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基于空间面板数据模型的中国区域二氧化碳边际减排成本的收敛分析。

Convergence analysis of regional marginal abatement cost of carbon dioxide in China based on spatial panel data models.

机构信息

Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.

School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116, China.

出版信息

Environ Sci Pollut Res Int. 2021 Aug;28(29):38929-38946. doi: 10.1007/s11356-021-13288-9. Epub 2021 Mar 20.

Abstract

China has announced to launch a national emission trading system (ETS). The heterogeneity of marginal abatement cost (MAC) is prerequisite for trading, and the knowledge about the evolutionary characteristics of MAC is particularly necessary. However, the β convergence theory has been proved to be suitable yet rarely applied to the study of MAC of CO. To fill this gap, this paper connects them creatively, and the convergence of MAC during 2001-2015 and the influential factors are explored by spatial panel data models. Results show that China's MAC converges during the study period whether the spatial effect is considered or not. When evaluating the convergence of MAC, the spatial effect should not be ignored, because it will improve the explanatory power of models and promote the convergence. The size of labor force, emission level, coal consumption, foreign direct investment, and industrial structure significantly affect the growth rate of MAC. Low-carbon policies could be formulated fully considering the factors and their spillover effects. Those findings are certainly significant in imposing carbon reduction targets and adopting policy instruments. In addition, a national ETS is more applicable to China's reality at this stage and suggested to introduce carbon tax in due course in the future.

摘要

中国宣布启动全国碳排放交易体系(ETS)。边际减排成本(MAC)的异质性是交易的前提,因此了解 MAC 的演变特征尤为必要。然而,β收敛理论已被证明适用于 CO 的 MAC 研究,但很少被应用。为了填补这一空白,本文将两者创造性地结合起来,利用空间面板数据模型探讨了 2001-2015 年期间 MAC 的收敛性及其影响因素。结果表明,无论是否考虑空间效应,中国的 MAC 在研究期间都呈现出收敛趋势。在评估 MAC 的收敛性时,不应忽视空间效应,因为它会提高模型的解释力并促进收敛。劳动力规模、排放水平、煤炭消费、外国直接投资和产业结构显著影响 MAC 的增长率。在制定低碳政策时,可以充分考虑这些因素及其溢出效应。这些发现对于制定碳减排目标和采取政策工具具有重要意义。此外,在现阶段,全国 ETS 更适合中国的实际情况,未来建议适时引入碳税。

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