Abstract
Subsidy policy to electric vehicles in China was initially launched in 2001. This study uses the perspective of the characteristics of subsidy policy and applies generalized propensity score matching (GPS) to estimate the impact of different subsidy policy intensities on the change in consumer demand for EVs and find the interval to optimize. The study shows that the optimization interval of the policy is in the 40%–70% treatment level, which maximizes the effect of the subsidy on China’s EVs. For a treatment effect lower than 40%, it is difficult to effectively create an incentive to enter the EVs market in China because consumers think that the product is difficult to satisfy the demand of too low technology; by contrast, for the treatment level higher than 70%, the cost of the high endurance mileage power battery increases exponentially, and the complementary effect of subsidies is insufficient. Consequently, we propose three suggestions: The government should 1) use big data technology to supervise subsidies and design a real-time reporting mechanism and punishment mechanism for subsidy-misuse; 2) adopt the incentive regulation to promote the battery range of new energy vehicles (e.g., optimizing the subsidy ladder, innovating the form of subsidies) and gradually eliminate low-technology product; and 3) reasonably design a targeted regulatory mechanism that increases the cost of fraud and breach of contract to encourage firms to truthfully report technical indicators.
Highlights
Electric vehicles (EVs) are the main types of new energy vehicles in China and are the target of financial subsidies implemented by governments
The corresponding research conclusions are as follows: the current new energy subsidy policy has three levels of effects, the first level focuses on the range of 179 km, which is the worst, and is mainly reflected in the threshold effect; the second level focuses on the range of 179 km–334 km, which is the most likely to cause consumer demand, and its main contribution value is more than 65%, which should be regarded as the key area of optimization and inclination; the final level mainly focuses on more than 334 km, the policy effect of this level is affected by factors such as price and consumer group characteristics, and its contribution degree is approximately 30%
According to these research conclusions, we propose the following two suggestions: First, the government must understand the adjustment of subsidy policy, optimize and establish the structure of subsidy policy, and use the role of subsidy policy on the demand side
Summary
Electric vehicles (EVs) are the main types of new energy vehicles in China and are the target of financial subsidies implemented by governments. China’s EVs, especially domestic EVs, are among the world’s best in terms of the level of scale development and the speed of technological progress. In 2018, the International Energy Agency (IEA) published the paper ‟IEA Global Electric Vehicle Outlook, 2018.”. China’s EV ownership in 2017 was approximately 40% of the world’s, which in that year was approximately 3.1 million. These achievements are inseparable from the Chinese government’s sustained financial policy support. The subsidy policy of EVs has led to price distortions and serious deception; the
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
