碳排放权交易政策能否提高污染与碳的协同减排效率?来自中国216个城市的证据

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-10-08 DOI:10.1002/mde.4014
Tingting Bai, Yong Qi, Zihao Li, Dong Xu
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引用次数: 0

摘要

基于中国216个城市2008 - 2018年面板数据,采用超效率松弛测度模型计算污染与碳协同减排效率(SREPC)。采用差异中差异(DID)、倾向得分匹配(PSM) -DID和空间DID分析了碳排放交易(CET)政策对SREPC的影响。研究结果表明:SREPC总体上没有得到改善,呈现出东高效西低的不平衡发展特征;Meta - frontier结果表明,在实施CET政策前后,试点城市与非试点城市之间确实存在显著差异。机制试验表明,节能减排通过提高能效和优化产业结构来促进SREPC的发展。空间分析表明,CET具有空间溢出效应,降低了周边城市的SREPC。这些减少效应出现在邻近的非试点城市,并与地理距离的增加呈倒U型关系,在500-600 km范围内尤为显著。反数据包络分析表明,CET可以利用污染和碳的协同减排潜力。
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Will carbon emission trading policy improve the synergistic reduction efficiency of pollution and carbon? Evidence from 216 Chinese cities
Abstract Based on the panel data of 216 Chinese cities from 2008 to 2018, the synergistic reduction efficiency of pollution and carbon (SREPC) was calculated using the super‐efficiency slack‐based measure model. Differences‐in‐differences (DID), propensity score matching (PSM)–DID, and spatial‐DID were adopted to study the impact of the carbon emission trading (CET) policy on SREPC. The study results show that SREPC was not improved overall, with an unbalanced development characteristic of high efficiency in the east and low efficiency in the west. The Meta‐frontier results show that there were indeed significant differences between pilot and non‐pilot cities before and after the implementation of the CET policy. Mechanism tests reveal that CET promoted SREPC by improving energy efficiency and optimizing industrial structures. Spatial analysis shows that CET had spatial spillover effects and decreased SREPC in neighboring cities. These reduction effects occurred in neighboring non‐pilot cities and showed an inverted U‐shaped relationship with increasing geographical distance, particularly significant within 500–600 km. Inverse data envelopment analysis shows that CET can utilize the synergistic reduction potential of pollution and carbon.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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