世界经济 ›› 2016, Vol. ›› Issue (12): 166-188.

• 马克思主义研究专栏 • 上一篇    下一篇

地方政府的环境治理决策:基于SO2减排的面板数据分析

黄滢1, 刘庆2, 王敏3   

  1. 1. 中国人民大学经济学院;
    2. 北京大学经济学院 北京 100871;
    3. 北京大学国家发展研究院
  • 收稿日期:2016-08-01 出版日期:2016-12-10 发布日期:2017-01-03
  • 通讯作者: 刘庆(通讯作者),电子信箱:liuqing624624@163.com E-mail:liuqing624624@163.com

Environmental Policies of Local Governments: An Panel Data Analysis of SO2 Abatement

Huang Ying1, Liu Qing2, Wang Min3   

  • Received:2016-08-01 Online:2016-12-10 Published:2017-01-03

摘要: 本文基于地方政府的环境治理决策,构建了一个地方政府与企业之间的两阶段博弈模型。地方政府在政绩最大化的目标函数下制定环境政策。污染企业则根据地方政府制定的环境政策进行生产决策。理论模型的推导表明,在官员晋升考核体制下,产业结构(第二产业GDP占比)对于地方政府环境政策强度存在U型影响的可能。在此基础上,本文运用2003-2011年的城市面板数据对模型的结论进行经验检验,结果表明:当第二产业GDP占比低于(高于)55%时,第二产业比重越大,则环境政策强度越小(越大)。最后,通过对文献中常用的环境政策指标进行对比分析,本文还发现选取不同的环境政策指标进行回归分析,会产生截然不同的结果,这说明研究中国的环境问题,选择合理正确的环境政策指标至关重要。

关键词: 产业结构, 环境政策, 晋升激励, 减排率, 面板固定效应模型

Abstract: This paper constructs a theoretic model to study the behaviors of China local governments in environmental policy-making process. In our model, local governments make environmental policies under promotion incentives, while polluting firms produce according to such policies. The model predicts a U-shaped relationship between the GDP ratio of local secondary industry and the strictness of local environmental policies, which we use the 2003-2011 "China City Statistical Yearbook" panel data to test. The regression results confirm the theory prediction and find that the turning point is around 55%. That is, when the GDP ratio of secondary industry is below (or above) 55%, the strictness of local environmental policies monotonically decrease (or increase) in the GDP ratio of the second industry in the local economy. We also compare the regression results with different indicators of environmental policy and find heterogeneous effects, which implies that it is extremely crucial to use the right policy indicator when we study the environmental problem in China.

Key words: industrial structure, environmental policy, promotion incentives, rate of abatement, panel-data fixed effects model

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