Abstract ▼
Electric mobility is seen as a promising technology on the way to a carbon-neutral economy. Globally, policy makers introduce incentive schemes to enhance the diffusion of electric engine technologies. This creates a need for tools able to inform the policy making process by providing predictions about the market impacts of the proposed policies. This thesis aims at testing the predictive accuracy of structural market simulation methods to predict the impacts of a subsidy for electric vehicles, using the introduction of federal purchase incentives in Germany in 2016 as a case study. For the simulation, I implement a nested logit demand system, where demand is estimated by IV using BLP-style instruments. I use the demand estimates to compute a multi-product Bertrand (Nash) equilibrium of sales volumes and prices for the German car market, and compare the equilibrium outcomes under a subsidy with a non-subsidy scenario. In addition, I conduct an econometric ex-post evaluation of the German EV subsidy reform, and I find that the structural model overpredicts the subsidy impact on electric vehicle sales. Potential reasons include changes in consumer preferences coinciding with the introduction of the subsidy, shifts in firm conduct, consumer expectations about future subsidies, firm reactions through channels other than price adjustments, or an understatement of the subsidy impacts in the ex-post evaluation.