Investigating factors affecting electric vehicles adoption: an aggregated panel data analysis over U.S. states

Abstract

Increasing the usage of electric vehicles has been proposed as a policy to decrease aggregate fuel consumption and greenhouse gas (GHG) emissions in an effort to mitigate the causes of climate change. In order to increase the attraction of electric vehicles for consumers, governments have employed a number of incentives. In this study, the relationship between shares of electric vehicle and the presence of government incentives as well as other influential socioeconomic factors were examined. The methodology of this study is based on a crosssectional/time-series (panel) analysis. The developed model is an aggregated binomial logit share model that estimates the modal split between EV and conventional vehicles for different U.S. states from 2003 to 2011. The model was estimated using different panel data methods and the results were compared. The results demonstrated that electricity prices were negatively associated with EV use while, urban roads and government incentives were positively correlated with states' electric vehicle market share. Sensitivity analysis suggested that of these factors, electricity price affects electric vehicle adoption rate the most. According to the sensitivity analysis of electric vehicle adoption rate, state of Vermont has the most sensitivity with respect to electricity price and New Jersey is the most sensitive state with respect to urban roads and incentives. Moreover, the time trend model analysis found that the electric vehicle adoption has been increasing over time, which is consistent with diffusion of new technology theory.

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