This study applied a synthetic control method (SCM) to investigate the impacts of state electric vehicle purchase incentives implemented in the United States between 2011 and 2018. The goal was to develop a model to replicate the impacts of PEV (plug-in electric vehicle) incentives on vehicle sales given the socio-economic characteristics of the treatment states. The goodness-of-fit between trajectories reproduced by SCM and the corresponding treatment region provides a clear means of visualizing the effectiveness of the model and results. For example, the results show that Georgia income tax credits appear to have induced 17,000 BEV (battery electric vehicle) sales between January 2011 and July 2015. The SCM analysis was also applied to other states, showing that the SCM methodology can represent PEV sales in many states in the United States. Accordingly, the modeling results suggest that incentives implemented in some U.S. states were effective in promoting PEV sales. The study also concluded that the SCM with a weighting factor between 0 and 1 (i.e., extrapolation avoided) may not be the approach of a choice for the states whose demographic/economic attributes significantly deviate from the control regions, or the states that implement “unique” programs, because there are insufficient system data for counterfactual analysis.

本研究采用综合控制方法 (SCM) 调查 2011 年至 2018 年间美国实施的国家电动汽车购买激励措施的影响。目的是开发一个模型来复制 PEV（插电式电动汽车）的影响鉴于处理国家的社会经济特征，对车辆销售的激励。SCM 重现的轨迹与相应治疗区域之间的拟合优度提供了一种清晰的方法来可视化模型和结果的有效性。例如，结果显示，佐治亚州的所得税抵免似乎在 2011 年 1 月至 2015 年 7 月期间促成了 17,000 辆 BEV（电池电动汽车）的销售。SCM 分析也适用于其他州，表明 SCM 方法可以代表 PEV 销售在美国的许多州。因此，建模结果表明，美国一些州实施的激励措施在促进 PEV 销售方面是有效的。该研究还得出结论，对于人口/经济属性显着偏离控制区域的州或实施“ unique”程序，因为没有足够的系统数据进行反事实分析。