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Cornell University DEEP-GREEN-RADAR Research Associate Dr. Jon Cook's dynamic structural model of wind turbine shutdowns and upgrades was presented at the Stanford Institute for Theoretical Economics (SITE) session on Empirical Implementation of Theoretical Models of Strategic Interaction and Dynamic Behavior and at the National Bureau of Economic Research (NBER) Summer Institute Environmental and Energy Economics workshop.

For his research, Dr. Cook analyzed the factors that affect the decisions to invest in, shut down, and/or upgrade wind turbines in Denmark. The research topic is an important one, as the development of renewable sources of energy is becomingly increasingly urgent in the face of the impending scarcity of fossil fuels and the environmental degradation that arises from fossil fuel production and use. Dr. Cook's research has the potential to make a significant impact on policy. The outputs of his research will enable him to propose and design policies that will promote wind energy development, production, and use.

Shutting down and/or upgrading existing productive assets are important economic decisions for the owners of those assets and are also the fundamental decisions that underlie the development of new, growing industries. These actions are particularly relevant for assets that produce or consume a large amount of electricity due to their large upfront costs, long expected lifetimes and environmental impacts.

Dr. Cook develops a dynamic structural econometric model of wind turbine owners' decisions about whether and when to add new turbines to a pre-existing stock, scrap an existing turbine, or replace old turbines with newer versions (i.e., upgrade). He applies his model to owner-level panel data for Denmark over the period 1980-2011 to estimate the underlying profit structure for wind producers and evaluate the impact of technology and government policy on wind industry development. His structural econometric model explicitly takes into account the dynamics and interdependence of shutdown and upgrade decisions and generates parameter estimates with direct economic interpretations.

Results from the model indicate that the growth and development of the Danish wind industry was primarily driven by government policies as opposed to technological improvements. The parameter estimates are used to simulate counterfactual policy scenarios in order to quantify the effectiveness of the Danish feed-in-tariff and replacement certificate programs. Results show that both of these policies significantly impacted the timing of shutdown and upgrade decisions made by turbine owners and accelerated the development of the wind industry in Denmark. Dr. Cook also finds that when compared with the feed-in-tariff; a declining feed-in-tariff; and the replacement certificate program and the feed-in-tariff combined, the replacement certificate program was the most cost-effective policy both for increasing payoffs to turbine owners and also for decreasing carbon emissions.

Dr. Cook's research integrates direct observation with economic theory, dynamic optimization, and econometric modeling, and is grounded in a deep knowledge of the wind energy industry in Denmark. Dr. Cook collected and assembled an impressively comprehensive turbine-level data set to use for his analysis. As part of his research, he went to Denmark for a summer to gather detailed information about the wind industry there.

The dynamic structural econometric model Dr. Cook develops can be applied to any set of interdependent shutdown and upgrade decisions. His application to the Danish wind industry has important implications for the design of renewable energy policies worldwide.

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