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An evaluation of government incentives for new energy vehicles in China focusing on vehicle purchasing restrictions

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  • Ma, Shao-Chao
  • Fan, Ying
  • Feng, Lianyong

Abstract

In order to reduce carbon emissions and urban smog, the Chinese government has instituted a number of policies to promote the diffusion of new energy vehicles (NEVs), achieving remarkable results. This paper aims to quantify the effectiveness of various policies. After reviewing and quantifying the policies directly related to the sales and driving of NEVs in the past five years, we established a multivariate co-integration model and an error correction model to analyse the long- and short-term effects of these policies. The results demonstrate positive co-integration for the relationship between the NEV market share and the NEV purchase subsidy, tax exemption, the policy of restricting internal combustion engine vehicle (ICEV) purchase, and the abolishment of traffic restrictions for NEVs. China's unique policy of restricting ICEVs has in fact promoted NEV sales by adjusting the supply and demand to influence the consumers' choices. Finally, we found technology to still be a bottleneck factor in the NEV industry, and technological progress's effect on NEV diffusion is greater than the economic subsidy policy. Therefore, this study suggests that the funds being made available from the gradual reduction of the purchase subsidy should be transferred to research and development.

Suggested Citation

  • Ma, Shao-Chao & Fan, Ying & Feng, Lianyong, 2017. "An evaluation of government incentives for new energy vehicles in China focusing on vehicle purchasing restrictions," Energy Policy, Elsevier, vol. 110(C), pages 609-618.
    • Handle: RePEc:eee:enepol:v:110:y:2017:i:c:p:609-618
    DOI: 10.1016/j.enpol.2017.07.057
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    1. Gnann, Till & Plötz, Patrick & Kühn, André & Wietschel, Martin, 2015. "Modelling market diffusion of electric vehicles with real world driving data – German market and policy options," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 95-112.
    2. Kang, Min Jung & Park, Heejun, 2011. "Impact of experience on government policy toward acceptance of hydrogen fuel cell vehicles in Korea," Energy Policy, Elsevier, vol. 39(6), pages 3465-3475, June.
    3. Hunt Allcott, 2011. "Consumers' Perceptions and Misperceptions of Energy Costs," American Economic Review, American Economic Association, vol. 101(3), pages 98-104, May.
    4. Green, Erin H. & Skerlos, Steven J. & Winebrake, James J., 2014. "Increasing electric vehicle policy efficiency and effectiveness by reducing mainstream market bias," Energy Policy, Elsevier, vol. 65(C), pages 562-566.
    5. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    6. Chen, Pu & Hsiao, Chih-Ying, 2010. "Looking behind Granger causality," MPRA Paper 24859, University Library of Munich, Germany.
    7. Taefi, Tessa T. & Kreutzfeldt, Jochen & Held, Tobias & Fink, Andreas, 2016. "Supporting the adoption of electric vehicles in urban road freight transport – A multi-criteria analysis of policy measures in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 61-79.
    8. Skippon, Stephen M. & Kinnear, Neale & Lloyd, Louise & Stannard, Jenny, 2016. "How experience of use influences mass-market drivers’ willingness to consider a battery electric vehicle: A randomised controlled trial," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 26-42.
    9. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    10. Massiani, Jérôme, 2015. "Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: Methods and results," Transport Policy, Elsevier, vol. 38(C), pages 19-26.
    11. Rolf Larsson & Johan Lyhagen & Mickael Lothgren, 2001. "Likelihood-based cointegration tests in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-41.
    12. Han, Sun Sheng, 2010. "Managing motorization in sustainable transport planning: the Singapore experience," Journal of Transport Geography, Elsevier, vol. 18(2), pages 314-321.
    13. Zhang, Xian & Wang, Ke & Hao, Yu & Fan, Jing-Li & Wei, Yi-Ming, 2013. "The impact of government policy on preference for NEVs: The evidence from China," Energy Policy, Elsevier, vol. 61(C), pages 382-393.
    14. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    15. Langbroek, Joram H.M. & Franklin, Joel P. & Susilo, Yusak O., 2016. "The effect of policy incentives on electric vehicle adoption," Energy Policy, Elsevier, vol. 94(C), pages 94-103.
    16. Riesz, Jenny & Sotiriadis, Claire & Ambach, Daisy & Donovan, Stuart, 2016. "Quantifying the costs of a rapid transition to electric vehicles," Applied Energy, Elsevier, vol. 180(C), pages 287-300.
    17. Li, Wenbo & Long, Ruyin & Chen, Hong, 2016. "Consumers’ evaluation of national new energy vehicle policy in China: An analysis based on a four paradigm model," Energy Policy, Elsevier, vol. 99(C), pages 33-41.
    18. Diamond, David, 2009. "The impact of government incentives for hybrid-electric vehicles: Evidence from US states," Energy Policy, Elsevier, vol. 37(3), pages 972-983, March.
    19. Plötz, Patrick & Schneider, Uta & Globisch, Joachim & Dütschke, Elisabeth, 2014. "Who will buy electric vehicles? Identifying early adopters in Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 96-109.
    20. Xu, Lei & Su, Jun, 2016. "From government to market and from producer to consumer: Transition of policy mix towards clean mobility in China," Energy Policy, Elsevier, vol. 96(C), pages 328-340.
    21. Yuan, Xueliang & Liu, Xin & Zuo, Jian, 2015. "The development of new energy vehicles for a sustainable future: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 298-305.
    22. Wu, Geng & Inderbitzin, Alessandro & Bening, Catharina, 2015. "Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments," Energy Policy, Elsevier, vol. 80(C), pages 196-214.
    23. Hao, Han & Ou, Xunmin & Du, Jiuyu & Wang, Hewu & Ouyang, Minggao, 2014. "China’s electric vehicle subsidy scheme: Rationale and impacts," Energy Policy, Elsevier, vol. 73(C), pages 722-732.
    24. Sierzchula, William & Nemet, Gregory, 2015. "Using patents and prototypes for preliminary evaluation of technology-forcing policies: Lessons from California's Zero Emission Vehicle regulations," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 213-224.
    25. Silvia, Chris & Krause, Rachel M., 2016. "Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: An agent-based model," Energy Policy, Elsevier, vol. 96(C), pages 105-118.
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