Impact of Energy Efficiency and Financial Support on Green Upgrading in China’s Industrial Sector

Yingying Zhou, Ning Yang, Panpan Meng, Xiaoqian Jing, Fengran Lu
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Abstract

The report from the 20th National Congress of China emphasizes the importance of focusing on the clean, low-carbon, and efficient use of energy, increasing financial support, and promoting green upgrading within the industrial sector. This paper, based on annual data, employs the entropy weight method to construct a comprehensive index reflecting the impact of green upgrading in industrial sectors. To delve deeper, it utilizes the DEA model to measure energy efficiency and its subdivision BCC model to break down energy efficiency into technical and scale efficiency. The financial support landscape is examined from the vantage points of both direct and indirect financing. Using a multivariate time series model, this paper thoroughly investigates the influence of energy efficiency and financial support on the green upgrading of the industrial sector. The findings reveal a significant positive impact of both energy efficiency and financial support on green upgrading in industrial industries. Notably, scale efficiency emerges as the primary driver of energy efficiency. Moreover, indirect financing proves to be more effective in promoting financial support than direct financing. The empirical results retain their robustness even after substituting explanatory variables. The study concludes by contextualizing the research findings within the current real-world scenario, offering practical insights, and proposing specific recommendations.
能效和财政支持对中国工业部门绿色升级的影响
中国第二十次全国代表大会报告强调,要以能源清洁低碳高效利用为重点,加大财政支持力度,推动工业领域绿色升级。本文基于年度数据,采用熵权法构建了反映工业领域绿色升级影响的综合指数。为了深入研究,本文利用 DEA 模型来衡量能源效率,并利用其细分 BCC 模型将能源效率分解为技术效率和规模效率。本报告从直接融资和间接融资两个角度考察了金融支持情况。本文采用多元时间序列模型,深入研究了能效和金融支持对工业部门绿色升级的影响。研究结果表明,能效和金融支持对工业产业的绿色升级都有显著的积极影响。值得注意的是,规模效率是能源效率的主要驱动力。此外,间接融资比直接融资更能有效促进金融支持。即使在替换了解释变量后,实证结果仍然保持稳健。研究最后将研究结果与当前的现实情况相结合,提出了切实可行的见解,并提出了具体建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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