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In the first essay, I examined how technological change affects experience-earning profiles through a simultaneous estimation of industry choice and wage determination with correction for self-selection on industry. Using data from Current Population Survey, I found positive truncation effects and nonhierarchical sorting into industries. Experience-earning profiles turned out to be higher and flatter in low-tech industries than in high-tech industries. Earnings peaks occurred at similar experience levels for the two types of industries. Differences in the curvature of experience-earning profiles between high-tech and low-tech industries were substantially reduced after correcting for selection bias.

In the second essay, I made a distinction between human capital obtained from schooling and human capital obtained from training based on their different responses to technological change, and assessed how technological change affects these two types of human capital. Relying on National Longitudinal Survey of Youth 79 data, I estimated the parameters of a dynamic structural human capital investment model in an environment of rapid technological change using nonlinear least squares method. I found that the productivity of schooling human capital increased under rapid technological change in spite of the obsolescence while the net effect of technological change on training human capital was fast obsolescence. These findings suggest that individuals with more schooling enjoy an advantage in dealing with technological change over those with less schooling.

In the third essay, I analyzed empirically how technological change affects life-cycle human capital investment, in particular, schooling and training choices. Using the parameter estimates for the human capital investment model constructed in the second essay, I solved the value function and optimal decision rules for the dynamic programming problem numerically. I further simulated the life-cycle profiles of schooling and training under different rates of technological change for two ability groups respectively. I found that technological change tended to result in more schooling and training for the high-ability group while exerting little impact on human capital investment for the low-ability group.