Economists have long been interested in the effect of technological change on the labor market. Our recent research has focused on how technological change influences the retirement decisions of older workers,(1) the skill acquisition of young workers,(2) and the interindustry wage structure.(3) Since data on the rate of technological change faced by workers in their jobs is unavailable in any non-firm-level dataset, we have used industry-level measures of technological change instead. In our early work on retirement, we studied the manufacturing and nonmanufacturing sectors and used the Jorgenson productivity growth series as a proxy for the industry rate of technological change. In our work on skill acquisition and the interindustry wage structure, we restricted the analysis to the manufacturing sector because of the difficulties in accurately measuring technological change outside the manufacturing sector. We used a number of additional proxies for technological change: the NBER productivity series; the Census of Manufacturers series on investment in computers; the industry's R and D-to-sales ratio; the industry's use of patents; and the number of scientists and engineers employed within the industry. This approach has enabled us to examine the robustness of alternative measures of technological change, thereby increasing our confidence in the results.
Technological Change and Retirement Decisions
Technological change can affect retirement decisions in two main ways: directly, through its effect on the amount of on-the-job training, and indirectly, through its effect on the depreciation rate of the stock of human capital. Economic theory does not clearly predict the effect of technological change on the optimal level of on-the-job training, though. This relationship depends on the effects of technological change on the marginal return to training, and on the complementarity and substitutability between schooling and training. If technological change and on-the-job training are positively correlated, then human capital theory predicts that workers in industries with higher rates of technological change will retire later.(4) However, in industries that have higher rates of technological change, human capital will depreciate at a faster rate. These higher rates of depreciation will lead to a lower optimal level of investment, inducing earlier retirement. Hence, from a theoretical perspective, the relationship between the long-run variation in the rate of technological change across industries and the age of retirement is ambiguous. If there is a net positive correlation between on-the-job training and technological change, though, the industries that are characterized by higher rates of technological change will have later retirement ages.
Unexpected changes in the industry rate of technological change can also influence retirement decisions. For example, an unexpected increase in the rate of technological change will produce an increase in the depreciation rate of the human capital stock, leading to a revised rate of investment in human capital. If older workers are unlikely to revise their planned investments in human capital, then the higher depreciation rate will induce earlier retirement.
In our empirical work using the 1966-83 National Longitudinal Surveys of Older Men, we find that it is important to distinguish between long-run variations and unexpected changes in industry rates of technological change. Our two main findings are that workers in industries with higher average rates of technological change retire later than workers in industries with lower rates of technological change, and that an unexpected increase in the rate of technological change induces earlier retirement, especially for workers 65 and older.
Technological Change and the Skill Acquisition of Young Workers
Observed investments in training are the outcome of a supply and demand interaction between employers and workers. …