Measuring long‐run gasoline price elasticities in urban travel demand
构建了一个包含转换成本的动态离散选择模型，利用芝加哥汽车和公共交通使用的面板数据，估计了汽油的长期价格弹性，发现长期弹性远大于短期弹性，且静态模型会低估弹性。
Abstract 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.