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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Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity
November 2023
Working Paper Number:
CES-23-55
Shifting earnings inequality among U.S. workers over the last five decades has been widely stud ied, but understanding how these shifts evolve across smaller groups has been difficult. Publicly available data sources typically only ensure representative data at high levels of aggregation, so they obscure many details of earnings distributions for smaller populations. We define and construct a set of granular statistics describing income distributions, income mobility and con ditional income growth for a large number of subnational groups in the U.S. for a two-decade period (1998-2019). In this paper, we use the resulting data to explore the evolution of income inequality and mobility for detailed groups defined by race and ethnicity. We find that patterns identified from the universe of tax filers and W-2 recipients that we observe differ in important ways from those that one might identify in public sources. The full set of statistics that we construct is available publicly as the Income Distributions and Dynamics in America, or IDDA, data set.
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Who Gentrifies Low Income Neighborhoods?
January 2008
Working Paper Number:
CES-08-02
This paper uses confidential Census data, specifically the 1990 and 2000 Census Long- Form data, to study the demographic processes underlying the gentrification of low income urban neighborhoods during the 1990's. In contrast to previous studies, the analysis is conducted at the more refined census-tract level with a narrower definition of gentrification and more narrowly defined comparison neighborhoods. The analysis is also richly disaggregated by demographic characteristic, uncovering differential patterns by race, education, age and family structure that would not have emerged in the more aggregate analysis in previous studies. The results provide little evidence of displacement of low-income non-white households in gentrifying neighborhoods. The bulk of the income gains in gentrifying neighborhoods are attributed to white college graduates and black high school graduates. It is the disproportionate in-migration of the former and the disproportionate retention and income gains of the latter that appear to be the main engines of gentrification.
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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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Potential Bias When Using Administrative Data to Measure the Family Income of School-Aged Children
January 2025
Working Paper Number:
CES-25-03
Researchers and practitioners increasingly rely on administrative data sources to measure family income. However, administrative data sources are often incomplete in their coverage of the population, giving rise to potential bias in family income measures, particularly if coverage deficiencies are not well understood. We focus on the school-aged child population, due to its particular import to research and policy, and because of the unique challenges of linking children to family income information. We find that two of the most significant administrative sources of family income information that permit linking of children and parents'IRS Form 1040 and SNAP participation records'usefully complement each other, potentially reducing coverage bias when used together. In a case study considering how best to measure economic disadvantage rates in the public school student population, we demonstrate the sensitivity of family income statistics to assumptions about individuals who do not appear in administrative data sources.
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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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Trends in the Relative Household Income of Working-Age Men with Work Limitations: Correcting the Record Using Internal Current Population Survey Data
March 2008
Working Paper Number:
CES-08-05
Previous research measuring the economic well-being of working-age men with work limitations relative to such men without work limitations in the public use March Current Population Survey (CPS) systematically understates the mean household income of both groups; overstates the relative household income of those with work limitations; and understates the decline in their relative household income over time. Using the internal March CPS, we demonstrate this by creating a cell mean series beginning in 1975 that provides the mean reported income of all topcoded persons for each source of income in the public use March CPS data. Using our cell mean series with the public use March CPS, we closely match the yearly mean income of working-age men with and without work limitations over the period 1987-2004 in the internal data and show that this match is superior to ones using alternative methods of correcting for topcoding currently used in the disability literature. We then provide levels and trends in the relative income of working-age men with work limitations from 1980-2006, the earliest year in the March CPS that such comparisons can be made.
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The Antipoverty Impact of the EITC: New Estimates from Survey and Administrative Tax Records
April 2019
Working Paper Number:
CES-19-14R
We reassess the antipoverty effects of the EITC using unique data linking the CPS Annual Social and Economic Supplement to IRS data for the same individuals spanning years 2005-2016. We compare EITC benefits from standard simulators to administrative EITC payments and find that significantly more actual EITC payments flow to childless tax units than predicted, and to those whose family income places them above official poverty thresholds. However, actual EITC payments appear to be target efficient at the tax unit level. In 2016, about 3.1 million persons were lifted out of poverty by the EITC, substantially less than prior estimates.
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Estimating Trends in U.S. Income Inequality Using the Current Population Survey: The Importance of Controlling for Censoring
August 2008
Working Paper Number:
CES-08-25
Using internal and public use March Current Population Survey (CPS) data, we analyze trends in US income inequality (1975'2004). We find that the upward trend in income inequality prior to 1993 significantly slowed thereafter once we control for top coding in the public use data and censoring in the internal data. Because both series do not capture trends at the very top of the income distribution, we use a multiple imputation approach in which values for censored observations are imputed using draws from a Generalized Beta distribution of the Second Kind (GB2) fitted to internal data. Doing so, we find income inequality trends similar to those derived from unadjusted internal data. Our trend results are generally robust to the choice of inequality index, whether Gini coefficient or other commonly-used indices. When we compare our best estimates of the income shares held by the richest tenth with those reported by Piketty and Saez (2003), our trends fairly closely match their trends, except for the top 1 percent of the distribution. Thus, we argue that if United States income inequality has been substantially increasing since 1993, such increases are confined to this very high income group.
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The Demographics of the Recipients of the First Economic Impact Payment
May 2023
Working Paper Number:
CES-23-24
Starting in April 2020, the federal government began to distribute Economic Impact Payments (EIPs) in response to the health and economic crisis caused by COVID-19. More than 160 million payments were disbursed. We produce statistics concerning the receipt of EIPs by individuals and households across key demographic subgroups. We find that payments went out particularly quickly to households with children and lower-income households, and the rate of receipt was quite high for individuals over age 60, likely due to a coordinated effort to issue payments automatically to Social Security recipients. We disaggregate statistics by race/ethnicity to document whether racial disparities arose in EIP disbursement. Receipt rates were high overall, with limited differences across racial/ethnic subgroups. We provide a set of detailed counts in tables for use by the public.
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Recent Trends in Top Income Shares in the USA: Reconciling Estimates from March CPS and IRS Tax Return Data
September 2009
Working Paper Number:
CES-09-26
Although the vast majority of US research on trends in the inequality of family income is based on public-use March Current Population Survey (CPS) data, a new wave of research based on Internal Revenue Service (IRS) tax return data reports substantially higher levels of inequality and faster growing trends. We show that these apparently inconsistent estimates can largely be reconciled once one uses internal CPS data (which better captures the top of the income distribution than public-use CPS data) and defines the income distribution in the same way. Using internal CPS data for 1967'2006, we closely match the IRS data-based estimates of top income shares reported by Piketty and Saez (2003), with the exception of the share of the top 1 percent of the distribution during 1993'2000. Our results imply that, if inequality has increased substantially since 1993, the increase is confined to income changes for those in the top 1 percent of the distribution.
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