|Authors:||Paal Brevik Wangsness|
The road transport market has many market imperfections such as local and global pollution, accidents, noise and road wear. Electric vehicles (EVs) avoid some of these by not having any tailpipe CO2 emissions, but they still contribute to external costs such as congestion. Our research questions are: What characterizes the set of secondbest road prices for internalizing external costs from driving EVs and ICEVs when you also have distortionary labor taxes and binding government budget constraints? How are these prices affected by distortions elsewhere in the economy? How does this second-best pricing fit with government set goals of reducing CO2 emissions? This paper further develops an analytical framework for assessing first- and secondbest road prices on vehicle kilometers, extending it to include EVs and externalities that vary geographically and by time of day. Expressions for the optimal road prices are derived analytically, and then solved numerically. We find that optimal road prices largely vary with external cost, giving high prices for driving in cities during peak hours, and relatively low prices for driving in rural areas. We also see that the road prices’ interactions with the rest of the fiscal system have implications for determining the optimal set of road prices. However, the optimal set of road prices leads to little or no reductions in carbon emissions with the currently recommended social cost of carbon estimates. This implies that any required reduction in CO2emissions will require a shadow price that exceeds the current social cost estimate.