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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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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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Who are the people in my neighborhood? The 'contextual fallacy' of measuring individual context with census geographies
February 2018
Working Paper Number:
CES-18-11
Scholars deploy census-based measures of neighborhood context throughout the social sciences and epidemiology. Decades of research confirm that variation in how individuals are aggregated into geographic units to create variables that control for social, economic or political contexts can dramatically alter analyses. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude in the literature and in their own projects. By using confidential access to the complete 2010 U.S. Decennial Census, we are able to construct'for all persons in the US'individual-specific contexts, which we group according to the Census-assigned block, block group, and tract. We compare these individual-specific measures to the published statistics at each scale, and we then determine the magnitude of variation in context for an individual with respect to the published measures using a simple statistic, the standard deviation of individual context (SDIC). For three key measures (percent Black, percent Hispanic, and Entropy'a measure of ethno-racial diversity), we find that block-level Census statistics frequently do not capture the actual context of individuals within them. More problematic, we uncover systematic spatial patterns in the contextual variables at all three scales. Finally, we show that within-unit variation is greater in some parts of the country than in others. We publish county-level estimates of the SDIC statistics that enable scholars to assess whether mis-specification in context variables is likely to alter analytic findings when measured at any of the three common Census units.
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Decennial Census Return Rates: The Role of Social Capital
January 2017
Working Paper Number:
CES-17-39
This paper explores how useful information about social and civic engagement (social capital)
might be to the U.S. Census Bureau in their efforts to improve predictions of mail return rates for the Decennial Census (DC) at the census tract level. Through construction of Hard-to-count (HRC) scores and multivariate analysis, we find that if information about social capital were available, predictions of response rates would be marginally improved.
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Racial Disparity in an Era of Increasing Income Inequality
January 2017
Working Paper Number:
carra-2017-01
Using unique linked data, we examine income inequality and mobility across racial and ethnic groups in the United States. Our data encompass the universe of tax filers in the U.S. for the period 2000 to 2014, matched with individual-level race and ethnicity information from multiple censuses and American Community Survey data. We document both income inequality and mobility trends over the period. We find significant stratification in terms of average incomes by race and ethnic group and distinct differences in within-group income inequality. The groups with the highest incomes - Whites and Asians - also have the highest levels of within-group inequality and the lowest levels of within-group mobility. The reverse is true for the lowest-income groups: Blacks, American Indians, and Hispanics have lower within-group inequality and immobility. On the other hand, our low-income groups are also highly immobile when looking at overall, rather than within-group, mobility. These same groups also have a higher probability of experiencing downward mobility compared with Whites and Asians. We also find that within-group income inequality increased for all groups between 2000 and 2014, and the increase was especially large for Whites. In regression analyses using individual-level panel data, we find persistent differences by race and ethnicity in incomes over time. We also examine young tax filers (ages 25-35) and investigate the long-term effects of local economic and racial residential segregation conditions at the start of their careers. We find persistent long-run effects of racial residential segregation at career entry on the incomes of certain groups. The picture that emerges from our analysis is of a rigid income structure, with mainly Whites and Asians confined to the top and Blacks, American Indians, and Hispanics confined to the bottom.
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Small Business Growth and Failure during the Great Recession: The Role of House Prices, Race & Gender
November 2016
Working Paper Number:
carra-2016-08
Using 2002-2011 data from the Longitudinal Business Database linked to the 2002 and 2007 Survey of Business Owners, this paper explores whether (through a collateral channel) the rise in home prices over the early 2000's and their subsequent fall associated with the Great Recession had differential impacts on business performance across owner race, ethnicity and gender. We find that the employment growth rate of minority-owned firms, particularly black and Hispanic-owned firms, is more sensitive to changes in house prices than is that of their nonminority-owned counterparts.
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Structural versus Ethnic Dimensions of Housing Segregation
March 2016
Working Paper Number:
CES-16-22
Racial residential segregation is still very high in many American cities. Some portion of segregation is attributable to socioeconomic differences across racial lines; some portion is caused by purely racial factors, such as preferences about the racial composition of one's neighborhood or discrimination in the housing market. Social scientists have had great difficulty disaggregating segregation into a portion that can be explained by interracial differences in socioeconomic characteristics (what we call structural factors) versus a portion attributable to racial and ethnic factors. What would such a measure look like? In this paper, we draw on a new source of data to develop an innovative structural segregation measure that shows the amount of segregation that would remain if we could assign households to housing units based only on non-racial socioeconomic characteristics. This inquiry provides vital building blocks for the broader enterprise of understanding and remedying housing segregation.
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Urban-Suburban Migration in the United States, 1955-2000
February 2016
Working Paper Number:
CES-16-08
This study uses census microdata from 1960 to 2010 to look at the rates of suburbanization in the 100 largest metro areas. Looking at the racial and ethnic composition of the population, and then further breaking down these groups by income, it's clear that more affluent people were more likely to move to the suburbs. Also, the White non-Hispanic population has long been the most suburbanized group. A majority of the White population lived in suburbs by 1960 in the 100 largest metro areas, while most of the Black non-Hispanic population lived in urban core areas as late as 2000. The Hispanic and Asian populations went from majority urban to majority suburban during this period.
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The Impact of Immigration on the Labor Market Outcomes of Native Workers: Evidence using Longitudinal Data from the LEHD
January 2016
Working Paper Number:
CES-16-56
Empirical estimates of the effect of immigration on native workers that rely on spatial comparisons have generally found small effects, but have been subject to the criticism that out-migration by native workers dampens the observed effect by spreading it over a larger area. In contrast, studies that rely on variation in immigration across industries, occupations, or education-based skill-levels often report large negative effects, but rely primarily on repeated cross-sectional data sets which also cannot account for the adjustment of native workers over time. In this paper, we use a newly available data set, the Longitudinal Employer Household Data (LEHD), which provides quarterly earnings records, geographic location, and firm and industry identifiers for 97% of all privately employed workers in 29 states. We use this data to analyze the impact of immigration on earnings changes and the mobility response of native workers. Overall, we find that although immigration has a negative effect on the earnings and employment of native workers, and positive effects on their firm, industry, and cross-state mobility, the overall size of the effects is small.
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