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| Human Capital, Green Technology Innovation, and Total Factor Carbon Emission Efficiency in the Yangtze River Economic Belt |
| He Weijun1,Li Wenqin1,Deng Mingliang2,3 |
| (1.School of Economics and Management, China Three Gorges University, Yichang 443002,China;2.School of Economics and Management, Wuhan University;3.China Institute of Development Strategy and Planning, Wuhan University, Wuhan 430072,China) |
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Abstract With the gradual transformation of China's economy and society, China has entered a new stage of high-quality development. It has become an important symbol and task of China's high-quality economic and social development to accelerating carbon emission reduction and realizing carbon peak and carbon neutralization as soon as possible. The Yangtze River Economic Belt holds a major strategic position related to the overall development of the country, coordinating high-quality development and high-level protection, continuously promoting the accumulation of human capital, supporting green technological innovation and accelerating the improvement of total factor carbon emission efficiency. High-quality development of the Yangtze River Economic Belt is vital to China's ecological priority green development and national economic development. Therefore this study aims to explore the ways in which human capital, green technology innovation affects total factor carbon emission efficiency, whether green technology innovation can effectively play the mediating effect, and the impact of human capital on the overall efficiency of green technology innovation with the constraints of green technology innovation. There are theoretical and practical issues such as whether the influence of factor carbon emission efficiency has nonlinear characteristics.#br#Therefore, based on the panel data of the Yangtze River Economic Belt from 1999 to 2019, the study first uses the global super-efficiency SBM model to measure the total factor carbon emission efficiency. Then, based on the extended STIRPAT model, a mediation effect test model is constructed to examine the path of human capital and green technology innovation affecting the total factor carbon emission efficiency of the Yangtze River Economic Belt. Finally, this study uses the interaction term and panel threshold model to examine the differences and nonlinear characteristics of human capital-driven total factor carbon emission efficiency with different levels of green technology innovation.#br#The main conclusions of this paper are as follows. (1) Human capital and green technological innovation can effectively promote the green and low-carbon development of the Yangtze River Economic Belt. Human capital is the main body and basic condition of green and low-carbon development. The research results show that the improvement of human capital level can effectively promote the efficiency of total factor carbon emission in the Yangtze River Economic Belt, and promote the comprehensive green and low-carbon transformation of production and lifestyle. The test results show that the improvement of green technology innovation level has a significant positive driving effect on the total factor carbon emission efficiency of the Yangtze River Economic Belt. It can play an important supporting role in carbon development. (2) Green technological innovation can play a partial intermediary effect in human capital driving the improvement of total factor carbon emission efficiency in the Yangtze River Economic Belt. The test results of the mediation effect model show that the improvement of human capital can promote the comprehensive green and low-carbon transformation by popularization and promotion of the concept of green and low-carbon, as well as the improvement of the total factor carbon emission efficiency of the Yangtze River Economic Belt. (3) Green technological innovation has the characteristic of gradualness ingiving full play to the green and low-carbon effect of human capital. The nonlinear test results show that the level of green technology innovation can effectively promote the green and low-carbon effect of human capital. At the same time, the improvement of green technology innovation ability and level can promote human capital to drive the improvement of total factor carbon emission efficiency in the Yangtze River Economic Belt to a greater extent.#br# Different from the traditional methods and perspectives for carbon emission reading and single factor carbon emission efficiency, this study uses the global super-efficiency SBM model to measure the total factor carbon emission efficiency. It focuses on technological innovation from the carbon perspective, and explores the impact of green technological innovation on the efficiency of total factor carbon emissions. Moreover the study combines human capital, green technological innovation, the total factor carbon emission efficiency into the same analysis framework, and the mediation effect model and the panel threshold model are used to examine the path and nonlinear characteristics of human capital and green technology innovation affecting the total factor carbon emission efficiency of the Yangtze River Economic Belt. It enriches the research content and perspective of green and low-carbon development in the Yangtze River Economic Belt, expands the application field of total factor productivity and provides a reference for subsequent research.#br#
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Received: 02 August 2021
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| [1] 吴传清，邓明亮. 科技创新、对外开放与长江经济带高质量发展[J]. 科技进步与对策， 2019, 36(3): 33-41. [2] LIU G, WANG B, ZHANG N. A coin has two sides:which one is driving China's green TFP growth[J]. Economic Systems， 2016, 40(3): 481-498. [3] 万建香，汪寿阳. 社会资本与技术创新能否打破“资源诅咒”——基于面板门槛效应的研究[J]. 经济研究，2016, 51(12): 76-89. [4] 宁论辰，郑雯，曾良恩. 2007—2016年中国省域碳排放效率评价及影响因素分析——基于超效率SBM-Tobit模型的两阶段分析[J]. 北京大学学报(自然科学版)， 2021, 57(1): 181-188. [5] 张永强，田媛，王珧，等. 农村人力资本、农业技术进步与农业碳排放[J]. 科技管理研究， 2019, 39(14): 266-274. [6] 车维平，苏睿. 人力资本积累对低碳经济发展的影响[J]. 河北大学学报(哲学社会科学版)， 2014, 39(4): 105-108. [7] 安超，雷明. 二氧化碳排放、人力资本和内生经济增长研究[J]. 中国管理科学， 2019, 27(5): 149-160. [8] 张翱祥，邓荣荣. 中部六省碳排放效率与产业结构优化的耦合协调度及影响因素分析[J]. 生态经济，2021, 37(3): 31-37. [9] 赵领娣，贾斌，胡明照. 基于空间计量的中国省域人力资本与碳排放密度实证研究[J]. 人口与发展， 2014, 20(4): 2-10. [10] 高鸣，陈秋红. 贸易开放、经济增长、人力资本与碳排放绩效——来自中国农业的证据[J]. 农业技术经济， 2014(11): 101-110. [11] 郭炳南，卜亚. 人力资本、产业结构与中国碳排放效率——基于SBM与Tobit模型的实证研究[J]. 当代经济管理， 2018, 40(6): 13-20. [12] 李荣杰，张磊，赵领娣. 中国清洁能源使用、要素配置结构与碳生产率增长——基于引入能源和人力资本的生产函数[J]. 资源科学，2016, 38(4): 645-657. [13] 姚增福，唐华俊，刘欣. 要素积累、人力资本与农业环境效率间门槛效应研究——低碳约束下面板门槛模型检验[J]. 重庆大学学报(社会科学版)， 2017, 23(4): 26-36. [14] 程钰，孙艺璇，王鑫静，等. 全球科技创新对碳生产率的影响与对策研究[J]. 中国人口·资源与环境，2019, 29(9): 30-40. [15] 刘仁厚，王革，黄宁，等. 中国科技创新支撑碳达峰、碳中和的路径研究[J]. 广西社会科学， 2021，37(8): 1-7. [16] 张玉华，张涛. 改革开放以来科技创新、城镇化与碳排放[J]. 中国科技论坛， 2019(4): 28-34. [17] 高大伟. 中国科技创新与低碳经济的协调发展研究[J]. 技术经济与管理研究， 2015，36(7): 34-37. [18] GERLAGH R. Measuring the value of induced technological change[J]. Energy Policy， 2007, 35(11): 5287-5297. [19] 刘晓慧. 我国区域碳排放效率实证研究[J]. 煤炭技术， 2021, 40(9): 212-214. [20] 金培振，张亚斌，彭星. 技术进步在二氧化碳减排中的双刃效应——基于中国工业35个行业的经验证据[J]. 科学学研究， 2014, 32(5): 706-716. [21] FISHER-VANDEN K, WING I S. Accounting for quality: issues with modeling the impact of R&D on economic growth and carbon emissions in developing economies[J]. Energy Economics， 2008, 30(6): 2771-2784. [22] 熊爱华，丁友强，胡玉凤. 低碳门槛下绿色创新补贴对全要素生产率的影响[J]. 资源科学， 2020, 42(11): 2184-2195. [23] 袁晖光，范思凯. 人力资本驱动科技创新的动力机制研究[J]. 山东社会科学， 2021，35(6): 127-132. [24] 何小洲，何优军. 官产学合作对社会资本与技术创新的中介效应研究[J]. 科技进步与对策， 2016, 33(21): 11-15. [25] 高素英，陈蓉，张艳丽，等. 京津冀人力资本与区域科技创新能力的关系研究[J]. 天津大学学报(社会科学版)， 2011, 13(6): 551-555. [26] 李林汉，田卫民. 科技金融、人力资本与科技创新关系研究——来自中国省级面板数据的证据[J]. 科技促进发展， 2019, 15(1): 26-35. [27] 梁军，赵青. 教育人力资本及其溢出效应对中国科技创新的影响研究——基于省际面板数据的经验分析[J]. 上海大学学报(社会科学版)，2018, 35(6): 122-131. [28] 吕洪燕，于翠华，孙喜峰，等. 人力资本结构高级化对科技创新绩效的影响[J]. 科技进步与对策， 2020, 37(3): 133-141. [29] 闫沛慈，芮雪琴. 人力资本集聚促进区域科技创新吗——基于门槛回归模型的分析[J]. 管理现代化， 2018, 38(6): 95-99. [30] 常青青，仲伟周. 互联网、人力资本和科技创新门槛效应的实证[J]. 统计与决策， 2018, 34(24): 101-104. [31] 赖一飞，谢潘佳，叶丽婷，等. 我国区域科技创新效率测评及影响因素研究——基于超效率SBM-Malmquist-Tobit模型[J]. 科技进步与对策， 2021, 38(13): 37-45. [32] 田超杰. 科技创新、人力资本对创意经济的影响研究[J]. 科技进步与对策， 2013, 30(15): 146-149. [33] 郝金磊，姜诗尧. 健康人力资本、科技创新效率与经济增长[J]. 西安电子科技大学学报(社会科学版)， 2016, 26(1): 52-58. [34] 肖滢，马静. 科技创新、人力资本与城市发展质量的实证分析[J]. 统计与决策，2018, 34(16): 169-172. [35] 常文涛. 农业科技创新资金与科技人力资本支农绩效实证分析[J]. 统计与决策， 2018, 34(21): 113-116. [36] 苏科，周超. 人力资本、科技创新与绿色全要素生产率——基于长江经济带城市数据分析[J]. 经济问题， 2021，43(5): 71-79. [37] 徐维祥，姜丽佳，徐志雄. 人力资本、科技创新与信息经济发展关系研究——异质性视角[J]. 科技进步与对策， 2019, 36(14): 76-84. [38] 张雪峰，宋鸽，闫勇. 要素投入对中国工业碳生产率的影响研究——来自Heckman两阶段的经验数据[J]. 经济问题， 2021，43(6): 60-64. [39] 刘在洲，汪发元. 绿色科技创新、财政投入对产业结构升级的影响——基于长江经济带2003-2019年数据的实证分析[J]. 科技进步与对策，2021, 38(4): 53-61. [40] 张华，丰超. 创新低碳之城:创新型城市建设的碳排放绩效评估[J]. 南方经济， 2021，39(3): 36-53. [41] 刘健强，马晓钰. 人口老龄化、产业结构升级与碳排放——基于Stirpat模型的空间计量分析[J]. 金融与经济， 2021，42(7): 54-62. [42] 陈占明，吴施美，马文博，等. 中国地级以上城市二氧化碳排放的影响因素分析:基于扩展的Stirpat模型[J]. 中国人口·资源与环境，2018, 28(10): 45-54. [43] 金浩，刘肖. 产业协同集聚、技术创新与经济增长——一个中介效应模型[J]. 科技进步与对策， 2021, 38(11): 46-53. [44] 刘荣增，何春. 环境规制对城镇居民收入不平等的门槛效应研究[J]. 中国软科学，2021，36(8): 41-52. [45] 曹珂，屈小娥. 中国区域碳排放绩效评估及减碳潜力研究[J]. 中国人口·资源与环境， 2014, 24(8): 24-32. [46] HANSEN B E. Threshold effects in non-dynamic panels: estimation, testing, and inference[J]. Journal of Econometrics，1999, 93(2): 345-368. |
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