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.
CITATION STYLE
Donna, J. D. (2021). Measuring long-run gasoline price elasticities in urban travel demand. RAND Journal of Economics, 52(4), 945–994. https://doi.org/10.1111/1756-2171.12397
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