Influence Mechanism of Different Environmental Regulations on Carbon Emission Efficiency

Abstract

The rational use of environmental regulation tools has become an important means by which to improve the efficiency of carbon emissions. Different types of environmental regulations and their combinations have different impacts on carbon emission efficiency. In order to determine the environmental regulation configurations that may achieve high carbon emission efficiency or lead to low carbon emission efficiency, we constructed an analytical framework of connections between environmental regulation configurations and carbon emission efficiency. Moreover, 30 Chinese provinces from the period covering 2016 to 2019 were selected as research cases. In addition, the super slacks-based measure of efficiency (SE-SBM) model was applied to evaluate carbon emission efficiency. Finally, the fuzzy-set qualitative comparative analysis (fsQCA) method was employed to analyze the impact of different environmental regulation configurations on carbon emission efficiency. The results showed that the carbon emission efficiency of various regions of China is generally low (with most regions not having reached an effective level) and that there are large regional differences. We found that there are four environmental regulation configurations that can achieve high carbon emission efficiency and two environmental regulation configurations that lead to low carbon emission efficiency. Based on these configurations, we draw three conclusions: (1) There are three paths to achieving high carbon emission efficiency: one that values command-and-control environmental regulation but disfavors market-incentive environmental regulation, another that combines command-and-control environmental regulation with market-incentive environmental regulation, and a third that couples command-and-control environmental regulation with voluntary environmental regulation. (2) Two paths that may lead to low carbon emission efficiency were established: excessive penalties and the lack of specific measures. (3) In some conditions, environmental governance investment and fiscal expenditure could be substituted for each other; environmental protection administrative penalties and pollution charges are synchronized; environmental governance investment in the promotion of carbon emission efficiency is indispensable. Policies and suggestions on how the government can use environmental regulation tools to improve carbon emission efficiency are proposed from a general coordinative perspective in the final section of this paper.

Threshold Effect of Environmental Regulation and Green Innovation Efficiency: From the Perspective of Chinese Fiscal Decentralization and Environmental Protection Inputs

“…The DEA method is widely used in efficiency measurement, but the traditional DEA model ignores unexpected outputs and does not consider the input-output slack at the same time. The DEA-SBM unexpected output model proposed by Tone (2001) [27], which considers the inefficiency scenario from both input and output perspectives and adds slack variables to the objective function, solves the above problems and has been widely used in agriculture [28], economic development [29], and environmental resources [30,31] studies, among others. Based on this, we used a DEA-SBM model to measure the green innovation efficiency (GIE) of each province following Wang (2019) [32].…”

“…Researchers have measured fiscal decentralization mainly from three perspectives: fiscal revenue, fiscal freedom, and fiscal expenditure. We referred to Zhang et al (2022) [48] to measure fiscal decentralization from the perspective of fiscal expenditure and to eliminate the influence of demographic factors, the proportion of local fiscal expenditure to the local population, and the proportion of central fiscal expenditure to the national population.…”

Research on Carbon Emission Efficiency and Its Improvement Path of China’s Provinces Based on SBM-ML Model and fsQCA Model

“…The SFA method is limited by artificial parameter setting, so DEA is currently the mainstream tool for measuring carbon emission efficiency. Initially, scholars used the traditional DEA model to find the carbon emission efficiency [7][8][9]. Still, the traditional DEA model does not consider the influence of undesirable outputs and has problems such as the accuracy can be affected by improper output selection, which does not apply to carbon emission studies where there are nondesired outputs.…”

Research on spatial and temporal differences of carbon emissions and influencing factors in eight economic regions of China based on LMDI model

“…With China's increasing willingness to achieve a carbon peak by 2030, scholars at home and abroad have conducted a lot of research on China’s carbon emissions, focusing on the feasibility extrapolation and realization path of China's 3060 plan, carbon emission efficiency analysis 10 , carbon emission peak projection 11 , carbon emission impact factor decomposition 12 , 13 , carbon emission research and emission reduction strategies by industry and region 13 . For carbon emissions research, scholars have mainly used the DEA model, IPAT model, Kaya constant equation, LMDI decomposition method, environmental Kuznets curve, etc.…”