Measuring Long-Run Gasoline Price Elasticities in Urban Travel Demand

I develop a structural model of urban travel to estimate long run gasoline price elasticities. I model the demand for transportation services using a dynamic discrete-choice model with switching costs and estimate it using a panel dataset with public market-level data on automobile and public transit use in Chicago. Long-run own- (automobile) and cross- (transit) price elasticities are substantially more elastic than short-run elasticities. Elasticity estimates from static and myopic models are downward biased. I use the estimated model to evaluate the response to several counterfactual policies. A gasoline tax is less regressive after accounting for the long-run substitution behavior.