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我国省域绿色全要素生产率的增长机制及其时空非平稳性研究

Research on the Influencing Factors and Spatio-Temporal Nonstationarity of Provincial Green Total Factor Productivity in China
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摘要 科学分析我国绿色全要素生产率的提升机制,对于制定经济发展提质增效的路径具有重要意义。本文利用SBM-GML指数测算了2000-2020年中国30个省份的绿色全要素生产率,并分别基于全局回归模型(OLS)、时间加权回归模型(TWR)、地理加权回归模型(GWR)和时空地理加权回归模型(GTWR)对其提升机制进行了分析。实证研究表明:我国绿色全要素生产率及其提升机制具有明显的时空非平稳性;在研究期内,人均GDP对各地区绿色全要素生产率的影响以正向为主,影响效应呈现以2010年左右为拐点的U型变化趋势;第三产业占比、研发投入强度及环境规制强度三个因素对绿色全要素生产率的影响具有较强的时空非平稳性,在不同时空下呈现不同的作用方向及作用强度;人均资本存量在大部分省域对绿色全要素生产率呈负向作用;FDI和高等学历人员占比对绿色全要素生产率的增长在大部分区域呈现正向作用,但作用强度在研究期内呈递减趋势。本文认为,为提高省域绿色全要素生产率,中国应继续全面促进经济增长;因地制宜的制定区域产业结构优化目标;放慢资本深化进程;加大力度引进技术型外商直接投资;完善研发投入产出机制,强调创新产出效益;改革人才培养机制,将人才培养模式从“面向学科”向“面向社会需求”转变;建立环境保护与经济发展协同监控机制,差异化的确定环境规制的强度与合理性。 Analysis of the impact mechanism of green total factor productivity(GTFP)in China is important for formulating the path of economic development to improve quality and efficiency.This paper uses the SBM-GML model to measure the green total factor productivity of 30 provinces in China from 2000 to 2020,and uses the global regression model(OLS),temporally weighted regression model(TWR),geographically weighted regression model(GWR)and geographically and temporally weighted regression model(GTWR)to analyze the influencing factors of China's GTFP.The empirical research shows that the impact mechanism of GTFP in China is obviously spatial temporal non-stationary.During the study period,per capital GDP has a positive effect on the growth of green total factor productivity,and the impact effect presents a U-shaped change with the inflection point around 2010;the proportion of the tertiary industry,R&D investment intensity and environmental regulation intensity have different directions and intensities on the growth of GTFP in different time and space;per capital stock has a negative effect on GTFP in most provinces;the proportion of FDI and higher education employment has a positive effect on the growth of green total factor productivity in the most regions,and show a decreasing trend.Based on the research results,this article puts forward the following suggestions to improve GTFP:(1)China should comprehensively promote economic growth;(2)Formulating regional industrial structure optimization objectives according to local conditions;(3)Slowing down the process of capital deepening;(4)Increasing efforts to introduce technology-based foreign direct investment;(5)Improving the input-output mechanism of R&D and emphasize the benefits of innovation and output;(6)Reforming the talent training mechanism,and change the talent training mode from discipline to social demand oriented;(7)Establishing a collaborative monitoring mechanism between environmental protection and economic development,and deferentially determining the strength and rationality of environmental regulation.
作者 罗良清 谢海洋 LUO Liang-qing;XIE Hai-yang(School of Statistics,Jiangxi University of Finance and Economics,Nanchang 330031,China;Jiangxi Applied Statistics Research Center,Jiangxi University of Finance and Economics,Nanchang 330031,China)
出处 《数理统计与管理》 北大核心 2024年第2期315-330,共16页 Journal of Applied Statistics and Management
基金 国家社科基金一般项目(20BTJ009) 江西省2020年度研究生创新专项资金项目(YC2020-B119)。
关键词 绿色全要素生产率 影响因素 时空地理加权回归模型 时空非平稳性 green total factor productivity influence factors geographically and temporally weighted regression(GTWR) spatial-temporal non-stationary
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