Our analysis provides the rst disaggregated examination of earnings inequality and immobility within the Hispanic ethnic group and the Asian race group in the U.S. over the period of 2005-2015. Our analysis differentiates between long-term immigrant and native-born Hispanics and Asians relative to recent immigrants to the U.S. (post 2005) and new labor market entrants. Our results show that for the Asian and Hispanic population aged 18-45, earnings inequality is constant or slightly decreasing for the long-term immigrant and native-born populations. However, including new labor market entrants and recent immigrants to the U.S. contributes significantly to the earnings inequality for these groups at both the aggregate and disaggregated race or ethnic group levels. These findings have important implications for the measurement of inequality for racial and ethnic groups that have higher proportions of new immigrants and new labor market entrants in the U.S.
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Foreign vs. U.S. Graduate Degrees: The Impact on Earnings Assimilation and Return Migration for the Foreign Born
June 2019
Working Paper Number:
CES-19-17
Using a novel panel data set of recent immigrants to the U.S., we identify return migration rates and earnings trajectories of two immigrant groups: those with foreign graduate degrees and those with a U.S. graduate degree. We focus on immigrants (of both genders) to the U.S. who arrive in the same entry cohort and from the same country of birth over the period 2005-2015. In Census-IRS administrative data, we find that downward earnings trajectories are predictive of return migration for immigrants with degrees acquired abroad. Meanwhile, immigrants with U.S.-acquired graduate degrees experience mainly upward earnings mobility.
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Immigrants' Earnings Growth and Return Migration from the U.S.: Examining their Determinants using Linked Survey and Administrative Data
March 2019
Working Paper Number:
CES-19-10
Using a novel panel data set of recent immigrants to the U.S. (2005-2007) from individual-level linked U.S. Census Bureau survey data and Internal Revenue Service (IRS) administrative records, we identify the determinants of return migration and earnings growth for this immigrant arrival cohort. We show that by 10 years after arrival almost 40 percent have return migrated. Our analysis examines these flows by educational attainment, country of birth, and English language ability separately for each gender. We show, for the first time, that return migrants experience downward earnings mobility over two to three years prior to their return migration. This finding suggests that economic shocks are closely related to emigration decisions; time-variant unobserved characteristics may be more important in determining out-migration than previously known. We also show that wage assimilation with native-born populations occurs fairly quickly; after 10 years there is strong convergence in earnings by several characteristics. Finally, we confirm that the use of stock-based panel data lead to estimates of slower earnings growth than is found using repeated cross-section data. However, we also show, using selection-correction methods in our panel data, that stock-based panel data may understate the rate of earnings growth for the initial immigrant arrival cohort when emigration is not accounted for.
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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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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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Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data
January 2017
Working Paper Number:
CES-17-24
Using earnings data from the U.S. Census Bureau, this paper analyzes the role of the employer in explaining the rise in earnings inequality in the United States. We first establish a consistent frame of analysis appropriate for administrative data used to study earnings inequality. We show that the trends in earnings inequality in the administrative data from the Longitudinal Employer-Household Dynamics Program are inconsistent with other data sources when we do not correct for the presence of misused SSNs. After this correction to the worker frame, we analyze how the earnings distribution has changed in the last decade. We present a decomposition of the year-to-year changes in the earnings distribution from 2004-2013. Even when simplifying these flows to movements between the bottom 20%, the middle 60% and the top 20% of the earnings distribution, about 20.5 million workers undergo a transition each year. Another 19.9 million move between employment and nonemployment. To understand the role of the firm in these transitions, we estimate a model for log earnings with additive fixed worker and firm effects using all jobs held by eligible workers from 2004-2013. We construct a composite log earnings firm component across all jobs for a worker in a given year and a non-firm component. We also construct a skill-type index. We show that, while the difference between working at a low-or middle-paying firm are relatively small, the gains from working at a top-paying firm are large. Specifically, the benefits of working for a high-paying firm are not only realized today, through higher earnings paid to the worker, but also persist through an increase in the probability of upward mobility. High-paying firms facilitate moving workers to the top of the earnings distribution and keeping them there.
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Who Gains from Creative Destruction? Evidence from High-Quality Entrepreneurship in the United States
October 2019
Working Paper Number:
CES-19-29
The question of who gains from high-quality entrepreneurship is crucial to understanding whether investments in incubating potentially innovative start-up firms will produce socially beneficial outcomes. We attempt to bring new evidence to this question by combining new aggregate measures of local area income inequality and income mobility with measures of entrepreneurship from Guzman and Stern (2017). Our new aggregate measures are generated by linking American Community Survey data with the universe of IRS 1040 tax returns. In both fixed effects and IV models using a Bartik-style instrument, we find that entrepreneurship increases income inequality. Further, we find that this increase in income inequality arises due to the fact that almost all of the individual gains associated with increased entrepreneurship accrue to the top 10 percent of the income distribution. While we find mixed evidence for small positive effects of entrepreneurship lower on the income distribution, we find little if any evidence that entrepreneurship increases income mobility.
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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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The Changing Nature of Pollution, Income, and Environmental Inequality in the United States
January 2024
Working Paper Number:
CES-24-04
This paper uses administrative tax records linked to Census demographic data and high-resolution measures of fine small particulate (PM2.5) exposure to study the evolution of the Black-White pollution exposure gap over the past 40 years. In doing so, we focus on the various ways in which income may have contributed to these changes using a statistical decomposition. We decompose the overall change in the Black-White PM2.5 exposure gap into (1) components that stem from rank-preserving compression in the overall pollution distribution and (2) changes that stem from a reordering of Black and White households within the pollution distribution. We find a significant narrowing of the Black-White PM2.5 exposure gap over this time period that is overwhelmingly driven by rank-preserving changes rather than positional changes. However, the relative positions of Black and White households at the upper end of the pollution distribution have meaningfully shifted in the most recent years.
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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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Trends in Earnings Inequality and Earnings Instability among U.S. Couples: How Important is Assortative Matching?
January 2015
Working Paper Number:
CES-15-04
We examine changes in inequality and instability of the combined earnings of married couples over the 1980-2009 period using two U.S. panel data sets: Social Security earnings data matched to Survey of Income and Program Participation panels (SIPP-SSA) and the Panel Study of Income Dynamics. Relative to male earnings inequality, the inequality of couples' earnings is both lower in levels and rises by a smaller amount. We also find that couples' earnings instability is lower in levels compared to male earnings instability and actually declines in the SIPP-SSA data. While wives' earnings played an important role in dampening the rise in inequality and year-to-year variation in resources at the family level, we find that marital sorting and coordination of labor supply decisions at the family level played a minor role. Comparing actual couples to randomly paired simulated couples, we find very similar trends in earnings inequality and instability.
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