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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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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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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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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When Race and Hispanic Origin Reporting are Discrepant Across Administrative Records and Third Party Sources: Exploring Methods to Assign Responses
December 2015
Working Paper Number:
carra-2015-08
The U.S. Census Bureau is researching uses of administrative records and third party data in survey and decennial census operations. One potential use of administrative records is to utilize these data when race and Hispanic origin responses are missing. When federal and third party administrative records are compiled, race and Hispanic origin responses are not always the same for an individual across sources. We explore different methods to assign one race and one Hispanic response when these responses are discrepant. We also describe the characteristics of individuals with matching, non-matching, and missing race and Hispanic origin data by demographic, household, and contextual variables. We find that minorities, especially Hispanics, are more likely to have non-matching Hispanic origin and race responses in administrative records and third party data compared to the 2010 Census. Minority groups and individuals ages 0-17 are more likely to have missing race or Hispanic origin data in administrative records and third party data. Larger households tend to have more missing race data in administrative records and third party data than smaller households.
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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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Noncitizen Coverage and Its Effects on U.S. Population Statistics
August 2023
Working Paper Number:
CES-23-42
We produce population estimates with the same reference date, April 1, 2020, as the 2020 Census of Population and Housing by combining 31 types of administrative record (AR) and third-party sources, including several new to the Census Bureau with a focus on noncitizens. Our AR census national population estimate is higher than other Census Bureau official estimates: 1.8% greater than the 2020 Demographic Analysis high estimate, 3.0% more than the 2020 Census count, and 3.6% higher than the vintage-2020 Population Estimates Program estimate. Our analysis suggests that inclusion of more noncitizens, especially those with unknown legal status, explains the higher AR census estimate. About 19.8% of AR census noncitizens have addresses that cannot be linked to an address in the 2020 Census collection universe, compared to 5.7% of citizens, raising the possibility that the 2020 Census did not collect data for a significant fraction of noncitizens residing in the United States under the residency criteria used for the census. We show differences in estimates by age, sex, Hispanic origin, geography, and socioeconomic characteristics symptomatic of the differences in noncitizen coverage.
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Foreign-Born and Native-Born Migration in the U.S.: Evidence from IRS Administrative and Census Survey Records
July 2018
Working Paper Number:
carra-2018-07
This paper details efforts to link administrative records from the Internal Revenue Service (IRS) to American Community Survey (ACS) and 2010 Census microdata for the study of migration among foreign-born and native-born populations in the United States. Specifically, we (1) document our linkage strategy and methodology for inferring migration in IRS records; (2) model selection into and survival across IRS records to determine suitability for research applications; and (3) gauge the efficacy of the IRS records by demonstrating how they can be used to validate and potentially improve migration responses for native-born and foreign-born respondents in ACS microdata. Our results show little evidence of selection or survival bias in the IRS records, suggesting broad generalizability to the nation as a whole. Moreover, we find that the combined IRS 1040, 1099, and W2 records may provide important information on populations, such as the foreign-born, that may be difficult to reach with traditional Census Bureau surveys. Finally, while preliminary, the results of our comparison of IRS and ACS migration responses shows that IRS records may be useful in improving ACS migration measurement for respondents whose migration response is proxy, allocated, or imputed. Taking these results together, we discuss the potential application of our longitudinal IRS dataset to innovations in migration research on both the native-born and foreign-born populations of the United States.
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The Use of Administrative Records and the American Community Survey to Study the Characteristics of Undercounted Young Children in the 2010 Census
May 2018
Working Paper Number:
carra-2018-05
Children under age five are historically one of the most difficult segments of the population to enumerate in the U.S. decennial census. The persistent undercount of young children is highest among Hispanics and racial minorities. In this study, we link 2010 Census data to administrative records from government and third party data sources, such as Medicaid enrollment data and tenant rental assistance program records from the Department of Housing and Urban Development, to identify differences between children reported and not reported in the 2010 Census. In addition, we link children in administrative records to the American Community Survey to identify various characteristics of households with children under age five who may have been missed in the last census. This research contributes to what is known about the demographic, socioeconomic, and household characteristics of young children undercounted by the census. Our research also informs the potential benefits of using administrative records and surveys to supplement the U.S. Census Bureau child population enumeration efforts in future decennial censuses.
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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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Migration and Dispersal of Hispanic and Asian Groups: An Analysis of the 2006-2008 Multiyear American Community Survey
October 2011
Working Paper Number:
CES-11-33
This report seeks to evaluate selective migration processes of Hispanic and Asian nationality groups in the US from established settlement areas, using recent migration data from the American Community Survey. The underlying goal is to detect migration tendencies leading toward an increased dispersion of these groups associated with their migration processes. Using descriptive statistics, maps, and migration models, we assess how migration processes in the 2006-8 period are leading to the dispersal of Hispanic and Asian race ethnic groups across metropolitan areas, with special attention to the roles of co-ethnic communities and spatial assimilation. These analyses employ migration data available from the 3-year 2006-8 American Community Survey using restricted data from the US Census Bureau's Research Data Centers. This use of the restricted ACS files permitted the first post 2000 analysis of inter-metropolitan migration for Hispanic groups (Mexicans, Puerto Ricans, Cubans, Salvadorans, Dominicans) and Asian groups (Chinese, Indians, Filipinos, Vietnamese, Koreans) using the detailed demographic and geographic attributes available with these files. The data and analysis presented here provide a benchmark for further research of this kind with the American Community Survey in light of the fact that migration data will no longer be available from the US decennial census. The study examines migration from these groups' major settlement areas to other metropolitan area destinations as they are affected by the attraction of co-ethnic communities and by a migrant selectivity pattern consistent with the perspective of spatial assimilation. The migration processes themselves were evaluated in terms of two components: the out--migration rates of residents, and the destination selection of movers. From the perspective of co-ethnic community attraction, it was hypothesized that the outmigration rates from high co-ethnic settlement areas would be lower than those from areas where the group had a smaller overall presence and that the destination selections of out-migrants would be positively affected by the presence of high co-ethnic population shares in destination areas. From the spatial assimilation perspective, it was hypothesized that out-migration from high coethnic areas would least likely occur for group members with lowest education, poor facility with English, and recently arrived in the US; whereas the selection of destinations with large coethnic population shares would be most likely to occur for these same population categories. The results strongly confirm that co-ethnic community attraction continues to reduce outmigration of groups from major settlement origins and positively influences their destination selections. A series of multivariate migrant destination selection models confirm a consistent draw of ethnically similar destinations across individual Hispanic and Asian groups when other economic, demographic and structural metropolitan attributes are taken into account. In contrast, results regarding spatial assimilation are typically mixed or nonexistent in characterizing both out-migration and mover destination selectivity patterns. In fact, we find contrary evidence for some Asian groups for whom it is the most educated, and native born migrants who show a penchant for selecting destinations with greater co-ethnic population shares. Among the greatest destinations for Indians, for example, are Philadelphia, Seattle, Dallas, Boston and Atlanta- areas with higher than average Indian population shares, and areas that also house knowledge-based industries. The selection of co-ethnic destinations among Hispanic group migrants appears somewhat impervious to education attainment and Hispanic and Mexican group movers, who are foreign born and who arrived since 2000, are least, rather than most, prone to select co-ethnic destinations. The mover destination models make plain that employment growth at destination provides a strong draw for all Hispanic groups. This suggests that recent growth in low skilled jobs in parts of the country with small Hispanic populations are nonetheless attracting newly arrived, and less skilled Mexicans and other Hispanics who might have previously been especially lured to destinations with large co-ethnic population shares.
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