Many view the period after the Second Industrial Revolution as a paradigm of a transition to a new economy following a technological revolution, including the Information Technology Revolution. We build a quantitative model of diffusion and growth during transitions to evaluate that view. With a learning process quantified by data on the life cycle of US manufacturing plants, the model accounts for the key features of the transition after the Second Industrial Revolution. But we find that features like those will occur in other transitions only if a large amount of knowledge about old technologies exists before the transition begins.
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