Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model
Achieving sustainable development that harmonizes environmental protection with economic growth in the Yangtze River Economic Belt (YREB) remains a critical area of research. Examining green total factor productivity (GTFP) aids in pinpointing the key factors and pathways essential for fostering gre...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1508785/full |
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| author | Fei Chen Liling Zhu Yi Li |
| author_facet | Fei Chen Liling Zhu Yi Li |
| author_sort | Fei Chen |
| collection | DOAJ |
| description | Achieving sustainable development that harmonizes environmental protection with economic growth in the Yangtze River Economic Belt (YREB) remains a critical area of research. Examining green total factor productivity (GTFP) aids in pinpointing the key factors and pathways essential for fostering green economic development. On the basis of 108 prefecture-level cities in the YREB, a three-stage SBM-ML index model was constructed to measure the GTFP level from 2009 to 2022. ArcGIS software was used to analyze the spatiotemporal evolution of GTFP dynamically. Finally, the multidimensional factors affecting GTFP were systematically analyzed via the Tobit model. The study revealed that (1) GTFP exhibits notable spatial disparities among the upper, middle, and lower reaches of the YREB, with the downstream areas showing higher levels than the upstream and midstream areas do. (2) After excluding environmental factors and random errors, the true GTFP level significantly decreases, indicating a notable environmental masking effect, with a masking effect of up to 63.9%. (3) The spatial distribution of GTFP overall shows a “low-high-low-high” pattern from west to east, forming an “N”-shaped spatial pattern. (4) The Tobit model regression results show that government governance enhances GTFP, while economic growth and intergovernmental fiscal decentralization hinder real GTFP. Although urbanization was initially insignificant, it significantly boosted real GTFP post-COVID-19. Finally, policy recommendations to promote green development in river basins are proposed. |
| format | Article |
| id | doaj-art-42b75d3ac7254803b45faef3702bd05b |
| institution | Kabale University |
| issn | 2296-665X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj-art-42b75d3ac7254803b45faef3702bd05b2024-12-18T05:10:29ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2024-12-011210.3389/fenvs.2024.15087851508785Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index modelFei ChenLiling ZhuYi LiAchieving sustainable development that harmonizes environmental protection with economic growth in the Yangtze River Economic Belt (YREB) remains a critical area of research. Examining green total factor productivity (GTFP) aids in pinpointing the key factors and pathways essential for fostering green economic development. On the basis of 108 prefecture-level cities in the YREB, a three-stage SBM-ML index model was constructed to measure the GTFP level from 2009 to 2022. ArcGIS software was used to analyze the spatiotemporal evolution of GTFP dynamically. Finally, the multidimensional factors affecting GTFP were systematically analyzed via the Tobit model. The study revealed that (1) GTFP exhibits notable spatial disparities among the upper, middle, and lower reaches of the YREB, with the downstream areas showing higher levels than the upstream and midstream areas do. (2) After excluding environmental factors and random errors, the true GTFP level significantly decreases, indicating a notable environmental masking effect, with a masking effect of up to 63.9%. (3) The spatial distribution of GTFP overall shows a “low-high-low-high” pattern from west to east, forming an “N”-shaped spatial pattern. (4) The Tobit model regression results show that government governance enhances GTFP, while economic growth and intergovernmental fiscal decentralization hinder real GTFP. Although urbanization was initially insignificant, it significantly boosted real GTFP post-COVID-19. Finally, policy recommendations to promote green development in river basins are proposed.https://www.frontiersin.org/articles/10.3389/fenvs.2024.1508785/fullgreen total factor productivitythree-stage SBMmasking effecttobit modeldynamic evolution |
| spellingShingle | Fei Chen Liling Zhu Yi Li Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model Frontiers in Environmental Science green total factor productivity three-stage SBM masking effect tobit model dynamic evolution |
| title | Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model |
| title_full | Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model |
| title_fullStr | Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model |
| title_full_unstemmed | Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model |
| title_short | Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model |
| title_sort | dynamic evolution and influencing factors of green total factor productivity in the yangtze river economic belt a study based on the three stage sbm ml index model |
| topic | green total factor productivity three-stage SBM masking effect tobit model dynamic evolution |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1508785/full |
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