Allowance rates for disability insurance applications vary by race and ethnicity, but it is unclear to what extent these differences are artifacts of other differing socio-economic and health characteristics, or selection issues in SSA's race and ethnicity data. This paper uses the 2015 American Community Survey linked to 2015-2019 SSA administrative data to investigate DI application allowance rates among non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, non-Hispanic American Indian/Alaska Native, and Hispanic applicants aged 25-65. The analysis uses regression, propensity score matching, and inverse probability weighting to estimate differences in allowance rates among applicants who are similar on observable characteristics. Relative to raw comparisons, differences by race and ethnicity in multivariate analyses are substantially smaller in magnitude and are generally not statistically significant.
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The Work Disincentive Effects of the Disability Insurance Program in the 1990s
February 2006
Working Paper Number:
CES-06-05
In this paper we evaluate the work disincentive effects of the Disability Insurance program during the 1990s. To accomplish this we construct a new large data set with detailed information on DI application and award decisions and use two different econometric evaluation methods. First, we apply a comparison group approach proposed by John Bound to estimate an upper bound for the work disincentive effect of the current DI program. Second, we adopt a Regression-Discontinuity approach that exploits a particular feature of the DI eligibility determination process to provide a credible point estimate of the impact of the DI program on labor supply for an important subset of DI applicants. Our estimates indicate that during the 1990s the labor force participation rate of DI beneficiaries would have been at most 20 percentage points higher had none received benefits. In addition, we find even smaller labor supply responses for the subset of 'marginal' applicants whose disability determination is based on vocational factors.
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Evaluating Race and Hispanic Origin Responses of Medicaid Participants Using Census Data
April 2015
Working Paper Number:
carra-2015-01
Health and health care disparities associated with race or Hispanic origin are complex and continue to challenge researchers and policy makers. With the intention of improving the measurement and monitoring of these disparities, provisions of the Patient Protection and Affordable Care Act (ACA) of 2010 require states to collect, report and analyze data on demographic characteristics of applicants and participants in Medicaid and other federally supported programs. By linking Medicaid records to 2010 Census, American Community Survey, and Census 2000, this new large-scale study examines and documents the extent to which pre-ACA Medicaid administrative records match self-reported race and Hispanic origin in Census data. Linked records allow comparisons between individuals with matching and non-matching race and Hispanic origin data across several demographic, socioeconomic and neighborhood characteristics, such as age, gender, language proficiency, education and Census tract variables. Identification of the groups most likely to have non-matching and missing race and Hispanic origin data in Medicaid relative to Census data can inform strategies to improve the quality of demographic data collected from Medicaid populations.
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Coverage and Agreement of Administrative Records and 2010 American Community Survey Demographic Data
November 2014
Working Paper Number:
carra-2014-14
The U.S. Census Bureau is researching possible uses of administrative records in decennial census and survey operations. The 2010 Census Match Study and American Community Survey (ACS) Match Study represent recent efforts by the Census Bureau to evaluate the extent to which administrative records provide data on persons and addresses in the 2010 Census and 2010 ACS. The 2010 Census Match Study also examines demographic response data collected in administrative records. Building on this analysis, we match data from the 2010 ACS to federal administrative records and third party data as well as to previous census data and examine administrative records coverage and agreement of ACS age, sex, race, and Hispanic origin responses. We find high levels of coverage and agreement for sex and age responses and variable coverage and agreement across race and Hispanic origin groups. These results are similar to findings from the 2010 Census Match Study.
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The Impact of Unemployment Insurance Extensions On Disability Insurance Application and Allowance Rates
March 2013
Working Paper Number:
CES-13-10
Both unemployment insurance (UI) extensions and the availability of disability benefits have disincentive effects on job search. But UI extensions can reduce the efficiency cost of disability benefits if UI recipients delay disability application until they exhaust their unemployment benefits. This paper, the first to focus on the effect of UI extensions on disability applications, investigates whether UI eligibility, extension, and exhaustion affect the timing of disability applications and the composition of the applicant pool. Jobless individuals are significantly less likely to apply to Social Security Disability Insurance (SSDI) during UI extensions, and significantly more likely to apply when UI is ultimately exhausted. Healthier potential applicants appear more likely to delay, as state allowance rates increase after a new UI extension. Simulations find that a 13-week UI extension decreases SSDI and Medicare costs, offsetting about half of the increase in UI payments; this suggests that the benefits of UI extensions may be understated ' permanent disability benefits are diverted to shorter-run unemployment benefits and, potentially, new jobs, while easing the burden on the nearly insolvent SSDI Trust Fund.
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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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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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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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Reporting of Indian Health Service Coverage in the American Community Survey
May 2018
Working Paper Number:
carra-2018-04
Response error in surveys affects the quality of data which are relied on for numerous research and policy purposes. We use linked survey and administrative records data to examine reporting of a particular item in the American Community Survey (ACS) - health coverage among American Indians and Alaska Natives (AIANs) through the Indian Health Service (IHS). We compare responses to the IHS portion of the 2014 ACS health insurance question to whether or not individuals are in the 2014 IHS Patient Registration data. We evaluate the extent to which individuals misreport their IHS coverage in the ACS as well as the characteristics associated with misreporting. We also assess whether the ACS estimates of AIANs with IHS coverage represent an undercount. Our results will be of interest to researchers who rely on survey responses in general and specifically the ACS health insurance question. Moreover, our analysis contributes to the literature on using administrative records to measure components of survey error.
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Assimilation and Coverage of the
Foreign-Born Population in Administrative Records
April 2015
Working Paper Number:
carra-2015-02
The U.S. Census Bureau is researching ways to incorporate administrative data in decennial census and survey operations. Critical to this work is an understanding of the coverage of the population by administrative records. Using federal and third party administrative data linked to the American Community Survey (ACS), we evaluate the extent to which administrative records provide data on foreign-born individuals in the ACS and employ multinomial logistic regression techniques to evaluate characteristics of those who are in administrative records relative to those who are not. We find that overall, administrative records provide high coverage of foreign-born individuals in our sample for whom a match can be determined. The odds of being in administrative records are found to be tied to the processes of immigrant assimilation - naturalization, higher English proficiency, educational attainment, and full-time employment are associated with greater odds of being in administrative records. These findings suggest that as immigrants adapt and integrate into U.S. society, they are more likely to be involved in government and commercial processes and programs for which we are including data. We further explore administrative records coverage for the two largest race/ethnic groups in our sample - Hispanic and non-Hispanic single-race Asian foreign born, finding again that characteristics related to assimilation are associated with administrative records coverage for both groups. However, we observe that neighborhood context impacts Hispanics and Asians differently.
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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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