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The Icing on the Cake: The Effects of Monetary Incentives on Income Data Quality in the SIPP

January 2024

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The 10 most similar working papers to the working paper 'The Icing on the Cake: The Effects of Monetary Incentives on Income Data Quality in the SIPP' are listed below in order of similarity.

• Working Paper

  
  
  An Analysis of Sample Selection and the Reliability of Using Short-term Earnings Averages in SIPP-SSA Matched Data
  

  December 2011

  Authors: Bhashkar Mazumder, Jonathan Davis

  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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• Working Paper

  
  
  Parental Earnings and Children's Well-Being and Future Success: An Analysis of the SIPP Matched to SSA Earnings Data
  

  April 2011

  Authors: Bhashkar Mazumder, Jonathan Davis

  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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• Working Paper

  
  
  Self-Employment Income Reporting on Surveys
  

  April 2023

  Authors: John Voorheis, Christian Imboden, Caroline Weber

  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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• Working Paper

  
  
  Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation
  

  April 2011

  Authors: Bruce Meyer, Robert Goerge

  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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• Working Paper

  
  
  Non-Random Assignment of Individual Identifiers and Selection into Linked Data: Implications for Research
  

  January 2026

  Authors: Liana Christin Landivar, Kyle Raze, Nicole Perales

  Working Paper Number:

  CES-26-06

  The U.S. Census Bureau's Person Identification Validation System facilitates anonymous linkages between survey and administrative records by assigning Protected Identification Keys (PIKs) to person records. While PIK assignment is generally accurate, some person records are not successfully assigned a PIK, which can lead to sample selection bias in analyses of linked data. Using the American Community Survey (ACS) and the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) between 2005 and 2022, we corroborate and extend existing findings on the drivers of PIK assignment, showing that the rate of PIK assignment varies widely across socio-demographic subgroups. Using earnings as a test case, we then show that limiting a survey sample of wage earners to person records with PIKs or successful linkages to W-2 wage records tends to overestimate self-reported wage earnings, on average, indicative of linkage-induced selection bias. In a validation exercise, we demonstrate that reweighting methods, such as inverse probability weighting or entropy balancing, can mitigate this bias.
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• Working Paper

  
  
  Employment and Earnings Trajectories of HUD Program Participants
  

  May 2026

  Authors: Sonya R. Porter, Rachel M. Shattuck, Denise Flanagan-Doyle, Thomas B. Foster, Ethan Krohn, Kyle Raze, David Pritchard, Veronica Garrison, Jacqueline Bachand

  Working Paper Number:

  CES-26-31

  Federal housing assistance programs, such as those run by the U.S. Department of Housing and Urban Development (HUD), have been shown to reduce rent burden and improve housing stability for program participants, which may in turn have downstream impacts on their labor market attachment and career trajectories. However, existing studies from individual cities or states provide mixed evidence on the association of housing assistance with labor market outcomes. By linking HUD administrative records to matched employee-employer earnings records from the Longitudinal Employer-Household Dynamics (LEHD) program, we document how the labor market trajectories of program participants change as they enter and exit federal housing assistance programs, examining outcomes over a 14-year window surrounding entry or exit. In our analysis of entry, we find that the employment rates and earnings of first-time HUD program participants begin to increase upon entering a HUD program, which represents a reversal of prior declining trends in these outcomes. Suggestive of a positive association, these increases in employment and earnings trends exceed those of low-income non-participants from the American Community Survey (ACS). In our analysis of exits, we find that program participants who eventually leave a HUD program have increasing pre-exit trends in employment and earnings that then flatten upon exiting. Comparing these negative changes in trend to the relatively stable trajectories of those who remain in HUD programs throughout the analysis suggests that exits are associated with diminished employment and earnings trajectories.
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• Working Paper

  
  
  The Measurement of Medicaid Coverage in the SIPP: Evidence from California, 1990-1996
  

  September 2002

  Authors: David Card, Andrew KG Hildreth, Lara D Shore-Sheppard

  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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• Working Paper

  
  
  Criminal court fees, earnings, and expenditures: A multi-state RD analysis of survey and administrative data
  

  February 2023

  Authors: Michael Mueller-Smith, Carl Lieberman, Elizabeth Luh

  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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• Working Paper

  
  
  The Antipoverty Impact of the EITC: New Estimates from Survey and Administrative Tax Records
  

  April 2019

  Authors: Maggie R. Jones, James P. Ziliak

  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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• Working Paper

  
  
  Measuring Income of the Aged in Household Surveys: Evidence from Linked Administrative Records
  

  June 2024

  Authors: Joshua Mitchell, Adam Bee, Irena Dushi, Brad Trenkamp

  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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