures, making the 2012 drought the most extensive since 1956. A striking aspect of the 2012 drought was the rapid increase in severity in early July. While the drought eased somewhat during early September, conditions during the June to August period largely determine production for most crops. By mid-August, crops worth 50 percent of the total value of all crops were exposed to drought.

Crop losses were most substantial for corn. In the spring of 2012, the U.S. Department of Agriculture estimated an expected corn yield of 166.0 bushels an acre. By October 2012, those estimates had dropped to 122.3 bushels an acre -- a reduction of 27 percent. Soybeans, somewhat more drought tolerant, experienced a 14 percent yield reduction (from 43.9 to 37.8 bushels an acre). The livestock industry, still recovering from the 2011 drought in the Southern Plains, was hit especially hard. As of late October of 2012, 54 percent of pastures and ranges in the United States were rated poor to very poor. Beef production in 2012 was projected to decline 2.3 percent from 2011 levels and to fall another 4.2 percent in 2013. Broiler and pork production were also expected to experience declines in 2013, while milk production is expected to remain stable.

The effects of the drought on food prices were reflected first in the livestock sector, with increases in the price of meat and dairy products in late 2012 and projected into 2013. The full effects of the increase in corn and other commodity prices will likely take as long as a year to be fully captured in higher retail food prices.

Despite the drought, average income for farm businesses remained steady in 2012 at $86,200, reflecting the increased prices for corn and soybeans as well as increases in crop insurance indemnities, which as of February 2013 had already paid out $12.9 billion for 2012 losses (USDA 2013). Income increases on crop farms should more than offset livestock farmers' higher feed expenses and a decline in sales of wholesale milk. Additionally, the longstanding environment of strong commodity prices and low interest rates means that farm debt-to-equity ratios are approaching historic lows, which has reduced the financial vulnerability of farms to the production shocks.

_____________________________________________________________________

 

 

The Agricultural Sector in 2012

 

 

In the 1920s, farm households accounted for more than 25 percent of the U.S. workforce and generated approximately 8 percent of gross domestic product (GDP). Today they account for only 1.6 percent of the work force and generate approximately 1 percent of GDP. Over the same period, the rural share of the population has fallen far less, from 49 percent to 19 percent, suggesting that rural areas are less dependent on farming's contribution to the rural economy (Table 8-1). The agricultural sector is still vital to our country, but because of growth in other sectors of the economy and rapid gains in agricultural productivity that have lowered the relative prices of agricultural products, it has become a smaller share of the U.S. economy.

The structure of farming continues to move toward fewer, but larger commercial operations producing the bulk of farm commodities, complemented by a growing number of smaller farms earning most of their income from off-farm sources. Small family farms -- those with annual sales less than $250,000 -- make up 90 percent of U.S. farms. They also hold about 62 percent of all farm assets, including 49 percent of the land owned by farms. However, commercial farms, which make up the other 10 percent of the sector, account for 83 percent of the value of U.S. production (Table 8-2).

While most of these large farms have a positive profit margin, average profit margins for small farms are negative because of high operating costs, low sales, and lower productivity (Table 8-3). Farms are predominantly organized as sole proprietorships (86.5 percent), followed by partnerships (7.9 percent) and corporations (4.4 percent).1

Fifty years ago, average household income for the farm population was approximately half that of the general population. Today, however, farm households tend to be better off than other American households; in 2011, median income for farm households was about 13 percent higher than the U.S. median household income (Figure 8-1). The difference in income between farm households and the nonfarm households is due in part to the broad Department of Agriculture (USDA) definition of what constitutes a farm, which includes farms where the principal operator is retired or has a main occupation other than farming ("residence farms"). Households operating rural residence farms earn more than the U.S. median household income even though their net cash income from farming is negative. Households operating intermediate farms (farms where the principal operator is not retired and reports farming as his or her main occupation) have on average positive net cash income from their farming operations, but most household income comes from sources other than farming. The sources of income for farm households are increasingly diversified, which means that many of them are less vulnerable to the fluctuations of farm income. In 2011, households operating commercial farms had median household incomes two and a half times the overall U.S. median household income, with most of their income from farming.

                                   Table 8-1

 

               90 Years of Structural Change in U.S. Agriculture

 

 ______________________________________________________________________________

 

 

 Year                                      1920    1950    1980    2000    2010

 

 ______________________________________________________________________________

 

 

 Number of farms (thousands)              6,518   5,648   2,440   2,167   2,192

 

 Average farm size (acres)                  147     213     426     436     419

 

 Rural share of population (percent)       48.8    36.0    26.3    21.0    19.3

 

 Farm share of workforce (percent)         25.4    12.1     3.4     1.8     1.6

 

 Farm share of GDP (percent)                7.7     6.8     2.2     1.0     0.9

 

 ______________________________________________________________________________

 

 

 Note: 1920 data for farm share of GDP not available. Value reported is for

 

 1930, as calculated by the Department of Agriculture, Economic Research

 

 Service.

 

 

 Source: Department of Agriculture, National Agricultural Statistics Service,

 

 Farms, Land in Farms, and Livestock Operations; Bureau of Economic Analysis,

 

 GDP by Industry; Sobek (2006); CEA calculations.

 

 

                                   Table 8-2

 

                                   Farm Types

 

 ______________________________________________________________________________

 

 

 Small family        Rural-residence    Retirement farms. Small farms whose

 

 farms (gross        family farms:      operators report they are retired.

 

 sales less than

 

 $250,000)                              Residential/lifestyle farms. Small

 

                                        farms whose operators report a major

 

                                        occupation other than farming.

 

 

                     Intermediate       Farming-occupation    Low-sales farms.

 

                     family farms:      farms. Small family   Gross sales less

 

                                        farms whose           than $100,000.

 

                                        operators report

 

                                        farming as their      High-sales farms.

 

                                        major occupation.     Gross sales

 

                                                              between $100,000

 

                                                              and $249,999.

 

 

 Large-scale         Commercial         Large family farms. Gross sales between

 

 family farms        family farms:      $250,000 and $499,999.

 

 (gross sales of

 

 $250,000 or                            Very large family farms. Gross sales of

 

 more)                                  $500,000 or more

 

 

 Nonfamily farms   Any farm not class as a family farm, that is, any farm for

 

                   which the majority of the farm business is not owned by

 

                   individuals related by blood, marriage, or adoption.

 

 ______________________________________________________________________________

 

 

 Note: The National Commission on Small Farms selected $250,000 in gross sales

 

 as the cutoff between small and large-scale farms.

 

 

 Source: Department of Agriculture, Economic Research Service, Farm Household

 

 Well-being

 

 

By 2000, 93 percent of farm households had income from off-farm sources, including off-farm wages, salaries, business income, investments, and Social Security. Off-farm work has played a key role in raising farm household income. In 2011, only 46 percent of principal operators of farms reported that farming was their main occupation. While farm household incomes have become more diversified, farm operations have become increasingly specialized: In 1900, a farm produced an average of about five commodities; by 2000, the average had fallen to just over one. This change reflects not only the production and marketing efficiencies gained by concentration on fewer commodities, but also the effects of farm price and income policies that have reduced the risk of depending on returns from only one crop or just a few crops.

                                   Table 8-3

 

               Farm Income and Farm Operator Household Income by

 

                       USDA Farm Size Classification, 2010

 

 ______________________________________________________________________________

 

 

                                      Rural       Inter-    Commer-

 

                                      residence   mediate   cial

 

                                      farms       farms     farms     All farms

 

 ______________________________________________________________________________

 

 

 Farm operator households             1,311,117   617,876   214,070   2,143,063

 

 

 Average gross cash farm income

 

 (dollars)                               14,974    52,790   840,315     108,320

 

 

     Average gross cash farm income,

 

     by source (%)

 

 

     Crop, livestock, and other

 

     farm-related income                   91.6      94.6      97.0        96.2

 

 

     Government payments                    8.4       5.4       3.0         3.8

 

 

     Average per farm operator

 

     household (dollars)

 

 

     Total cash farm expenses            17,216    46,142   613,486      85,117

 

 

     Net cash farm income                -2,242     6,648   226,829      23,203

 

 

 Farm operator household income          83,738    51,054   185,098      84,440

 

 ______________________________________________________________________________

 

 

 Source: Department of Agriculture, Agricultural Resource Management Survey.

 

Figure 8-1

 

Median Income for Farm Households by Farm Type

 

and Income Type, 2010-2012

 

 

 

 

Note: 2012 forecasted values included for "all" farms. Values for farm-type breakouts are 2010-2011 averages.

Source: Department of Agriculture, Economic Research Service, Agricultural Resource Management Survey.

The average age of U.S. farmers and ranchers has been increasing over time. In 1978, 16.4 percent of principal farm operators were over age 65. By 2007, 30 percent of all farms were operated by producers over 65. In comparison, only 8 percent of self-employed workers in nonagricultural industries in 2007 were that old (Hoppe, McDonald, and Korb 2010). One reason the farming sector is relatively older is that farmers are living longer and often reside on their farms. Many established farmers never retire. Additionally, one-third of beginning farmers are over age 55, indicating that many farmers move into agriculture only after retiring from a different career. More than 20 percent of farm operators report that they are retired. Another 32 percent of all farms are operated by farmers aged 55 to 64 years. Farmers aged 55 and older account for more than half of the total value of production. Farmers under 35 contribute only 6 percent of the total value of production (Figure 8-2). This demographic transition has implications for the future of the U.S. agricultural sector.

Barriers to Entry and Succession Planning in U.S. Agriculture

Starting a farm operation can be an expensive endeavor. Startup requires access to land and capital equipment, as well as the operator's time. In 2011, the average farm operated 415 acres and held assets worth just under $1 million, accounted for mostly by land and structures. Even for farm operators under age 35, asset values averaged $811,500, highlighting the extent to which startup costs represent a hurdle for new entrants (USDA 2011).

 

Figure 8-2

 

Distribution of Farms by Age of Principal Operator, 2010

 

 

 

 

Source: USDA (2010).

The Federal Government recognizes the need to support and develop new farm operators. Through the Farm Service Agency, the USDA helps beginning farmers who are unable to obtain financing from commercial lenders by targeting a portion of its direct and guaranteed loan funds to farmers and ranchers who have not operated a farm or ranch for more than 10 years and do not own a farm or ranch greater than 30 percent of the median size farm in the county, as determined by the most current Census for Agriculture.

After spending a lifetime accumulating wealth in agricultural assets, farmers often wish to pass the farm business to their heirs. Special provisions in the Federal estate tax, such as a rule that allows farm assets of an estate to be valued at their farm-use value rather than a higher market value, facilitate the transfer of farm estates from one generation to the next. (See Economics Application Box 8-2 on the Federal estate tax.)

As farmers begin to consider transitioning from active operation to retirement, questions about what will happen to their land remain. In some cases, the land is passed to an heir who continues the family business; in other cases, it is sold at auction perhaps to another farmer, but sometimes for other purposes such as residential or commercial development. As much as 2 million acres of America's farms, ranches, forests, wildlife habitat, and other open spaces are lost to fragmentation and development each year, with significant implications for water resources, outdoor recreation, wildlife, rural economies, and other resources.

Making a donation of a qualified conservation easement is one way for farmers and ranchers to maintain their current operation and conserve the amenities and natural assets of rural America for future generations. Such a donation allows the farmer to create a separate, special right on the designated land stipulating that it will be used only for certain purposes, such as agricultural production. The farmer or rancher can continue to use the land for production, knowing that in the future, it will continue to be used in the same manner. In return for placing the land into a qualified conservation easement, the landowner may deduct the value of the easement from his or her income for tax purposes.

Starting in 2006, a new law encouraged additional conservation easements by significantly expanding the tax benefits landowners may receive when they donate easements to qualified organizations, such as a land trust or public agency. More specifically, this enhanced incentive raises the maximum annual deduction a donor can take for the donation of a conservation easement and extends the period to claim the deduction from 5 to 15 years, from the year of the donation. In 2007 and 2008, a survey found that this incentive helped America's 1,700 local land trusts increase the pace of conservation by about 250,000 acres each year -- a 36 percent increase over previous years.

 

_____________________________________________________________________

 

 

Economics Application Box 8-2: The Federal Estate

 

Tax and Farm Business Succession Planning

 

 

An estate -- in general, a collection of assets passed down from a decedent upon his or her death -- is one vehicle available to farmers to transfer agricultural property from one generation to the next. Under current law, only those returns that have a taxable estate above the exempt amount after deductions for expenses, debts, and bequests to a surviving spouse or charity are subject to the tax.

While the estate tax has been amended many times, it has never directly affected a large percentage of taxpayers, including farmers. In fact, in no year since 1916 has the percentage of adult deaths generating a taxable estate surpassed 8 percent (Jacobson, Raub, Johnson 2012). Several targeted provisions have reduced the potential impact of estate taxes on the transfer of a farm or other small business to the next generation (Durst 2009). These provisions include:

  • A special provision that allows farm real estate to be valued at farm-use value rather than at its fair-market value, which is often higher because it reflects the value of the land for housing or commercial development.

  • An installment payment provision that allows an estate to elect to pay the estate tax attributable to the decedent's interest in a closely held business in up to 10 equal, annual installments. The provision covers a decedent whose interest in the closely held business exceeds 35 percent of the adjusted gross estate, which describes a typical farm estate.

  • A provision aimed at encouraging farmers and other landowners to donate an easement or other restriction on development that has provided additional estate tax relief.

 

The box figure illustrates the relatively low and declining burden the Federal estate tax has placed on farm estates. In 2001, 16.9 percent of farm estates were required to file a tax return and less than 4 percent had an estate tax liability. By 2011, as a result of the generous tax-exemption amount and low tax rate, those figures had declined to 1.28 percent and 0.6 percent, respectively. Total tax liability in 2011 was also lower than it had been the prior 10 years, despite record high agricultural land value, which represents a large majority of the assets in a farm estate. The American Taxpayer Relief Act of 2012 made permanent a maximum estate tax rate of 40 percent; it also set the exclusion amount at $5 million and allowed for inflation adjustment, continuing the tax relief to most farm estates.
The Share of Farm Estates Required to File a Return and Pay

 

Federal Estate Taxes, 2001-2013

 

 

 

 

Note: 2012 and 2013 are forecasts based on 2011 data.

Source: Department of Agriculture, Economic Research Service, Federal Tax Issues.

 

_____________________________________________________________________

 

 

The enhanced incentive provisions expired in 2009 but were renewed through December 31, 2013, by the American Taxpayer Relief Act of 2012. Making permanent the expanded tax incentives beyond 2013 would further bolster land conservation and job creation, especially on working lands, helping to keep landowners on their property and achieve a broad range of conservation outcomes.

A Mature Domestic Food Market

Americans benefit from a highly efficient agricultural sector and have higher standards of living now than at any point in the past. Of concern to producers in the U.S. food market is how much of their disposable income American consumers will spend on food in the future as well as what food products they will demand. Engel's law, which postulates that rising incomes lead to an increase in the nominal amount of income spent on food while the proportion of income spent on food falls, still holds in the United States. The share of American household budgets devoted to food fell from 15 percent in 1984 to 13 percent in 2009. However, a rise in per capita income since 1984 has counteracted the decrease in the share of household budgets devoted to food, as real per capita spending on food has increased from $3,592 in 1985 to $4,229 in 2011 (in 2011 dollars) (Figure 8-3).

As their real incomes rise, most Americans do not need larger quantities of food to satisfy their nutritional needs. They are, however, changing their food choices to include higher value foods, such as better cuts of meat, a variety of fruits and vegetables, and organic and specialty food items. A mature U.S. food market will require the agricultural sector to focus on innovations that produce value-added products for the domestic market in order to satisfy rising U.S. consumer demand for specialty goods.

New Markets in Agriculture

Organic farming has been one of the fastest-growing sectors in agriculture, and double-digit growth in sales of organic foods has provided market incentives for the U.S. agricultural sector across a broad range of products. The retail value of the organic industry grew to $31.4 billion a year in 2011, up from $21.1 billion in 2008 and $3.6 billion in 1997 (Dimitri and Oberholtzer 2009; USDA 2012a). Between 2002 and 2008, acres under organic production grew by an average of 16.5 percent a year. Organic sales currently account for more than 3 percent of total U.S. food sales, and provide a larger share in categories such as produce and dairy. Growth has been particularly evident in the organic dairy sector, which accounted for 16 percent of organic sales in 2008. The number of organic milk cows on U.S. farms increased by annual average of 26 percent between 2000 and 2008. As demand for organic food has increased, the U.S. agricultural sector has taken steps to meet it; the number of operations certified as organic grew by 1,109 -- or more than 6 percent -- between 2009 and 2011.

 

Figure 8-3

 

U.S. Real Per Capita Food Expenditures, 1985-2011

 

 

 

 

Source: USDA (2013c).

The USDA has taken steps both to promote and to regulate the growing organic food industry by establishing the National Organic Program (NOP), whose mission is to ensure the integrity of USDA-certified organic products in the United States and throughout the world. The NOP accredits nearly 50 domestic organic certifying agents who are authorized to issue an organic certificate to operations that comply with the USDA organic regulations. Between 2009 and 2011, the USDA has also supported its own scientists and university researchers with more than $117 million in funding focused on improving the productivity and success of organic agriculture. For example, USDA research on weed management for organic vegetable production has produced techniques and tools that can help control 70 percent of weeds at 15 percent of the previous cost for weed control. Spreading the USDA organic research findings to people in the field is critical, and the "eOrganic" electronic extension service funded by the USDA has become an essential tool for compiling and disseminating knowledge about organic production.

The increasing demand for organic foods has been accompanied by a growing "local" movement. The markets for organic and local food regularly overlap: organic farmers are much more likely than conventional farmers to sell their products locally (Kremen, Greene, and Hanson 2004), with about a quarter of all organic sales in 2004 made within an hour's drive of the farm (Greene et al. 2009). Similarly, 82 percent of all farmers' markets had at least one organic vendor. Sales of locally produced foods make up a small but growing part of U.S. agricultural sales, particularly for small farms. The USDA estimates that the farm-level value of local food sales totaled nearly $5 billion in 2008, or 1.6 percent of the U.S. market for agricultural products. An estimated 107,000 farms, or 5 percent of all U.S. farms, are engaged in local food systems, with small farms (those with less than $50,000 in gross annual sales) accounting for 81 percent of all farms reporting local food sales in 2008 (Low and Vogel 2011). Examples of the types of farming businesses that are engaged in local foods are direct-to-consumer marketing, farmers' markets, farm-to-school programs, community-supported agriculture, community gardens, school gardens, food hubs and market aggregators, kitchen incubators, and mobile slaughter units, among a myriad of other types of operations.

Local goods are also good for the economy. A USDA study found that produce growers selling into local and regional markets generated 13 full-time operator jobs for every $1 million in revenue earned, for a total of 61,000 jobs in 2008 (Low and Vogel 2011). Farmers that did not sell into these markets generated only three full-time operator jobs per $1 million revenue. To foster exposure to and growth in local foods, the USDA has created the Know Your Farmer, Know Your Food management and communications initiative, which helps stakeholders navigate USDA resources and efforts related to local and regional food systems. Future growth of the agricultural economy can be enhanced by growth in those sectors.

Today's Farm Structure

The current strength of the farm economy is also built on the restructuring that has taken place over time, making the most productive farms larger and more efficient. Agricultural innovations have been labor-saving, greatly reducing the amount of labor needed for specific farm tasks. Labor-saving innovations also affect farm structure, because they allow a farmer to manage more cropland or raise more livestock. In addition, innovations have led farms to contract out for specialized services. Farmers now rely extensively on private consultants, government extension agents, lenders, and supplier representatives for technical advice.

Some of these managerial innovations rely on further developments in the design of organizations and contractual relationships to effectively manage a series of complicated commercial relationships. The share of production under marketing or production contracts increased from 28 percent in 1991 to more than 38 percent by 2010. Corn, soybean, and wheat producers, for example, place about half of their production under forward contracts; many of them also invest in storage facilities to store products when anticipating future price increases, and nearly 30 percent of them use futures markets to hedge the risks from their cash sales (MacDonald and Korb 2011). Similarly, farmers have realized more intensive use of capital by leasing equipment from specialized suppliers, and they often engage additional specialized expertise and capital equipment by contracting with custom service providers for farm tasks such as spraying, field preparation, or harvesting.

Livestock operations have undergone dramatic changes in the last 30 years. Farmers now use information technology to adjust feed mixes and climate controls automatically to meet the precise needs of animals in confined feeding operations. Integrated hog operations, for example, sharply reduced the amount of feed, capital, and labor needed to produce hogs as new technologies and organizational forms swept the industry. As a result, live hog prices were nearly a third lower than they would have been without the productivity growth that occurred between 1992 and 2004, and retail pork prices were 9 percent lower (Key and McBride 2007).

The market, scientific, and technological opportunities beckoning American farmers are as great as they have ever been. Over the past three decades, a series of revolutions in the understanding of the science of living organisms and exponential growth in the processing power of information technology have raised the potential for productivity growth in American agriculture that could outstrip even the impressive record of growth it logged over the course of the 20th century. But as America's own history shows, neither revolutions in science and technology nor market signals will find practical application on America's farms and ranches without careful, effective, smart investment by public science institutions. Even America's larger farms are too small to support sophisticated basic research, and many of the most significant improvements that farms can be expected to make as they apply the fruits of this research are not patentable. The partnership between public science and the private farm must continue if these possibilities are to be realized, particularly in the face of climate change. The Obama Administration believes America's agricultural future is worth investing in and has committed to increases in scientific research that could benefit the agricultural sector for decades to come.

Investing in Agricultural Productivity

In 1950, the average dairy cow produced about 5,300 pounds of milk. Today the average cow produces about 22,000 pounds of milk, thanks to improvements in cow genetics, feed formula, and management practices. Over that time period, the number of dairy cows in America has fallen by more than half, yet U.S. milk production has nearly doubled.

Persistent gains in efficiency have defined American agriculture. Public and private investments in agricultural research and development (R&D) have helped U.S. farmers find ways to grow more with less. While growth in U.S. industrial output over the past 50 years has come primarily from increases in capital and labor, agricultural output growth mainly has come from substantial increases in total factor productivity. American farmers have continually found ways to grow more with less; new seeds are less susceptible to disease and produce higher yields, new tractors are guided by satellites and spread fertilizer optimally across the field, and animals' diets are optimally calibrated to grow larger animals with less feed. These innovations have caused improvements in farm productivity to outpace improvements in non-farm productivity over the past 25 years.

From 1948 to 2009, farm productivity nearly tripled, growing at a rate of 1.6 percent a year. In the early part of that period, increased productivity, measured as output per unit of combined inputs, combined with increased use of equipment and chemical inputs to drive the growth in agricultural output. Between 1980 and 2009, equipment stocks fell along with continued declines in labor and land inputs; chemical use continued to rise, but at a much slower rate. Despite reduced input use, agricultural output grew by 1.5 percent a year in 1980-2009, with increasing productivity accounting for almost all of the growth (Figure 8-4).

Research and Development Drives Productivity Growth

Increasing productivity on U.S. farms stems largely from the rapid and widespread adoption of a continuing series of biological, chemical, mechanical, and organizational advances. Formal research programs are carried out in universities, government labs, and private firms. Agricultural innovations building on that research are developed by input suppliers in the private sector or by public institutions.

Public support of agricultural R&D generates high payoffs for farmers and the public. Fuglie and Heisey (2007) found that every dollar invested in public agricultural research generates 10 times that amount in benefits to society. Another recent study (Alston et al. 2009) found an even higher return on Federal and State agricultural research expenditures, with estimated benefits of $20 for every $1 invested. Other academic studies reached broadly similar conclusions.

 

Figure 8-4

 

Farm and Nonfarm Productivity, 1948-2009

 

 

 

 

Source: Department of Agriculture, Economic Research Service, Agricultural Productivity in the U.S.; Bureau of Labor Statistics, Major Sector Productivity and Costs.

Total R&D spending in agriculture reached $11 billion in 2007, or nearly 8 percent of the value added in the sector. Annual public agricultural R&D spending, through universities as well as government laboratories, rose 77 percent between 1970 and 2002 (after accounting for inflation). Public expenditures have not kept up with R&D cost inflation since, however, falling by 13 percent in real terms between 2002 and 2009. Private R&D expenditures are sensitive to the business cycle but doubled in inflation-adjusted terms between 1970 and 2007 (Figure 8-5).

Spillovers are ubiquitous in R&D in general and in agricultural R&D in particular. Ideas that are discovered by one institution may have an impact on the research productivity of another. Some of the important, and overlapping, categories of spillovers in agricultural R&D are geographical, for example, from one state or one country to another; institutional, from the private sector to the public, or vice versa, across competing institutions such as universities, or from one industry to another; and across scientific areas, from "pretechnology" sciences to agricultural sciences, for example, or from biomedical science to agricultural science.

 

Figure 8-5

 

Public and Private U.S. Agricultural R&D Spending, 1971-2009

 

 

 

 

Note: All R&D spending; in 2006 dollars using ERS R&D deflator.

Source: Department of Agriculture, Economic Research Service, Agricultural Research Funding in the Public and Private Sectors.

Economists have studied spillovers related to agriculture R&D (see, for example, Evenson 1988 or Griliches 1998). One of the more commonly addressed spillover areas for agricultural research is the geographical spillover from one state to another. Pardey and Alston (2011) estimated that roughly one-third of the benefits of state-level agricultural R&D are generated through spillovers to states other than those in which the research was conducted.

Conservation Practices and the Environment

The overuse of nitrogen fertilizer has widely recognized detrimental effects on the environment, especially downstream of treated fields. Particularly in the Gulf of Mexico, excess nitrogen is associated with low oxygen environments, or "dead zones." Corn is the most widely planted crop in the United States and the largest user of nitrogen fertilizer. In 2010, more than 97 percent of planted corn acres received nitrogen fertilizer (commercial and manure), an increase of 18 percent from 2001. At the same time, farmers have improved their use of nitrogen -- corn acres where nitrogen was applied in excess of agronomically necessary rates declined from 41 percent to 31 percent (Ribaudo et al. 2012).

Adoption of other conservation management practices also has the potential to reduce environmentally harmful impacts of agricultural production. Since 2000, corn, cotton, soybean, and wheat acreage under conservation tillage (mulch, ridge, and no till) has increased; conservation tillage may reduce soil erosion and water pollution but increase pest management costs (Osteen, Gottlieb, and Vasavada 2012).

The Federal Government plays an important role in encouraging conservation adoption by offering numerous conservation programs to assist private landowners in conserving the soil, water, wildlife, and other natural resources found on their property. These programs give landowners incentives to consider natural resources in their agricultural practices. Two relatively new programs, Working Lands for Wildlife and the National Water Quality Initiative, help producers stay in operation by providing financial and technical support, as well as regulatory certainty, if the landowner takes steps to restore and conserve wildlife habitat or water quality on their property.

The USDA's National Water Quality Initiative works with farmers, ranchers, and forest landowners in priority watersheds to help improve water quality and aquatic habitats in impaired streams. As of 2012, approximately $34 million had been obligated for improvements on about 161,000 acres. Another $21 million was obligated through more than 800 contracts with private landowners for Working Lands for Wildlife, also administered by the Natural Resources Conservation Service and Fish and Wildlife Service. The contracts will restore wildlife habitat on more than 310,000 acres of range, pasture, and forest lands across the country.

Natural Capital, Conservation, and the Outdoor Economy

Agriculture, as a land use, affects a large amount of natural capital (land, water, air, and genetic resources on farms and ranches) in the United States. Based on 2002 data, private farms accounted for 41 percent of all U.S. land, including 434 million acres of cropland, 395 million acres of pasture and range, and 76 million acres of forest and woodland (Ribaudo et al. 2008). This capital can provide a host of environmental services, including water quality, air quality, flood control, wildlife, and carbon sequestration. These services can be consumed directly or combined by consumers with other goods to create final goods, such as sightseeing, fishing, wildlife viewing, or hunting, all of which support the outdoor economy.

Multisector efforts under the President's America's Great Outdoors initiative have bolstered outdoor recreation, conservation, and restoration of America's natural resources on public lands, as well as on working farms, ranches, and forests. In a 2012 study of 11 western states, economists found that national parks, monuments, and other protected Federal public lands promote more rapid job growth and are correlated with higher levels of per capita income in surrounding areas. Companies use the high quality of life provided by localities with access to healthy and protected lands and waters as a recruiting tool to attract new and talented employees who value natural beauty and outdoor recreational opportunities.

Outdoor recreation is an often overlooked but significant economic driver in the United States, with one industry study estimating that it provided 6.1 million jobs, spurred $646 billion in spending, much of it on travel and tourism, and raised $80 billion in Federal, State, and local tax revenue in 2010 (Outdoor Industry Association 2012). National parks and Federal lands and waters located across the entire United States, including in many rural areas, play a significant role in supporting the travel and tourism industry. Each year, millions of international tourists visit U.S. public lands and small towns, spending money at local businesses that provide lodging, dining, retail shopping, and entertainment. Rural America plays a particularly important role in the national tourism economy by attracting and retaining tourists for longer visits (Interior 2012).

 

Growing Global Demand for Food

 

and Agricultural Commodities

 

 

The U.N. Food and Agricultural Organization (FAO) estimates that global agricultural production will need to increase by around 60 percent to meet the anticipated increase in demand in 2050, given an additional 2.3 billion people and current consumption patterns. Meeting this demand will depend largely on increases in agricultural productivity because input scarcity, particularly of natural resources and environmental services, will become more binding with population growth and climate change.

Population Growth and Urbanization

The world's population grows by more than 200,000 people each day and is expected to increase from 7 billion in 2012 to more than 9.2 billion in 2050. More than 95 percent of all population growth is expected to occur in low-income countries (Figure 8-6).

As the worldwide population increases, most of the growth will come from urbanization. More than half of the world's population was living in urban areas by 2008, compared with just 29 percent in the 1950s. Approximately 70 percent of the world population is expected to be living in urban areas by 2050 (Figure 8-7).

 

Figure 8-6

 

Population by Region, 1950-2050

 

 

 

 

Note: 2020-2050 data are projections.

Source: UN (2011).

 

Figure 8-7

 

Percentage of Population Residing in Urban Areas, 1950-2050

 

 

 

 

Source: UN (2012a).

A world population living primarily in cities and towns will present unique challenges to the agricultural sector, because urban populations rely heavily on a stable and efficient worldwide food chain to provide the nutrient-dense and diverse foods they demand. The rising global population is also expected to be accompanied by falling poverty rates and increasing incomes for a large fraction of the world's population, particularly in Asia. Notably, the poverty rate in East Asia fell from nearly 80 percent in 1980 to less than 20 percent in 2005. Along with the decline in poverty, there is an emerging middle class in the Asia Pacific region that the OECD projects will increase rapidly, from 525 million in 2009, to more than 1.7 billion in 2020, and to 3.2 billion in 2030 (Figure 8-8) (Kharas 2010). The result will likely be increased consumption of food per capita and a change in diets toward a higher proportion of meat.

Rising global food demand and the expected change in dietary patterns accompanying the growth in income throughout the world, particularly in China, will lead to opportunities for growth in the U.S. agricultural sector, most notably in meat export. World meat and dairy consumption doubled between 1950 and 2009. Global meat consumption has been growing much more rapidly than consumption of grains and oilseeds, and between 1985 and 1990, production of meat (beef, pork, chicken, and turkey) rose more than 3 percent a year, well above the world's population growth rate of 1.7 percent a year.

 

Figure 8-8

 

Middle-Class Population by Region, 2009-2030

 

 

 

 

Source: Kharas (2010).

Pressure on Agricultural Land and the Environment

Continuing increases in the demand for agricultural products, especially resource intensive foods such as meat, are expected to have a deleterious impact on agricultural land, soil, and water, and to create broader ecosystem-level pressures (UN 2012b). According to the United Nations, global food production currently uses nearly one-quarter of all the habitable land on earth, accounts for more than 70 percent of fresh water consumption, and produces more than 30 percent of global greenhouse gas emissions. In addition, global food production accounts for 80 percent of deforestation and is the largest single cause of species and biodiversity loss.

A collaborative report on climate change prepared by the USDA and scholars from a variety of universities and other Federal and nongovernmental agencies suggests that climate change will impact both agricultural productivity and commodity price volatility (Walthall et al. 2012). The increased temperature will increase the likelihood of grain and oilseed crop failure, forest fires, insect outbreaks, and tree mortality. Further, elevated levels of carbon dioxide are expected to reduce the productivity of livestock and dairy animals and increase weed growth. Although some agricultural and forest systems may experience productivity increases in the near term, the benefits provided by these ecosystems, such as clean drinking water and natural waste decomposition, will diminish over the long term, requiring a change in management regimes. Management of water resources will become more challenging, and natural disasters such as forest fires, insect outbreaks, severe storms, and drought will occur with increased frequency and severity, placing heavy demands on management resources, such as Federal disaster assistance. (For additional discussion of climate change, see Chapter 6.)

 

Global Commodity Markets and Price Volatility

 

 

Trade in agricultural commodities is a global endeavor and prices respond to supply and demand conditions around the world. As a result, agricultural commodity markets are characterized by a high degree of volatility. Four major market fundamentals explain why that is the case. First, agricultural output is in large part at the mercy of nature. Shocks from weather, pests, and other natural phenomena have unpredictable effects on supply. With the effects of global climate change already being seen in many parts of the globe and projected to continue, the unpredictability of these impacts is likely to increase over time. Second, diets are somewhat inflexible in the short run, which means demand for certain foods remains relatively constant.2 A third source of volatility is the natural growing cycle, which contributes to a relatively fixed short-run supply. Finally, declining stock-to-consumption ratios amplify the effects of food price shocks.

The integration of markets can also be a source of volatility. Food and energy markets in the United States and around the world have become increasingly interlinked through the use of agricultural feedstock in the production of ethanol and the use of oil and natural gas in agricultural production.3 Growth in the use of biofuels, for example, not only increases the demand for agricultural feedstocks but may also make demand less elastic through such measures as biofuel blending requirements. As such, integration can cause shocks in one market to be transmitted to another.

Since the early 1970s, food prices have become much more volatile. In general, high food prices bring with them higher price volatility, and average real food prices in the past five years were 35 percent higher than prices in the previous decade, according to the FAO's Food Price Index. The index tracks the monthly change in the average international prices of five commodity groups, namely, meat, dairy, cereals, oils, and sugar. The index peaked in February 2011 and has since fallen 10 percent. Overall food prices surged in the summer of 2012, driven by higher cereal prices. Food price spikes are not uncommon, and in most cases prices eventually fall as much as they have risen. Figure 8-9 demonstrates the increasing variability in the nominal price of corn since 1866-67.

 

Meeting the Challenges and Harnessing the

 

Opportunities of Global Demand Growth

 

 

For U.S. agriculture to benefit fully from the growing food demand and changing food patterns around the world, access to the global market must be ensured. Successful efforts by the Federal Government to open foreign markets have contributed to an agricultural export boom. In FY 2012, American agricultural exports reached $135.7 billion, just short of the record high level of $137.4 billion set in FY 2011. Additionally, America runs a trade surplus in agricultural goods -- a surplus that reached $32.4 billion in FY 2012 (USDA 2012b).

Open Trade and Access to Global Food Markets

The Obama Administration has made reducing trade barriers to market access overseas for U.S. farmers and ranchers a top priority, alongside efforts to ensure that America's trading partners fully honor all the commitments they have made under existing trade agreements. The President has signed several historic trade agreements that significantly expand market access for U.S. agricultural exporters. The recently implemented U.S.-Korea Free Trade Agreement (KORUS) is set to deliver substantial gains for U.S. agricultural exports in coming years. In a separate beef import protocol concluded in 2008, Korea agreed to adjust its import restrictions on U.S. beef. As a result, U.S. beef exports to Korea more than doubled in value from 2008 to 2011, to about $686 million. Under KORUS, Korea will gradually bring its tariffs on imports of U.S. beef and pork down to zero, and the U.S. meat industry will benefit from even greater gains in trade. The improved access provided by the agreement for a wide range of other products, beginning in 2012 and continuing over the agreement's phase-in period, will yield new market opportunities for U.S. exporters. The USDA estimates that, when fully implemented, KORUS will expand U.S. agricultural exports to Korea by an estimated $1.9 billion a year -- gains that will benefit agricultural producers and processors across the United States. The Korean Free Trade Agreement, together with the free trade agreements with Panama and Colombia passed at the same time is expected to boost U.S. agricultural exports by $2.3 billion a year (Wainio, Gehlhar, and Dyck 2011).

 

Figure 8-9

 

Corn Yields and Price, 1866-2012

 

 

 

 

Source: Department of Agriculture, Economic Research Service, Feed Grains Database.

The Obama Administration has worked with a number of other developing and developed countries to reopen their markets to U.S. beef products. Partly as a consequence of these steps, U.S. beef exports in 2011 exceeded 2003's historic levels for the first time, reaching $5.4 billion. Similarly, 57 countries, including many important emerging markets, have now lifted bans on U.S. poultry products. Between 2007 and 2011, the value of U.S. poultry exports increased from $4.1 billion to $5.6 billion. U.S. pork exports to the rapidly growing Chinese market soared after H1N1-related bans were lifted. Immediately before the ban, the United States exported on average about $132 million a year in pork and pork products to China. In 2010, pork exports to China totaled only $79.3 million. In 2011, pork exports to China grew by a factor of six, exceeding $477 million and quickly demonstrating the value of better access to this key emerging market. In the first quarter of 2012, roughly two years after the ban was lifted, the United States exported about $122 million in pork and pork products to China.

Hired Farm Labor Costs in a Global Economy

Hired labor is a crucial component of U.S. agricultural production. Costs associated with such labor account for 17 percent of variable production expenses for all agricultural commodities and 40 percent of expenses in the production of labor-intensive crops such as fruits, vegetables, and nursery products.

For fruits and vegetables, total agricultural production expenses are near parity between U.S. and international producers, but labor costs are often much lower for foreign growers. In response to higher labor costs, U.S. farms have already turned to mechanization of the harvesting and production processes. For example, mechanized production of raisins, including harvesting and drying of grapes, increased from 1 percent of the raisin crop to 45 percent between 2000 and 2007. Harvesting of baby leaf lettuce is currently 70-80 percent mechanized (Calvin and Martin 2010). These trends will likely increase if wages rise and could potentially lead to consolidation among growers. Some crops are not well suited for fully mechanical production, however. U.S. growers of such commodities may invest in technology that increases labor productivity, such as conveyor belts now common in Southern California strawberry fields.

Although mechanization is attractive in many cases, the costs associated with converting to mechanical processes are high, and larger farms typically stand to profit the most from mechanization. Moreover, growers may be hesitant to adopt the technology because of concerns about loss of quality. Given the difficulties associated with converting to mechanized production in the short run, the affordability of hired farm labor, and immigrant labor in particular, takes on greater importance. It is estimated that, for the past 15 years, about half of all hired laborers working in crop agriculture have lacked the proper immigration designation to work in the United States (Zahniser et al. 2012). Immigration policy, which influences the supply of and demand for labor as well as food prices ultimately paid by the consumer, is an important issue in the agricultural sector.

In their research, Zahniser et al. (2012) used a simulation to illustrate the effects different changes in immigration policy could have on the agricultural sector, including the effects of disruptions in the supply of labor on farm wages and crop production. Expanding the number of agricultural workers eligible for the H-2A Temporary Agricultural Program, which allows U.S. farms to hire temporary nonimmigrant foreign workers if not enough domestic workers are available, would increase agricultural production and exports by around 1.6 percent and 2.5 percent, respectively, in the long run for labor-intensive sectors like produce and nursery products. On the other hand, a 5.8 million decrease in the overall number of undocumented workers would reduce production and exports throughout all sectors of the economy, with agriculture and other labor-intensive sectors the hardest hit. Agricultural exports would fall by about 3.7 percent.

Improving Risk Management

Traditionally, every five years, Congress passes a bundle of legislation, commonly called the "Farm Bill" that sets national agriculture, nutrition, conservation, and forestry policy. The last Farm Bill, passed in 2008, was set to expire on September 30, 2012 but was extended through fiscal year 2013. The coming expiration of the current Farm Bill represents an opportunity to make the most significant reforms in agricultural policy in decades. The Senate Agricultural Reform, Food and Jobs Act of 2012 would end direct payments -- fixed annual payments to farmers based on their farms' historical crop production, paid without regard to whether a crop is currently grown -- and streamline and consolidate farm programs, as well as reduce the Federal deficit by as much as $23.6 billion over 10 years (CBO 2012). It could also strengthen priorities, such as efficient risk management, that help farmers, ranchers, and small business owners protect their investments and ensure a stable supply of needed agricultural product, while continuing to help the U.S. agricultural sector grow the economy.

Highly volatile agricultural commodity prices can create significant income risk for farmers. At the same time, the current farm safety net is inefficient and unfair, creating distortions in production and crowding out market-based risk management options. Because program commodity production is concentrated on larger farms, these farms receive the largest share of taxpayer-supported program payments, even though this group of farm households has incomes that are on average three times the average U.S. household (Figure 8-10).

Currently, those households with an average adjusted gross nonfarm income up to $500,000 are eligible to receive government payments, while those with as much as $750,000 in average adjusted farm income are eligible for direct payments. Farmers who produce fruits and vegetables do not receive any government program payments. Adding provisions that make lands that have not previously been used to grow crops ineligible for crop insurance or other Federal benefits would help protect the nation's prairies and forests from being converted into marginal cropland.

Today's agricultural commodity support programs are rooted in the landmark New Deal legislation that followed the agricultural depression of the 1920s and 1930s. These programs were designed to sustain prices and incomes for producers of cotton, milk, wheat, rice, corn, sugar, tobacco, peanuts, and other crops, at a time when a large portion of the U.S. population was engaged in farming. Today, less the 2 percent of the U.S. population is engaged in farming, and changing economic conditions and trends in agriculture since these programs began suggest that many of the original motivations for these farm programs no longer apply.

 

Figure 8-10

 

Government Commodity Payments by Farm Type

 

 

 

 

Source: USDA (2001, 2011).

For example, the increasing reliance of farm families on income earned from sources other than their farms and a shift toward market-oriented farm policies have made farms and commodity markets less vulnerable to adverse price changes than before. These changes imply that moving away from traditional commodity support programs would have a much smaller impact on farm household income than in previous decades. Nonetheless, substantial government support of agriculture remains.

Risk management involves choosing among many options for reducing the financial effects of such uncertainties. In addition to participating in government commodity programs that are available for certain commodities, farmers today have private options for managing risk that were not available when commodity price support programs were introduced. For instance, the growth of futures and options markets provides a market-based method for farmers to protect themselves against short-term price declines. Other private means to stabilize farm incomes include saving; borrowing; diversifying among different types of crops, trees, livestock and ecosystem services; contracting farm output with processors at assured prices; crop insurance and total revenue insurance; utilizing a wide range of farm management practices that reduce crop loss (such as irrigation, pesticide use); leasing out farmland; and taking advantage of expanded opportunities for earning nonfarm income.

The Dodd-Frank Wall Street Reform and Consumer Protection Act

In 2010, President Obama signed the Dodd-Frank Wall Street Reform and Consumer Protection Act, with the goal of addressing the lack of transparency, systemic risks, and interconnectedness risks in the over-the-counter (OTC) derivatives markets that, in part, precipitated the recent financial crisis. Modern farm operations -- and agribusiness in general -- rely greatly on services provided by the OTC derivatives market, including the swaps market. Derivatives, which are financial instruments whose value is based on the value of an underlying asset, liability, or event, perform essential economic functions of price discovery and risk management. The Act strengthens financial market regulation by requiring most standardized swaps to be centrally cleared and traded on an exchange or execution facility, with exemptions from clearing for commercial end-users; subjecting dealers and major participants that trade these derivatives to registration, business conduct, risk management, and collateral requirements; and subjecting all swaps to new recordkeeping and reporting rules.

Although the OTC derivatives market serves an important risk-management role amounting to trillions of dollars in notional value, in the past, OTC derivatives were essentially an unregulated market. The lack of market oversight allowed substantial counterparty credit risk to build up in these markets, with significant consequences for the financial system. In addition, the lack of regulation created inefficiencies by reducing information available to market participants and regulators, hampering price discovery, and facilitating opportunities for fraud. Before passage of the Act, regulators had no authority to monitor the market and prescribe rules. The new clearing and margin requirements will act as safeguards for the performance of the OTC derivatives markets, eliminating counterparty credit risk between the original traders. In addition, new real-time public reporting requirements and execution standards will improve market transparency and lower transaction costs.

The Act further seeks to protect the market for agricultural swaps, while ensuring that agricultural market participants are still able to access risk-management markets. The Act provides that derivatives on agricultural commodities may be conducted only by eligible contract participants -- that is, counterparties who hold more than $10 million in assets or have a net worth of $1 million or more. Because many smaller farmers would not qualify as eligible contract participants and consequently could not engage in swap contracts that are not traded on a designated contract market (an exchange) or swap execution facility (SEF), the U.S. Commodity Futures Trading Commission granted them an exemption for physical commodity options. This exemption provides flexibility for all farmers to manage risk using agricultural derivatives contracts.

 

Conclusion

 

 

Although farming has become a progressively smaller share of the U.S. economy, the President believes that a vibrant U.S. agricultural sector is vital for the Nation's prosperity. U.S. agriculture has remained a bright spot in the economy during the Great Recession and its immediate aftermath and despite the most severe drought in more than a half-century. Much of the sector's success can be attributed to growth in global demand for American agricultural exports. In 2012, agricultural exports reached a near record level and are projected to continue to expand. The world's population is expected to reach more than 9.2 billion people by 2050, with most of the growth occurring in countries that are net food importers. President Obama believes that expanding overseas market access is crucial for the continued strength of American agriculture.

Persistent gains in efficiency have defined American agriculture and nearly tripled farm productivity in the second half of the twentieth century. To continue this tradition and maintain the strength of the sector, the Nation must continue to invest in agricultural R&D, helping farmers find new ways to grow more with less and to continue their stewardship of natural resources for future generations. The agricultural sector is increasingly vulnerable to price volatility because of the globalization of agricultural commodities, volatile weather conditions as a result of climate change, and changing consumption patterns. To cope with these challenges, U.S. agriculture must stay at the forefront of agricultural innovation.

 

FOOTNOTE TO CHAPTER 8

 

 

1 Corporations include both Sub-chapter C and S corporations.

2 For data on commodity and food elasticities, see USDA Economic Research Service, http://www.ers.usda.gov/data-products/commodity-and-food-elasticities.aspx.

3 Natural gas is the primary feedstock in the production of ammonia, and ammonia is the primary input for all nitrogen fertilizers.

 

END OF FOOTNOTE TO CHAPTER 8

 

 

* * * * *

 

 

REFERENCES

 

 

CHAPTER 1

 

INTRODUCTION

 

 

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CHAPTER 2

 

THE YEAR IN REVIEW AND THE YEARS AHEAD

 

 

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CHAPTER 3

 

FISCAL POLICY

 

 

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Smith, Adam. 1776. An Inquiry into the Nature and Causes of the Wealth of Nations. (Elecronic version: http://www2.hn.psu.edu/faculty/jmanis/adam-smith/wealth-nations.pdf).

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Wilson, Janette, and Pearson Liddell. 2010. "Sales of Capital Assets Reported on Individual Tax Returns, 2007." Statistics of Income Bulletin 29, no. 3: 75-104 (http://www.irs.gov/pub/irs-soi/10winbulcapitalassets.pdf).

 

CHAPTER 4

 

JOBS, WORKERS, AND SKILLS

 

 

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Almond, Douglas, and Janet Currie. 2011. "Human Capital Development Before Age Five." In Handbook of Labor Economics 4B, edited by Orley Ashenfelter and David Card, pp. 1315-486. London: Elsevier.

Anderson, Stuart, and Michaela Platzer. 2006. "American Made: The Impact of Immigrant Entrepreneurs and Professionals on U.S. Competitiveness." Arlington, VA: National Venture Capital Association.

Bardasi, Elena, and Janet C. Gornick. 2008. "Working for Less? Women's Part-Time Wage Penalties Across Countries." Feminist Economist 14, no. 1: 37-72.

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CEA (Council of Economic Advisers). 2010. "Work-Life Balance and the Economics of Workplace Flexibility."

College Board. 2010. "Trends in College Pricing." Trends in Higher Education Series. New York.

Cortes, Patricia. 2008. "The Effect of Low-Skilled Immigration on U.S. Prices: Evidence from CPI Data." Journal of Political Economy 116, no. 3: 381-421.

Cunha, Flavio, and James J. Heckman. 2008. "Formulating, Identifying, and Estimating the Technology for the Formation of Skills." Journal of Human Resources 43, no. 4: 738-82.

Cunha, Flavio, James J. Heckman, and Susanne M. Schennach. 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation." Econometrica 78, no. 3: 883-931.

Deming, David, Claudia Goldin, and Lawrence F. Katz. 2012. "The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators?" Journal of Economic Perspectives 26, no. 1: 139-64.

Department of Education. 2012. "First Official Three Year Student Loan Default Rates Published." September (http://www.ed.gov/news/press-releases/first-official-three-year-student-loan-default-ratespublished).

DHS (Department of Homeland Security). 2011. "2011 Yearbook of Immigration Statistics."

Doucouliagos, Hristos, and T. D. Stanley. 2009. "Publication Selection Bias in Minimum-Wage Research? A Meta-Regression Analysis." British Journal of Industrial Relations 47, no. 2: 406-28.

Dube, Arindrajit, T. William Lester, and Michael Reich. 2010. "Minimum Wage Effects Across State Borders: Estimates using Contiguous Counties." Review of Economics and Statistics 92, no. 4: 945-64

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Fairlie, Robert W. 2012. "Immigrant Entrepreneurs and Small Business Owners, and Their Access to Financial Capital." Small Business Administration, Office of Advocacy.

Figlio, David N., Mark Rush, and Lu Yin. 2010. "Is It Live or Is It Internet? Experimental Estimates of the Effect of Online Instruction on Student Learning." Working Paper 16089. Cambridge, MA: National Bureau of Economic Research.

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Gauthier-Loiselle, Marjolaine, and Jennifer Hunt. 2010. "How Much Does Immigration Boost Innovation?" American Economic Journal: Macroeconomics 2, no. 2: 31-56.

Goldin, Claudia, and Lawrence F. Katz. 2011. "The Cost of Workplace Flexibility for High-Powered Professionals." Annals of the American Academy of Political and Social Science 638, no. 1: 45-67.

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Grogger, Jeffrey. 2003. "The Effects of Time Limits, the EITC, and Other Policy Changes on Welfare Use, Work, and Income Among Female-Headed Families." Review of Economics and Statistics 85, no. 2: 394-408.

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Holzer, Harry J. 2011. "Raising Job Quality and Skills for American Workers: Creating More-Effective Education and Workforce Development Systems in the States." Discussion Paper 2011-10. Washington: The Hamilton Project.

Jasso, Guillermina, and Mark R. Rosenzweig. 2008. "Selection Criteria and the Skill Composition of Immigrants: A Comparative Analysis of Australian and U.S. Employment Immigration." IZA Discussion Paper. Bonn: Institute for the Study of Labor. June (http://www.iza.org/en/webcontent/publications/papers/viewAbstract?dp_id=356).

Kerr, William R., and William F. Lincoln. 2009. "The Supply Side of Innovation: H-1B Visa Reforms and US Ethnic Invention." Working Paper 09-005. Harvard Business School.

Kochan, Thomas, David Finegold, and Paul Osterman. 2012 "Who Can Fix the 'Middle-Skills' Gap?" Harvard Business Review. December.

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Langdon, David, George McKittrick, David Beede, Beethika Kahn, and Mark Doms. 2011. "STEM: Good Jobs Now and for the Future." U.S. Department of Commerce, Economics and Statistics Administration.

Maestas, Nicole, and Julie Zissimopoulos. 2010. "How Longer Work Lives Ease the Crunch of Population Aging." Journal of Economic Perspectives 23, no. 1: 39-60.

Maguire, Sheila, Joshua Freely, Carol Clymer, Maureen Conway and Deena Schwartz. 2010. "Tuning In to Local Labor Markets." Oakland, CA: Public/Private Ventures (http://www2.oaklandnet.com/oakca/groups/ceda/documents/report/dowd021455.pdf).

Manning, Alan, and Barbara Petrongolo. 2008. "The Part-Time Pay Penalty for Women in Britain." Economic Journal 118, no. 526: 29-51.

Meissner, Doris, Donald M. Kerwin, Muzaffar Chishti, and Clarie Bergeron. 2013. "Immigration Enforcement in the United States: The Rise of a Formidable Machinery." Washington: Migration Policy Institute.

Meyer, Bruce D., and Dan T. Rosenbaum. 2001. "Welfare, the Earned Income Tax Credit, and the Labor Supply of Single Mothers." Quarterly Journal of Economics 116, no. 3: 1063-114.

Moffitt, Robert A. 2003. "The Temporary Assistance for Needy Families Program." In Means-Tested Transfer Programs in the United States, edited by Robert A. Moffit. pp. 291-363. Chicago: University of Chicago Press.

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National Science Foundation/National Center for Science and Engineering Statistics. 2010. "National Survey of College Graduates."

OECD (Organisation for Economic Co-operation and Development). 2012a. "Gender Gap Report 2012." Paris (http://www3.weforum.org/docs/WEF_GenderGap_Report_2012.pdf).

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Ottaviano, Gianmarco I.P., and Giovanni Peri. 2012 "Rethinking the Effect of Immigration on Wages." Journal of the European Economic Association 10, no. 1: 152-97.

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Peri, Giovanni, and Chad Sparber. 2009. "Task Specialization, Immigration and Wages." American Economic Journal: Applied Economics 1, no. 3: 135-69

Rossin-Slater, Maya, Christopher J. Ruhm, and Jane Waldfogel. 2011. "The Effects of California's Paid Family Leave Program on Mothers' Leave-Taking and Subsequent Labor Market Outcomes." Working Paper 17715. Cambridge, MA: National Bureau of Economic Research.

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Wellington, Allison J. 1991. "Effects of the Minimum Wage on Employment Status of Youths. An Update." Journal of Human Resources 26, no. 1: 27-46.

 

CHAPTER 5

 

REDUCING COSTS AND IMPROVING THE QUALITY OF HEALTH CARE

 

 

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Aizcorbe, Ana, Eli B. Liebman, David M. Cutler, and Allison B. Rosen. 2012. "Household Consumption Expenditures for Medical Care: An Alternate Presentation." Bureau of Economic Analysis, U.S. Department of Commerce.

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Berwick, Donald M., and Andrew D. Hackbarth. 2012. "Eliminating Waste in US Health Care." American Medical Association (http://www.hta.hca.wa.gov/documents/Waste_in_Healthcare_JAMA_2012.pdf).

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CBO (Congressional Budget Office). 2012a. "The Distribution of Household Income and Federal Taxes, 2008 and 2009." July.

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CHAPTER 6

 

CLIMATE CHANGE AND THE PATH TOWARD

 

SUSTAINABLE ENERGY SOURCES

 

 

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Logan, Jeffrey, et al. 2012. "Natural Gas and the Transformation of the U.S. Energy Sector: Electricity." NREL/TP-6A50-55538. Golden, CO: National Renewable Energy Laboratory for the Joint Institute for Strategic Energy Analysis.

Mendelsohn, Robert, Kerry Emanuel, Shun Chonabayashi and Laura Bakkensen. 2012. "The Impact of Climate Change on Global Tropical Cyclone Damage." Nature Climate Change 2: 205-209 (doi:10.1038/nclimate1357).

Munich Reinsurance Company. 2012. "Costliest Natural Disasters: Insured Loses." NatCat Service (http://www.munichre.com/en/reinsurance/business/non-life/georisks/natcatservice/significant_natural_catastrophes.aspx).

Narita, Daiju, Richard S.J. Tol, and David Anthoff. 2009. "Damage Cost of Climate Change through Intensification of Tropical Cyclone Activities: An Application of FUND." Climate Research 39: 87-97.

NOAA (National Oceanic and Atmospheric Administration). 2012. "Global Sea Level Rise Scenarios for the United States National Climate Assessment." NOAA Tech Memo OAR CPO.

Nordhaus, William. 2010. "Economic Aspects of Global Warming in a Post-Copenhagen Environment." Yale University.

Onatski, Alexei, and James H. Stock. 2002. "Robust Monetary Policy Under Model Uncertainty in a Small Model of the U.S. Economy." Macroeconomic Dynamics 6, no. 1: 85-110.

Pielke, Roger A. 2007. "Future Economic Damage from Tropical Cyclones: Sensitivities to Societal and Climate Change." Philosophical Transactions of the Royal Society. doi:10.1098/rsta.2007.2086.

Rhines, A., and P. Huybers. 2013. "Frequent Summer Temperature Extremes Reflect Changes in the Mean, Not the Variance." Proceedings of the National Academy of Sciences110, no.7: E546. doi:10.1073/pnas.1218748110.

Roe, Gerald H., and Marcia B. Baker. 2007. "Why Is Climate Sensitivity So Unpredictable?" Science 318: 629-32.

Rohling, E. J., et al. 2012. "Making Sense of Palaeoclimate Sensitivity." Nature 491: 683-91.

Small, Kenneth A., and Kurt Van Dender. 2007. "Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect." Energy Journal 28, no. 1: 25-51.

Stern, Nicholas. 2006. The Stern Review: The Economic Effects of Climate Change. Cambridge University Press.

USGCRP (United States Global Change Research Program). 2009. Global Climate Change Impacts in the United States, edited by Thomas R. Karl, Jerry M. Melillo, and Thomas C. Peterson. Cambridge University Press.

Weitzman, Martin L. 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change." Review of Economics and Statistics 91, no. 1: 1-19.

_____. 2011. "Fat-Tailed Uncertainty in the Economics of Catastrophic Climate Change." Review of Environmental Economics and Policy 5, no. 2: 275-92.

White House. 2010. "Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866." February (http://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf).

_____. 2011a. "Driving Efficiency: Cutting Costs for Families at the Pump and Slashing Dependence on Oil." July (http://whitehouse.gov/sites/default/files/fuel_economy_report.pdf).

_____. 2011b. "A Policy Framework for the 21st Century Grid: Enabling Our Secure Energy Future." June. (http://www.whitehouse.gov/sites/default/files/microsites/ostp/nstc-smart-grid-june2011.pdf).

 

CHAPTER 7

 

INTERNATIONAL TRADE AND COMPETITIVENESS

 

 

Amiti, Mary, and Shang-Jin Wei. 2009. "Service Offshoring and Productivity: Evidence from the US." World Economy 20, no. 42: 203-20.

Autor, David. H., David Dorn, and Gordon H. Hanson. Forthcoming. "The China Syndrome: Local Labor Market Effects of Import Competition in the United States." American Economic Review.

Bartel, Ann, Casey Ichniowski, and Kathryn Shaw. 2007. "How Does Information Technology Really Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement and Worker Skills." Quarterly Journal of Economics 122, no. 4: 1721-58.

Bernanke, Ben S. 2005. "The Global Saving Glut and the U.S. Current Account Deficit." Sandridge Lecture, Virginia Association of Economists. March.

Bernard, Andrew B., J. Bradford Jensen, and Peter K. Schott. 2006. "Trade Costs, Firms and Productivity." Journal of Monetary Economics 53, no. 5: 917-37.

Borchert, Ingo, Batshur Gootiiz, and Aaditya Mattoo. 2012. "Policy Barriers to International Trade in Services: Evidence from a New Database." Policy Research Working Paper 6109. Washington, DC: World Bank.

Boston Consulting Group. 2012. "Rising U.S. Exports -- Plus Reshoring -- Could Help Create up to 5 Million Jobs by 2020." Boston. September.

Bosworth, Barry P., and Jack E. Triplett. 2007. "The Early 21st Century U.S. Productivity Expansion Is Still in Services." International Productivity Monitor 14: 3-19.

Branstetter, Lee. 2001. "Are Knowledge Spillovers International or International in Scope? Microeconometric Evidence from Japan and the United States." Journal of International Economics 53: 53-79.

Ceglowski, Janet, and Stephen S. Golub. 2012. "Does China Still Have a Labor Cost Advantage?" Global Economy Journal 12, no 3.

Chirinko, Robert S., and Daniel J. Wilson. 2008. "State Investment Tax Incentives: A Zero-Sum Game?" Journal of Public Economics 92, no. 12: 2362-84.

Davidson, Adam. 2013. "Workers of the World, Sit Tight." New York Times. January 29.

ESA (Economics and Statistics Administration). 2012. The Benefits of Manufacturing Jobs. Department of Commerce.

Ferreira, John and Mike Heilala. 2011. "Manufacturing's Secret Shift: Gaining Competitive Advantage by Getting Closer to the Customer." Acenture. (http://www.accenture.com/sitecollectiondocuments/PDF/Accenture_Manufacturings_Secret_Shift.pdf).

Greenstone, Michael, Richard Hornbeck,and Enrico Moretti. 2010. "Identifying Agglomeration Spillovers: Evidence from Million Dollar Plants." Journal of Political Economy 118, no. 3: 536-98.

Hackel, Karee. 2011. "Returning from China." The SRQ Business Journal: 6-7. October.

Helper, Susan, Timothy Krueger, and Howard Wial. 2012. "Why Does Manufacturing Matter? Which Manufacturing Matters? A Policy Framework." Washington, DC: Brookings Institution.

Houseman, Susan, et al. 2011. "Offshoring Bias in U.S. Manufacturing." Journal of Economic Perspectives 25, no. 2: 111-32.

Hubbard, Thomas N. 2003. "Information, Decisions, and Productivity: On-Board Computers and Capacity Utilization in Trucking." American Economic Review 93, no. 4: 1328-53.

Hufbauer, Gary Clyde, Jeffery J. Schott, and Woan Foong Wong. 2010. Figuring Out the Doha Round. Washington, DC: Peterson Institute for International Economics.

IMF (International Monetary Fund). 2012. "Coping with High Debt and Sluggish Growth." World Economic Outlook: October 2012. Washington, DC.

Inch, John, and Neil Dutta. 2012. U.S. Manufacturing Renaissance. New York: Bank of America Merrill Lynch. March.

Jaffe, Adam B. 1989. "Real Effects of Academic Research." American Economic Review 79, no. 5: 957-70.

Jensen, J. Bernard. 2009. "Globalization and Business Services: A Growth Opportunity?" Washington, DC: Georgetown University McDonough School of Business.

_____. 2011. "Global Trade in Services: Fear, Facts, and Offshoring." Washington, DC: Peterson Institute for International Economics.

Johnson, Bradford C. 2002. "Retail: The Walmart Effect." McKinsey Quarterly. February.

Johnson, Robert C., and Guillermo Noguera. 2012. "Fragmentation and Trade in Value Added over Four Decades." Working Paper 18186. Cambridge, MA: National Bureau for Economic Research.

Koerner, Brendan I. 2011. "Made in America: Small Businesses Buck the Offshoring Trend." Wired. February 28.

Koopman, Robert, et al. 2010. "Give Credit Where Credit Is Due: Tracing Value Added in Global Production Chains." Working Paper 16426. Cambridge, MA: National Bureau for Economic Research.

Levy, Frank, and Richard J. Murnane. 2005. The New Division of Labor: How Computers Are Creating the Next Job Market. Princeton University Press.

Lileeva, Alla, and Daniel Trefler. 2010. "Improved Access to Foreign Markets Raises Plant-Level Productivity . . . For Some Plants." Quarterly Journal of Economics 125, no. 3: 1051-99.

Marshall, Alfred. 1890. Principles of Economics. New York: Macmillan and Company.

Moretti, Enrico. 2012. The New Geography of Jobs. New York: Houghton Mifflin Harcourt.

Obstfeld, Maurice. 2012. "Does the Current Account Still Matter?" American Economic Review 102: 1-24.

OECD (Organisation for Economic Co-operation and Development). 2013. "Measuring Trade in Value-Added: An OECD-WTO Joint Initiative" (http://www.oecd.org/industry/industryandglobalisation/measuringtradeinvalue-addedanoecd-wtojointinitiative.htm).

Pierce, Justin. 2011. "Plant-level Responses to Antidumping Duties: Evidence from U.S. Manufacturers." Journal of International Economics 85, no. 2: 222-33.

Pierce, Justin, and Peter K. Schott. 2012. "The Surprisingly Swift Decline of U.S. Manufacturing Employment." Working Paper 18655. Cambridge, MA: National Bureau for Economic Research.

Pisano, Gregory P., and Willy C. Shih. 2012. Producing Prosperity: Why America Needs a Manufacturing Renaissance. Boston: Harvard Business Review Press.

Prasso, Sheridan. 2011. "Why We Left Our Factories in China." CNN Money. June 29.

Reinhart, Carmen M., and Kenneth S. Rogoff. 2011. "From Financial Crash to Debt Crisis." American Economic Review 101, no. 5: 1676-706.

Rosenthal, Stuart S., and William C. Strange. 2003. "Geography, Industrial Organization, and Agglomeration." Review of Economics and Statistics 85, no. 2: 377-93.

Simchi-Levi, David, James Paul Peruvankal, Narendra Mulani, and John Ferreira. 2011. "Made in America: Rethinking the Future of U.S. Manufacturing." Accenture. (http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Made-in-America.pdf).

Story, Louise. 2012. "As Companies Seek Tax Deals, Governments Pay High Price." New York Times, December 1.

Wailgum, Thomas. 2007. "How Wal-Mart Lost Its Technology Edge." CIO. October 4.

Wan, William. 2013. "China's Economic Data Draw Sharp Scrutiny from Experts Analyzing Global Trends." Washington Post, February 4.

Weil, David. 2011. "Enforcing Labor Standards in Fissured Workplaces: The US Experience." The Economic and Labor Relations Review 22, 2: 33-54

Zhu, Kevin. 2004. "The Complementarity of Information Technology Infrastructure and E-Commerce Capability: A Resource-Based Assessment of Their Business Value." Journal of Management Systems 21, no.1: 167-202.

 

CHAPTER 8

 

CHALLENGES AND OPPORTUNITIES IN U.S. AGRICULTURE

 

 

Alston, Julian M., et al. 2009. Persistence Pays: U.S. Agricultural Productivity Growth and the Benefits from Public R&D Spending. Natural Resource Management and Policy Series, vol. 34. Springer: New York. (http://www.card.iastate.edu/publications/synopsis.aspx?id=1155).

Calvin, Linda, and Philip Martin. 2010. "The U.S. Produce Industry and Labor: Facing the Future in a Global Economy." Economic Research Report 106. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/publications/err-economicresearch-report/err106.aspx).

CBO (Congressional Budget Office). 2012. "Cost Estimate: S. 3240 Agriculture Reform, Food, and Jobs Act of 2012." May (http://www.cbo.gov/sites/default/files/cbofiles/attachments/s3240.pdf).

Dimitri, Carolyn, and Lydia Oberholtzer. 2009. "Marketing U.S. Organic Foods: Recent Trends from Farms to Consumers." Economic Information Bulletin 58. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/185272/eib58_1_. pdf).

Durst, Ron. 2009. "Federal Estate Taxes Affecting Fewer Farmers But the Future Is Uncertain." Amber Waves. U.S. Department of Agriculture, Economic Research Service (http://webarchives.cdlib.org/sw1tx36512/http:/www.ers.usda.gov/AmberWaves/June09/Features/FederalEstateTax.htm#special).

Evenson, Robert E. 1988. "Research, Extension, and U.S. Agricultural Productivity: A Statistical Decomposition Analysis." Agricultural Productivity: Measurement and Explanation, edited by Susan M. Capalbo and John M. Antle. Johns Hopkins University Press for Resources for the Future.

Fuglie, Keith O., and Paul W. Heisey. 2007. "Economic Returns to Public Agricultural Research." Economic Brief 10. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/195594/eb10_1_.pdf).

Greene, C., et al. 2009. "Emerging Issues in the U.S. Organic Industry." Economic Information Bulletin 55. U.S. Dept. of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/452867/eib55fm_1_.pdf).

Griliches, Zvi. 1998. "Introduction to 'R&D: The Econometric Evidence.'" R&D and Productivity: The Econometric Evidence. University of Chicago Press for the National Bureau of Economic Research (http://www.nber.org/chapters/c8339.pdf).

Hoppe, Robert A., James M. MacDonald, and Penni Korb. 2010. "Small Farms in the United States: Persistence Under Pressure." Economic Information Bulletin 63. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/147007/eib63_1_. pdf).

Interior (U.S. Department of the Interior). 2012. "National Travel and Tourism Strategy." Task Force on Travel and Competiveness (http://www.doi.gov/news/pressreleases/upload/NT-TS_final051512.pdf).

Jacobson, Darien, Brian Raub, and Barry Johnson. 2012. "The Estate Tax: Ninety Years and Counting." Compendium of Federal Estate and Personal Wealth Studies, Volume II. Internal Revenue Service, Statistics of Income (http://www.irs.gov/uac/SOI-Tax-Stats-Compendium-of-Federal-Estate-Tax-and-Personal-Wealth-Studies,-Volume-2).

Key, Nigel, and William McBride. 2007. "The Changing Economics of U.S. Hog Production." Economic Research Report 52. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/244843/err52.pdf).

Kharas, Homi. 2010. "The Emerging Middle Class in Developing Countries." Working Paper 185. Paris: OECD Development Center (http://www.oecd.org/dev/44457738.pdf).

Kremen, Amy, Catherine Greene, and Jim Hanson. 2004. "Organic Produce, Price Premiums, and Eco-Labeling in U.S. Farmers' Markets." Outlook. VGS-301-01. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/269468/vgs30101_1_.pdf).

Low, Sarah A., and Stephen Vogel. 2011. "Direct and Intermediated Marketing of Local Foods in the United States." Economic Research Report 128. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/publications/err-economicresearch-report/err128.aspx).

MacDonald, James M., and Penni Korb. 2011. "Agricultural Contracting Update: Contracts in 2008." Economic Information Bulletin 72. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/104365/eib72.pdf).

Osteen, Craig, Jessica Gottlieb, and Utpal Vasavade eds. 2012. "Agricultural Resources and Environmental Indicators, 2012 Edition." Economic Information Bulletin No 98 (http://www.ers.usda.gov/media/874175/eib98.pdf).

Outdoor Industry Association. 2012. The Outdoor Recreation Economy. Boulder, CO (http://www.outdoorindustry.org/images/researchfiles/OIA_OutdoorRecEconomyReport2012.pdf?167)

Pardey, Philip G. and Julian M. Alston. 2011. "For Want of a Nail: The Case for Increased Agricultural R&D Spending." Washington, DC: American Enterprise Institute (http://www.aei.org/files/2011/11/04/-for-want-of-a-nail-the-case-for-increased-agricultural-rd-spending_152830448674.pdf).

Ribaudo, M., et al. 2008. "The Use of Markets to Increase Private Investment in Environmental Stewardship." Economic Research Report 64, U.S. Department of Agriculture, Economic Research Service (http://www.ers.USDA.gov/publications/err-economic-research-report/err64.aspx).

Ribaudo, M., et al. 2012. "Nitrogen Management on U.S. Corn Acres, 2001-2010." Economic Brief No 20 (http://www.ers.usda.gov/media/947769/eb20.pdf). (http://hsus.cambridge.org/HSUSWeb/search/searchTable.do?id=Ba652-669).

UN (United Nations). 2011. "World Population Prospects: The 2010 Revision, CD-ROM Edition." Department of Economic and Social Affairs, Populations Division (http://esa.un.org/wpp/).

_____. 2012a. "World Urbanization Prospects: The 2011 Revision, CD-ROM Edition." Department of Economic and Social Affairs, Populations Division (http://esa.un.org/unup/).

_____. 2012b. "Population Distribution, Urbanization, Internal Migration and Development: An International Perspective." Department of Economic and Social Affairs.

USDA. 2001. Agricultural Resource Management Survey. Economic Research Service (http://www.ers.usda.gov/data-products/armsfarm-financial-and-crop-production-practices/tailored-reports. aspx).

_____. 2010. Agricultural Resource Management Survey. Economic Research Service (http://www.ers.usda.gov/data-products/arms-farm-financial-and-crop-production-practices/tailored-reports.aspx).

_____. 2011. Agricultural Resource Management Survey. Economic Research Service (http://www.ers.usda.gov/data-products/arms-farm-financial-and-crop-production-practices/tailored-reports.aspx).

_____. 2012a. "USDA Accomplishments 2009-2012: Organic Agriculture." (usda.gov/documents/Results-Organic-Agriculture.pdf).

_____. 2012b. "USDA Accomplishments 2009-2012: Trade." (http://www.usda.gov/documents/Results-Trade.pdf)

_____. 2013a. "U.S. and State Farm Income and Wealth Statistics." Economic Research Service.

_____. 2013b. "Summary of Business Report for 2010 thru 2013." Federal Crop Insurance Corp (http://www3.rma.usda.gov/apps/sob/current_week/sobrpt2010-2013.pdf).

_____. 2013c. "Food Expenditures." Economic Research Service (http://www.ers.usda.gov/data-products/food-expenditures.aspx).

Wainio, John, Mark Gehlhar, and John Dyck. 2011. "Selected Trade Agreements and Implications for U.S. Agriculture." Economic Research Report 115. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/media/128130/err115.pdf).

Walthall, C.L., et al. 2012. "Climate Change and Agriculture in the United States: Effects and Adaptation." U.S. Department of Agriculture Technical Bulletin No 1935 (http://www.usda.gov/oce/climate_change/effects_2012/CC%20and%20Agriculture%20Report%20(02-04-2013)b.pdf).

Zahniser, Steven, et al. 2012. "The Potential Impact of Changes in Immigration Policy on U.S. Agriculture and the Market for Hired Farm Labor: A Simulation Analysis." Economic Research Report 135. U.S. Department of Agriculture, Economic Research Service (http://www.ers.usda.gov/publications/err-economic-research-report/err135.aspx).

 

* * * * *

 

 

APPENDIX A

 

 

REPORT TO THE PRESIDENT

 

ON THE ACTIVITIES OF THE COUNCIL OF

 

ECONOMIC ADVISERS DURING 2012

 

 

LETTER OF TRANSMITTAL

 

 

COUNCIL OF ECONOMIC ADVISORS

 

Washington D.C.,

 

December 31, 2012

 

 

Mr. President:

The Council of Economic Advisers submits this report on its activities during calendar year 2012 in accordance with the requirements of the Congress, as set forth in section 10(d) of the Employment Act of 1946 as amended by the Full Employment and Balanced Growth Act of 1978.

Sincerely yours,

 

 

Alan B. Krueger, Chairman

 

Katharine G. Abraham, Member

 

James H. Stock, Member

 

                   Council Members and Their Dates of Service

 

 _____________________________________________________________________________

 

 

 Name                  Position         Oath of office date  Separation date

 

 _____________________________________________________________________________

 

 

 Edwin G. Nourse       Chairman         August 9, 1946       November 1, 1949

 

 

 Leon H. Keyserling    Vice Chairman    August 9, 1946

 

                       Acting Chairman  November 2, 1949

 

                       Chairman         May 10, 1950         January 20, 1953

 

 

 John D. Clark         Member           August 9, 1946

 

                       Vice Chairman    May 10, 1950         February 11, 1953

 

 

 Roy Blough            Member           June 29, 1950        August 20, 1952

 

 

 Robert C. Turner      Member           September 8, 1952    January 20, 1953

 

 

 Arthur F. Burns       Chairman         March 19, 1953       December 1, 1956

 

 

 Neil H. Jacoby        Member           September 15, 1953   February 9, 1955

 

 

 Walter W. Stewart     Member           December 2, 1953     April 29, 1955

 

 

 Raymond J. Saulnier   Member           April 4, 1955

 

                       Chairman         December 3, 1956     January 20, 1961

 

 

 Joseph S. Davis       Member           May 2, 1955          October 31, 1958

 

 

 Paul W. McCracken     Member           December 3, 1956     January 31, 1959

 

 

 Karl Brandt           Member           November 1, 1958     January 20, 1961

 

 

 Henry C. Wallich      Member           May 7, 1959          January 20, 1961

 

 

 Walter W. Heller      Chairman         January 29, 1961     November 15, 1964

 

 

 James Tobin           Member           January 29, 1961     July 31, 1962

 

 

 Kermit Gordon         Member           January 29, 1961     December 27, 1962

 

 

 Gardner Ackley        Member           August 3, 1962

 

                       Chairman         November 16, 1964    February 15, 1968

 

 

 John P. Lewis         Member           May 17, 1963         August 31, 1964

 

 

 Otto Eckstein         Member           September 2, 1964    February 1, 1966

 

 

 Arthur M. Okun        Member           November 16, 1964

 

                       Chairman         February 15, 1968    January 20, 1969

 

 

 James S. Duesenberry  Member           February 2, 1966     June 30, 1968

 

 

 Merton J. Peck        Member           February 15, 1968    January 20, 1969

 

 

 Warren L. Smith       Member           July 1, 1968         January 20, 1969

 

 

 Paul W. McCracken     Chairman         February 4, 1969     December 31, 1971

 

 

 Hendrik S. Houthakker Member           February 4, 1969     July 15, 1971

 

 

 Herbert Stein         Member           February 4, 1969

 

                       Chairman         January 1, 1972      August 31, 1974

 

 

 Ezra Solomon          Member           September 9, 1971    March 26, 1973

 

 

 Marina v. N. Whitman  Member           March 13, 1972       August 15, 1973

 

 

 Gary L. Seevers       Member           July 23, 1973        April 15, 1975

 

 

 William J. Fellner    Member           October 31, 1973     February 25, 1975

 

 

 Alan Greenspan        Chairman         September 4, 1974    January 20, 1977

 

 

 Paul W. MacAvoy       Member           June 13, 1975        November 15, 1976

 

 

 Burton G. Malkiel     Member           July 22, 1975        January 20, 1977

 

 

 Charles L. Schultze   Chairman         January 22, 1977     January 20, 1981

 

 

 William D. Nordhaus   Member           March 18, 1977       February 4, 1979

 

 

 Lyle E. Gramley       Member           March 18, 1977       May 27, 1980

 

 

 George C. Eads        Member           June 6, 1979         January 20, 1981

 

 

 Stephen M. Goldfeld   Member           August 20, 1980      January 20, 1981

 

 

 Murray L. Weidenbaum  Chairman         February 27, 1981    August 25, 1982

 

 

 William A. Niskanen   Member           June 12, 1981        March 30, 1985

 

 

 Jerry L. Jordan       Member           July 14, 1981        July 31, 1982

 

 

 Martin Feldstein      Chairman         October 14, 1982     July 10, 1984

 

 

 William Poole         Member           December 10, 1982    January 20, 1985

 

 

 Beryl W. Sprinkel     Chairman         April 18, 1985       January 20, 1989

 

 

 Thomas Gale Moore     Member           July 1, 1985         May 1, 1989

 

 

 Michael L. Mussa      Member           August 18, 1986      September 19, 1988

 

 

 Michael J. Boskin     Chairman         February 2, 1989     January 12, 1993

 

 

 John B. Taylor        Member           June 9, 1989         August 2, 1991

 

 

 Richard L.

 

 Schmalensee           Member           October 3, 1989      June 21, 1991

 

 

 David F. Bradford     Member           November 13, 1991    January 20, 1993

 

 

 Paul Wonnacott        Member           November 13, 1991    January 20, 1993

 

 

 Laura D'Andrea Tyson  Chair            February 5, 1993     April 22, 1995

 

 

 Alan S. Blinder       Member           July 27, 1993        June 26, 1994

 

 

 Joseph E. Stiglitz    Member           July 27, 1993

 

                       Chairman         June 28, 1995        February 10, 1997

 

 

 Martin N. Baily       Member           June 30, 1995        August 30, 1996

 

 

 Alicia H. Munnell     Member           January 29, 1996     August 1, 1997

 

 

 Janet L. Yellen       Chair            February 18, 1997    August 3, 1999

 

 

 Jeffrey A. Frankel    Member           April 23, 1997       March 2, 1999

 

 

 Rebecca M. Blank      Member           October 22, 1998     July 9, 1999

 

 

 Martin N. Baily       Chairman         August 12, 1999      January 19, 2001

 

 

 Robert Z. Lawrence    Member           August 12, 1999      January 12, 2001

 

 

 Kathryn L. Shaw       Member           May 31, 2000         January 19, 2001

 

 

 R. Glenn Hubbard      Chairman         May 11, 2001         February 28, 2003

 

 

 Mark B. McClellan     Member           July 25, 2001        November 13, 2002

 

 

 Randall S. Kroszner   Member           November 30, 2001    July 1, 2003

 

 

 N. Gregory Mankiw     Chairman         May 29, 2003         February 18, 2005

 

 

 Kristin J. Forbes     Member           November 21, 2003    June 3, 2005

 

 

 Harvey S. Rosen       Member           November 21, 2003

 

                       Chairman         February 23, 2005    June 10, 2005

 

 

 Ben S. Bernanke       Chairman         June 21, 2005        January 31, 2006

 

 

 Katherine Baicker     Member           November 18, 2005    July 11, 2007

 

 

 Matthew J. Slaughter  Member           November 18, 2005    March 1, 2007

 

 

 Edward P. Lazear      Chairman         February 27, 2006    January 20, 2009

 

 

 Donald B. Marron      Member           July 17, 2008        January 20, 2009

 

 

 Christina D. Romer    Chair            January 29, 2009     September 3, 2010

 

 

 Austan D. Goolsbee    Member           March 11, 2009

 

                       Chairman         September 10, 2010   August 5, 2011

 

 

 Cecilia Elena Rouse   Member           March 11, 2009       February 28, 2011

 

 

 Katharine G. Abraham  Member           April 19, 2011

 

 

 Carl Shapiro          Member           April 19, 2011       May 4, 2012

 

 

 Alan B. Krueger       Chairman         November 7, 2011

 

 

 James H. Stock        Member           February 7, 2013

 

* * * * *

 

 

REPORT TO THE PRESIDENT

 

ON THE ACTIVITIES OF THE

 

COUNCIL OF ECONOMIC ADVISERS

 

DURING 2012

 

 

The Council of Economic Advisers was established by the Employment Act of 1946 to provide the President with objective economic analysis and advice on the development and implementation of a wide range of domestic and international economic policy issues. The Council is governed by a Chairman and two Members. The Chairman is appointed by the President and confirmed by the United States Senate. The Members are appointed by the President.

 

THE CHAIRMAN OF THE COUNCIL

 

 

Alan B. Krueger continued to chair the Council during 2012. Dr. Krueger is on a leave of absence from Princeton University, where he is the Bendheim Professor of Economics and Public Affairs. He served as Assistant Secretary for Economic Policy at the Treasury Department from 2009 to 2010.

Chairman Krueger is a member of the President's Cabinet and is responsible for communicating the Council's views on economic matters directly to the President through personal discussions and written reports. Chairman Krueger represents the Council at Presidential economic briefings, daily White House senior staff meetings, budget meetings, Cabinet meetings, a variety of inter-agency meetings, and other formal and informal meetings with the President, the Vice President, and other senior government officials. He also meets with members of Congress well as with business, academic and labor leaders to discuss economic policy issues.

 

THE MEMBERS OF THE COUNCIL

 

 

Katharine G. Abraham is a Member of the Council of Economic Advisers. She is on a leave of absence from the University of Maryland, where she is a faculty associate in the Maryland Population Research Center and a professor in the Joint Program in Survey Methodology. Dr. Abraham served as the Commissioner of the Bureau of Labor Statistics from 1993 to 2001.

James H. Stock was appointed by the President on February 7, 2013. He served as Chief Economist of the Council of Economic Advisers from September 12, 2012 until then. Dr. Stock is on leave from Harvard University, where he is the Harold Hitchings Burbank Professor of Political Economy. Dr. Stock served as the Chair of the Harvard University Department of Economics from 2006 to 2009.

Carl Shapiro resigned as Member of the Council on May 4, 2012 to return to the University of California, where he is the Transamerica Professor of Business Strategy at the Haas School of Business.

 

AREAS OF ACTIVITIES

 

 

A central function of the Council is to advise the President on all economic issues and developments. In the past year, as in the three previous years, advising the President on policies to spur economic growth and job creation, and evaluating the effects of the policies on the economy, have been a priority.

The Council works closely with various government agencies, including the National Economic Council, the Office of Management and Budget, White House senior staff, and other officials and engages in discussions on numerous policy matters. In the area of international economic policy, the Council coordinates with other units of the White House, the Treasury Department, the State Department, the Commerce Department, and the Federal Reserve on matters related to the global financial system.

Among the specific economic policy areas that received attention in 2012 were: housing policies, including foreclosure mitigation and prevention and refinancing; implementation of the Affordable Care Act; income inequality; individual and corporate taxation; college affordability; small business lending; regional development; intellectual property and innovation; infrastructure investment; regulatory measures; trade policies; unemployment insurance; job training; and policies to promote the international competitiveness of American manufacturing companies. The Council also worked on several issues related to the quality of the data available for assessing economic conditions.

The Council prepares for the President, the Vice President, and the White House senior staff a daily economic briefing memo analyzing current economic developments, and almost-daily memos on key economic data releases. Chairman Krueger has also presented regular monthly briefings on the state of the economy to senior White House officials.

The Council, the Department of Treasury, and the Office of Management and Budget -- the Administration's economic "troika" -- are responsible for producing the economic forecasts that underlie the Administration's budget proposals. The Council initiates the forecasting process twice each year, consulting with a wide variety of outside sources, including leading private sector forecasters and other government agencies.

The Council was an active participant in the trade policy process, participating in the Trade Policy Staff Committee and the Trade Policy Review Group. The Council provided analysis and opinions on a range of trade-related issues involving the enforcement of existing trade agreements, reviews of current U.S. trade policies, and consideration of future policies. The Council also participated on the Trade Promotion Coordinating Committee, helping to examine the ways in which exports may support economic growth in the years to come. In the area of investment and security, the Council participated on the Committee on Foreign Investment in the United States (CFIUS), reviewing individual cases before the committee.

Council Members and staff regularly met with economists, policy officials, and government officials from other countries to discuss issues relating to the global economy. The Council's role also included policy development and planning for the G-20 Summit in Saint Petersburg, Russia, and the G-8 Summit in Northern Ireland.

The Council is a leading participant in the Organisation for Economic Co-operation and Development (OECD), an important forum for economic cooperation among high-income industrial economies. The Council coordinated and oversaw the OECD's review of the U.S. economy. Dr. Krueger is chairman of the OECD's Economic Policy Committee, and Council Members and staff participate actively in working-party meetings on macroeconomic policy and coordination and contribute to the OECD's research agenda.

The Council issued a series of reports in 2012. In February, the Council released two reports: Supporting Retirement for American Families and The Economic Benefits of New Spectrum for Wireless Broadband. In May, the Council led the preparation of a White House report on the labor market situation of America's veterans. In June, the Council was a primary contributor to a White House report on job creation in rural communities. In November, the Council led the preparation of a White House report on the impact of tax cuts on the middle class and the subsequent effect on consumer spending and retailers. The Council continued its efforts to improve the public's understanding of economic developments and of the Administration's economic policies through briefings with the economic and financial press, speeches, discussions with outside economists, presentations to outside organizations, and regular updates on major data releases on the CEA blog. The Chairman and Members also regularly met to exchange views on the economy with the Chairman and Members of the Board of Governors of the Federal Reserve System.

 

PUBLIC INFORMATION

 

 

The Council's annual Economic Report of the President is an important vehicle for presenting the Administration's domestic and international economic policies. It is available for purchase through the Government Printing Office, and is viewable on the Internet at www.gpo.gov/erp.

The Council prepared numerous reports in 2012, and the Chairman and Members gave numerous public speeches. The reports and texts of speeches are available at the Council's website, www.whitehouse.gov/cea. Finally, the Council published the monthly Economic Indicators, which is available on-line at www.gpo.gov/economicindicators.

 

THE STAFF OF THE COUNCIL OF ECONOMIC ADVISERS

 

 

The staff of the Council consists of the senior staff, senior economists, economists, staff economists, research economists, a research assistant, and the administrative and support staff. The staff at the end of 2012 was:

 

Senior Staff

 

 

David P. Vandivier

 

Chief of Staff

 

 

Petra Smeltzer Starke

 

General Counsel

 

 

Steven N. Braun

 

Director of Macroeconomic Forecasting

 

 

Adrienne Pilot

 

Director of Statistical Office

 

 

Archana Snyder

 

Director of Finance and Administration

 

Senior Economists

 

 

Bevin Ashenmiller

 

Environment, Energy

 

 

Benjamin H. Harris

 

Tax, Budget

 

 

Susan Helper

 

Manufacturing, Innovation, Small Business

 

 

Chinhui Juhn

 

Labor

 

 

Paul Lengermann

 

Macroeconomics

 

 

Emily Y. Lin

 

Tax, Budget

 

 

Rodney D. Ludema

 

International

 

 

James M. Williamson

 

Agriculture, Transportation, Tax

 

 

Wesley Yin

 

Health, Housing

 

Economist

 

 

David Cho

 

Macroeconomics

 

Staff Economists

 

 

Nicholas Li

 

Labor, Health, Housing

 

 

Ben Meiselman

 

Macroeconomics, Public Finance

 

 

Nicholas Tilipman

 

Labor, Health, Immigration

 

 

Lee Tucker

 

Labor, Immigration, Housing

 

 

Jeffery Y. Zhang

 

Energy, Environment, Macroeconomics

 

Research Economists

 

 

Matthew L. Aks

 

Macroeconomics, International

 

 

Carys Golesworthy

 

International, Trade

 

 

Dina Grossman

 

Labor, Health, Immigration

 

 

Cordaye T. Ogletree

 

Energy, Environment, International Trade

 

 

Spencer Smith

 

Public Finance, Energy, Environment

 

 

Rudy Telles Jr

 

Agriculture, Tax

 

Research Assistant

 

 

Philip K. Lambrakos

 

Macroeconomics, International

 

Statistical Office

 

 

The Statistical Office gathers, administers, and produces statistical information for the Council. Duties include preparing the statistical appendix to the Economic Report of the President and the monthly publication Economic Indicators. The staff also creates background materials for economic analysis and verifies statistical content in Presidential memoranda. The Office serves as the Council's liaison to the statistical community.

Brian A. Amorosi

 

Statistical Analyst

 

 

Sarah Murray

 

Economic Statistician

 

Office of the Chairman

 

 

Michael P. Bourgeois

 

Special Assistant to the Chairman

 

 

Emily C. Berret

 

Special Assistant to the Members

 

 

Natasha S. Lawrence

 

Staff Assistant

 

Administrative Office

 

 

The Administrative Office provides general support for the Council's activities. This includes financial management, human resource management, travel, operations of facilities, security, information technology, and telecommunications management support.

Doris T. Searles

 

Administrative and Information

 

Management Specialist

 

 

Thomas F. Hunt

 

Staff Assistant

 

Interns

 

 

Student interns provide invaluable help with research projects, day-to-day operations, and fact-checking. Interns during the year were: Norm Dannen, Laura Du, Shawn Du, Conor Foley, Scott Freitag, Rebecca Freidman, Isaac Green, Sonya Huang, Christopher Kilgore, Zachary Kleinbart, Amaze Lusompa, Nathan Mayo, John McDonough, Joel Moore, Yolanda Ngo, Robert Owens, Scott Pippin, Katharine Rodihan, Charles Rubenfeld, Rebecca Sachs, Zachary Silvis, Craig Smyser, Michael Sullivan, David Wasser, William Weber, Derek Wu, and Barr Yaron.

 

DEPARTURES IN 2012

 

 

Judith K. Hellerstein left her position as Chief Economist of the Council in May, and she has returned to her position as Professor of Economics at the University of Maryland, College Park.

The senior economists who resigned in 2012 (with the institutions to which they returned after leaving the Council in parentheses) were: Gene Amromin (Federal Reserve Bank of Chicago), Lee G. Branstetter (Carnegie Mellon University, Heinz College), Thomas C. Buchmueller (University of Michigan, Ross School of Business), Lisa D. Cook (Michigan State University), Robert Johansson (U.S. Department of Agriculture), Craig T. Peters (Department of Justice), Charles R. Pierret (U.S. Bureau of Labor Statistics), and Daniel J. Vine (Federal Reserve Board).

The economist who departed in 2012 was Reid Stevens (UC, Berkeley). Reid served the CEA for more than two and a half years and was the first recipient of the Robert M. Solow Award for Distinguished Service.

The staff economists who departed in 2012 were Jeffrey Borowitz, Colleen M. Carey, Judd N.L. Cramer, and Edward Zhong.

The research economists who departed in 2012 at the were Julia H. Yoo and Pedro Spivakovsky-Gonzalez.

The research assistants who departed in 2012 were Sandra M. Levy, Carter Mundell and Seth H. Werfel.

Andres Bustamante resigned from his position as Special Assistant to the Chairman and Staff Economist to pursue other endeavors. Paige Shevlin resigned from her position as Special Assistant to the Chairman. Sharon Thomas resigned from her position as Administrative Support Assistant, after serving in the Federal Government for over 25 years. Lindsay M. Kuberka completed her detail as a statistical analyst and returned to the Census Bureau.

 

* * * * *

 

 

APPENDIX B

 

 

STATISTICAL TABLES RELATING TO INCOME,

 

EMPLOYMENT, AND PRODUCTION

 

 

                                CONTENTS

 

 

 NATIONAL INCOME OR EXPENDITURE

 

 

 B-1.   Gross domestic product, 1964-2012

 

 

 B-2.   Real gross domestic product, 1964-2012 324

 

 

 B-3.   Quantity and price indexes for gross domestic product, and

 

        percent changes, 1964-2012

 

 

 B-4.   Percent changes in real gross domestic product, 1964-2012

 

 

 B-5.   Contributions to percent change in real gross domestic product,

 

        1964-2012

 

 

 B-6.   Chain-type quantity indexes for gross domestic product,

 

        1964-2012

 

 

 B-7.   Chain-type price indexes for gross domestic product, 1964-2012

 

 

 B-8.   Gross domestic product by major type of product, 1964-2012

 

 

 B-9.   Real gross domestic product by major type of product, 1964-2012

 

 

 B-10.  Gross value added by sector, 1964-2012

 

 

 B-11.  Real gross value added by sector, 1964-2012

 

 

 B-12.  Gross domestic product (GDP) by industry, value added, in

 

        current dollars and as a percentage of GDP, 1981-2011

 

 

 B-13.  Real gross domestic product by industry, value added, and

 

        percent changes, 1981-2011

 

 

 B-14.  Gross value added of nonfinancial corporate business, 1964-2012

 

 

 B-15.  Gross value added and price, costs, and profits of nonfinancial

 

        corporate business, 1964-2012

 

 

 B-16.  Personal consumption expenditures, 1964-2012

 

 

 B-17.  Real personal consumption expenditures, 1995-2012

 

 

 B-18.  Private fixed investment by type, 1964-2012

 

 

 B-19.  Real private fixed investment by type, 1995-2012

 

 

 B-20.  Government consumption expenditures and gross investment by

 

        type, 1964-2012

 

 

 B-21.  Real government consumption expenditures and gross investment

 

        by type, 1995-2012

 

 

 B-22.  Private inventories and domestic final sales by industry,

 

        1964-2012

 

 

 B-23.  Real private inventories and domestic final sales by industry,

 

        1964-2012

 

 

 B-24.  Foreign transactions in the national income and product

 

        accounts, 1964-2012

 

 

 B-25.  Real exports and imports of goods and services, 1995-2012

 

 

 B-26.  Relation of gross domestic product, gross national product, net

 

        national product, and national income, 1964-2012

 

 

 B-27.  Relation of national income and personal income, 1964-2012

 

 

 B-28.  National income by type of income, 1964-2012

 

 

 B-29.  Sources of personal income, 1964-2012

 

 

 B-30.  Disposition of personal income, 1964-2012

 

 

 B-31.  Total and per capita disposable personal income and personal

 

        consumption expenditures, and per capita gross domestic

 

        product, in current and real dollars, 1964-2012

 

 

 B-32.  Gross saving and investment, 1964-2012

 

 

 B-33.  Median money income (in 2011 dollars) and poverty status of

 

        families and people, by race, 2002-2011

 

 

 POPULATION, EMPLOYMENT, WAGES, AND PRODUCTIVITY

 

 

 B-34.  Population by age group, 1940-2012

 

 

 B-35.  Civilian population and labor force, 1929-2012

 

 

 B-36.  Civilian employment and unemployment by sex and age, 1966-2012

 

 

 B-37.  Civilian employment by demographic characteristic, 1966-2012

 

 

 B-38.  Unemployment by demographic characteristic, 1966-2012

 

 

 B-39.  Civilian labor force participation rate and

 

        employment/population ratio, 1966-2012

 

 

 B-40.  Civilian labor force participation rate by demographic

 

        characteristic, 1972-2012

 

 

 B-41.  Civilian employment/population ratio by demographic

 

        characteristic, 1972-2012

 

 

 B-42.  Civilian unemployment rate, 1966-2012

 

 

 B-43.  Civilian unemployment rate by demographic characteristic,

 

        1972-2012

 

 

 B-44.  Unemployment by duration and reason, 1966-2012

 

 

 B-45.  Unemployment insurance programs, selected data, 1980-2012

 

 

 B-46.  Employees on nonagricultural payrolls, by major industry,

 

        1968-2012

 

 

 B-47.  Hours and earnings in private nonagricultural industries,

 

        1966-2012

 

 

 B-48.  Employment cost index, private industry, 1997-2012

 

 

 B-49.  Productivity and related data, business and nonfarm business

 

        sectors, 1963-2012

 

 

 B-50.  Changes in productivity and related data, business and nonfarm

 

        business sectors, 1963-2012

 

 

 PRODUCTION AND BUSINESS ACTIVITY

 

 

 B-51.  Industrial production indexes, major industry divisions,

 

        1965-2012

 

 

 B-52.  Industrial production indexes, market groupings, 1965-2012

 

 

 B-53.  Industrial production indexes, selected manufacturing

 

        industries, 1972-2012

 

 

 B-54.  Capacity utilization rates, 1965-2012

 

 

 B-55.  New construction activity, 1968-2012

 

 

 B-56.  New private housing units started, authorized, and completed and

 

        houses sold, 1967-2012

 

 

 B-57.  Manufacturing and trade sales and inventories, 1971-2012

 

 

 B-58.  Manufacturers' shipments and inventories, 1971-2012

 

 

 B-59.  Manufacturers' new and unfilled orders, 1971-2012

 

 

 PRICES

 

 

 B-60.  Consumer price indexes for major expenditure classes, 1969-2012

 

 

 B-61.  Consumer price indexes for selected expenditure classes,

 

        1969-2012

 

 

 B-62.  Consumer price indexes for commodities, services, and special

 

        groups, 1969-2012

 

 

 B-63.  Changes in special consumer price indexes, 1969-2012

 

 

 B-64.  Changes in consumer price indexes for commodities and services,

 

        1941-2012

 

 

 B-65.  Producer price indexes by stage of processing, 1966-2012

 

 

 B-66.  Producer price indexes by stage of processing, special groups,

 

        1974-2012

 

 

 B-67.  Producer price indexes for major commodity groups, 1966-2012

 

 

 B-68. Changes in producer price indexes for finished goods, 1973-2012

 

 

 MONEY STOCK, CREDIT, AND FINANCE

 

 

 B-69.  Money stock and debt measures, 1973-2012

 

 

 B-70.  Components of money stock measures, 1973-2012

 

 

 B-71.  Aggregate reserves of depository institutions and the monetary

 

        base, 1982-2012

 

 

 B-72.  Bank credit at all commercial banks, 1975-2012

 

 

 B-73.  Bond yields and interest rates, 1941-2012

 

 

 B-74.  Credit market borrowing, 2004-2012

 

 

 B-75.  Mortgage debt outstanding by type of property and of financing,

 

        1955-2012

 

 

 B-76.  Mortgage debt outstanding by holder, 1955-2012

 

 

 B-77.  Consumer credit outstanding, 1961-2012

 

 

 GOVERNMENT FINANCE

 

 

 B-78.  Federal receipts, outlays, surplus or deficit, and debt, fiscal

 

        years, 1946-2013

 

 

 B-79.  Federal receipts, outlays, surplus or deficit, and debt, as

 

        percent of gross domestic product, fiscal years 1940-2013

 

 

 B-80.  Federal receipts and outlays, by major category, and surplus or

 

        deficit, fiscal years 1946-2013

 

 

 B-81.  Federal receipts, outlays, surplus or deficit, and debt, fiscal

 

        years 2007-2012

 

 

 B-82.  Federal and State and local government current receipts and

 

        expenditures, national income and product accounts (NIPA),

 

        1964-2012

 

 

 B-83.  Federal and State and local government current receipts and

 

        expenditures, national income and product accounts (NIPA), by

 

        major type, 1964-2012

 

 

 B-84.  Federal Government current receipts and expenditures, national

 

        income and product accounts (NIPA), 1964-2012

 

 

 B-85.  State and local government current receipts and expenditures,

 

        national income and product accounts (NIPA), 1964-2012

 

 

 B-86.  State and local government revenues and expenditures, selected

 

        fiscal years, 1948-2010

 

 

 B-87.  U.S. Treasury securities outstanding by kind of obligation,

 

        1974-2012

 

 

 B-88.  Maturity distribution and average length of marketable

 

        interest-bearing public debt securities held by private

 

        investors, 1974-2012

 

 

 B-89.  Estimated ownership of U.S. Treasury securities, 1999-2012

 

 

 CORPORATE PROFITS AND FINANCE

 

 

 B-90.  Corporate profits with inventory valuation and capital

 

        consumption adjustments, 1964-2012

 

 

 B-91.  Corporate profits by industry, 1964-2012

 

 

 B-92.  Corporate profits of manufacturing industries, 1964-2012

 

 

 B-93.  Sales, profits, and stockholders' equity, all manufacturing

 

        corporations, 1971-2012

 

 

 B-94.  Relation of profits after taxes to stockholders' equity and to

 

        sales, all manufacturing corporations, 1963-2012

 

 

 B-95.  Historical stock prices and yields, 1949-2003

 

 

 B-96.  Common stock prices and yields, 2000-2012

 

 

 AGRICULTURE

 

 

 B-97.  Real farm income, 1950-2012

 

 

 B-98.  Farm business balance sheet, 1960-2012

 

 

 B-99.  Farm output and productivity indexes, 1950-2009

 

 

 B-100. Farm input use, selected inputs, 1950-2012

 

 

 B-101. Agricultural price indexes and farm real estate value,

 

        1975-2012

 

 

 B-102. U.S. exports and imports of agricultural commodities,

 

        1951-2012

 

 

 INTERNATIONAL STATISTICS

 

 

 B-103. U.S. international transactions, 1953-2012

 

 

 B-104. U.S. international trade in goods by principal end-use

 

        category, 1965-2012

 

 

 B-105. U.S. international trade in goods by area, 2004-2012

 

 

 B-106. U.S. international trade in goods on balance of payments (BOP)

 

        and Census basis, and trade in services on BOP basis, 1985-2012

 

 

 B-107. International investment position of the United States at

 

        year-end, 2005-2011

 

 

 B-108. Industrial production and consumer prices, major industrial

 

        countries, 1986-2012

 

 

 B-109. Civilian unemployment rate, and hourly compensation, major

 

        industrial countries, 1986-2012

 

 

 B-110. Foreign exchange rates, 1993-2012

 

 

 B-111. International reserves, selected years, 1992-2012

 

 

 B-112. Growth rates in real gross domestic product, 1994-2013

 

_____________________________________________________________________

 

 

General Notes

 

 

Detail in these tables may not add to totals because of rounding.

Because of the formula used for calculating real gross domestic product (GDP), the chained (2005) dollar estimates for the detailed components do not add to the chained-dollar value of GDP or to any intermediate aggregate. The Department of Commerce (Bureau of Economic Analysis) no longer publishes chained-dollar estimates prior to 1995, except for selected series.

Unless otherwise noted, all dollar figures are in current dollars.

Symbols used:

 

p Preliminary.

. . . Not available (also, not applicable).

 

Data in these tables reflect revisions made by the source agencies through January 30, 2013 with two exceptions. Current employment statistics (CES) estimates from the Department of Labor (Bureau of Labor Statistics) include revisions released February 1, 2013, and national income and product account (NIPA) estimates from the Department of Commerce (Bureau of Economic Analysis) incorporate revisions released on February 28, 2013.
_____________________________________________________________________

 

 

National Income or Expenditure

 

 

Table B-1. Gross domestic product, 1964-2012

 

 

[ Editor's Note: To view Table B-1,

 

see Doc 2013-6225 , p. 307.]

 

 

Table B-2. Real gross domestic product, 1964-2012

 

 

[ Editor's Note: To view Table B-2,

 

see Doc 2013-6225 , p. 309.]

 

 

Table B-3. Quantity and price indexes

 

for gross domestic product, and percent changes, 1964-2012

 

 

[ Editor's Note: To view Table B-3,

 

see Doc 2013-6225 , p. 311.]

 

 

Table B-4. Percent changes in real gross domestic product,

 

1964-2012

 

 

[ Editor's Note: To view Table B-4,

 

see Doc 2013-6225 , p. 312.]

 

 

Table B-5. Contributions to percent change

 

in real gross domestic product, 1964-2012

 

 

[ Editor's Note: To view Table B-5,

 

see Doc 2013-6225 , p. 313.]

 

 

Table B-6. Chain-type quantity indexes

 

for gross domestic product, 1964-2012

 

 

[ Editor's Note: To view Table B-6,

 

see Doc 2013-6225 , p. 315.]

 

 

Table B-7. Chain-type price indexes

 

for gross domestic product, 1964-2012

 

 

[ Editor's Note: To view Table B-7,

 

see Doc 2013-6225 , p. 317.]

 

 

Table B-8. Gross domestic product

 

by major type of product, 1964-2012

 

 

[ Editor's Note: To view Table B-8,

 

see Doc 2013-6225 , p. 319.]

 

 

Table B-9. Real gross domestic product

 

by major type of product, 1964-2012

 

 

[ Editor's Note: To view Table B-9,

 

see Doc 2013-6225 , p. 320.]

 

 

Table B-10. Gross value added by sector, 1964-2012

 

 

[ Editor's Note: To view Table B-10,

 

see Doc 2013-6225 , p. 321.]

 

 

Table B-11. Real gross value added by sector, 1964-2012

 

 

[ Editor's Note: To view Table B-11,

 

see Doc 2013-6225 , p. 322.]

 

 

Table B-12. Gross domestic product (GDP) by industry, value added,

 

in current dollars and as a percentage of GDP,

 

1981-2011

 

 

[ Editor's Note: To view Table B-12,

 

see Doc 2013-6225 , p. 323.]

 

 

Table B-13. Real gross domestic product by industry, value added,

 

and percent changes, 1981-2011

 

 

[ Editor's Note: To view Table B-13,

 

see Doc 2013-6225 , p. 325.]

 

 

Table B-14. Gross value added of nonfinancial corporate business,

 

1964-2012

 

 

[ Editor's Note: To view Table B-14,

 

see Doc 2013-6225 , p. 327.]

 

 

Table B-15. Gross value added and price, costs, and

 

profits of nonfinancial corporate business, 1964-2012

 

 

[ Editor's Note: To view Table B-15,

 

see Doc 2013-6225 , p. 328.]

 

 

Table B-16. Personal consumption expenditures, 1964-2012

 

 

[ Editor's Note: To view Table B-16,

 

see Doc 2013-6225 , p. 329.]

 

 

Table B-17. Real personal consumption expenditures, 1995-2012

 

 

[ Editor's Note: To view Table B-17,

 

see Doc 2013-6225 , p. 330.]

 

 

Table B-18. Private fixed investment by type, 1964-2012

 

 

[ Editor's Note: To view Table B-18,

 

see Doc 2013-6225 , p. 331.]

 

 

Table B-19. Real private fixed investment by type, 1995-2012

 

 

[ Editor's Note: To view Table B-19,

 

see Doc 2013-6225 , p. 332.]

 

 

Table B-20: Government consumption expenditures and

 

gross investment by type, 1964-2012

 

 

[ Editor's Note: To view Table B-20,

 

see Doc 2013-6225 , p. 333.]

 

 

Table B-21: Real government consumption expenditures and

 

gross investment by type, 1995-2012

 

 

[ Editor's Note: To view Table B-21,

 

see Doc 2013-6225 , p. 334.]

 

 

Table B-22: Private inventories and

 

domestic final sales by industry, 1964-2012

 

 

[ Editor's Note: To view Table B-22,

 

see Doc 2013-6225 , p. 335.]

 

 

Table B-23: Real private inventories and

 

domestic final sales by industry, 1964-2012

 

 

[ Editor's Note: To view Table B-23,

 

see Doc 2013-6225 , p. 336.]

 

 

Table B-24: Foreign transactions in the

 

national income and product accounts, 1964-2012

 

 

[ Editor's Note: To view Table B-24,

 

see Doc 2013-6225 , p. 337.]

 

 

Table B-25: Real exports and imports of goods and services,

 

1995-2012

 

 

[ Editor's Note: To view Table B-25,

 

see Doc 2013-6225 , p. 338.]

 

 

Table B-26: Relation of gross domestic product, gross national

 

product, net national product, and national income, 1964-2012

 

 

[ Editor's Note: To view Table B-26,

 

see Doc 2013-6225 , p. 339.]

 

 

Table B-27: Relation of national income and personal income,

 

1964-2012

 

 

[ Editor's Note: To view Table B-27,

 

see Doc 2013-6225 , p. 340.]

 

 

Table B-28: National income by type of income, 1964-2012

 

 

[ Editor's Note: To view Table B-28,

 

see Doc 2013-6225 , p. 341.]

 

 

Table B-29: Sources of personal income, 1964-2012

 

 

[ Editor's Note: To view Table B-29,

 

see Doc 2013-6225 , p. 343.]

 

 

Table B-30: Disposition of personal income, 1964-2012

 

 

[ Editor's Note: To view Table B-30,

 

see Doc 2013-6225 , p. 345.]

 

 

Table B-31: Total and per capita disposable personal income and

 

personal consumption expenditures, and per capita

 

gross domestic product, in current and real dollars, 1964-2012

 

 

[ Editor's Note: To view Table B-31,

 

see Doc 2013-6225 , p. 346.]

 

 

Table B-32: Gross saving and investment, 1964-2012

 

 

[ Editor's Note: To view Table B-32,

 

see Doc 2013-6225 , p. 347.]

 

 

Table B-33: Median money income (in 2011 dollars) and

 

poverty status of families and people, by race, 2002-2011

 

 

[ Editor's Note: To view Table B-33,

 

see Doc 2013-6225 , p. 349.]

 

 

Population, Employment, Wages, and Productivity

 

 

Table B-34: Population by age group, 1940-2012

 

 

[ Editor's Note: To view Table B-34,

 

see Doc 2013-6225 , p. 350.]

 

 

Table B-35: Civilian population and labor force, 1929-2012

 

 

[ Editor's Note: To view Table B-35,

 

see Doc 2013-6225 , p. 351.]

 

 

Table B-36: Civilian employment and unemployment by sex and age,

 

1966-2012

 

 

[ Editor's Note: To view Table B-36,

 

see Doc 2013-6225 , p. 353.]

 

 

Table B-37: Civilian employment by demographic characteristic,

 

1966-2012

 

 

[ Editor's Note: To view Table B-37,

 

see Doc 2013-6225 , p. 354.]

 

 

Table B-38: Unemployment by demographic characteristic,

 

1966-2012

 

 

[ Editor's Note: To view Table B-38,

 

see Doc 2013-6225 , p. 355.]

 

 

Table B-39: Civilian labor force participation rate and

 

employment/population ratio, 1966-2012

 

 

[ Editor's Note: To view Table B-39,

 

see Doc 2013-6225 , p. 356.]

 

 

Table B-40: Civilian labor force participation rate

 

by demographic characteristic, 1972-2012

 

 

[ Editor's Note: To view Table B-40,

 

see Doc 2013-6225 , p. 357.]

 

 

Table B-41: Civilian employment/population ratio

 

by demographic characteristic, 1972-2012

 

 

[ Editor's Note: To view Table B-41,

 

see Doc 2013-6225 , p. 358.]

 

 

Table B-42: Civilian unemployment rate, 1966-2012

 

 

[ Editor's Note: To view Table B-42,

 

see Doc 2013-6225 , p. 359.]

 

 

Table B-43: Civilian unemployment rate by

 

demographic characteristic, 1972-2012

 

 

[ Editor's Note: To view Table B-43,

 

see Doc 2013-6225 , p. 360.]

 

 

Table B-44: Unemployment by duration and reason, 1966-2012

 

 

[ Editor's Note: To view Table B-44,

 

see Doc 2013-6225 , p. 361.]

 

 

Table B-45: Unemployment insurance programs,

 

selected data, 1980-2012

 

 

[ Editor's Note: To view Table B-45,

 

see Doc 2013-6225 , p. 362.]

 

 

Table B-46: Employees on nonagricultural payrolls,

 

by major industry, 1968-2012

 

 

[ Editor's Note: To view Table B-46,

 

see Doc 2013-6225 , p. 363.]

 

 

Table B-47: Hours and earnings in private

 

nonagricultural industries, 1966-2012

 

 

[ Editor's Note: To view Table B-47,

 

see Doc 2013-6225 , p. 365.]

 

 

Table B-48: Employment cost index, private industry,

 

1997-2012

 

 

[ Editor's Note: To view Table B-48,

 

see Doc 2013-6225 , p. 366.]

 

 

Table B-49: Productivity and related data, business and

 

nonfarm business sectors, 1963-2012

 

 

[ Editor's Note: To view Table B-49,

 

see Doc 2013-6225 , p. 367.]

 

 

Table B-50: Changes in productivity and related data, business and

 

nonfarm business sectors, 1963-2012

 

 

[ Editor's Note: To view Table B-50,

 

see Doc 2013-6225 , p. 368.]

 

 

Production and Business Activity

 

 

Table B-51: Industrial production indexes,

 

major industry divisions, 1965-2012

 

 

[ Editor's Note: To view Table B-51,

 

see Doc 2013-6225 , p. 369.]

 

 

Table B-52: Industrial production indexes, market groupings,

 

1965-2012

 

 

[ Editor's Note: To view Table B-52,

 

see Doc 2013-6225 , p. 370.]

 

 

Table B-53: Industrial production indexes,

 

selected manufacturing industries, 1972-2012

 

 

[ Editor's Note: To view Table B-53,

 

see Doc 2013-6225 , p. 371.]

 

 

Table B-54: Capacity utilization rates, 1965-2012

 

 

[ Editor's Note: To view Table B-54,

 

see Doc 2013-6225 , p. 372.]

 

 

Table B-55: New construction activity, 1968-2012

 

 

[ Editor's Note: To view Table B-55,

 

see Doc 2013-6225 , p. 373.]

 

 

Table B-56: New private housing units started, authorized, and

 

completed and houses sold, 1967-2012

 

 

[ Editor's Note: To view Table B-56,

 

see Doc 2013-6225 , p. 374.]

 

 

Table B-57: Manufacturing and trade sales and inventories,

 

1971-2012

 

 

[ Editor's Note: To view Table B-57,

 

see Doc 2013-6225 , p. 375.]

 

 

Table B-58: Manufacturers' shipments and inventories,

 

1971-2012

 

 

[ Editor's Note: To view Table B-58,

 

see Doc 2013-6225 , p. 376.]

 

 

Table B-59: Manufacturers' new and unfilled orders,

 

1971-2012

 

 

[ Editor's Note: To view Table B-59,

 

see Doc 2013-6225 , p. 377.]

 

 

Prices

 

 

Table B-60: Consumer price indexes for major expenditure classes,

 

1969-2012

 

 

[ Editor's Note: To view Table B-60,

 

see Doc 2013-6225 , p. 378.]

 

 

Table B-61: Consumer price indexes for

 

selected expenditure classes, 1969-2012

 

 

[ Editor's Note: To view Table B-61,

 

see Doc 2013-6225 , p. 379.]

 

 

Table B-62: Consumer price indexes for commodities, services, and

 

special groups, 1969-2012

 

 

[ Editor's Note: To view Table B-62,

 

see Doc 2013-6225 , p. 381.]

 

 

Table B-63: Changes in special consumer price indexes,

 

1969-2012

 

 

[ Editor's Note: To view Table B-63,

 

see Doc 2013-6225 , p. 382.]

 

 

Table B-64: Changes in consumer price indexes for

 

commodities and services, 1941-2012

 

 

[ Editor's Note: To view Table B-64,

 

see Doc 2013-6225 , p. 383.]

 

 

Table B-65: Producer price indexes by stage of processing,

 

1966-2012

 

 

[ Editor's Note: To view Table B-65,

 

see Doc 2013-6225 , p. 384.]

 

 

Table B-66: Producer price indexes by stage of processing,

 

special groups, 1974-2012

 

 

[ Editor's Note: To view Table B-66,

 

see Doc 2013-6225 , p. 386.]

 

 

Table B-67: Producer price indexes for major commodity groups,

 

1966-2012

 

 

[ Editor's Note: To view Table B-67,

 

see Doc 2013-6225 , p. 387.]

 

 

Table B-68: Changes in producer price indexes for finished goods,

 

1973-2012

 

 

[ Editor's Note: To view Table B-68,

 

see Doc 2013-6225 , p. 389.]

 

 

Money, Stock, Credit, and Finance

 

 

Table B-69: Money stock and debt measures, 1973-2012

 

 

[ Editor's Note: To view Table B-69,

 

see Doc 2013-6225 , p. 390.]

 

 

Table B-70: Components of money stock measures, 1973-2012

 

 

[ Editor's Note: To view Table B-70,

 

see Doc 2013-6225 , p. 391.]

 

 

Table B-71: Aggregate reserves of depository institutions and the

 

monetary base, 1982-2012

 

 

[ Editor's Note: To view Table B-71,

 

see Doc 2013-6225 , p. 393.]

 

 

Table B-72: Bank credit all commercial banks, 1975-2012

 

 

[ Editor's Note: To view Table B-72,

 

see Doc 2013-6225 , p. 394.]

 

 

Table B-73: Bond yields and interest rates, 1941-2012

 

 

[ Editor's Note: To view Table B-73,

 

see Doc 2013-6225 , p. 395.]

 

 

Table B-74: Credit market borrowing, 2004-2012

 

 

[ Editor's Note: To view Table B-74,

 

see Doc 2013-6225 , p. 397.]

 

 

Table B-75: Mortgage debt outstanding by

 

type of property and of financing, 1955-2012

 

 

[ Editor's Note: To view Table B-75,

 

see Doc 2013-6225 , p. 399.]

 

 

Table B-76: Mortgage debt outstanding by holder, 1955-2012

 

 

[ Editor's Note: To view Table B-76,

 

see Doc 2013-6225 , p. 400.]

 

 

Table B-77: Consumer credit outstanding, 1961-2012

 

 

[ Editor's Note: To view Table B-77,

 

see Doc 2013-6225 , p. 401.]

 

 

Government Finance

 

 

Table B-78: Federal receipts, outlays, surplus or deficit,

 

and debt, fiscal years, 1946-2013

 

 

[ Editor's Note: To view Table B-78,

 

see Doc 2013-6225 , p. 402.]

 

 

Table B-79: Federal receipts, outlays, surplus or deficit,

 

and debt, as percent of gross domestic product, fiscal years,

 

1940-2013

 

 

[ Editor's Note: To view Table B-79,

 

see Doc 2013-6225 , p. 403.]

 

 

Table B-80: Federal receipts, and outlays, by major category, and

 

surplus or deficit, fiscal years, 1946-2013

 

 

[ Editor's Note: To view Table B-80,

 

see Doc 2013-6225 , p. 404.]

 

 

Table B-81: Federal receipts, outlays, surplus or deficit,

 

and debt, fiscal years 2007-2012

 

 

[ Editor's Note: To view Table B-81,

 

see Doc 2013-6225 , p. 405.]

 

 

Table B-82: Federal and State and local government current receipts

 

and expenditures, national income and product accounts (NIPA),

 

1964-2012

 

 

[ Editor's Note: To view Table B-82,

 

see Doc 2013-6225 , p. 406.]

 

 

Table B-83: Federal and State and local government current receipts

 

and expenditures, national income and product accounts (NIPA),

 

by major type, 1964-2012

 

 

[ Editor's Note: To view Table B-83,

 

see Doc 2013-6225 , p. 407.]

 

 

Table B-84: Federal Government current receipts and expenditures,

 

national income and product accounts (NIPA),

 

1964-2012

 

 

[ Editor's Note: To view Table B-84,

 

see Doc 2013-6225 , p. 408.]

 

 

Table B-85: State and local government current receipts and

 

expenditures, national income and product accounts (NIPA),

 

1964-2012

 

 

[ Editor's Note: To view Table B-85,

 

see Doc 2013-6225 , p. 409.]

 

 

Table B-86: State and local government revenues and expenditures,

 

selected fiscal years, 1948-2010

 

 

[ Editor's Note: To view Table B-86,

 

see Doc 2013-6225 , p. 410.]

 

 

Table B-87: U.S. Treasury securities outstanding by kind of

 

obligation, 1974-2012

 

 

[ Editor's Note: To view Table B-87,

 

see Doc 2013-6225 , p. 411.]

 

 

Table B-88: Maturity distribution and average length of marketable

 

interest-bearing public debt securities held by private investors,

 

1974-2012

 

 

[ Editor's Note: To view Table B-88,

 

see Doc 2013-6225 , p. 412.]

 

 

Table B-89: Estimated ownership of U.S. Treasury securities,

 

1999-2012

 

 

[ Editor's Note: To view Table B-89,

 

see Doc 2013-6225 , p. 413.]

 

 

Corporate Profits and Finance

 

 

Table B-90: Corporate profits with inventory valuation and

 

capital consumption adjustments, 1964-2012

 

 

[ Editor's Note: To view Table B-90,

 

see Doc 2013-6225 , p. 414.]

 

 

Table B-91: Corporate profits by industry, 1964-2012

 

 

[ Editor's Note: To view Table B-91,

 

see Doc 2013-6225 , p. 415.]

 

 

Table B-92: Corporate profits of manufacturing industries,

 

1964-2012

 

 

[ Editor's Note: To view Table B-92,

 

see Doc 2013-6225 , p. 416.]

 

 

Table B-93: Sales, profits and stockholders' equity,

 

all manufacturing corporations, 1971-2012

 

 

[ Editor's Note: To view Table B-93,

 

see Doc 2013-6225 , p. 417.]

 

 

Table B-94: Relation of profits after taxes to stockholders' equity

 

and to sales, all manufacturing corporations,

 

1963-2012

 

 

[ Editor's Note: To view Table B-94,

 

see Doc 2013-6225 , p. 418.]

 

 

Table B-95: Historical stock prices and yields, 1949-2003

 

 

[ Editor's Note: To view Table B-95,

 

see Doc 2013-6225 , p. 419.]

 

 

Table B-96: Common stock prices and yields, 2000-2012

 

 

[ Editor's Note: To view Table B-96,

 

see Doc 2013-6225 , p. 420.]

 

 

Agriculture

 

 

Table B-97: Real farm income, 1950-2012

 

 

[ Editor's Note: To view Table B-97,

 

see Doc 2013-6225 , p. 421.]

 

 

Table B-98: Farm business balance sheet, 1960-2012

 

 

[ Editor's Note: To view Table B-98,

 

see Doc 2013-6225 , p. 422.]

 

 

Table B-99: Farm output and productivity indexes, 1950-2009

 

 

[ Editor's Note: To view Table B-99,

 

see Doc 2013-6225 , p. 423.]

 

 

Table B-100: Farm input use, selected inputs, 1950-2012

 

 

[ Editor's Note: To view Table B-100,

 

see Doc 2013-6225 , p. 424.]

 

 

Table B-101: Agricultural price indexes and farm real estate value,

 

1975-2012

 

 

[ Editor's Note: To view Table B-101,

 

see Doc 2013-6225 , p. 425.]

 

 

Table B-102: U.S. exports and imports of agricultural commodities,

 

1951-2012

 

 

[ Editor's Note: To view Table B-102,

 

see Doc 2013-6225 , p. 426.]

 

 

International Statistics

 

 

Table B-103: U.S. international transactions, 1953-2012

 

 

[ Editor's Note: To view Table B-103,

 

see Doc 2013-6225 , p. 427.]

 

 

Table B-104: U.S. international trade in goods by

 

principal end-use category, 1965-2012

 

 

[ Editor's Note: To view Table B-104,

 

see Doc 2013-6225 , p. 429.]

 

 

Table B-105: U.S. international trade in goods by area,

 

2004-2012

 

 

[ Editor's Note: To view Table B-105,

 

see Doc 2013-6225 , p. 430.]

 

 

Table B-106: U.S. international trade in goods on

 

balance of payments (BOP) and Census basis,

 

and trade in services on BOP basis, 1985-2012

 

 

[ Editor's Note: To view Table B-106,

 

see Doc 2013-6225 , p. 431.]

 

 

Table B-107: International investment position of the

 

United States at year-end, 2005-2011

 

 

[ Editor's Note: To view Table B-107,

 

see Doc 2013-6225 , p. 432.]

 

 

Table B-108: Industrial production and consumer prices,

 

major industrial countries, 1986-2012

 

 

[ Editor's Note: To view Table B-108,

 

see Doc 2013-6225 , p. 433.]

 

 

Table B-109: Civilian unemployment rate, and hourly compensation,

 

major industrial countries, 1986-2012

 

 

[ Editor's Note: To view Table B-109,

 

see Doc 2013-6225 , p. 434.]

 

 

Table B-110: Foreign exchange rates, 1993-2012

 

 

[ Editor's Note: To view Table B-110,

 

see Doc 2013-6225 , p. 435.]

 

 

Table B-111: International reserves, selected years,

 

1992-2012

 

 

[ Editor's Note: To view Table B-111,

 

see Doc 2013-6225 , p. 436.]

 

 

Table B-112: Growth rates in real gross domestic product,

 

1994-2013

 

 

[ Editor's Note: To view Table B-112,

 

see Doc 2013-6225 , p. 437.]
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