Spillovers and the Direction of Innovation:
An Application to the Clean Energy Transition

Transitioning to clean energy is thought to require massive policy intervention to overcome the incumbency of fossil fuels. This paper shows that cross-technology knowledge spillovers, by allowing clean technologies to achieve catchup growth, can prevent technological lock-in and the need for a “big push”. I develop an endogenous growth model with clean and dirty technologies linked by a spillover network and characterize the size and speed of technological transition following a policy reform. Spillovers, together with market size effects, determine whether the economy favors technological leaders or laggards, implying a novel result: policy can generate rapid short-run change or substantial long-run redirection, but not both. I then examine the role of spillovers in optimal innovation policy, deriving subsidies under arbitrary carbon prices. Using patent data to estimate the spillover network, I apply my model to US transport and electricity generation, finding that a big push is neither necessary nor desirable.

Awards:

Graduate Student Paper Award (Finalist), Bank of Canada, 2023

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