The Census Bureau's Environmental Impacts Frame (EIF) is a microdata infrastructure that combines individual-level information on residence, demographics, and economic characteristics with environmental amenities and hazards from 1999 through the present day. To better understand the long-run consequences and intergenerational effects of exposure to a changing environment, we expand the EIF by extending it backward to 1940. The Historical Environmental Impacts Frame (HEIF) combines the Census Bureau's historical administrative data, publicly available 1940 address information from the 1940 Decennial Census, and historical environmental data. This paper discusses the creation of the HEIF as well as the unique challenges that arise with using the Census Bureau's historical administrative data.
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Building the Prototype Census Environmental Impacts Frame
April 2023
Working Paper Number:
CES-23-20
The natural environment is central to all aspects of life, but efforts to quantify its influence have been hindered by data availability and measurement constraints. To mitigate some of these challenges, we introduce a new prototype of a microdata infras tructure: the Census Environmental Impacts Frame (EIF). The EIF provides detailed individual-level information on demographics, economic characteristics, and address level histories ' linked to spatially and temporally resolved estimates of environmental conditions for each individual ' for almost every resident in the United States over the past two decades. This linked microdata infrastructure provides a unique platform for advancing our understanding about the distribution of environmental amenities and hazards, when, how, and why exposures have evolved over time, and the consequences of environmental inequality and changing environmental conditions. We describe the construction of the EIF, explore issues of coverage and data quality, document patterns and trends in individual exposure to two correlated but distinct air pollutants as an application of the EIF, and discuss implications and opportunities for future research.
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Geographic Immobility in the United States: Assessing the Prevalence and Characteristics of Those Who Never Migrate Across State Lines Using Linked Federal Tax Microdata
March 2025
Working Paper Number:
CES-25-19
This paper explores the prevalence and characteristics of those who never migrate at the state scale in the U.S. Studying people who never migrate requires regular and frequent observation of their residential location for a lifetime, or at least for many years. A novel U.S. population-sized longitudinal dataset that links individual level Internal Revenue Service (IRS) and Social Security Administration (SSA) administrative records supplies this information annually, along with information on income and socio-demographic characteristics. We use these administrative microdata to follow a cohort aged between 15 and 50 in 2001 from 2001 to 2016, differentiating those who lived in the same state every year during this period (i.e., never made an interstate move) from those who lived in more than one state (i.e., made at least one interstate move). We find those who never made an interstate move comprised 75 percent of the total population of this age cohort. This percentage varies by year of age but never falls below 62 percent even for those who were teenagers or young adults in 2001. There are also variations in these percentages by sex, race, nativity, and income, with the latter having the largest effects. We also find substantial variation in these percentages across states. Our findings suggest a need for more research on geographically immobile populations in U.S.
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Internal Migration in the U.S. During the COVID-19 Pandemic
September 2024
Working Paper Number:
CES-24-50
Survey and administrative internal migration data disagree on whether the COVID-19 pandemic increased or decreased mobility in the U.S. Moreover, though scholars have theorized and documented migration in response to environmental hazards and economic shocks, the novel conditions posed by a global pandemic make it difficult to hypothesize whether and how American migration might change as a result. We link individual-level data from the United States Postal Service's National Change of Address (NCOA) registry to American Community Survey (ACS) and Current Population Survey (CPS-ASEC) responses and other administrative records to document changes in the level, geography, and composition of migrant flows between 2019 and 2021. We find a 2% increase in address changes between 2019 and 2020, representing an additional 603,000 moves, driven primarily by young adults, earners at the extremes of the income distribution, and individuals (as opposed to families) moving over longer distances. Though the number of address changes returned to pre-pandemic levels in 2021, the pandemic-era geographic and compositional shifts in favor of longer distance moves away from the Pacific and Mid-Atlantic regions toward the South and in favor of younger, individual movers persisted. We also show that at least part of the disconnect between survey, media, and administrative/third-party migration data sources stems from the apparent misreporting of address changes on Census Bureau surveys. Among ACS and CPS-ASEC householders linked to NCOA data and filing a permanent change of address in their 1-year survey response reference period, only around 68% of ACS and 49% of CPS-ASEC householders also reported living in a different residence one year ago in their survey response.
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The Privacy-Protected Gridded Environmental Impacts Frame
December 2024
Working Paper Number:
CES-24-74
This paper introduces the Gridded Environmental Impacts Frame (Gridded EIF), a novel privacy-protected dataset derived from the U.S. Census Bureau's confidential Environmental Impacts Frame (EIF) microdata infrastructure. The EIF combines comprehensive administrative records and survey data on the U.S. population with high-resolution geospatial information on environmental hazards. While access to the EIF is restricted due to the confidential nature of the underlying data, the Gridded EIF offers a broader research community the opportunity to glean insights from the data while preserving confidentiality. We describe the data and privacy protection process, and offer guidance on appropriate usage, presenting practical applications.
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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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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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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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Mobility, Opportunity, and Volatility Statistics (MOVS):
Infrastructure Files and Public Use Data
April 2024
Working Paper Number:
CES-24-23
Federal statistical agencies and policymakers have identified a need for integrated systems of household and personal income statistics. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in well-being between different types of individuals and families. Until recently, longitudinal income data that are rich enough to calculate detailed income statistics and include demographic characteristics, such as race and ethnicity, have not been available. The Mobility, Opportunity, and Volatility Statistics project (MOVS) fills this gap in comprehensive income statistics. Using linked demographic and tax records on the population of U.S. working-age adults, the MOVS project defines households and calculates household income, applying an equivalence scale to create a personal income concept, and then traces the progress of individuals' incomes over time. We then output a set of intermediate statistics by race-ethnicity group, sex, year, base-year state of residence, and base-year income decile. We select the intermediate statistics most useful in developing more complex intragenerational income mobility measures, such as transition matrices, income growth curves, and variance-based volatility statistics. We provide these intermediate statistics as part of a publicly released data tool with downloadable flat files and accompanying documentation. This paper describes the data build process and the output files, including a brief analysis highlighting the structure and content of our main statistics.
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Geographic Disparities in Alzheimer's Disease and Related Dementia Mortality in the US: Comparing Impacts of Place of Birth and Place of Residence
January 2025
Working Paper Number:
CES-25-11
Objective: Building on the hypothesis that early-life exposures might influence the onset of Alzheimer's Disease and Related Dementia (ADRD), this study delves into geographic variations in ADRD mortality in the US. By considering both state of residence and state of birth, we aim to discern the comparative significance of these geospatial factors.
Methods: We conducted a secondary data analysis of the National Longitudinal Mortality Study (NLMS), that has 3.5 million records from 1973-2011 and over 0.5 million deaths. We focused on individuals born in or before 1930, tracked in NLMS cohorts from 1979-2000. Employing multi-level logistic regression, with individuals nested within states of residence and/or states of birth, we assessed the role of geographical factors in ADRD mortality variation.
Results: We found that both state of birth and state of residence account for a modest portion of ADRD mortality variation. Specifically, state of residence explains 1.19% of the total variation in ADRD mortality, whereas state of birth explains only 0.6%. When combined, both state of residence and state of birth account for only 1.05% of the variation, suggesting state of residence could matter more in ADRD mortality outcomes.
Conclusion: Findings of this study suggest that state of residence explains more variation in ADRD mortality than state of birth. These results indicate that factors in later life may present more impactful intervention points for curbing ADRD mortality. While early-life environmental exposures remain relevant, their role as primary determinants of ADRD in later life appears to be less pronounced in this study.
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Income, Wealth, and Environmental Inequality in the United States
October 2024
Working Paper Number:
CES-24-57
This paper explores the relationships between air pollution, income, wealth, and race by combining administrative data from U.S. tax returns between 1979'2016, various measures of air pollution, and sociodemographic information from linked survey and administrative data. In the first year of our data, the relationship between income and ambient pollution levels nationally is approximately zero for both non-Hispanic White and Black individuals. However, at every single percentile of the national income distribution, Black individuals are exposed to, on average, higher levels of pollution than White individuals. By 2016, the relationship between income and air pollution had steepened, primarily for Black individuals, driven by changes in where rich and poor Black individuals live. We utilize quasi-random shocks to income to examine the causal effect of changes in income and wealth on pollution exposure over a five year horizon, finding that these income'pollution elasticities map closely to the values implied by our descriptive patterns. We calculate that Black-White differences in income can explain ~10 percent of the observed gap in air pollution levels in 2016.
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