This paper examines how spatial frictions that differ among heterogeneous workers and establishments shape the geographic and demographic incidence of alternative local labor demand shocks, with implications for the appropriate level of government at which to fund local economic initiatives. LEHD data featuring millions of job transitions facilitate estimation of a rich two-sided labor market assignment model. The model generates simulated forecasts of many alternative local demand shocks featuring different establishment compositions and local areas. Workers within 10 miles receive only 11.2% (6.6%) of nationwide welfare (employment) short-run gains, with at least 35.9% (62.0%) accruing to out-of-state workers, despite much larger per-worker impacts for the closest workers. Local incidence by demographic category is very sensitive to shock composition, but different shocks produce similar demographic incidence farther from the shock. Furthermore, the remaining heterogeneity in incidence at the state or national level can reverse patterns of heterogeneous demographic impacts at the local level. Overall, the results suggest that reduced-form approaches using distant locations as controls can produce accurate estimates of local shock impacts on local workers, but that the distribution of local impacts badly approximates shocks' statewide or national incidence.
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Firm Dynamics and Assortative Matching
May 2014
Working Paper Number:
CES-14-25
I study the relationship between firm growth and the characteristics of newly hired workers. Using Census microdata I obtain a novel empirical result: when a given firm grows faster it hires workers with higher past wages. These results suggest that productive, fast-growing firms tend to hire more productive workers, a form of positive assortative matching. This contrasts with prior research that has found negligible or negative sorting between workers and firms. I present evidence that this difference arises because previous studies have focused on cross-sectional comparisons across firms and industries, while my results condition on firm characteristics (e.g. size, industry, or firm fixed effects). Motivated by the empirical findings I develop a search model with heterogeneous workers and firms. The model is the first to study worker-firm sorting in an environment with worker heterogeneity, firm productivity shocks, multi-worker firms, and search frictions. Despite this richness the model is tractable, allowing me to characterize assortative matching, compositional dynamics and other properties analytically. I show that the model reproduces the positive firm growth-quality of hires correlation when worker and firm types are strong complements in production (i.e. the production function is strictly log-supermodular).
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Modeling Labor Markets with Heterogeneous Agents and Matches
May 2002
Working Paper Number:
tp-2002-19
I present a matching model with heterogeneous workers, firms, and worker-fim
matches. The model generalizes the seminal Jovanovic (1979) model to the case of
heterogeneous agents. The equilibrium wage is linear in a person-specific component,
a firm-specific component, and a match specific component that varies with tenure.
Under certain conditions, the equilibrium wage takes a simpler structure where the
match specific component does not vary with tenure. I discuss fixed- and mixedeffect
methods for estimating wage models with this structure on longitudinal linked
employer-employee data. The fixed effect specification relies on restrictive identification
conditions, but is feasible for very large databases. The mixed model requires less
restrictive identification conditions, but is feasible only on relatively small databases.
Both the fixed and mixed models generate empirical person, firm, and match effects
with characteristics that are consistent with predictions from the matching model; the
mixed model moreso than the fixed model. Shortcomings of the fixed model appear to
be artifacts of the identification conditions.
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U.S. Worker Mobility Across Establishments within Firms: Scope, Prevalence, and Effects on Worker Earnings
May 2024
Working Paper Number:
CES-24-24
Multi-establishment firms account for around 60% of U.S. workers' primary employers, providing ample opportunity for workers to change their work location without changing their employer. Using U.S. matched employer-employee data, this paper analyzes workers' access to and use of such between-establishment job transitions, and estimates the effect on workers' earnings growth of greater access, as measured by proximity of employment at other within-firm establishments. While establishment transitions are not perfectly observed, we estimate that within-firm establishment transitions account for 7.8% percent of all job transitions and 18.2% of transitions originating from the largest firms. Using variation in worker's establishment locations within their firms' establishment network, we show that having a greater share of the firm's jobs in nearby establishments generates meaningful increases in workers' earnings: a worker at the 90th percentile of earnings gains from more proximate within-firm job opportunities can expect to enjoy 2% higher average earnings over the following five years than a worker at the 10th percentile with the same baseline earnings.
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Displaced workers, early leavers, and re-employment wages
November 2002
Working Paper Number:
tp-2002-18
In this paper, we lay out a search model that takes explicitly into account the
information flow prior to a mass layoff. Using universal wage data files that allow
us to identify individuals working with healthy and displacing firms both at
the time of displacement as well as any other time period, we test the predictions
of the model on re-employment wage differentials. Workers leaving a "distressed"
firm have higher re-employment wages than workers who stay with the
distressed firm until displacement. This result is robust to the inclusion of controls
for worker quality and unobservable firm characteristics.
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Pay, Employment, and Dynamics of Young Firms
July 2019
Working Paper Number:
CES-19-23
Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.
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Recalculating... : How Uncertainty in Local Labor Market Definitions Affects Empirical Findings
January 2017
Working Paper Number:
CES-17-49R
This paper evaluates the use of commuting zones as a local labor market definition. We revisit Tolbert and Sizer (1996) and demonstrate the sensitivity of definitions to two features of the methodology: a cluster dissimilarity cutoff, or the count of clusters, and uncertainty in the input data. We show how these features impact empirical estimates using a standard application of commuting zones and an example from related literature. We conclude with advice to researchers on how to demonstrate the robustness of empirical findings to uncertainty in the definition of commuting zones
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Abandoning the Sinking Ship: The Composition of Worker Flows Prior to Displacement
August 2002
Working Paper Number:
tp-2002-11
declines experienced by workers several years before displacement occurs. Little attention, however,
has been paid to other changes in compensation and employment in firms prior to the actual
displacement event. This paper examines changes in the composition of job and worker flows
before displacement, and compares the "quality" distribution of workers leaving distressed firms to
that of all movers in general.
More specifically, we exploit a unique dataset that contains observations on all workers over
an extended period of time in a number of US states, combined with survey data, to decompose
different jobflow statistics according to skill group and number of periods before displacement.
Furthermore, we use quantile regression techniques to analyze changes in the skill profile of workers
leaving distressed firms. Throughout the paper, our measure for worker skill is derived from
person fixed effects estimated using the wage regression techniques pioneered by Abowd, Kramarz,
and Margolis (1999) in conjunction with the standard specification for displaced worker studies
(Jacobson, LaLonde, and Sullivan 1993).
We find that there are significant changes to all measures of job and worker flows prior to
displacement. In particular, churning rates increase for all skill groups, but retention rates drop
for high-skilled workers. The quantile regressions reveal a right-shift in the distribution of worker
quality at the time of displacement as compared to average firm exit flows. In the periods prior
to displacement, the patterns are consistent with both discouraged high-skilled workers leaving the
firm, and management actions to layoff low-skilled workers.
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Two Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files
January 2017
Working Paper Number:
CES-17-34
Commuting flows and workplace employment data have a wide constituency of users including urban and regional planners, social science and transportation researchers, and businesses. The U.S. Census Bureau releases two, national data products that give the magnitude and characteristics of home to work flows. The American Community Survey (ACS) tabulates households' responses on employment, workplace, and commuting behavior. The Longitudinal Employer-Household Dynamics (LEHD) program tabulates administrative records on jobs in the LEHD Origin-Destination Employment Statistics (LODES). Design differences across the datasets lead to divergence in a comparable statistic: county-to-county aggregate commute flows. To understand differences in the public use data, this study compares ACS and LEHD source files, using identifying information and probabilistic matching to join person and job records. In our assessment, we compare commuting statistics for job frames linked on person, employment status, employer, and workplace and we identify person and job characteristics as well as design features of the data frames that explain aggregate differences. We find a lower rate of within-county commuting and farther commutes in LODES. We attribute these greater distances to differences in workplace reporting and to uncertainty of establishment assignments in LEHD for workers at multi-unit employers. Minor contributing factors include differences in residence location and ACS workplace edits. The results of this analysis and the data infrastructure developed will support further work to understand and enhance commuting statistics in both datasets.
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The Alpha Beta Gamma of the Labor Market
April 2022
Working Paper Number:
CES-22-10
Using a large panel dataset of US workers, we calibrate a search-theoretic model of the labor market, where workers are heterogeneous with respect to the parameters governing their employment transitions. We first approximate heterogeneity with a discrete number of latent types, and then calibrate type-specific parameters by matching type-specific moments. Heterogeneity is well approximated by 3 types: as, 's and ?s. Workers of type a find employment quickly because they have large gains from trade, and stick to their jobs because their productivity is similar across jobs. Workers of type ? find employment slowly because they have small gains from trade, and are unlikely to stick to their job because they keep searching for jobs in the right tail of the productivity distribution. During the Great Recession, the magnitude and persistence of aggregate unemployment is caused by ?s, who are vulnerable to shocks and, once displaced, they cycle through multiple unemployment spells before finding stable employment.
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Revisiting the Effects of Unemployment Insurance Extensions on Unemployment: A Measurement Error-Corrected Regression Discontinuity Approach
March 2016
Working Paper Number:
carra-2016-01
The extension of Unemployment Insurance (UI) benefits was a key policy response to the Great Recession. However, these benefit extensions may have had detrimental labor market effects. While evidence on the individual labor supply response indicates small effects on unemployment, recent work by Hagedorn et al. (2015) uses a county border pair identification strategy to find that the total effects inclusive of effects on labor demand are substantially larger. By focusing on variation within border county pairs, this identification strategy requires counties in the pairs to be similar in terms of unobservable factors. We explore this assumption using an alternative regression discontinuity approach that controls for changes in unobservables by distance to the border. To do so, we must account for measurement error induced by using county-level aggregates. These new results provide no evidence of a large change in unemployment induced by differences in UI generosity across state boundaries. Further analysis suggests that individuals respond to UI benefit differences across boundaries by targeting job search in high-benefit states, thereby raising concerns of treatment spillovers in this setting. Taken together, these two results suggest that the effect of UI benefit extensions on unemployment remains an open question.
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