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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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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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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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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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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Long-Run Earnings Volatility and Health Insurance Coverage: Evidence from the SIPP Gold Standard File
October 2011
Working Paper Number:
CES-11-35
Despite the notable increase in earnings volatility and the attention paid to the growing ranks of the uninsured, the relationship between career earnings and short- and mediumrun health insurance status has been ignored due to a lack of data. I use a new dataset, the SIPP Gold Standard File, that merges health insurance status and demographics from the Survey of Income and Program Participation with career earnings records from the Social Security Administration (SSA) and the Internal Revenue Service (IRS) to examine the relationship between long-run family earnings volatility and health insurance coverage. I find that more volatile career earnings are associated with an increased probability of experiencing an uninsured episode, with larger effects for men, young workers, and the unmarried. These findings are consistent with the 'scarring' literature, and suggest the importance of safety-net measures for job losses and health insurance coverage.
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Trends in Earnings Volatility using Linked Administrative and Survey Data
August 2020
Working Paper Number:
CES-20-24
We document trends in earnings volatility separately by gender in combination with other characteristics such as race, educational attainment, and employment status using unique linked survey and administrative data for the tax years spanning 1995-2015. We also decompose the variance of trend volatility into within- and between-group contributions, as well as transitory and permanent shocks. Our results for continuously working men suggest that trend earnings volatility was stable over our period in both survey and tax data, though with a substantial countercyclical business-cycle component. Trend earnings volatility among women declined over the period in both survey and administrative data, but unlike for men, there was no change over the Great Recession. The variance decompositions indicate that nonresponders, low-educated, racial minorities, and part-year workers have the greatest group specific earnings volatility, but with the exception of part-year workers, they contribute least to the level and trend of volatility owing to their small share of the population. There is evidence of stable transitory volatility, but rising permanent volatility over the past two decades in male and female earnings.
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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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Maternal and Infant Health Inequality: New Evidence from Linked Administrative Data
November 2022
Working Paper Number:
CES-22-55
We use linked administrative data that combines the universe of California birth records, hospitalizations, and death records with parental income from Internal Revenue Service tax records and the Longitudinal Employer-Household Dynamics file to provide novel evidence on economic inequality in infant and maternal health. We find that birth outcomes vary nonmonotonically with parental income, and that children of parents in the top ventile of the income distribution have higher rates of low birth weight and preterm birth than those in the bottom ventile. However, unlike birth outcomes, infant mortality varies monotonically with income, and infants of parents in the top ventile of the income distribution---who have the worst birth outcomes---have a death rate that is half that of infants of parents in the bottom ventile. When studying maternal health, we find a similar pattern of non-monotonicity between income and severe maternal morbidity, and a monotonic and decreasing relationship between income and maternal mortality. At the same time, these disparities by parental income are small when compared to racial disparities, and we observe virtually no convergence in health outcomes across racial and ethnic groups as income rises. Indeed, infant and maternal health in Black families at the top of the income distribution is markedly worse than that of white families at the bottom of the income distribution. Lastly, we benchmark the health gradients in California to those in Sweden, finding that infant and maternal health is worse in California than in Sweden for most outcomes throughout the entire income distribution.
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