对外贸易、FDI与中国绿色全要素生产率OACHSSCDCSTPCD
Foreign Trade,FDI,and China's Green Total Factor Productivity
实现双碳目标、提高全要素生产率、推动经济绿色转型是数字时代下中国迈向经济高质量发展阶段的重要目标.本文采用四阶段DEA方法,结合SBM模型和Tobit回归,测算2005-2020年中国30个省份的绿色全要素生产率,以对外贸易、外商直接投资作为核心解释变量,以产业结构、环境规制等为控制变量构建空间面板数据模型,探究对外贸易、外商直接投资对我国绿色全要素生产率的影响.实证研究表明:对外贸易有利于促进技术进步,进而对我国绿色全要素生产率具有显著的促进作用,而外商直接投资对我国绿色全要素生产率的影响,在统计上并不显著.产业结构水平和人口密度对我国绿色全要素生产率的提升有抑制作用.
Achieving the dual carbon goals,improving total factor productivity,and promoting green economic transformation are important goals for China to move towards a stage of high-quality economic development in the digital age.This paper employs a four-stage DEA method,combining the SBM model and Tobit regression to measure the green total factor productivity of 30 provinces in China from 2005 to 2020.Using foreign trade and foreign direct investment as the core explanatory variables,and industrial structure and environmental regu-lation as control variables,a spatial panel data model is constructed to explore the impacts of foreign trade and foreign direct investment on China's green total factor productivity.Empirical research shows that foreign trade is conducive to promoting technological progress,thus having a significant positive effect on China's green total factor productivity,while the impact of foreign direct investment on China's green total factor productivity is not statistically significant.The level of industrial structure and population density have a suppressive effect on the improvement of China's green total factor productivity.
吴嘉慧;房彦兵;王婷
宁夏大学 数学统计学院,宁夏 银川 750021宁夏大学 教育与社会学部,宁夏 银川 750021中国人民银行宁夏回族自治区分行,宁夏 银川 750001
经济学
对外贸易外商直接投资四阶段DEA绿色全要素生产率
foreign tradeforeign direct investmentfour-stage DEAgreen total factor productivity
《宁夏大学学报（自然科学版）》 2024 (003)
225-232 / 8
宁夏自然科学基金资助项目(2020AAC03070);国家自然科学基金资助项目(12061055)
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