We augment standard log earnings equations for workers in US manufacturing with variables reflecting measured and unmeasured attributes of their employer. Using panel employee-establishment data, we find that establishment-level employment, education of coworkers, capital equipment per worker, and firm-level R&D intensity affects earnings substantially. Unobserved characteristics of employers captured by employer fixed effects also contribute to the variance of log earnings, although less than unobserved characteristics of individuals captured by individual fixed effects. The observed and unobserved measures of employers mediate the effects of individual characteristics on earnings and increase earnings inequality through sorting of workers among establishments.

Employee involvement (EI) programs are the leading-edge form of personnel and labor relations in the United States. While many managers believe that these programs raise productivity and profits, the statistical evidence that EI improves the performance of firms is equivocal. The coefficients on measures of EI in production functions are usually positive but often insignificant or small (Commission on the Future of Worker–Management Relations, 1994 Ch. 2; Peter Cappelli and David Neumark, 1999) or contingent on other factors (Sandra E. Black and Lisa M. Lynch, 1997; Casey Ichniowski et al., 1997). A detailed case study of EI has further confirmed these small effects that were found in large data sets (Kleiner et al., 1999). If EI programs do not greatly affect productivity, why does business think so highly of them? In this study, we argue that the main beneficiaries of EI are workers and managers. We estimate the effects of EI on productivity using panel data on firms and the effects of EI on workers using a survey of employees and find that EI barely affects firm productivity but substantially improves worker well-being. We offer two explanations for this result.