Adjusting to a New Technology: Experience and Training
December 1998 How does the economy react to the arrival of a new major technology? The existing literature on General Purpose Technologies (GPTs) has studied the role that mechanisms like secondary innovations, diffusion, and learning by firms play in the adjustment process. By contrast, we focus on a new mechanisms based on the interplay between technological change and human capital accumulation. We show that technological change that requires more education and training, like computerization, necessarily produces an initial slowdown. Surprisingly, however, technological change that lowers the training requirement, like the move from the artisan shop to the factory, can produce either a bust or a boom. We identify three key properties that determine which effect will occur: (1) the productivity of inexperienced workers; (2) the speed with which experience increases productivity; and (3) the level of general skills required to operate the new technology.
In this paper we study how aggregate output responds to the arrival of a new General Purpose Technology (GPT) by looking at adjustment mechanisms that operate through labor markets. We show that under a wide set of circumstances the arrival of a new GPT that raises long-run output can trigger a recession in the short-run. Furthermore, we characterize features of the GPT that produce a cyclical adjustment path. An initial recession occurs whenever a higher education level is required to operate the new GPT. But a recession can also occur when the new GPT has lower educational requirements. A cyclical adjustment path is more likely when inexperienced workers are less productive with the new technology and the faster productivity rises with experience in the new sector.
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