Industry, Environment, or Both? Analyzing State-Level Electric Vehicle Policy Mixes in the U.S.

• In Event: Adoption of Electric Vehicles and Charging Infrastructure: Policy Design and Effectiveness

Abstract

In about a decade, the number of Electric Vehicles (EVs) registered in the US has increased from 0.28 million to 3.5 million (TransAtlas, 2025). This growth is at least partly enabled by the wide range of policies supporting EV production and adoption. In addition to national policies supporting the EV sector, states across the US have adopted a range of actions from encouraging EV adoption by consumers to improve environmental quality to battery manufacturing to support the automotive industry.

Studies have examined the role of industrial policy, particularly in the context of national policies affecting the trajectory and adoption of EV actions (Collantes & Sperling, 2008). For example, comparative analyses of national trajectories on decarbonization policies reveal the importance of policy choices and the pre-evolution of policy actions in Germany and the US (Meckling and Nahm , 2017, 2022).   Given the federal context of policy making in the US, it is pertinent to examine this question at the sub-national levels, especially in the context of potential national-level rollbacks in policies. In addition, sub-national policy design has implications for the instruments used and the policy recipients affected by policy adoption, and ultimately affect policy outcomes.  

This study examines the impact of the intended goals of state policies and the framing of these actions (environmentally focused or industrial action) on the design and ultimate success of policies.  Specifically, it aims to answer three research questions: (1) What frames have state-level policy makers deployed in advancing EVs? (2) What role do the differing political and economic contexts play in determining the choice of frames? And, (3) To what extent do different approaches to policy framing result in different policy outcomes? To that end, we combine data from the Department of Energy’s Alternative Fuels Data Center repository with state-level metrics on industry composition, employment, and states’ political make-up to analyze the three research questions. The data analysis combines human and automated text analysis, topic modelling, and uncover policy frames in state-level policy actions over the past decade. Then, we combine the policy frames with data on state EV registration and other state-level socio-economic and political characteristics to create a panel dataset to estimate the impact of different policy frames on outcomes in the EV market. 

Author

• Anmol Soni, Louisiana State University
  Presenting Author