College of Management Science, Chengdu University of Technology, Chengdu, 610051, China.
Faculty of Management and Administrative Sciences, Department of Business Administration, University of Sialkot, Punjab, Pakistan.
Environ Sci Pollut Res Int. 2023 Oct;30(46):102818-102838. doi: 10.1007/s11356-023-29551-0. Epub 2023 Sep 6.
Amidst resource loss and environmental protection constraints, achieving green development necessitates enhancing green total factor productivity (GTFP) as a means of promoting rational and efficient resource allocation, thereby balancing economic growth and environmental preservation. Meanwhile, literature on the subject matter of GTFP from a sustainability viewpoint is minimal. As a result, this study employs the panel dataset from 30 provinces of China spanning the period 2005 to 2020 and utilizes the method of moments quantile regression (MMQR) developed by Machado and Santos Silva (2019) to analyze the heterogeneous role of green innovation, environmental regulations, and fiscal expenditure on GTFP. Moreover, the controlling variable for this study includes renewable energy and economic growth. Furthermore, this study investigates the heterogeneous combined impact of green innovation and fiscal expenditure (GTEFSE) on GTFP. The findings of the MMQR reveal that green innovation has a positive impact on GTFP, while fiscal expenditure, environmental regulations, and renewable energy consumption have a negative impact. GTEFSE has a positive and significant effect on GTFP, indicating that FSE can reinforce and increase the positive impact of GTE on GTFP in the long run. The study also reveals that economic growth has a mixed effect on GTFP, depending on the quantiles. Furthermore, environmental regulation has a significant and negative impact on GTFP, contradicting the Porter hypothesis. Likewise, the robustness of the findings is confirmed by the results of the fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations, which indicate a similar impact of the determinants on GTFP as observed in the MMQR analysis. This reinforces the validity of the findings and suggests that the observed relationships are robust to different estimation techniques. Furthermore, the findings of the Dumitrescu and Hurlin (D-H) panel causality test reveal significant bidirectional causality between renewable energy consumption and GTFP and fiscal expenditure and GTFP. Policy-makers need to channel a large chuck of their fiscal spending into green innovation so as to boost sustainability.
在资源损失和环境保护的限制下,实现绿色发展需要提高绿色全要素生产率(GTFP),以促进合理高效的资源配置,从而平衡经济增长和环境保护。同时,从可持续发展角度研究 GTFP 的文献很少。因此,本研究采用 2005 年至 2020 年中国 30 个省份的面板数据,利用 Machado 和 Santos Silva(2019 年)提出的矩分位数回归(MMQR)方法,分析绿色创新、环境规制和财政支出对 GTFP 的异质作用。此外,本研究的控制变量包括可再生能源和经济增长。此外,本研究还考察了绿色创新和财政支出(GTEFSE)对 GTFP 的异质综合影响。MMQR 的结果表明,绿色创新对 GTFP 有正向影响,而财政支出、环境规制和可再生能源消费对 GTFP 有负向影响。GTEFSE 对 GTFP 有正向且显著的影响,表明 FSE 可以长期强化和增加 GTE 对 GTFP 的正向影响。研究还发现,经济增长对 GTFP 的影响是混合的,取决于分位数。此外,环境规制对 GTFP 有显著的负向影响,与波特假说相悖。同样,完全修正的 OLS(FMOLS)和动态 OLS(DOLS)估计的结果证实了结果的稳健性,表明在 MMQR 分析中观察到的决定因素对 GTFP 的影响相似。这增强了结果的有效性,并表明观察到的关系对不同的估计技术是稳健的。此外,Dumitrescu 和 Hurlin(D-H)面板因果检验的结果表明,可再生能源消费和 GTFP 之间以及财政支出和 GTFP 之间存在显著的双向因果关系。政策制定者需要将大量的财政支出用于绿色创新,以提高可持续性。