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Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report
April 2023
Authors:
J. David Brown,
Danielle H. Sandler,
Lawrence Warren,
Moises Yi,
Misty L. Heggeness,
Joseph L. Schafer,
Matthew Spence,
Marta Murray-Close,
Carl Lieberman,
Genevieve Denoeux,
Lauren Medina
Working Paper Number:
CES-23-21
This report develops a method using administrative records (AR) to fill in responses for nonresponding American Community Survey (ACS) housing units rather than adjusting survey weights to account for selection of a subset of nonresponding housing units for follow-up interviews and for nonresponse bias. The method also inserts AR and modeling in place of edits and imputations for ACS survey citizenship item nonresponses. We produce Citizen Voting-Age Population (CVAP) tabulations using this enhanced CVAP method and compare them to published estimates. The enhanced CVAP method produces a 0.74 percentage point lower citizen share, and it is 3.05 percentage points lower for voting-age Hispanics. The latter result can be partly explained by omissions of voting-age Hispanic noncitizens with unknown legal status from ACS household responses. Weight adjustments may be less effective at addressing nonresponse bias under those conditions.
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Universal Preschool Lottery Admissions and Its Effects on Long-Run Earnings and Outcomes
March 2023
Working Paper Number:
CES-23-09
We use an admissions lottery to estimate the effect of a universal (non-means tested) preschool program on students' long-run earnings, income, marital status, fertility and geographic mobility. We observe long-run outcomes by linking both admitted and non-admitted individuals to confidential administrative data including tax records. Funding for this preschool program comes from an Indigenous organization, which grants Indigenous students admissions preference and free tuition. We find treated children have between 5 to 6 percent higher earnings as young adults. The results are strongest for individuals from the lower half of the household income distribution in childhood. Likely mechanisms include high-quality teachers and curriculum.
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Full Report of the Comparisons of Administrative Record Rosters to Census Self-Responses and NRFU Household Member Responses
March 2023
Working Paper Number:
CES-23-08
One of the U.S. Census Bureau's innovations in the 2020 U.S. Census was the use of administrative records (AR) to create household rosters for enumerating some addresses when a self response was not available but high-quality ARs were. The goal was to reduce the cost of fieldwork during the Nonresponse Followup operation (NRFU). The original plan had NRFU beginning in mid-May and continuing through late July 2020. However, the COVID-19 pandemic forced the delay of NRFU and caused the Internal Revenue Service to postpone the income tax filing deadline, resulting in an interruption in the delivery of ARs to the U.S. Census Bureau. The delays were not anticipated when U.S. Census Bureau staff conducted the research on AR enumeration with the 2010 Census data in preparation for the 2020 Census or during the fine tuning of plans for using ARs during the 2018 End-to-End Census Test. These circumstances raised questions about whether the quality of the AR household rosters was high enough for use in enumeration. To aid in investigating the concern about the quality of the AR rosters, our analyses compared AR rosters to self-response rosters and NRFU household member responses at addresses where both ARs and a self-response were available.
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National Experimental Wellbeing Statistics - Version 1
February 2023
Working Paper Number:
CES-23-04
This is the U.S. Census Bureau's first release of the National Experimental Wellbeing Statistics (NEWS) project. The NEWS project aims to produce the best possible estimates of income and poverty given all available survey and administrative data. We link survey, decennial census, administrative, and third-party data to address measurement error in income and poverty statistics. We estimate improved (pre-tax money) income and poverty statistics for 2018 by addressing several possible sources of bias documented in prior research. We address biases from 1) unit nonresponse through improved weights, 2) missing income information in both survey and administrative data through improved imputation, and 3) misreporting by combining or replacing survey responses with administrative information. Reducing survey error substantially affects key measures of well-being: We estimate median household income is 6.3 percent higher than in survey estimates, and poverty is 1.1 percentage points lower. These changes are driven by subpopulations for which survey error is particularly relevant. For house holders aged 65 and over, median household income is 27.3 percent higher and poverty is 3.3 percentage points lower than in survey estimates. We do not find a significant impact on median household income for householders under 65 or on child poverty. Finally, we discuss plans for future releases: addressing other potential sources of bias, releasing additional years of statistics, extending the income concepts measured, and including smaller geographies such as state and county.
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Estimating the Impact of the Age of Criminal Majority: Decomposing Multiple Treatments in a Regression Discontinuity Framework
January 2023
Working Paper Number:
CES-23-01
This paper studies the impact of adult prosecution on recidivism and employment trajectories for adolescent, first-time felony defendants. We use extensive linked Criminal Justice Administrative Record System and socio-economic data from Wayne County, Michigan (Detroit). Using the discrete age of majority rule and a regression discontinuity design, we find that adult prosecution reduces future criminal charges over 5 years by 0.48 felony cases (? 20%) while also worsening labor market outcomes: 0.76 fewer employers (? 19%) and $674 fewer earnings (? 21%) per year. We develop a novel econometric framework that combines standard regression discontinuity methods with predictive machine learning models to identify mechanism-specific treatment effects that underpin the overall impact of adult prosecution. We leverage these estimates to consider four policy counterfactuals: (1) raising the age of majority, (2) increasing adult dismissals to match the juvenile disposition rates, (3) eliminating adult incarceration, and (4) expanding juvenile record sealing opportunities to teenage adult defendants. All four scenarios generate positive returns for government budgets. When accounting for impacts to defendants as well as victim costs borne by society stemming from increases in recidivism, we find positive social returns for juvenile record sealing expansions and dismissing marginal adult charges; raising the age of majority breaks even. Eliminating prison for first-time adult felony defendants, however, increases net social costs. Policymakers may still find this attractive if they are willing to value beneficiaries (taxpayers and defendants) slightly higher (124%) than potential victims.
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Maternal and Infant Health Inequality: New Evidence from Linked Administrative Data
November 2022
Working Paper Number:
CES-22-55
We use linked administrative data that combines the universe of California birth records, hospitalizations, and death records with parental income from Internal Revenue Service tax records and the Longitudinal Employer-Household Dynamics file to provide novel evidence on economic inequality in infant and maternal health. We find that birth outcomes vary nonmonotonically with parental income, and that children of parents in the top ventile of the income distribution have higher rates of low birth weight and preterm birth than those in the bottom ventile. However, unlike birth outcomes, infant mortality varies monotonically with income, and infants of parents in the top ventile of the income distribution---who have the worst birth outcomes---have a death rate that is half that of infants of parents in the bottom ventile. When studying maternal health, we find a similar pattern of non-monotonicity between income and severe maternal morbidity, and a monotonic and decreasing relationship between income and maternal mortality. At the same time, these disparities by parental income are small when compared to racial disparities, and we observe virtually no convergence in health outcomes across racial and ethnic groups as income rises. Indeed, infant and maternal health in Black families at the top of the income distribution is markedly worse than that of white families at the bottom of the income distribution. Lastly, we benchmark the health gradients in California to those in Sweden, finding that infant and maternal health is worse in California than in Sweden for most outcomes throughout the entire income distribution.
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LEHD Snapshot Documentation, Release S2021_R2022Q4
November 2022
Working Paper Number:
CES-22-51
The Longitudinal Employer-Household Dynamics (LEHD) data at the U.S. Census Bureau is a quarterly database of linked employer-employee data covering over 95% of employment in the United States. These data are used to produce a number of public-use tabulations and tools, including the Quarterly Workforce Indicators (QWI), LEHD Origin-Destination Employment Statistics (LODES), Job-to-Job Flows (J2J), and Post-Secondary Employment Outcomes (PSEO) data products. Researchers on approved projects may also access the underlying LEHD microdata directly, in the form of the LEHD Snapshot restricted-use data product. This document provides a detailed overview of the LEHD Snapshot as of release S2021_R2022Q4, including user guidance, variable codebooks, and an overview of the approvals needed to obtain access. Updates to the documentation for this and future snapshot releases will be made available in HTML format on the LEHD website.
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Measuring the Characteristics and Employment Dynamics of U.S. Inventors
September 2022
Working Paper Number:
CES-22-43
Innovation is a key driver of long run economic growth. Studying innovation requires a clear view of the characteristics and behavior of the individuals that create new ideas. A general lack of rich, large-scale data has constrained such analyses. We address this by introducing a new dataset linking patent inventors to survey, census, and administrative microdata at the U.S. Census Bureau. We use this data to provide a first look at the demographic characteristics, employer characteristics, earnings, and employment dynamics of inventors. These linkages, which will be available to researchers with approved access, dramatically increases the scope of what can be learned about inventors and innovative activity.
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Covering Undocumented Immigrants: The Effects of a Large-Scale Prenatal Care Intervention
August 2022
Working Paper Number:
CES-22-28
Undocumented immigrants are ineligible for public insurance coverage for prenatal care in most states, despite their children representing a large fraction of births and having U.S. citizenship. In this paper, we examine a policy that expanded Medicaid pregnancy coverage to undocumented immigrants. Using a novel dataset that links California birth records to Census surveys, we identify siblings born to immigrant mothers before and after the policy. Implementing a mothers' fixed effects design, we find that the policy increased coverage for and use of prenatal care among pregnant immigrant women, and increased average gestation length and birth weight among their children.
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Diversity and Labor Market Outcomes in the Economics Profession
July 2022
Working Paper Number:
CES-22-26
While the lack of gender and racial diversity in economics in academia (for students and professors) is well-established, less is known about the overall placement and earnings of economists by gender and race. Understanding demand-side factors is important, as improvements in the supply side by diversifying the pipeline alone may not be enough to improve equity in the profession. Using the Survey of Earned Doctorates (SED) linked to Longitudinal Employer-Household Dynamics (LEHD) jobs data, we examine placements and earnings for economists working in the U.S. after receiving a PhD by gender and race. We find enormous dispersion in pay for economists within and across sectors that grows over time. Female PhD economists earn about 12 percent less than their male colleagues on average; Black PhD economists earn about 15 percent less than their white counterparts on average; and overall underrepresented minority PhD economists earn about 8 percent less than their white counterparts. These pay disparities are attenuated in some sectors and when controlling for rank of PhD granting institution and employer.
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