Modeling optimal incentives for the electric vehicle market

Governments face increasing pressure to meet legally binding net-zero targets, requiring a rapid transition from internal combustion engine (ICE) vehicles to electric vehicles (EVs). Designing effective incentive schemes is challenging because vehicle fleets adjust slowly, policy interventions are fiscally costly, and electrification erodes fuel-tax revenues. This paper develops a dynamic policy evaluation framework that combines cross-country evidence on EV adoption with long-run fleet dynamics under uncertainty. Using both the United Kingdom and France as case studies, we simulate optimal time paths of EV purchase incentives under alternative policy objectives, including terminal fleet targets, sales-based penalties, and fiscal revenue considerations. The results reveal three core findings. First, stock-based (terminal) penalties may delay intervention but strongly stabilize long-run fleet outcomes, while sales-based penalties induce earlier but less targeted action. Second, dependence on fuel-tax revenues creates a fiscal lock-in mechanism that weakens optimal electrification incentives. Third, the effectiveness of subsidy programs depends critically on consumer responsiveness to price incentives. Overall, the analysis shows that EV transition policy is best evaluated jointly with fiscal reform and long-run fleet dynamics. Well-timed and fiscally coherent intervention can substantially reduce emissions while limiting long-term budgetary risks.