Wednesday, November 15, 2023
8:30 AM - 10:00 AM
EV Adoption: "Good Enough" Modeling in a Data-Constricted World
Session ID
A7 - Lightning: Transportation

This research delves into the intersection of behavioral economics and energy policy, focusing on electric vehicle (EV) policy and the challenge of establishing sub-territory forecasts and projections of EV purchasing. The presentation is tailored for policymakers, researchers, and stakeholders grappling with data-lacking environments while developing policies. The lack of publicly available sub-state light-duty vehicle (LDV) registration data creates an obstacle for policymakers and program designers crafting EV programs that incentivize EV adoption and plan for charging infrastructure. To surmount this hurdle, the presentation suggests leveraging known LDV buying behavior data to gain insights into the EV market at a sub-state and sub-population level. By using this method, the author can make critical observations about likely EV buying behavior without relying on granular sales and registration data. The presentation highlights the importance of recognizing that all models are inherently flawed, but they remain useful tools for policy planning purposes. Instead of striving for perfection, the presentation advocates for developing "good enough" models that facilitate effective policy planning. The proposed model in this presentation serves as an example of this approach, using limited data and resources to estimate the potential for EV adoption resulting from a newly proposed residential building code.

Supporting Document 1