Have China’s Regional Carbon Emissions Trading Schemes Promoted Industrial Resource Allocation Efficiency? The Evidence from Heavily Polluted Industries at the Provincial Level

Chunhua Lu and Hong Li ()
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Chunhua Lu: School of Economics, Peking University, Beijing 100871, China
Hong Li: School of Economics, Peking University, Beijing 100871, China

Sustainability, 2023, vol. 15, issue 3, 1-20

Abstract: Based on the data of A-share listed companies in China, this paper examines how China’s regional carbon emissions trading scheme (ETS) affects the resource allocation efficiency of China’s provincial heavily polluted industries through the DID method. The empirical results show that China’s regional carbon ETSs have reduced the TFP dispersion of enterprises in the industry, thus improving the industries’ resource allocation efficiency. The heterogeneity analysis shows that China’s regional carbon ETSs have more significantly promoted the resource allocation efficiency in industries with high competition and high external financing dependence, while the policy effects in industries with low competition and low external financing dependence are less significant. Further mechanism analysis shows that, on the one hand, China’s regional carbon ETSs have promoted the flow of capital resources from low-TFP enterprises to high-TFP enterprises. On the other hand, China’s regional carbon ETSs have promoted low-TFP enterprises to improve TFP to a higher degree than high-TFP enterprises, which reduces the TFP dispersion among different enterprises in the industry. In addition, China’s regional carbon ETSs have promoted the market share of high-TFP enterprises and restricted low-TFP enterprises entering the market, which raises the TFP threshold for new enterprises entering the market.

Keywords: emissions trading scheme; enterprise production efficiency; productivity dispersion; resource allocation; heavily polluted industries (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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