In spite of the large and growing importance of the employer size-wage premium, previous attempts to account for this premium using observable worker or employer characteristics have had limited success. The problem is that, while most theoretical explanations for the size-wage premium are based on the matching of employers and employees, previous empirical work has relied on either worker surveys with little information about the employer, or establishment surveys with little information about the workers. In contrast, this study uses the newly created Worker-Establishment Characteristic Database, which contains linked employer-employee data for a large sample of U.S. manufacturing workers and establishments, to examine seven explanations for the employer size-wage premium. A number of the explanations can account for some of the observed cross-sectional variation in worker wages. However, none of the explanations can fully account for the employer size-wage premium. In the end there remains a large, significant, and unexplained premium paid to workers of large employers.

This article studies interfirm racial segregation in two newly developed firm‐level databases. We find that the interfirm distribution of black and white workers is close to what would be implied by random assignment. We also find that black workers are clustered in employers where managers, owners, and customers are also black. These findings may be reconciled by the facts that (a) there are not enough black employers to generate much segregation and that (b) other forces may systematically integrate black and white workers. Finally, we find that the black/white wage gap is primarily a within‐firm phenomenon.

Examining the Employer-Size Wage Premium in the Manufacturing, Retail Trade, and Service Industries Using Employer-Employee Matched Data by Kimberly Bayard and Kenneth R. Troske. Published in volume 89, issue 2, pages 99-103 of American Economic Review, May 1999

We use administrative data from Missouri to examine the sensitivity of earnings impact estimates for a job training program based on alternative nonexperimental methods. We consider regression adjustment, Mahalanobis distance matching, and various methods using propensity-score matching, examining both cross-sectional estimates and difference-in-difference estimates. Specification tests suggest that the difference-in-difference estimator may provide a better measure of program impact. We find that propensity-score matching is most effective, but the detailed implementation is not of critical importance. Our analyses demonstrate that existing data can be used to obtain useful estimates of program impact.

The Appalachian region has experienced persistently higher poverty and lower earnings than the rest of the United States. We examine whether skill differentials or differences in the returns to those skills lie at the root of the Appalachian wage gap. Using census data, we decompose the Appalachian wage gap using both mean and full distribution methods. Our findings suggest that significant upgrading of skills within the region has prevented the gap from widening over the last 20 years. Additionally we find that urban areas within Appalachia have not experienced the rise in returns to skills as in non-Appalachian urban areas.

We use a unique new data set that combines data on individual workers and their employers to estimate marginal productivity differentials among different types of workers. We then compare these to estimated relative wages, leading to new evidence on productivity‐based and nonproductivity‐based explanations of the determination of wages. Among our findings are (1) the higher pay of prime‐aged workers (aged 35–54) and older workers (aged 55+) is reflected in higher point estimates of their relative marginal products, and (2) for the most part, the lower relative earnings of women are not reflected in lower relative marginal products.

Using establishment‐level data, we shed light on the sources of the changes in the structure of production, wages, and employment that have occurred over recent decades. Our findings are: (1) the between‐plant component of wage dispersion is an important and growing part of total wage dispersion; (2) much of the between‐plant increase in wage dispersion is within industries; (3) the between‐plant measures of wage and productivity dispersion have increased substantially over recent decades; and (4) a significant fraction of the rising dispersion in wages and productivity is accounted for by changes in the distribution of computer investment across plants.

We explore the effects of temporary help employment on welfare recipients' subsequent employment and welfare dynamics. We find that any employment—in temporary help services or other sectors—yields substantial benefits compared to no employment. Although welfare recipients who go to work for temporary help service firms have lower initial wages than those with jobs in other sectors, they experience faster subsequent wage growth. Two years later, they are no less likely to be employed, their wages are close to those of other workers, and they are only slightly more likely to remain on welfare.

Studies examining welfare‐to‐work program effectiveness present mixed and sometimes discrepant findings, partly due to research design, data, and methodological limitations. Using administrative data on Missouri and North Carolina welfare recipients, we substantially improve on past estimation approaches to identify the distinct effects of each state’s welfare‐to‐work subprograms—assessment, job search assistance and job readiness training, and more intensive programs designed to augment human capital. More intensive training is associated with greater initial earnings losses but also greater long‐run earnings gains. The negative program impacts we observe in quarters immediately following participation turn positive by the second year after participation.