Literature DB >> 32090824

Industrial policy, energy and environment efficiency: Evidence from Chinese firm-level data.

Yijun Zhang1, Xiaoping Li2, Feitao Jiang3, Yi Song4, Ming Xu5.   

Abstract

Based on a unique micro-level dataset of 30,689 mining enterprises from 2008 to 2011, this paper uses the non-radial directional distance function (NDDF) to calculate the unified efficiency index (UEI) and energy-environmental performance index (EEI) for China's mining enterprises. The double bootstrap method is then used to test how tax incentive policies affect the UEI and EEI of China's mining enterprises. The results show that: (1) the UEI and EEI of Chinese mining enterprises first decreased and then increased over the sample period; overall, Chinese mining enterprises had low energy and environmental efficiency, especially the coal mining enterprises, private mining enterprises and mining enterprises in the central and western regions. (2) Tax incentives positively affect the energy and environmental efficiency of mining enterprises, especially the efficiency of coal mining enterprises, non-state-owned mining enterprises and mining enterprises in the central and western regions. Our results remain robust after using the propensity score matching estimator (PSM). (3) There is a positive feedback between tax incentives and energy and environmental efficiency, more efficient mining enterprises receive more government incentives. Further analysis shows that although tax incentives do not reduce the total energy consumption of enterprises, reducing the energy consumption of enterprises can improve their UEI and EEI. In addition, R&D investment, profitability and resource taxes all contribute to improving the UEI and EEI of mining enterprises.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Keywords:  Energy and environmental efficiency; Mining enterprises; Non-radial directional distance function; Tax incentives

Year:  2020        PMID: 32090824     DOI: 10.1016/j.jenvman.2020.110123

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017.

Authors:  Jiandong Chen; Jialu Liu; Jie Qi; Ming Gao; Shulei Cheng; Ke Li; Chong Xu
Journal:  Sci Data       Date:  2022-03-24       Impact factor: 6.444

  1 in total

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