Complex Survey Questions and the Impact of Enumeration Procedures: Census/American Community Survey Disability Questions
April 2009
Working Paper Number:
CES-09-10
Abstract
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.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
statistical,
report,
census research,
survey,
respondent,
disadvantaged,
population,
medicaid,
eligibility,
eligible,
prevalence,
disability
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
National Science Foundation,
Current Population Survey,
Housing and Urban Development,
Cornell University,
Department of Education,
American Community Survey,
National Health Interview Survey,
Individual Characteristics File,
Department of Health and Human Services,
Census 2000,
Social Security Disability Insurance
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Complex Survey Questions and the Impact of Enumeration Procedures: Census/American Community Survey Disability Questions' are listed below in order of similarity.
-
Working PaperReporting 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.View Full Paper PDF
-
Working PaperEvaluating 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.View Full Paper PDF
-
Working PaperRESIDENTIAL 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.View Full Paper PDF
-
Working PaperCoverage 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.View Full Paper PDF
-
Working PaperFactors 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.View Full Paper PDF
-
Working PaperThe 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.View Full Paper PDF
-
Working PaperResponse 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.View Full Paper PDF
-
Working PaperForeign-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.View Full Paper PDF
-
Working PaperThe 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.View Full Paper PDF
-
Working PaperMedicare 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.View Full Paper PDF
