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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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Does Federally-Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts Using Longitudinal Data on Workers and Firms
January 2018
Working Paper Number:
CES-18-02
We study the job training provided under the US Workforce Investment Act (WIA) to adults and dislocated workers in two states. Our substantive contributions center on impacts estimated non-experimentally using administrative data. These impacts compare WIA participants who do and do not receive training. In addition to the usual impacts on earnings and employment, we link our state data to the Longitudinal Employer-Household Dynamics (LEHD) data at the US Census Bureau, which allows us to estimate impacts on the characteristics of the firms at which participants find employment. We find moderate positive impacts on employment, earnings and desirable firm characteristics for adults, but not for dislocated workers. Our primary methodological contribution consists of assessing the value of the additional conditioning information provided by the LEHD relative to the data available in state Unemployment Insurance (UI) earnings records. We find that value to be zero.
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Capturing More Than Poverty: School Free and Reduced-Price Lunch Data and Household Income
December 2017
Working Paper Number:
carra-2017-09
Educational researchers often use National School Lunch Program (NSLP) data as a proxy for student poverty. Under NSLP policy, students whose household income is less than 130 percent of the poverty line qualify for free lunch and students whose household income is between 130 percent and 185 percent of the poverty line qualify for reduced-price lunch. Linking school administrative records for all 8th graders in a California public school district to household-level IRS income tax data, we examine how well NSLP data capture student disadvantage. We find both that there is substantial disadvantage in household income not captured by NSLP category data, and that NSLP categories capture disadvantage on test scores above and beyond household income.
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Is Subsidized Childcare Associated with Lower Risk of Grade Retention for Low-Income Children? Evidence from Child Care and Development Fund Administrative Records Linked to the American Community Survey
June 2017
Working Paper Number:
carra-2017-06
This study investigates whether low-income young children's experience of Child Care and Development Fund (CCDF)-subsidized childcare is associated with a lower subsequent likelihood of being held back in grades K-12. High-quality childcare has been shown to improve low-income children's school readiness. However, no previous study has examined the link specifically between subsidized care and grade retention. I do so here by matching information on children from CCDF administrative records to later observations of the same children in the American Community Survey (ACS). I use logistic regression to compare the likelihood of grade retention between CCDF-recipient children and non-recipient children who also appear in the ACS in the years 2008-2014 (N=2,284,857). I find strong evidence for an association between CCDF-subsidized care and lower risk of grade retention, especially among non-Hispanic Black children and Hispanic children. I also find evidence that receiving CCDF-subsidized center-based care in particular is associated with a lower risk of being held back than CCDF-subsidized family daycare, babysitter care, or relative care, again with the largest apparent benefit to non-Hispanic Black children and Hispanic children.
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Medicare Coverage and Reporting
December 2016
Working Paper Number:
carra-2016-12
Medicare coverage of the older population in the United States is widely recognized as being nearly universal. Recent statistics from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) indicate that 93 percent of individuals aged 65 and older were covered by Medicare in 2013. Those without Medicare include those who are not eligible for the public health program, though the CPS ASEC estimate may also be impacted by misreporting. Using linked data from the CPS ASEC and Medicare Enrollment Database (i.e., the Medicare administrative data), we estimate the extent to which individuals misreport their Medicare coverage. We focus on those who report having Medicare but are not enrolled (false positives) and those who do not report having Medicare but are enrolled (false negatives). We use regression analyses to evaluate factors associated with both types of misreporting including socioeconomic, demographic, and household characteristics. We then provide estimates of the implied Medicare-covered, insured, and uninsured older population, taking into account misreporting in the CPS ASEC. We find an undercount in the CPS ASEC estimates of the Medicare covered population of 4.5 percent. This misreporting is not random - characteristics associated with misreporting include citizenship status, year of entry, labor force participation, Medicare coverage of others in the household, disability status, and imputation of Medicare responses. When we adjust the CPS ASEC estimates to account for misreporting, Medicare coverage of the population aged 65 and older increases from 93.4 percent to 95.6 percent while the uninsured rate decreases from 1.4 percent to 1.3 percent.
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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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Local Labor Demand and Program Participation Dynamics
November 2016
Working Paper Number:
carra-2016-10
Estimates the effect of fluctuations in local labor conditions on the likelihood that existing participants are able to transition out of the Supplemental Nutrition Assistance Program (SNAP). Our primary data are SNAP administrative records from New York (2007-2012) linked to the 2010 Census at the person-level. We further augment these data by linking to industry-specific labor market indicators at the county-level. We find that local labor markets matter for the length of time individuals spend on SNAP, but there is substantial heterogeneity in estimated effects across local industries. While employment growth in industries with small shares of SNAP participants has no impact on SNAP exits, growth in local industries with creases the likelihood that recipients exit the program. We also observe corresponding increases in entries when these industries experience localized contractions. Notably, estimated industry effects vary across race groups and parental status, with Black Alone non-Hispanic, Hispanic, and mothers benefiting the least from improvements in local labor market conditions.
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Introduction of Head Start and Maternal Labor Supply: Evidence from a Regression
Discontinuity Design
January 2016
Working Paper Number:
CES-16-35
I use the non-public decennial censuses in 1970 to investigate the effect of the Head Start program on maternal labor supply and schooling in its early years. I exploit a discontinuity in county-level Head Start funding beginning in the late 1960s to explore differences in countylevel maternal employment and maternal schooling. The results provide suggestive evidence that the more availability of Head Start led to an increase the nursery school enrollment of children and a decrease in maternal labor supply. In addition, the ITT estimates imply a relatively large, negative effect of enrollment on maternal labor supply. However, the estimates are somewhat sensitive to addition of covariates and the standard errors are also large to draw firm inferences.
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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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DO PUBLIC TUITION SUBSIDIES PROMOTE COLLEGE ENROLLMENT? EVIDENCE FROM COMMUNITY COLLEGE TAXING DISTRICTS IN TEXAS
September 2014
Working Paper Number:
CES-14-32
This paper estimates the effect of tuition rates on college enrollment using data for Texas from the 1990 and 2000 Censuses and the 2004 ' 2010 American Community Surveys and geographical data on Community College Taxing Districts. The effect of tuition on enrollment is identified by the facts that tuition rates for those living within a taxing district are lower than those living outside the taxing district and in Texas not all geographic locations are in a taxing district. While the estimated effect of tuition on enrollment depends on the sample used, it is negative and mostly statistically significant in the samples of iadults 18 and older and negative and sometimes statistically significant in the samples of traditional age students 18 to 24. The estimated effect of tuition on enrollment, however, is found to vary considerably by poverty level status with an increase in tuition rates having a statistically significant negative effect on college enrollment for those with household incomes that are at least 200% of the poverty level both for traditional aged students 18 to 24 years old and all adults 18 and older.
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