A unique dataset collected from the personnel records of a large company is used to study the relationship between on-the-job training and worker productivity. The analysis shows how information contained in a company database is useful for eliminating heterogeneity bias in the estimation of training's impact on wages and job performance. Even when selection bias in assignment to training programs is eliminated, training is found to have a positive and significant effect on both wage growth and the change in job performance scores, thereby confirming the robustness of the relationship between training and productivity.

"Analyzing the location choices of the post-1964 U.S. immigrants results in three main findings: (1) these immigrants are more geographically concentrated than natives of the same age and ethnicity and reside in cities with large ethnic populations; (2) education plays a key role in location choice, reducing geographic concentration and the likelihood of being in cities with a high concentration of fellow countrymen and increasing the probability of changing locations after arrival in the United States; (3) internal migration within the United States occurs more frequently among immigrants than natives and facilitates the process of assimilation for the more educated individuals."

Since technological change influences the rate at which human capital obsolesces and also increases the uncertainty associated with human capital investments, training may increase or decrease at higher rates of technological change. Using the National Longitudinal Survey of Youth, we find that production workers in manufacturing industries with higher rates of technological change are more likely to receive formal company training. At higher rates of technological change, the training gap between the more and less educated narrows, low‐skilled nonproduction workers receive significantly more training than higher‐skilled nonproduction workers, and the proportion of individuals receiving training increases.

According to human capital theory, technological change will influence the retirement decisions of older workers in two ways. First, workers in industries with high rates of technological change will retire later if there is a net positive correlation between technological change and on-the-job training. Second, an unexpected change in the rate of technological change will induce older workers to retire sooner because the required amount of retraining will be an unattractive investment. We matched industry data on productivity growth and occupational data on required training with data from the National Longitudinal Surveys of Older Men to test these hypotheses. Our results support both hypotheses.