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基于绿色索罗模型的中国碳排放峰值预测

Forecast of the Peak of China’s Carbon Dioxide Emissions Based on the Green Solow Model

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【作者】 付喆颜建晔孙艳梅何静

【Author】 Fu Zhe;Yan Jianye;Sun Yanmei;He Jing;School of Banking and Finance,University of International Business and Economics,"The Belt and Road" PPP Development and Research Center;Institute of New Structural Economics, Peking University;School of Banking and Finance, University of Internation Business and Economics;Business School,University of International Business and Economics;

【机构】 对外经济贸易大学金融学院"一带一路"PPP发展研究中心北京大学新结构经济学研究院对外经济贸易大学金融学院对外经济贸易大学商学院

【摘要】 本文对环境库兹涅茨曲线经典理论绿色索罗模型在微观基础的建立上进行改进,按照中国经济数据进行参数的校准与拟定,从理论和数值模拟的层面支持了中国数据的总体趋势和国内学者相关实证研究的结论:中国温室气体排放还未达到环境库兹涅茨曲线的拐点。更进一步,本文第一次使用理论模型预测出中国CO2排放的库兹涅茨曲线拐点(2030年左右),该预测高度契合了我国的2020、2030减排目标。同时,基于改变环境治理支出的反事实分析,本文发现加快减排技术进步相较提高治理支出,对于促进排放总量下降的效果更为明显。因此,在经济发展进入新常态的当下,我国应进一步优化能源的生产结构,同时通过增加技术投入、提高生产效率和优化所有制结构等途径,推动节能技术进步。

【Abstract】 This paper improves the classical theoretical model of the environmental Kuznets curve,the Green Solow Model on the establishment of the micro-foundation, and calibrates the parameters according to Chinese economic data. The results support the general trends of Chinese data and the conclusions made by domestic empirical researches from perspectives of theory and numerical simulation. Furthermore,through the numerical simulation method,it uses the theoretical model for the first time to predict the Kuznets curve inflection point of China’s carbon dioxide emissions(around 2030), which is highly consistent with China’s 2020 and 2030 emission reduction targets. Finally,based on the counterfactual analysis of changing environmental governance expenditures, it finds that the acceleration of emission reduction technological progress is more effective than improving governance expenditures in terms of accelerating the reduction of total emissions.

【基金】 对外经济贸易大学“一带一路”PPP发展研究中心课题“‘一带一路’相关国家环境库兹涅茨曲线拐点预测模型”(78170408)
  • 【文献出处】 华中师范大学学报(人文社会科学版) ,Journal of Central China Normal University(Humanities and Social Sciences) , 编辑部邮箱 ,2019年05期
  • 【分类号】X321;F124
  • 【被引频次】2
  • 【下载频次】805
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