Citation

Liu Y, Zhao X, Lu D, Li X. Transp. Res. A Policy Pract. 2023; 176: e103801.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.tra.2023.103801

PMID

unavailable

Abstract

Based on monthly data on electric vehicle (EV) sales in China from 2012 to 2020, a vector autoregressive model (VAR) and a vector error correction model (VECM) are used to empirically examine the long-term and short-term impacts of EV policy incentives in China. EV policy incentives, including monetary incentives, privilege incentives, demonstration incentives and charging incentives, are discussed from the perspective of policy combinations, and a variance decomposition analysis is used to solve the problem that the impact of policy incentives could not be compared cross-sectionally due to inconsistent units of measurement. The results reveal that in the short term, the policy combinations of monetary incentives and administrative controls, including purchase subsidy, purchase tax exemption and vehicle purchase restriction, are more effective in increasing the demand for EVs. However, in the long term, the policy combinations of privilege incentives, charging incentives and demonstration incentives are more effective in accelerating the adoption of EVs, such as no driving or purchase restrictions, improved charging networks, public procurement and gasoline price have a more significant long-term impact on EV sales. Monetary incentives and administrative controls should not be completely removed.

Language: en

Keywords

China; Electric vehicle; EV incentives; Long-term and short-term; Policy combinations