Abstract
This paper is concerned with the interactions between a policymaker and a population of vehicle owners through a bilevel model. The policymaker aims to minimize a cost function to come up with the optimal incentive for encouraging the largest possible percentage of fossil fuel vehicle owners to purchase an electric vehicle. The fossil fuel vehicle owners have to decide whether to purchase an electric vehicle or not. Both the policymaker and the fossil fuel vehicle owners care about the PM10 concentration. In particular, the policymaker can decide to impose a traffic ban if the PM10 concentration exceeds the safety threshold for many consecutive days. Traffic bans generate a cost to the owners of a fossil fuel vehicle. We reduce the initial bilevel problem to a single-level problem and analytically solve it. We further provide a model calibration on real data and a detailed comparative statics.
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