This paper studies the earnings and employment penalties associated with a criminal record. Using a large-scale dataset linking criminal justice and employer-employee wage records, we estimate two-way fixed effects models that decompose earnings into worker's portable earnings potential and firm pay premia, both of which are allowed to shift after a worker acquires a record. We find that firm pay premia explain a small share of earnings gaps between workers with and without a record. There is little evidence of variable within-firm premia gaps either. Instead, components of workers' earnings potential that persist across firms explain the bulk of gaps. Conditional on earnings potential, workers with a record are also substantially less likely to be employed. Difference-in-differences estimates comparing workers' first conviction to workers charged but not convicted or charged later support these findings. The results suggest that criminal record penalties operate primarily by changing whether workers are employed and their earnings potential at every firm rather than increasing sorting into lower-paying jobs, although the bulk of gaps can be attributed to differences that existed prior to acquiring a record.
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Location, Location, Location
October 2021
Working Paper Number:
CES-21-32R
We use data from the Longitudinal Employer-Household Dynamics program to study the causal effects of location on earnings. Starting from a model with employer and employee fixed effects, we estimate the average earnings premiums associated with jobs in different commuting zones (CZs) and different CZ-industry pairs. About half of the variation in mean wages across CZs is attributable to differences in worker ability (as measured by their fixed effects); the other half is attributable to place effects. We show that the place effects from a richly specified cross sectional wage model overstate the causal effects of place (due to unobserved worker ability), while those from a model that simply adds person fixed effects understate the causal effects (due to unobserved heterogeneity in the premiums paid by different firms in the same CZ). Local industry agglomerations are associated with higher wages, but overall differences in industry composition and in CZ-specific returns to industries explain only a small fraction of average place effects. Estimating separate place effects for college and non-college workers, we find that the college wage gap is bigger in larger and higher-wage places, but that two-thirds of this variation is attributable to differences in the relative skills of the two groups in different places. Most of the remaining variation reflects the enhanced sorting of more educated workers to higher-paying industries in larger and higher-wage CZs. Finally, we find that local housing costs at least fully offset local pay premiums, implying that workers who move to larger CZs have no higher net-of-housing consumption.
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Industry Wage Differentials: A Firm-Based Approach
August 2023
Working Paper Number:
CES-23-40
We revisit the estimation of industry wage differentials using linked employer-employee data
from the U.S. LEHD program. Building on recent advances in the measurement of employer wage premiums, we define the industry wage effect as the employment-weighted average workplace premium in that industry. We show that cross-sectional estimates of industry differentials overstate the pay premiums due to unmeasured worker heterogeneity. Conversely, estimates based on industry movers understate the true premiums, due to unmeasured heterogeneity in pay premiums within industries. Industry movers who switch to higher-premium industries tend to leave firms in the origin sector that pay above-average premiums and move to firms in the destination sector with below-average premiums (and vice versa), attenuating the measured industry effects. Our preferred estimates reveal substantial heterogeneity in narrowly-defined industry premiums, with a standard deviation of 12%. On average, workers in higher-paying industries have higher observed and unobserved skills, widening between-industry wage inequality. There are also small but systematic differences in industry premiums across cities, with a wider distribution of pay premiums and more worker sorting in cities with more highpremium firms and high-skilled workers.
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U.S. Long-Term Earnings Outcomes by Sex, Race, Ethnicity, and Place of Birth
May 2021
Working Paper Number:
CES-21-07R
This paper is part of the Global Income Dynamics Project cross-country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12-year average earnings for a single cohort of age 25-54 eligible workers. Differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings, although even after controlling for labor supply substantial earnings differences across demographic groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost all the earnings gap, however above the median the contribution of the differences in the returns to characteristics becomes the dominant component.
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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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NEW EVIDENCE ON SEX SEGREGATION AND SEX DIFFERENCES IN WAGES FROM MATCHED EMPLOYEE-EMPLOYER DATA*
December 1998
Working Paper Number:
CES-98-18
We assemble a new matched employer-employee data set covering essentially all industries and occupations across all regions of the U.S. We use this data set to re-examine the question of the relative contributions to the overall sex gap in wages of sex segregation vs. wage differences by sex within occupation, industry, establishment, and occupation-establishment cells. This new data set is especially useful because earlier research on this topic relied on data sets that covered only a narrow range of industries, occupations, or regions. Our results indicate that a sizable fraction of the sex gap in wages is accounted for by the segregation of women into lower-paying occupations, industries, establishments, and occupations within establishments. Nonetheless, a substantial part of the sex gap in wages remains attributable to the individual's sex. This latter finding contrasts sharply with the conclusions of previous research (especially Groshen, 1991), which indicated that sex segregation accounted for essentially all of the sex wage gap. Further research into the sources of within-establishment within-occupation sex wage differences is therefore much more important than previously thought.
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Escaping poverty for low-wage workers The role of employer characteristics and changes
June 2001
Working Paper Number:
tp-2001-02
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Computing Person and Firm Effects Using Linked Longitudinal Employer-Employee Data
March 2002
Working Paper Number:
tp-2002-06
In this paper we provide the exact formulas for the direct least squares estimation of statistical models that include both person and firm effects. We also provide an algorithm for determining the estimable functions of the person and firm effects (the identifiable effects). The computational techniques are also directly applicable to any linear two-factor analysis of covariance with two high-dimension non-orthogonal factors. We show that the application of the exact solution does not change the substantive conclusions about the relative importance of person and firm effects in the explanation of log real compensation; however, the correlation between person and firm effects is negative, not weakly positive, in the exact solution. We also provide guidance for using the methods developed in earlier work to obtain an accurate approximation.
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Criminal court fees, earnings, and expenditures: A multi-state RD analysis of survey and administrative data
February 2023
Working Paper Number:
CES-23-06
Millions of people in the United States face fines and fees in the criminal court system each year, totaling over $27 billion in overall criminal debt to-date. In this study, we leverage five distinct natural experiments in Florida, Michigan, North Carolina, Texas, and Wisconsin using regression discontinuity designs to evaluate the causal impact of such financial sanctions and user fees. We consider a range of long-term outcomes including employment, recidivism, household expenditures, and other self-reported measures of well-being, which we measure through a combination of administrative records on earnings and employment, the Criminal Justice Administrative Records System, and household surveys. We find consistent evidence across the range of natural experiments and subgroup analyses of precise null effects on the population, ruling out long-run impacts larger than +/-3.6% on total earnings and +/-4.7% on total recidivism. Failure to find changes in outcomes undermines popular narratives of poverty traps arising from criminal debt but argues against the use of fines and fees as a source of local revenue and as a crime control tool.
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The interactions of workers and firms in the low-wage labor market
August 2002
Working Paper Number:
tp-2002-12
This paper presents an analysis of workers who persistently have low earnings in
the labor market over a period of three or more years. Some of these workers manage to
escape from this low-earning status over subsequent years, while many do not. Using
data from the Longitudinal Employer Household Dynamics (LEHD) project at the U.S.
Census Bureau, we analyze the characteristics of persons and especially of their firms and
jobs that enable some to improve their earnings status over time.
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Re-assessing the Spatial Mismatch Hypothesis
April 2025
Working Paper Number:
CES-25-23
We use detailed location information from the Longitudinal Employer-Household Dynamics (LEHD) database to develop new evidence on the effects of spatial mismatch on the relative earnings of Black workers in large US cities. We classify workplaces by the size of the pay premiums they offer in a two-way fixed effects model, providing a simple metric for defining 'good' jobs. We show that: (a) Black workers earn nearly the same average wage premiums as whites; (b) in most cities Black workers live closer to jobs, and closer to good jobs, than do whites; (c) Black workers typically commute shorter distances than whites; and (d) people who commute further earn higher average pay premiums, but the elasticity with respect to distance traveled is slightly lower for Black workers. We conclude that geographic proximity to good jobs is unlikely to be a major source of the racial earnings gaps in major U.S. cities today.
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