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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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The EITC over the business cycle: Who benefits?
December 2014
Working Paper Number:
carra-2014-15
In this paper, I examine the impact of the Great Recession on Earned Income Tax Credit (EITC) eligibility. Because the EITC is structurally tied to earnings, the direction of this impact is not immediately obvious. Families who experience complete job loss for an entire tax year lose eligibility, while those experiencing underemployment (part-year employment, a reduction in hours, or spousal unemployment in married households) may become eligible. Determining the direction and magnitude of the impact is important for a number of reasons. The EITC has become the largest cash-transfer program in the U.S., and many low-earning families rely on it as a means of support in tough times. The program has largely been viewed as a replacement for welfare, enticing former welfare recipients into the labor force. However, the effectiveness of the EITC during a period of very high unemployment has not been assessed. To answer these questions, I first use the Current Population Survey (CPS) matched to Internal Revenue Service data from tax years 2005 to 2010 to assess patterns of employment and eligibility over the Great Recession for different labor-force groups. Results indicate that overall, EITC eligibility increased over the recession, but only among groups that were cushioned from total household earnings loss by marriage. I also use the 2006 CPS matched to tax data from 2005 through 2011 to examine changes in eligibility experienced by individuals over time. In assessing three competing causes of eligibility loss, I find that less-educated, unmarried women experienced a greater hazard of eligibility loss due a yearlong lack of earnings compared with other labor-market groups. I discuss the implications of these findings on the view of the EITC as a safety-net program.
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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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Do Doubled-up Families Minimize Household-level Tax Burden?
September 2014
Working Paper Number:
carra-2014-13
This paper examines a method of tax avoidance not previously studied: the sorting of dependent children among related filers who have 'doubled up' in a household for economic reasons. Using the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) linked with 1040 data from the Internal Revenue Service (IRS), we examine households with children and at least two adult tax filers to determine whether the household minimizes income tax burden, and thus maximizes refunds, by optimally claiming dependents. We examine specifically the relationship between the Earned Income Tax Credit (EITC) and the sorting of dependent children among filers in households. We find the following: The propensity to sort increases as the number of filers who are potentially eligible for the EITC increases; sorting probability increases as the optimal household EITC amount increases; and among households with at least one EITC-eligible filer, the propensity to sort increases as the difference between modeled household EITC amount and the optimal amount increases. We also exploit the 2009 change in EITC benefit for families with three or more children, finding that the propensity to sort to exactly three children increased among EITC-eligible filers after the rule change. The results of this analysis improve our understanding of filing behavior, particularly how households form filing units and pool resources, and have implications for poverty measurement in complex households This presentation was given at the CARRA Seminar, July 16, 2014
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Creating Linked Historical Data: An Assessment of the Census Bureau's Ability to Assign Protected Identification Keys to the 1960 Census
September 2014
Working Paper Number:
carra-2014-12
In order to study social phenomena over the course of the 20th century, the Census Bureau is investigating the feasibility of digitizing historical census records and linking them to contemporary data. However, historical censuses have limited personally identifiable information available to match on. In this paper, I discuss the problems associated with matching older censuses to contemporary data files, and I describe the matching process used to match a small sample of the 1960 census to the Social Security Administration Numeric Identification System.
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Person Matching in Historical Files using the Census Bureau's Person Validation System
September 2014
Working Paper Number:
carra-2014-11
The recent release of the 1940 Census manuscripts enables the creation of longitudinal data spanning the whole of the twentieth century. Linked historical and contemporary data would allow unprecedented analyses of the causes and consequences of health, demographic, and economic change. The Census Bureau is uniquely equipped to provide high quality linkages of person records across datasets. This paper summarizes the linkage techniques employed by the Census Bureau and discusses utilization of these techniques to append protected identification keys to the 1940 Census.
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America's Churning Races: Race and Ethnic Response Changes between Census 2000 and the 2010 Census
August 2014
Working Paper Number:
carra-2014-09
Race and ethnicity responses can change over time and across contexts - a component of population change not usually taken into account. To what extent do race and/or Hispanic origin responses change? Is change more common to/from some race/ethnic groups than others? Does the propensity to change responses vary by characteristics of the individual? To what extent do these changes affect researchers? We use internal Census Bureau data from the 2000 and 2010 censuses in which individuals' responses have been linked across years. Approximately 9.8 million people (about 6 percent) in our large, non-representative linked data have a different race and/or Hispanic origin response in 2010 than they did in 2000. Several groups experienced considerable fluidity in racial identification: American Indians and Alaska Natives, Native Hawaiians and Other Pacific Islanders, and multiple-race response groups, as well as Hispanics when reporting a race. In contrast, race and ethnic responses for single-race non-Hispanic whites, blacks, and Asians were relatively consistent over the decade, as were ethnicity responses by Hispanics. People who change their race and/or Hispanic origin response(s) are doing so in a wide variety of ways, as anticipated by previous research. For example, people's responses change from multiple races to a single race, from a single race to multiple races, from one single race to another, and some people add or drop a Hispanic response. The inflow of people to each race/Hispanic group is in many cases similar in size to the outflow from the same group, such that cross-sectional data would show a small net change. We find response changes across ages, sexes, regions, and response modes, with variation across groups. Researchers should consider the implications of changing race and Hispanic origin responses when conducting analyses and interpreting results.
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2010 American Community Survey Match Study
July 2014
Working Paper Number:
carra-2014-03
Using administrative records data from federal government agencies and commercial sources, the 2010 ACS Match Study measures administrative records coverage of 2010 ACS addresses, persons, and persons at addresses at different levels of geography as well as by demographic characteristics and response mode. The 2010 ACS Match Study represents a continuation of the research undertaken in the 2010 Census Match Study, the first national-level evaluation of administrative records data coverage. Preliminary results indicate that administrative records provide substantial coverage for addresses and persons in the 2010 ACS (92.7 and 92.1 percent respectively), and less extensive though substantial coverage, for person-address pairs (74.3 percent). In addition, some variation in address, person and/or person-address coverage is found across demographic and response mode groups. This research informs future uses of administrative records in survey and decennial census operations to address the increasing costs of data collection and declining response rates.
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Estimating Record Linkage False Match Rate for the Person Identification Validation System
July 2014
Working Paper Number:
carra-2014-02
The Census Bureau Person Identification Validation System (PVS) assigns unique person identifiers to federal, commercial, census, and survey data to facilitate linkages across files. PVS uses probabilistic matching to assign a unique Census Bureau identifier for each person. This paper presents a method to measure the false match rate in PVS following the approach of Belin and Rubin (1995). The Belin and Rubin methodology requires truth data to estimate a mixture model. The parameters from the mixture model are used to obtain point estimates of the false match rate for each of the PVS search modules. The truth data requirement is satisfied by the unique access the Census Bureau has to high quality name, date of birth, address and Social Security (SSN) data. Truth data are quickly created for the Belin and Rubin model and do not involve a clerical review process. These truth data are used to create estimates for the Belin and Rubin parameters, making the approach more feasible. Both observed and modeled false match rates are computed for all search modules in federal administrative records data and commercial data.
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The Person Identification Validation System (PVS): Applying the Center for Administrative Records Research and Applications' (CARRA) Record Linkage Software
July 2014
Working Paper Number:
carra-2014-01
The Census Bureau's Person Identification Validation System (PVS) assigns unique person identifiers to federal, commercial, census, and survey data to facilitate linkages across and within files. PVS uses probabilistic matching to assign a unique Census Bureau identifier for each person. The PVS matches incoming files to reference files created with data from the Social Security Administration (SSA) Numerical Identification file, and SSA data with addresses obtained from federal files. This paper describes the PVS methodology from editing input data to creating the final file.
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