This paper estimates the wage returns to training, paying careful attention to the choice of functional form. Both the National Longitudinal Survey of Youth (NLSY) and Employer Opportunity Pilot Project (EOPP) datasets indicate that the return to an extra hour of formal training diminishes sharply with the amount of training received. A cube root specification fits the data best, but the log specification also does well. The linear and quadratic specifications substantially understate the effect of training.
If wages are not adjusted continuously, estimating the total effect of training requires that one include lagged and lead training as well as current training in the regression equation. Consequently, the NLSY is ideally suited to estimate the total return to training. We find very large returns to formal training. These returns are sharply reduced when one adjusts for heterogeneity in wage growth. Returns are reduced further when one takes into account the effect of promotions and the fact that direct costs are a substantial portion of the total cost of training. The mixed continuous-discrete nature of the training variable means that measurement error can cause estimates of the effects of short spells of training to be biased upward, but we demonstrate that the maximum upward bias in estimated returns at the geometric mean is relatively small.
After correcting for confounding factors, we are left with a return to training that is several times the returns to schooling. Heterogeneity in returns explains how returns to formal training can be so high while most workers do not get formal training. In the EOPP data, the return to training is significantly higher in more complex jobs. With unobserved heterogeneity in returns, our estimates can be regarded as the return to training for the trained, but cannot be extrapolated to the untrained.