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Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector

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  • Li, Shuangmei
  • Zhu, Xuehong
  • Zhang, Tao

Abstract

Based on the new structural economics view that the combination of effective governments and efficient markets is the fundamental path to high-quality development, this study investigates how heterogeneous environmental policy instruments combine with marketization to improve the total factor energy-environmental efficiency (TFEEE) in China's metal sector. Utilizing the provincial panel data from 2006 to 2019, a super-efficiency slacks-based measure data envelopment analysis (SBM-DEA) integrated with the global Malmquist-Luenberger (GML) index is employed to estimate the energy-environmental efficiency and its dynamic changes. The evaluation results imply a significant increasing trend in the energy-environmental efficiency, but the overall level is rather low with disparities between sub-sectors and different regions. Using a dynamic panel threshold model, the “strong” version of the Porter Hypothesis is validated that command-and-control environmental policy (CEP), market-incentive environmental policy (MEP), and voluntary environmental policy (VEP) have an optimum stringency range to induce TFEEE growth, while the impact modes are drastically diverse. Further study verifies that higher marketization is conducive to triggering the facilitation effect of heterogeneous environmental policy instruments on the TFEEE but with completely different threshold values of marketization, which decrease sequentially corresponding to VEP, CEP, and MEP.

Suggested Citation

  • Li, Shuangmei & Zhu, Xuehong & Zhang, Tao, 2023. "Optimum combination of heterogeneous environmental policy instruments and market for green transformation: Empirical evidence from China's metal sector," Energy Economics, Elsevier, vol. 123(C).
  • Handle: RePEc:eee:eneeco:v:123:y:2023:i:c:s0140988323002335
    DOI: 10.1016/j.eneco.2023.106735
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