Association for Public Policy Analysis & Management

There is a long standing debate in economics about whether marginal pricing is effective at limiting energy consumption. This debate become even more complex in the context of the poorly understood market of plug-in electric vehicle (PEV) energy consumption. In this context, state authorities need to decide whether to implement time-based or energy-based pricing policies for charging stations. The time-based policies charge for the length time that electric vehicles are plugged into a charging station. This type of policy allows station owners to charge for parking but not for energy consumed kWh based state policies charge by total consumption of energy measured in kilowatt-hours.

With the availability of high velocity real-time data we are now able to approach this debate with new methodologies that have not been available in previous studies. The project considers the use of spatial regression discontinuity design with the time-based pricing as the treatment group and the kWh based pricing and the control group. We compare counties with similar characteristics but different state policies regarding consumers’ charging behavior. In particular, we will observe the electricity consumed in kWh and the time that the vehicles are plugged into charging stations in portions of Bergen County, NJ and Manhattan, the Bronx and Westchester County, NY. In this study, random assignment is based on geographical location, essentially which side of the Hudson River you are on.

Through a spatial regression discontinuity design our team aims to answer two related questions: the effect of pricing schemes in consumer’s charging behavior which leads to the answer of what kind of state policy (time-based and kWh-based) is the most effective for PEV station owners to recover investment costs.

This study is relevant to the study of consumer behavior. The project would add to the literature that studies consumers’ response to price incentives, particularly in the case of electric vehicles charging stations. Second, the results can inform policy making by determining which price scheme is more convenient when the objective is to minimize the necessary investment in charging stations. Overuse of charging stations would lead to inefficiencies in the market because more charging stations would be needed to charge the same number of electric vehicles.