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New Approaches for Measuring Poverty

Paper Session

Friday, Jan. 3, 2020 8:00 AM - 10:00 AM (PST)

Marriott Marquis, Rancho Santa Fe 2
Hosted By: American Economic Association
  • Chair: David S. Johnson, University of Michigan

Evaluating the Success of President Johnson’s War on Poverty: Revisiting the Historical Record Using a Full-Income Poverty Measure

Richard V. Burkhauser
,
Cornell University
Kevin Corinth
,
Council of Economic Advisers
James Elwell
,
Cornell University
Jeff Larrimore
,
Federal Reserve Board

Abstract

To evaluate success in President Johnson’s War on Poverty it is necessary to evaluate that success based on his scientifically arbitrary but policy relevant terms of engagement. No existing poverty measure is capable of measuring its success. We do so here by developing a Full-Income Poverty Measure (FPM) anchored to the Official Poverty Measure in 1963 (approximately equal to the one-fifth of Americans President Johnson declared to be in poverty at that time). We update nominal FPM thresholds for inflation each year and include as resources all sources of income (incorporating taxes as well as cash and in-kind transfers, including the market value of employer and government provided health insurance). Using Current Population Survey data, we show that our FPM-based poverty rate fell from 19.5 percent in 1963 to 2.3 percent in 2017. This compares to a reduction from 19.5 to 12.3 percent over the same period based on the Official Poverty Measure. Our wider income definition, the use of a more accurate inflation measure, and the use of a household rather than a family sharing unit are important drivers of this difference in poverty trends.

Potential Improvements to the Census Bureau’s Supplemental Poverty Measure for 2021

Liana Fox
,
U.S. Census Bureau
Thesia Garner
,
U.S. Bureau of Labor Statistics
Juan Munoz
,
U.S. Bureau of Labor Statistics
Laryssa Mykyta
,
University of Texas-Rio Grande Valley
Trudi Renwick
,
U.S. Census Bureau

Abstract

Following decades of research on poverty measurement and guidance from a National Academies of Sciences Panel and the Interagency Technical Working Group on Developing a Supplemental Poverty Measure (SPM), in 2011 the Census Bureau released the first annual SPM report. Since this first publication, no major changes have been made to the SPM, but research has been ongoing at the BLS and Census Bureau on potential improvements and validation of prior assumptions. The Office of Management and Budget (OMB) has established a new interagency technical working group, which has set 2021 as a target for making methodological improvements to the measure.

This paper examines the impact of various proposed improvements to the SPM on poverty rates overall and for major demographic groups. The proposals under consideration include several changes to the methodology for establishing the SPM poverty thresholds including, but not limited to: changing the range of expenditures which serve as the basis for the thresholds, expanding the estimation sample upon which the thresholds are based, imputing noncash transfers into thresholds, and applying alternative geographic adjustments using Regional Price Parities produced by the Bureau of Economic Analysis and/or an adjustment to reflect amenities. The final change to the SPM under consideration in this paper would change the methodology for assigning a value to nutritional assistance programs in the calculation of available resources. Using data from the Survey of Income and Program Participation (SIPP) as well as administrative data, this proposal explores the possibility of imputing school breakfast values (in addition to school lunch) and allowing WIC values to vary by state. Poverty and related statistics will be presented which highlight the impact of the planned improvements to the SPM.

Poverty in the United States Using the Comprehensive Income Dataset

Bruce Meyer
,
University of Chicago
Derek Wu
,
University of Chicago

Abstract

This paper provides new estimates of poverty in the United States using a groundbreaking set of linked survey and administrative data. The administrative data cover earnings, asset, and retirement income from IRS tax records, as well as transfer income for a myriad of safety net programs including Social Security, SSI, SNAP, housing assistance, and veterans’ benefits. We link these data to the Current Population Survey (the source of official poverty and inequality statistics) and the Survey of Income and Program Participation (the most comprehensive survey of income sources in the U.S.). Linking the administrative data to the surveys is vital given that surveys miss a large and rising share of income sources. Using these linked data, we find in the CPS that 55% fewer individuals are in poverty after incorporating taxes and in-kind transfers and correcting for measurement error using the administrative data. The corrections for measurement error are more important in percentage terms than the conceptual changes to income. Accounting for service flows from home and car ownership in the SIPP removes an additional 12% of individuals from poverty. We observe a demographic shift in the composition of the poor, with our adjustments leading to significantly more single individuals and fewer families with children in poverty. These estimated reductions in poverty are partly due to surveys underestimating the value of the anti-poverty effects of government programs like SNAP, the EITC, housing assistance, and SSI. We also find that incorporating taxes and in-kind transfers leads to a weaker correlation between income poverty and material deprivation, while accounting for assets and the administrative data leads to a stronger correlation between income poverty and material deprivation.
Discussant(s)
David S. Johnson
,
University of Michigan
Timothy Smeeding
,
University of Wisconsin-Madison
JEL Classifications
  • I3 - Welfare, Well-Being, and Poverty