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Social Indicators Research

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01-01-2019 | Original Research

The Effect of Benefit Underreporting on Estimates of Poverty in the United States

Author: Zachary Parolin

Published in: Social Indicators Research | Issue 2/2019

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Abstract

The household income data used most frequently to estimate poverty rates in the United States substantially underreports the value of means-tested transfers. This paper investigates how underreporting affects estimates of the incidence and composition of poverty in the U.S. from 2013 to 2015. Specifically, I apply benefit adjustments for the underreporting of three social transfers to the Current Population Survey (CPS ASEC) to provide more accurate estimates of poverty rates. Diagnostic checks indicate that the imputed benefit adjustments are imperfect, but do provide a more accurate representation of household income than the uncorrected CPS data. In 2015, the benefit adjustments add more than $30 billion of income transfers to the CPS ASEC, primarily concentrated among low-income households with children. I test the effects of the benefit corrections on two conceptualizations of poverty: the U.S. Supplemental Poverty Measure (SPM) and a relative measure of poverty set at 50% of federal median income. In 2015, the SPM poverty rate for the total population falls from 14.3 to 12.7%, a 1.6 percentage point (11%) decline, after adjusting for underreporting. Among children, the SPM poverty rate falls from 16.1 to 12.8%, a 3.3 percentage point (20%) decline. The percent-of-median poverty rate experiences similar declines after applying the benefit imputations. The findings suggest that the uncorrected CPS data meaningfully overestimates the incidence of poverty in the U.S., particularly among households with children. Documentation for applying the benefit adjustments to the CPS is provided for improved estimates in future poverty research.

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Each year, some survey respondents do not answer the survey questions on the value of social program programs (item nonresponse). The Census Bureau allocates participation and benefit values to households that do not provide a response, but are estimated to be participating in the given benefit (Wheaton and Tran 2018). Thus, what starts as a ‘missing data’ issue becomes a potential source of measurement error (if the imputed values are different from the true values) in the version of the CPS ASEC made public. The large majority of survey respondents, however, do provide answers to all social transfer questions (Kasprzyk 2005).

If a survey respondent mistakenly reported SSI benefits as SSDI benefits, it is possible that adjusting for the underreporting of SSI while not adjusting SSDI benefits may double count the income source. This would, in turn, affect the TRIM3-adjusted poverty estimates presented in this paper. To account for that possibility, I present revised poverty estimates disaggregated by program in “Appendix 3” type to clarify how TRIM3 would affect poverty rates even if the SSI adjustments were to be excluded. I thank an anonymous reviewer for bringing this to my attention.

I use the “source of welfare income” variable in the CPS ASEC to separate TANF benefits from other public assistance programs, such as state-provided General Assistance. When a respondent indicates that the source of his/her welfare income is both TANF and non-TANF assistance, I opt to include the total value in my calculation of TANF benefits. As the number of such cases is small (0.01% of respondents), removing the combined value from TANF calculations makes no substantive difference to the findings presented here.

TRIM3 creates replicates of immigrant households in its simulations to account for uncertainty in ‘undocumented status’ versus ‘legal permanent resident status’ when allocating transfer benefits. In utilizing the TRIM3-adjusted survey data, researchers can choose to either keep the replicate households and use a TRIM3-provided weight, or to re-aggregate the cloned households back into a single household, in which case the CPS-provided weights can be utilized. As detailed in the replication dofiles in “Appendix 4”, I convert the cloned households back into their original households. I follow TRIM3 guidelines in utilizing the replication weights to aggregate the TRIM3-adjusted benefits back to the original household level.

Access to administrative records on benefit dispersal that can be integrated into survey data are heavily restricted and not available for public use. Moreover, these records are generally available for only a small subset of states, as described before. Therefore, I am unable to compare the distribution of TRIM3 benefits directly to linked administrative-survey records.

Removing SNAP, TANF, and SSI transfers from income provides a clearer account of to whom the TRIM3-adjusted benefits are being transferred. If I were to already take the transfers into account, this would affect the underlying income distribution (the X-axes of Fig. 2). For example, the zero-income households receiving SNAP benefits would no longer appear as zero-income households if SNAP benefits were already included.

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Title: The Effect of Benefit Underreporting on Estimates of Poverty in the United States
Author: Zachary Parolin
Publication date: 01-01-2019
Publisher: Springer Netherlands
Published in: Social Indicators Research / Issue 2/2019
Print ISSN: 0303-8300
Electronic ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-018-02053-0

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