4.7 Article

Effects of urban environmental policies on improving firm efficiency: Evidence from Chinese new energy vehicle firms

期刊

JOURNAL OF CLEANER PRODUCTION
卷 215, 期 -, 页码 600-610

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.01.099

关键词

Chinese new energy vehicles firms; Policy and financial support; Firm efficiency; Data envelopment analysis model; Random effects model

资金

  1. National Natural Science Foundation of China [71804181, 71774100, 71690241]
  2. National Center for Mathematics and Interdisciplinary Sciences, CAS
  3. Fundamental Research Funds for the Central Universities

向作者/读者索取更多资源

This paper explores the determinants of the development of the new energy vehicles (NEVs) industry in China, which is important to the government in controlling the environmental pollution associated with the urbanization process. Urban governance policies have played an important role in promoting the sustainable development of cities. In this study, we investigate the dynamic effects of such policies and of financial support on the relationship between firm size and efficiency in the NEVs industry. These policies include subsidies from state and local governments during the production and promotion of NEVs. The sample includes an unbalanced panel data set of 148 firms closely related to the automobile industry in the Zhongguancun Science Park from 2005 to 2015. A data envelopment analysis model and a random effects model are used to test the hypotheses, and the results show that both government policies and financial support are beneficial in increasing the efficiency of large NEVs firms. However, small firms cannot benefit from these policies. To promote the technological progress of the NEVs industry, it is highly important to provide further government support for the small NEVs firms that play a leading role in the development of emerging technologies. Only in this way can the government create a healthy market environment for the future of NEVs industry, and reduce the pollution in urban areas. (C) 2019 Elsevier Ltd. All rights reserved.

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