Is it Who You Are, Where You Work, or With Whom You Work? Reassessing the Relationship Between Skill Segregation and Wage Inequality
AbstractIn a recent paper, Kremer & Maskin (QJE, forthcoming) develop an assignment model in which increases in the dispersion and mean of the skill distribution can lead simultaneously to increases in wage inequality and skill segregation. They then present evidence that, concurrent with rising wage inequality, wage segregation increased for production workers in the United States between 1975 and 1986. My paper argues that relying on wages as a proxy for skill may be problematic. Using a newly developed longitudinal dataset linking virtually the entire universe of workers in the state of Illinois to their employers, I decompose wages into components due, not only to person and firm heterogeneity, but also to the characteristics of their co-workers. Such "co-worker effects" capture the impact of a weighted sum of the characteristics of all workers in a firm on each individual employee’s wage. While rising wage segregation can result from greater skill segregation, it may also be due to changes in the variance of co-worker effects in the economy, or to changes in the covariance between the person, firm, and co-worker components of wages. Due to the limited availability of demographic information on workers, I rely on the person specific component of wages to proxy for co-worker "skills." Because these person effects are unknown ex ante, I implement an iterative estimation approach where they are first obtained from a preliminary regression that excludes any role for co-workers. Because virtually all person and firm effects are identified, the approach yields consistent estimates of the co-worker parameters. My estimates imply that a one standard deviation increase in both a firm’s average person effect and experience level is associated, on average, with wage increases of 3% to 5%. Firms that increase the wage premia they pay workers appear to do so in conjunction with upgrading worker quality. Interestingly, the average effect masks considerable variation in the relative importance of co-workers across industries. After allowing the co-worker parameters to vary across 2 digit industries, I find that industry average co-worker effects explain 26% of observed inter-industry wage differentials. Finally, I decompose the overall distribution of wages into components due to persons, firms, and coworkers. While co-worker effects do indeed serve to exacerbate wage inequality, the tendency for high and low skilled workers to sort non-randomly into firms plays a considerably more prominent role.
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Bibliographic InfoPaper provided by Center for Economic Studies, U.S. Census Bureau in its series Longitudinal Employer-Household Dynamics Technical Papers with number 2002-10.
Length: 60 pages
Date of creation: Jun 2002
Date of revision:
wage inequality; skill segregation; employer-employee data; panel data;
Find related papers by JEL classification:
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data
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