Abstract:

Based on the micro data of China’s electric vehicle enterprises(EVs), this paper constructs a heterogeneous stochastic frontier model (SFA)to measure the technical efficiency of EVs. On this basis, the regression discontinuity (RD)is used to objectively evaluate the technical efficiency of the declining of subsidies. The results of the study are as follows: The average technical efficiency of China’s EVs is about 66%; The declining of the subsidy policy effectively improves the technical efficiency of the industry by 2%; EVs have strategic “catering” behavior, that is to obtain local government subsidies and policy support; Too high assets and liabilities will bring instability to the technical efficiency. According to the corresponding conclusions, this paper suggests that we should re-recognize the necessity of the implementation of subsidies, optimize the implementation means to guide consumers’ behavior, and improve the financing mechanism.

Key words: Electric Vehicle, Subsidy Policy, Heterogeneity Stochastic Frontier Analysis, Regression Discontinuity

摘要：

本文利用中国新能源车企的微观数据,构建异质性随机前沿模型(SFA)并测算企业技术效率,在此基础上借助断点回归方法(RD)对新能源补贴退坡的技术效率效应进行客观评价。研究结果发现,新能源车企的平均技术效率约为66%,补贴退坡政策有效提升行业技术效率2个百分点;新能源车企存在策略性“迎合”行为(即为获得地方政府的补贴和政策支持),过高的资产负债率给技术效率带来不稳定性。因此,应重新认识补贴退坡政策实施的必要性,优化引导消费者行为的实施手段,健全新能源车企的融资机制。

关键词: 新能源汽车, 补贴退坡政策, 异质性随机前沿模型(SFA), 断点回归模型(RD)