The Dynamic Efficiency of Policy Uncertainty: Evidence from the Wind Industry

Luming Chen (University of Wisconsin, Madison)

February 8, 2024, 11:00–12:30

Auditorium 3

Room Auditorium 3

Job Market Seminar


This paper investigates the dynamic efficiency of policy uncertainty in the US wind energy industry. Policy expiration embedded in the Production Tax Credit induced uncertainty among wind farm investors and expedited investment. I compile a comprehensive data set of the investment, production, and long-term contracts on the US wind energy market. I find significant bunching in the number of new wind farms at the expiration dates of the short policy windows and a large mismatch among wind farm investment timing, continuously improving upstream turbine technology, and evolving demand for wind energy. I then develop an empirical model featuring the bilateral bargaining of long-term contracts, endogenous buyer matching, and dynamic wind farm investment under policy uncertainty. Model estimates reveal that a lapse in policy extension reduced the perceived likelihood of policy renewal to 30%, and counterfactual simulations demonstrate that removing policy uncertainty postpones the entry of 53% of the affected cohort by 3.5 years. Removing policy uncertainty increases the net social surplus by 5.9 billion dollars and could save fiscal expenditure without sacrificing social welfare.