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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Response Error & the Medicaid undercount in the CPS
December 2016
Working Paper Number:
carra-2016-11
The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) is an important source for estimates of the uninsured population. Previous research has shown that survey estimates produce an undercount of beneficiaries compared to Medicaid enrollment records. We extend past work by examining the Medicaid undercount in the 2007-2011 CPS ASEC compared to enrollment data from the Medicaid Statistical Information System for calendar years 2006-2010. By linking individuals across datasets, we analyze two types of response error regarding Medicaid enrollment - false negative error and false positive error. We use regression analysis to identify factors associated with these two types of response error in the 2011 CPS ASEC. We find that the Medicaid undercount was between 22 and 31 percent from 2007 to 2011. In 2011, the false negative rate was 40 percent, and 27 percent of Medicaid reports in CPS ASEC were false positives. False negative error is associated with the duration of enrollment in Medicaid, enrollment in Medicare and private insurance, and Medicaid enrollment in the survey year. False positive error is associated with enrollment in Medicare and shared Medicaid coverage in the household. We discuss implications for survey reports of health insurance coverage and for estimating the uninsured population.
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The Long-Term Effects of Income for At-Risk Infants: Evidence from Supplemental Security Income
March 2024
Working Paper Number:
CES-24-10
This paper examines whether a generous cash intervention early in life can "undo" some of the long-term disadvantage associated with poor health at birth. We use new linkages between several large-scale administrative datasets to examine the short-, medium-, and long-term effects of providing low-income families with low birthweight infants support through the Supplemental Security Income (SSI) program. This program uses a birthweight cutoff at 1200 grams to determine eligibility. We find that families of infants born just below this cutoff experience a large increase in cash benefits totaling about 27%of family income in the first three years of the infant's life. These cash benefits persist at lower amounts through age 10. Eligible infants also experience a small but statistically significant increase in Medicaid enrollment during childhood. We examine whether this support affects health care use and mortality in infancy, educational performance in high school, post-secondary school attendance and college degree attainment, and earnings, public assistance use, and mortality in young adulthood for all infants born in California to low-income families whose birthweight puts them near the cutoff. We also examine whether these payments had spillover effects onto the older siblings of these infants who may have also benefited from the increase in family resources. Despite the comprehensive nature of this early life intervention, we detect no improvements in any of the study outcomes, nor do we find improvements among the older siblings of these infants. These null effects persist across several subgroups and alternative model specifications, and, for some outcomes, our estimates are precise enough to rule out published estimates of the effect of early life cash transfers in other settings.
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Covering Undocumented Immigrants: The Effects of a Large-Scale Prenatal Care Intervention
August 2022
Working Paper Number:
CES-22-28
Undocumented immigrants are ineligible for public insurance coverage for prenatal care in most states, despite their children representing a large fraction of births and having U.S. citizenship. In this paper, we examine a policy that expanded Medicaid pregnancy coverage to undocumented immigrants. Using a novel dataset that links California birth records to Census surveys, we identify siblings born to immigrant mothers before and after the policy. Implementing a mothers' fixed effects design, we find that the policy increased coverage for and use of prenatal care among pregnant immigrant women, and increased average gestation length and birth weight among their children.
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Comparing Measures of Earnings Instability Based on Survey and Adminstrative Reports
August 2010
Working Paper Number:
CES-10-15
In Celik, Juhn, McCue, and Thompson (2009), we found that estimated levels of earnings instability based on data from the Current Population Survey (CPS) and the Survey of Income and Program Participation (SIPP) were reasonably close to each other and to others' estimates from the Panel Study of Income Dynamics (PSID), but estimates from unemployment insurance (UI) earnings were much larger. Given that the UI data are from administrative records which are often posited to be more accurate than survey reports, this raises concerns that measures based on survey data understate true earnings instability. To address this, we use links between survey samples from the SIPP and UI earnings records in the LEHD database to identify sources of differences in work history and earnings information. Substantial work has been done comparing earnings levels from administrative records to those collected in the SIPP and CPS, but our understanding of earnings instability would benefit from further examination of differences across sources in the properties of changes in earnings. We first compare characteristics of the overall and matched samples to address issues of selection in the matching process. We then compare earnings levels and jobs in the SIPP and LEHD data to identify differences between them. Finally we begin to examine how such differences affect estimates of earnings instability. Our preliminary findings suggest that differences in earnings changes for those in the lower tail of the earnings distribution account for much of the difference in instability 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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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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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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Potential Bias When Using Administrative Data to Measure the Family Income of School-Aged Children
January 2025
Working Paper Number:
CES-25-03
Researchers and practitioners increasingly rely on administrative data sources to measure family income. However, administrative data sources are often incomplete in their coverage of the population, giving rise to potential bias in family income measures, particularly if coverage deficiencies are not well understood. We focus on the school-aged child population, due to its particular import to research and policy, and because of the unique challenges of linking children to family income information. We find that two of the most significant administrative sources of family income information that permit linking of children and parents'IRS Form 1040 and SNAP participation records'usefully complement each other, potentially reducing coverage bias when used together. In a case study considering how best to measure economic disadvantage rates in the public school student population, we demonstrate the sensitivity of family income statistics to assumptions about individuals who do not appear in administrative data sources.
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Longitudinal analysis of SSN response on SIPP 1990-1993 panel
September 2000
Working Paper Number:
tp-2000-01
This document describes the analysis of the SIPP-SSN match quality, and the file resulting for that analysis as distributable to the Census RDCs.
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Earnings Mobility in the US: A New Look at Intergenerational Inequality
May 2002
Working Paper Number:
CES-02-11
This study uses a new data set that contains the Social Security earnings histories of parents and children in the 1984 Survey of Income and Program Participation, to measure the intergenerational elasticity in earnings in the United States. Earlier studies that found an intergenerational elasticity of 0.4 have typically used only up to five-year averages of fathers' earnings to measure fathers' permanent earnings. However, dynamic earnings models that allow for serial correlation in transitory shocks to earnings imply that using such a short time span may lead to estimates that are biased down by nearly 30 percent. Indeed, by using many more years of fathers' earnings than earlier studies, the intergenerational elasticity between fathers and sons is estimated to be around 0.6 implying significantly less mobility in the U.S. than previous research indicated. The elasticity in earnings between fathers and daughters is of a similar magnitude. The evidence also suggests that family income has an even larger effect than fathers' earnings on children's future labor market success. The elasticity of earnings is higher for families with low net worth, offering some empirical support for theoretical models that predict differences due to borrowing constraints. Some evidence of a higher elasticity among blacks is found but the results are not conclusive.
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