我国工业减污降碳的绿色偏向技术进步:要素贡献、偏向识别与影响因素
Green-Biased Technical Progress in Chinese Industrial Reduction of Pollution and Carbon Emissions:Factor Contributions,Bias Identification,and Influencing Factors
吴戈 1张月池 2苗壮3
作者信息
- 1. 西南财经大学公共管理学院、数字经济与交叉科学创新研究院
- 2. 西南财经大学经济学院
- 3. 西南财经大学经济学院、习近平经济思想研究院
- 折叠
摘要
精准推进绿色偏向技术进步,是聚焦节能降碳减污目标、实现我国工业部门全面绿色低碳转型与高质量发展的重要驱动力.本文将能源与CO2、VOCs、NOx要素纳入全要素生产率的框架,结合非角度、非径向的BAM-DEA模型和Luenberger生产率指标分解模型,科学测度2000-2020年我国省际工业绿色偏向技术进步的要素贡献,识别绿色技术进步的要素偏向,并进一步探究环境要素绿色偏向技术进步的影响因素.研究表明,绿色技术进步是我国工业绿色全要素生产率提升的主要驱动力,但促进作用力正渐趋弱化,其中劳动、能源与环境要素对工业绿色偏向技术进步的贡献显著.从偏向类型上看,投入要素和环境要素在技术进步中分别属于资本与劳动节约型、NOx与CO2减排型偏向技术进步.此外,绿色技术创新能力提升、资本深化与能源结构优化对我国工业环境绿色偏向技术进步的促增效应显著.本文为精准测度不同能源与环境要素的绿色偏向技术进步水平提供新的研究范式和方法,为寻求我国工业减污降碳协同治理和绿色低碳转型的技术创新路径提供科学依据.
Abstract
Accurately advancing green-biased technical progress represents a crucial impetus in achieving the objectives of energy conservation,carbon reduction and pollution reduction.It is pivotal for the holistic green and low-carbon transformation and the high-quality development of China's industrial sector.This paper incorporates energy consumption,CO2,VOCs,NOx emission into the framework of total factor productivity.Employing the non angular and non radial BAM-DEA model and Luenberger productivity indicator decomposition model,the factor contribution of green-biased technical progress in China's industrial sector between provinces from 2000 to 2020 is scientifically measured and the factor bias of green technical progress is identified.Then the influencing factors of environmental green-biased technical progress are further explored.The principal findings of this study are as follows.Green technical progress is the main driving force for the improvement of China's industrial green total factor productivity,albeit with a diminishing momentum.Factors such as labor,energy,and environment significantly influence industrial green-biased technical progress.In terms of bias types,the input factors predominantly exhibits capital and labor conservation bias in technical progress,and the environmental factors demonstrates a bias towards reducing NOx and CO2 emission in technical progress.Moreover,the enhancement of green technology innovation capability,capital deepening,and the optimization of the energy structure exert a remarkable promoting influence on environmental green-biased technical progress.This article provides a new research paradigm and method for accurately measuring the green-biased technical progress in different energy and environmental contexts.It offers a scientific basis for seeking innovative technological pathways for China's industrial pollution reduction and carbon reduction collaborative governance,and green and low-carbon transformation.
关键词
绿色偏向技术进步/Luenberger生产率指标/要素识别/减污降碳Key words
Green-biased Technical Progress/Luenberger Productivity Indicator/Factor Identification/Reduction of Pollution and Carbon Emissions引用本文复制引用
基金项目
国家自然科学基金面上项目(72373120)
国家自然科学基金面上项目(72074183)
国家自然科学基金青年基金(72204202)
出版年
2024
NETL
NSTL
万方数据