This paper explores challenges relating to the identification of the population with disabilities,focusing on Census Bureau efforts using the 2000 Decennial Census Long-Form (Census 2000) and 2000-2005 American Community Survey (ACS). In particular, the analyses explore the impact of survey methods on responses to the work limitation (i.e., employment disability) question in these two Census products. Building on the research of Stern (2003) and Stern and Brault (2005), we look for further evidence of misreporting of an employment disability by specific sub-populations using the participation in the Supplemental Security Income program as an exogenous employment disability status indicator along with a subset of ACS disability questions. We expand upon these earlier studies by examining both false-positive and falsenegative reports of employment disability by implementing logit estimations to examine the role of respondent/enumerator error on the accuracy of the employment disability response. In this manner, we enhance our understanding of Census 2000 and ACS responses to employment disability questions through an exploration of the role of enumeration procedures in two types of misclassifications, as well as by evaluating existing data and estimates to uncover characteristics that might make an individual more likely to misreport an employment disability.
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RESIDENTIAL MOBILITY ACROSS LOCAL AREAS IN THE UNITED STATES AND THE GEOGRAPHIC DISTRIBUTION OF THE HEALTHY POPULATION
February 2014
Working Paper Number:
CES-14-14
Determining whether population dynamics provide competing explanations to place effects for observed geographic patterns of population health is critical for understanding health inequality. We focus on the working-age population where health disparities are greatest and analyze detailed data on residential mobility collected for the first time in the 2000 US census. Residential mobility over a 5-year period is frequent and selective, with some variation by race and gender. Even so, we find little evidence that mobility biases cross-sectional snapshots of local population health. Areas undergoing large or rapid population growth or decline may be exceptions. Overall, place of residence is an important health indicator; yet, the frequency of residential mobility raises questions of interpretation from etiological or policy perspectives, complicating simple understandings that residential exposures alone explain the association between place and health. Psychosocial stressors related to contingencies of social identity associated with being black, urban, or poor in the U.S. may also have adverse health impacts that track with structural location even with movement across residential areas.
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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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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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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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The Impact of 2010 Decennial Census Hiring on the Unemployment Rate
June 2020
Working Paper Number:
CES-20-19
The decennial census is the largest peacetime operation of the U.S. federal government. The Census Bureau hires hundreds of thousands of temporary workers to conduct the decennial census. The magnitude of this temporary workforce influences the national employment situation when enumeration efforts ramp up and when they recede. The impact of decennial census hiring on the headline number of payroll jobs added each month is well established, but previous work has not established how decennial census hiring affects the headline unemployment rate. We link the 2010 Decennial Applicant Personnel and Payroll System data to the 2010 American Community Survey to answer this question. We find that the large hiring surge in May 2010 came mostly from people already employed (40 percent) or from people who were unemployed (33 percent). We estimate that the workers hired for Census 2010 lowered the May 2010 unemployment rate by one-tenth of a percentage point relative to the counterfactual. This one-tenth of a percentage point is within the standard error for the official unemployment rate, and BLS press releases would denote a change in the unemployment rate of 0.1% or less as 'unchanged.' We also estimate that relative to the counterfactual, the more gradual changes in decennial census employment influenced the unemployment rate by less than one-tenth of a percentage point in every other month during 2010.
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The Impact of Household Surveys on 2020 Census Self-Response
July 2022
Working Paper Number:
CES-22-24
Households who were sampled in 2019 for the American Community Survey (ACS) had lower self-response rates to the 2020 Census. The magnitude varied from -1.5 percentage point for household sampled in January 2019 to -15.1 percent point for households sampled in December 2019. Similar effects are found for the Current Population Survey (CPS) as well.
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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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State and Local Determinants of Employment Outcomes among Individuals with Disabilities
March 2016
Working Paper Number:
CES-16-21
In the United States, employment rates among individuals with disabilities are persistently low but vary substantially. In this study, we examine the relationship between employment outcomes and features of the state and county physical, economic, and policy environment among a national sample of individuals with disabilities. To do so, we merge a set of state- and county-level environmental variables with data from the 2009'2011 American Community Survey accessed in a U.S. Census Research Data Center. We estimate regression models of employment, work hours, and earnings as a function of health conditions, personal characteristics, and these environmental features. We find that certain environmental variables are significantly associated with employment outcomes. Although the estimated importance of environmental variables is small relative to individual health and personal characteristics, our results suggest that these variables may present barriers or facilitators to employment that can explain some geographic variation in employment outcomes across the United States.
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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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Factors that Influence Change in Hispanic Identification: Evidence from Linked Decennial Census and American Community Survey Data
October 2018
Working Paper Number:
CES-18-45
This study explores patterns of ethnic boundary crossing as evidenced by changes in Hispanic origin responses across decennial census and survey data. We identify socioeconomic, cultural, and demographic factors associated with Hispanic response change. In addition, we assess whether changes in the Hispanic origin question between the 2000 and 2010 censuses influenced changes in Hispanic reporting. We use a unique large dataset that links a person's unedited responses to the Hispanic origin question across Census 2000, the 2010 Census and the 2006-2010 American Community Survey five-year file. We find that most of the individuals in the sample identified consistently as Hispanic regardless of changes in the wording of the Hispanic origin question. Individuals who changed in or out of a Hispanic identification, as well as those who consistently identified as non-Hispanic (of Hispanic ancestry), differed in socioeconomic and cultural characteristics from individuals who consistently reported as Hispanic. The likelihood of changing their Hispanic origin response is higher among U.S.-born individuals, those reporting mixed Hispanic and non-Hispanic ancestries, those who speak only English at home, and those who live in tracts that are predominantly non-Hispanic. Racial identification and detailed Hispanic background also influence changes in Hispanic origin responses. Finally, changes in mode and relationship to the reference person in the household are associated with changes in Hispanic origin responses, suggesting that data collection elements also can influence Hispanic origin response change.
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