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The Radius of Economic Opportunity: Evidence from Migration and Local Labor Markets
July 2022
Working Paper Number:
CES-22-27
We examine the geographic incidence of local labor market growth across locations of childhood residence. We ask: when wages grow in a given US labor market, do the benefits flow to individuals growing up in nearby or distant locations? We begin by constructing new statistics on migration rates across labor markets between childhood and young adulthood. This migration matrix shows 80% of young adults migrate less than 100 miles from where they grew up. 90% migrate less than 500 miles. Migration distances are shorter for Black and Hispanic individuals and for those from low income families. These migration patterns provide information on the first order geographic incidence of local wage growth. Next, we explore the responsiveness of location choices to economic shocks. Using geographic variation induced by the recovery from the Great Recession, we estimate the elasticity of migration with respect to increases in local labor market wage growth. We develop and implement a novel test for validating whether our identifying wage variation is driven by changes in labor market opportunities rather than changes in worker composition due to sorting. We find that higher wages lead to increased in-migration, decreased out-migration and a partial capitalization of wage increases into local prices. Our results imply that for a 2 rank point increase in annual wages (approximately $1600) in a given commuting zone (CZ), approximately 99% of wage gains flow to those who would have resided in the CZ in the absence of the wage change. The geographically concentrated nature of most migration and the small magnitude of these migration elasticities suggest that the incidence of labor market conditions across childhood residences is highly local. For many individuals, the 'radius of economic opportunity' is quite narrow.
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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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Comparing the 2019 American Housing Survey to Contemporary Sources of Property Tax Records: Implications for Survey Efficiency and Quality
June 2022
Working Paper Number:
CES-22-22
Given rising nonresponse rates and concerns about respondent burden, government statistical agencies have been exploring ways to supplement household survey data collection with administrative records and other sources of third-party data. This paper evaluates the potential of property tax assessment records to improve housing surveys by comparing these records to responses from the 2019 American Housing Survey. Leveraging the U.S. Census Bureau's linkage infrastructure, we compute the fraction of AHS housing units that could be matched to a unique property parcel (coverage rate), as well as the extent to which survey and property tax data contain the same information (agreement rate). We analyze heterogeneity in coverage and agreement across states, housing characteristics, and 11 AHS items of interest to housing researchers. Our results suggest that partial replacement of AHS data with property data, targeted toward certain survey items or single-family detached homes, could reduce respondent burden without altering data quality. Further research into partial-replacement designs is needed and should proceed on an item-by-item basis. Our work can guide this research as well as those who wish to conduct independent research with property tax records that is representative of the U.S. housing stock.
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Age, Sex, and Racial/Ethnic Disparities and Temporal-Spatial Variation in
Excess All-Cause Mortality During the COVID-19 Pandemic: Evidence from Linked Administrative and Census Bureau Data
May 2022
Working Paper Number:
CES-22-18
Research on the impact of the COVID-19 pandemic in the United States has highlighted substantial racial/ethnic disparities in excess mortality, but reports often differ in the details with respect to the size of these disparities. We suggest that these inconsistencies stem from differences in the temporal scope and measurement of race/ethnicity in existing data. We address these issues using death records for 2010 through 2021 from the Social Security Administration, covering the universe of individuals ever issued a Social Security Number, linked to race/ethnicity responses from the decennial census and American Community Survey. We use these data to (1) estimate excess all-cause mortality at the national level and for age-, sex-, and race/ethnicity-specific subgroups, (2) examine racial/ethnic variation in excess mortality over the course of the pandemic, and (3) explore whether and how racial/ethnic mortality disparities vary across states.
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Measuring the Impact of COVID-19 on Businesses and People: Lessons from the Census Bureau's Experience
January 2021
Working Paper Number:
CES-21-02
We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the pandemic's impact: the Small Business Pulse Survey, weekly Business Formation Statistics, the Household Pulse Survey, and Community Resilience Estimates. We describe pandemic-related content introduced to existing surveys such as the Annual Business Survey and the Current Population Survey. We discuss adaptations to ensure the continuity and consistency of existing data products such as principal economic indicators and the American Community Survey.
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Validating Abstract Representations of Spatial Population Data while considering Disclosure Avoidance
February 2020
Working Paper Number:
CES-20-05
This paper furthers a research agenda for modeling populations along spatial networks and expands upon an empirical analysis to a full U.S. county (Gaboardi, 2019, Ch. 1,2). Specific foci are the necessity of, and methods for, validating and benchmarking spatial data when conducting social science research with aggregated and ambiguous population representations. In order to promote the validation of publicly-available data, access to highly-restricted census microdata was requested, and granted, in order to determine the levels of accuracy and error associated with a network-based population modeling framework. Primary findings reinforce the utility of a novel network allocation method'populated polygons to networks (pp2n) in terms of accuracy, computational complexity, and real runtime (Gaboardi, 2019, Ch. 2). Also, a pseudo-benchmark dataset's performance against the true census microdata shows promise in modeling populations along networks.
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LEHD Infrastructure S2014 files in the FSRDC
September 2018
Working Paper Number:
CES-18-27R
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2014 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifications made to the files to facilitate researcher access.
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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 Opportunities and Challenges of Linked IRS Administrative and Census Survey Records in the Study of Migration
July 2018
Working Paper Number:
carra-2018-06
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 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 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 that are hard to reach with traditional Census 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 applications of our longitudinal IRS dataset to innovations in migration research in the United States.
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Fathers, Children, and the Intergenerational
Transmission of Employers
March 2018
Working Paper Number:
CES-18-12
We document the tendency of fathers in the U.S. to share employers with their sons and daughters. We show that the rate of job sharing is much higher than can be explained by the fact that fathers and sons tend to live near each other. Younger children are much more likely to share their father's employer, as are children of high-earning fathers. We find that sons' earnings at shared jobs tend to be higher than at unshared jobs but see no statistically signi?cant di'erence for daughters. Much of the earnings differential is associated with jobs at shared employers being in higher-paying industries. When we control for employer characteristics, we see a much smaller son earnings premium for working together with his father. We also investigate the impact of sharing an employer on intergenerational mobility and demonstrate that for sons, sharing an employer at some point before age 30 is associated with a higher rank in the earnings distribution as an adult but that this association is independent of the father's rank in the earnings distribution.
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