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Is it Who You Are, Where You Work, or With Whom You Work? Reassessing the Relationship Between Skill Segregation and Wage Inequality
June 2002
Working Paper Number:
tp-2002-10
In 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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The Measurement of Human Capital in the U.S. Economy
April 2002
Working Paper Number:
tp-2002-09
We develop a new approach to measuring human capital that permits the distinction of both observable
and unobservable dimensions of skill by associating human capital with the portable part
of an individual's wage rate. Using new large-scale, integrated employer-employee data containing
information on 68 million individuals and 3.6 million firms, we explain a very large proportion
(84%) of the total variation in wages rates and attribute substantial variation to both individual
and employer heterogeneity. While the wage distribution remained largely unchanged between
1992-1997, we document a pronounced right shift in the overall distribution of human capital.
Most workers entering our sample, while less experienced, were otherwise more highly skilled, a
difference which can be attributed almost exclusively to unobservables. Nevertheless, compared
to exiters and continuers, entrants exhibited a greater tendency to match to firms paying below
average internal wages. Firms reduced employment shares of low skilled workers and increased
employment shares of high skilled workers in virtually every industry. Our results strongly suggest
that the distribution of human capital will continue to shift to the right, implying a continuing
up-skilling of the employed labor force.
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Large Plant Data in the LRD: Selection of a Sample for Estimation
March 1999
Working Paper Number:
CES-99-06
This paper describes preliminary work with the LRD during our tenure at the Census Bureau as participants in the ASA/NSF/Census Research Program. The objective of the work described here were two-fold. First, we wanted to examine the suitableness of these data for the calculation of plant-level productivity indexes, following procedures typically implemented with time series data. Second, we wanted to select a small number of 2-digit industry groups that would be well suited to the estimation of production functions and systems of factor share equations and factor demand forecasting equations with system-wide techniques. This description of our initial work may be useful to other researchers who are interested in the LRD for the analysis of productivity growth and/or the estimation of systems of factor equations, because the specific results reported in this memo suggest that the data are of good quality, or because the nature of the tasks undertaken provides insight into issues that arise in the analysis of longitudinal establishment data.
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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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Productivity Adjustments and Learning-by-Doing as Human Capital
November 1997
Working Paper Number:
CES-97-17
This paper measures plant-level productivity gains associated with learning curves across the entire manufacturing sector. We measure these gains at plant startups and also after major employment changes. We find: 1.) The gains are strongly associated with a variety of human capital measures implying that learning-by-doing is largely a firm-specific human capital investment. 2.) This implicit investment is large; many plants invest as much in learning-by-doing as they invest in physical capital and much more than they invest in formal job training. 3.) This investment differs persistently over industries and is higher with greater R&D. 4.) Consistent with a learning-by-doing interpretation, the human capital investment is much larger following employment decreases than increases. We conclude that learning-by-doing is a major factor in wage determination, technical progress and asymmetric employment adjustment costs.
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The Impact Of Ownership Change On Employment, Wages, And Labor Productivity In U.S. Manufacturing 1977-87
April 1995
Working Paper Number:
CES-95-08
This paper reports on the impact of ownership change on productivity, wages, and employment in U.S. food manufacturing for the period 1977-87. Our analysis is based on both firm and plant level data taken from the U. S. Census Bureau's Longitudinal Research Database (LRD). Three principal results emerge from the analysis. First, ownership change is positively associated with productivity and wage growth, although the effects are significantly smaller for large plants. Second, ownership change appears to be associated with increases, not decreases, in employment at operating plants. Third, plants changing ownership show a greater likelihood of survival than those that do not change owners. These findings run counter to the notion that mergers and acquisitions cut wages and reduce employment. Finally, neither of the first two results are observed when firm level data are used for the analysis. This suggests that firm level data hide important dynamic activities within the firm. Thus, plant level data are necessary for studying the structure and performance of firms over time.
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The Long-Run Demand for Labor: Estimates From Census Establishment Data
September 1993
Working Paper Number:
CES-93-13
This paper estimates long-run demand functions for production workers, production worker hours, and nonproduction workers using micro data from U.S. establishment surveys. The paper focuses on estimation of the wage and output elasticities of labor demand using data on over 41,000 U.S. manufacturing plants in 1975 and more than 30,000 plants in 1981. Particular attention is focused on the problems of unobserved producer heterogeneity and measurement errors in output that can affect labor demand estimates based on establishment survey data. The empirical results reveal that OLS estimates of both the own-price elasticity and the output elasticity of labor demand are biased downward as a result of unobserved heterogeneity. Differencing the data as a solution to this problem greatly exaggerates measurement error in the output coefficients. The use of capital stocks as instrumental variables to correct for measurement error in output significantly alters output elasticities in the expected direction but has no systematic effect on own-price elasticities. All of these patterns are found in estimates that pool establishment data across industries and in industry-specific regressions for the vast majority of industries. Estimates of the output elasticity of labor demand indicate that there are slight increasing returns for production workers and production hours, with a pooled data estimate of .92. The estimate for nonproduction workers in .98. The variation in the output elasticities across industries is fairly small. Estimates of the own-price elasticity vary more substantially with the year, type of differencing used, and industry. They average -.50 for production hours, -.41 for production workers, and -.44 for nonproduction workers. The price elasticities vary widely across manufacturing industries: the interquartile range for the industry estimates is approximately .40.
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