The Census Bureau prepared a number of alternative income-based measures of poverty to illustrate the distributional impacts of several alternatives to the official measure. The paper examines five income variants for two different units of analysis (families and households) for two different assumptions about inflation (the historical Consumer Price Index and a 'Research Series' alternative that uses current methods) for two different sets of thresholds (official and a formula-based alternative base on three parameters). The poverty rate effects are analyzed for the total population, the distributional effects are analyzed using poverty shares, and the anti-poverty effects of taxes and transfers are analyzed using a percentage reduction in poverty rates. Suggestions for future research are included.
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Measuring Poverty in the United States: History and Current Issues
April 2006
Working Paper Number:
CES-06-11
Formal measurement of poverty in the United States is now about 40 years old. This paper first briefly describes the origins and basis of the official poverty thresholds adopted by the federal government in the late 1960s. Then, it discusses in some detail some of the more current issues that observers suggest must be addressed if changes are to be made. The final sections discuss recent efforts to propose alternates to the current official approach.
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Recent Trends in Top Income Shares in the USA: Reconciling Estimates from March CPS and IRS Tax Return Data
September 2009
Working Paper Number:
CES-09-26
Although the vast majority of US research on trends in the inequality of family income is based on public-use March Current Population Survey (CPS) data, a new wave of research based on Internal Revenue Service (IRS) tax return data reports substantially higher levels of inequality and faster growing trends. We show that these apparently inconsistent estimates can largely be reconciled once one uses internal CPS data (which better captures the top of the income distribution than public-use CPS data) and defines the income distribution in the same way. Using internal CPS data for 1967'2006, we closely match the IRS data-based estimates of top income shares reported by Piketty and Saez (2003), with the exception of the share of the top 1 percent of the distribution during 1993'2000. Our results imply that, if inequality has increased substantially since 1993, the increase is confined to income changes for those in the top 1 percent of the distribution.
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Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net
October 2015
Working Paper Number:
CES-15-35
We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics, but provide evidence that our qualitative conclusions are likely to apply to other surveys. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the individual level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing assistance. We find that the survey data sharply understate the income of poor households, as conjectured in past work by one of the authors. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. Using the administrative measures of program receipt rather than the survey ones often reduces the share of single mothers falling through the safety net by one-half or more.
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Estimating Trends in U.S. Income Inequality Using the Current Population Survey: The Importance of Controlling for Censoring
August 2008
Working Paper Number:
CES-08-25
Using internal and public use March Current Population Survey (CPS) data, we analyze trends in US income inequality (1975'2004). We find that the upward trend in income inequality prior to 1993 significantly slowed thereafter once we control for top coding in the public use data and censoring in the internal data. Because both series do not capture trends at the very top of the income distribution, we use a multiple imputation approach in which values for censored observations are imputed using draws from a Generalized Beta distribution of the Second Kind (GB2) fitted to internal data. Doing so, we find income inequality trends similar to those derived from unadjusted internal data. Our trend results are generally robust to the choice of inequality index, whether Gini coefficient or other commonly-used indices. When we compare our best estimates of the income shares held by the richest tenth with those reported by Piketty and Saez (2003), our trends fairly closely match their trends, except for the top 1 percent of the distribution. Thus, we argue that if United States income inequality has been substantially increasing since 1993, such increases are confined to this very high income group.
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The Antipoverty Impact of the EITC: New Estimates from Survey and Administrative Tax Records
April 2019
Working Paper Number:
CES-19-14R
We reassess the antipoverty effects of the EITC using unique data linking the CPS Annual Social and Economic Supplement to IRS data for the same individuals spanning years 2005-2016. We compare EITC benefits from standard simulators to administrative EITC payments and find that significantly more actual EITC payments flow to childless tax units than predicted, and to those whose family income places them above official poverty thresholds. However, actual EITC payments appear to be target efficient at the tax unit level. In 2016, about 3.1 million persons were lifted out of poverty by the EITC, substantially less than prior estimates.
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Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation
April 2011
Working Paper Number:
CES-11-14
Benefit receipt in major household surveys is often underreported. This misreporting leads to biased estimates of the economic circumstances of disadvantaged populations, program takeup, and the distributional effects of government programs, and other program effects. We use administrative data on Food Stamp Program (FSP) participation matched to American Community Survey (ACS) and Current Population Survey (CPS) household data. We show that nearly thirty-five percent of true recipient households do not report receipt in the ACS and fifty percent do not report receipt in the CPS. Misreporting, both false negatives and false positives, varies with individual characteristics, leading to complicated biases in FSP analyses. We then directly examine the determinants of program receipt using our combined administrative and survey data. The combined data allow us to examine accurate participation using individual characteristics missing in administrative data. Our results differ from conventional estimates using only survey data, as such estimates understate participation by single parents, non-whites, low income households, and other groups. To evaluate the use of Census Bureau imputed ACS and CPS data, we also examine whether our estimates using survey data alone are closer to those using the accurate combined data when imputed survey observations are excluded. Interestingly, excluding the imputed observations leads to worse ACS estimates, but has less effect on the CPS estimates.
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DOES FAMILY PLANNING INCREASE CHILDREN'S OPPORTUNITIES?
EVIDENCE FROM THE WAR ON POVERTY AND THE EARLY YEARS OF TITLE X
January 2016
Working Paper Number:
CES-16-29
This paper examines the relationship between parents' access to family planning and the economic resources of the average child. Using the county-level introduction of U.S. family planning programs between 1964 and 1973, we find that children born after programs began had 2.5% higher household incomes. They were also 7% less likely to live in poverty and 11% less likely to live in households receiving public assistance. Even with extreme assumptions about selection, these estimates are large enough to imply that family planning programs directly increased children's resources, including increases in mothers' paid work and increased childbearing within marriage.
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Capturing More Than Poverty: School Free and Reduced-Price Lunch Data and Household Income
December 2017
Working Paper Number:
carra-2017-09
Educational researchers often use National School Lunch Program (NSLP) data as a proxy for student poverty. Under NSLP policy, students whose household income is less than 130 percent of the poverty line qualify for free lunch and students whose household income is between 130 percent and 185 percent of the poverty line qualify for reduced-price lunch. Linking school administrative records for all 8th graders in a California public school district to household-level IRS income tax data, we examine how well NSLP data capture student disadvantage. We find both that there is substantial disadvantage in household income not captured by NSLP category data, and that NSLP categories capture disadvantage on test scores above and beyond household income.
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Do Doubled-up Families Minimize Household-level Tax Burden?
September 2014
Working Paper Number:
carra-2014-13
This paper examines a method of tax avoidance not previously studied: the sorting of dependent children among related filers who have 'doubled up' in a household for economic reasons. Using the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) linked with 1040 data from the Internal Revenue Service (IRS), we examine households with children and at least two adult tax filers to determine whether the household minimizes income tax burden, and thus maximizes refunds, by optimally claiming dependents. We examine specifically the relationship between the Earned Income Tax Credit (EITC) and the sorting of dependent children among filers in households. We find the following: The propensity to sort increases as the number of filers who are potentially eligible for the EITC increases; sorting probability increases as the optimal household EITC amount increases; and among households with at least one EITC-eligible filer, the propensity to sort increases as the difference between modeled household EITC amount and the optimal amount increases. We also exploit the 2009 change in EITC benefit for families with three or more children, finding that the propensity to sort to exactly three children increased among EITC-eligible filers after the rule change. The results of this analysis improve our understanding of filing behavior, particularly how households form filing units and pool resources, and have implications for poverty measurement in complex households This presentation was given at the CARRA Seminar, July 16, 2014
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Evaluating the Use of Commercial Data to Improve Survey Estimates of Property Taxes
August 2016
Working Paper Number:
carra-2016-06
While commercial data sources offer promise to statistical agencies for use in production of official statistics, challenges can arise as the data are not collected for statistical purposes. This paper evaluates the use of 2008-2010 property tax data from CoreLogic, Inc. (CoreLogic), aggregated from county and township governments from around the country, to improve 2010 American Community Survey (ACS) estimates of property tax amounts for single-family homes. Particularly, the research evaluates the potential to use CoreLogic to reduce respondent burden, to study survey response error and to improve adjustments for survey nonresponse. The research found that the coverage of the CoreLogic data varies between counties as does the correspondence between ACS and CoreLogic property taxes. This geographic variation implies that different approaches toward using CoreLogic are needed in different areas of the country. Further, large differences between CoreLogic and ACS property taxes in certain counties seem to be due to conceptual differences between what is collected in the two data sources. The research examines three counties, Clark County, NV, Philadelphia County, PA and St. Louis County, MO, and compares how estimates would change with different approaches using the CoreLogic data. Mean county property tax estimates are highly sensitive to whether ACS or CoreLogic data are used to construct estimates. Using CoreLogic data in imputation modeling for nonresponse adjustment of ACS estimates modestly improves the predictive power of imputation models, although estimates of county property taxes and property taxes by mortgage status are not very sensitive to the imputation method.
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