Accurate measurement of key income variables plays a crucial role in economic research and policy decision-making. However, the presence of item nonresponse and measurement error in survey data can cause biased estimates. These biases can subsequently lead to sub-optimal policy decisions and inefficient allocation of resources. While there have been various studies documenting item nonresponse and measurement error in economic data, there have not been many studies investigating interventions that could reduce item nonresponse and measurement error. In our research, we investigate the impact of monetary incentives on reducing item nonresponse and measurement error for labor and investment income in the Survey of Income and Program Participation (SIPP). Our study utilizes a randomized incentive experiment in Waves 1 and 2 of the 2014 SIPP, which allows us to assess the effectiveness of incentives in reducing item nonresponse and measurement error. We find that households receiving incentives had item nonresponse rates that are 1.3 percentage points lower for earnings and 1.5 percentage points lower for Social Security income. Measurement error was 6.31 percentage points lower at the intensive margin for interest income, and 16.48 percentage points lower for dividend income compared to non-incentive recipient households. These findings provide valuable insights for data producers and users and highlight the importance of implementing strategies to improve data quality in economic research.
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An Analysis of Sample Selection and the Reliability of Using Short-term Earnings Averages in SIPP-SSA Matched Data
December 2011
Working Paper Number:
CES-11-39
In this paper, we document the extent to which the sample of the Survey of Income and Program Participation that is matched to the Social Security Administration's administrative earnings records is nationally representative. We conclude that the match bias is small, so selection is not a serious concern. The matched sample over-represents individuals who are wealthy, who have financial assets or who have received a government-transfer and under-represents individuals who attrited from the SIPP. We use this matched sample to examine the relationship between short-term averages of earnings from the SIPP earnings and average lifetime earnings from the administrative records. Our estimates suggest that using short averages of earnings may understate the effects of permanent income on particular outcomes of interest.
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Self-Employment Income Reporting on Surveys
April 2023
Working Paper Number:
CES-23-19
We examine the relation between administrative income data and survey reports for self-employed and wage-earning respondents from 2000 - 2015. The self-employed report 40 percent more wages and self-employment income in the survey than in tax administrative records; this estimate nets out differences between these two sources that are also shared by wage-earners. We provide evidence that differential reporting incentives are an important explanation of the larger self-employed gap by exploiting a well-known artifact ' self-employed respondents exhibit substantial bunching at the
first EITC kink in their administrative records. We do not observe the same behavior in their survey responses even after accounting for survey measurement concerns.
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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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Childhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing
January 2013
Working Paper Number:
CES-13-48RR
To date, research on the long-term effects of childhood participation in voucher-assisted and public housing has been limited by the lack of data and suitable identification strategies. We create a national level longitudinal data set that enables us to analyze how children's housing experiences affect adult earnings and incarceration rates. While naive estimates suggest there are substantial negative consequences to childhood participation in voucher assisted and public housing, this result appears to be driven largely by selection of households into housing assistance programs. To mitigate this source of bias, we employ household fixed-effects specifications that use only within-household (across-sibling) variation for identification. Compared to naive specifications, household fixed-effects estimates for earnings are universally more positive, and they suggest that there are positive and statistically significant benefits from childhood residence in assisted housing on young adult earnings for nearly all demographic groups. Childhood participation in assisted housing also reduces the likelihood of incarceration across all household race/ethnicity groups. Time spent in voucher-assisted or public housing is especially beneficial for females from non-Hispanic Black households, who experience substantial increases in expected earnings and lower incarceration rates.
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Parental Earnings and Children's Well-Being and Future Success: An Analysis of the SIPP Matched to SSA Earnings Data
April 2011
Working Paper Number:
CES-11-12
We estimate the association between parental earnings and a wide variety of indicators of child well-being using data from the Survey of Income and Program Participation (SIPP) matched to administrative earnings records from the Social Security Administration. We find that the use of longer time averages of parent earnings leads to substantially higher estimated effects compared to using only a single year of parent earnings. This suggests that previous studies may have understated the potential efficacy of income support programs to improve child well-being. Further, policy makers should take into account the attenuation bias when comparing studies that use different time spans to measure parental income. Using 7 year time averages of parent earnings, we show for example, that a doubling of parent earnings reduces the probability of a teenager reporting being in poor health by close to 50 percent and a child having insufficient food by 75 percent.
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Measuring Income of the Aged in Household Surveys: Evidence from Linked Administrative Records
June 2024
Working Paper Number:
CES-24-32
Research has shown that household survey estimates of retirement income (defined benefit pensions and defined contribution account withdrawals) suffer from substantial underreporting which biases downward measures of financial well-being among the aged. Using data from both the redesigned 2016 Current Population Survey Annual Social and Economic Supplement (CPS ASEC) and the Health and Retirement Study (HRS), each matched with administrative records, we examine to what extent underreporting of retirement income affects key statistics such as reliance on Social Security benefits and poverty among the aged. We find that underreporting of retirement income is still prevalent in the CPS ASEC. While the HRS does a better job than the CPS ASEC in terms of capturing retirement income, it still falls considerably short compared to administrative records. Consequently, the relative importance of Social Security income remains overstated in household surveys'53 percent of elderly beneficiaries in the CPS ASEC and 49 percent in the HRS rely on Social Security for the majority of their incomes compared to 42 percent in the linked administrative data. The poverty rate for those aged 65 and over is also overstated'8.8 percent in the CPS ASEC and 7.4 percent in the HRS compared to 6.4 percent in the linked administrative data. Our results illustrate the effects of using alternative data sources in producing key statistics from the Social Security Administration's Income of the Aged publication.
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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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Neighborhood Income and Material Hardship in the United States
January 2022
Working Paper Number:
CES-22-01
U.S. households face a number of economic challenges that affect their well-being. In this analysis we focus on the extent to which neighborhood economic conditions contribute to hardship. Specifically, using data from the 2008 and 2014 Survey of Income and Program Participation panel surveys and logistic regression, we analyze the extent to which neighborhoods income levels affect the likelihood of experiencing seven types of hardships, including trouble paying bills, medical need, food insecurity, housing hardship, ownership of basic consumer durables, neighborhood problems, and fear of crime. We find strong bivariate relationships between neighborhood income and all hardships, but for most hardships these are explained by other household characteristics, such as household income and education. However, neighborhood income retains a strong association with two hardships in particular even when controlling for a variety of other household characteristics: neighborhood conditions (such as the presence of trash and litter) and fear of crime. Our study highlights the importance of examining multiple measures when assessing well-being, and our findings are consistent with the notion that collective socialization and community-level structural features affect the likelihood that households experience deleterious neighborhood conditions and a fear of crime.
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The Measurement of Medicaid Coverage in the SIPP: Evidence from California, 1990-1996
September 2002
Working Paper Number:
CES-02-21
This paper studies the accuracy of reported Medicaid coverage in the Survey of Income and Program Participation (SIPP) using a unique data set formed by matching SIPP survey responses to administrative records from the State of California. Overall, we estimate that the SIPP underestimates Medicaid coverage in the California populaton by about 10 percent. Among SIPP respondents who can be matched to administrative records, we estimate that the probability someone reports Medicaid coverage in a month when they are actually covered is around 85 percent. The corresponding probability for low-income children is even higher ' at least 90 percent. These estimates suggest that the SIPP provides reasonably accurate coverage reports for those who are actually in the Medicaid system. On the other hand, our estimate of the false positive rate (the rate of reported coverage for those who are not covered in the administrative records) is relatively high: 2.5 percent for the sample as a whole, and up to 20 percent for poor children. Some of this is due to errors in the recording of Social Security numbers in the administrative system, rather than to problems in the SIPP.
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Criminal court fees, earnings, and expenditures: A multi-state RD analysis of survey and administrative data
February 2023
Working Paper Number:
CES-23-06
Millions of people in the United States face fines and fees in the criminal court system each year, totaling over $27 billion in overall criminal debt to-date. In this study, we leverage five distinct natural experiments in Florida, Michigan, North Carolina, Texas, and Wisconsin using regression discontinuity designs to evaluate the causal impact of such financial sanctions and user fees. We consider a range of long-term outcomes including employment, recidivism, household expenditures, and other self-reported measures of well-being, which we measure through a combination of administrative records on earnings and employment, the Criminal Justice Administrative Records System, and household surveys. We find consistent evidence across the range of natural experiments and subgroup analyses of precise null effects on the population, ruling out long-run impacts larger than +/-3.6% on total earnings and +/-4.7% on total recidivism. Failure to find changes in outcomes undermines popular narratives of poverty traps arising from criminal debt but argues against the use of fines and fees as a source of local revenue and as a crime control tool.
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