How does green finance affect green total factor productivity? Evidence from China

Energy Economics, Journal Year: 2022, Volume and Issue: 107, P. 105863 - 105863

Published: Jan. 29, 2022

Language: Английский

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Has China's Belt and Road Initiative promoted its green total factor productivity？——Evidence from primary provinces along the route

Energy Policy, Journal Year: 2019, Volume and Issue: 129, P. 360 - 369

Published: Feb. 19, 2019

Language: Английский

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How do environmental regulation and foreign investment behavior affect green productivity growth in the industrial sector? An empirical test based on Chinese provincial panel data

Journal of Environmental Management, Journal Year: 2021, Volume and Issue: 287, P. 112282 - 112282

Published: March 11, 2021

Language: Английский

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Regional analysis of the green development level differences in Chinese mineral resource-based cities

Resources Policy, Journal Year: 2019, Volume and Issue: 61, P. 261 - 272

Published: March 7, 2019

Language: Английский

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Path to sustainable development: Does digital economy matter in manufacturing green total factor productivity?

Sustainable Development, Journal Year: 2022, Volume and Issue: 31(1), P. 360 - 378

Published: Sept. 6, 2022

Abstract In the context of outbreak COVID‐19 pandemic and China's “digital power” strategy, realization a green shift manufacturing has become necessary condition to promote economy, digital factor increasingly new driving force. The DEA‐Malmquist index entropy method were used measure total productivity (GTFP) level economy from 2011 2018, respectively. This study then explored impact on GTFP based system generalized moments (GMM) model, as well adjustment effects talent aggregation financial scale according moderating model. research came four conclusions. (1) can significantly improve China, influence shows characteristic “marginal increase”; (2) notably, perspective decomposition indicates that exerts significant positive effect technical efficiency during current period but obviously hinders progress; (3) interestingly, mechanistic test showed two dimensions innovation environment—talent (0.385) (0.359)—play critical roles in influencing process; (4) evident regional heterogeneity—it is east negative central region west. Finally, corresponding policy suggestions are suggested.

Language: Английский

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How does artificial intelligence affect green economic growth?—Evidence from China

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 834, P. 155306 - 155306

Published: April 21, 2022

Language: Английский

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Environmental regulation and the growth of the total-factor carbon productivity of China's industries: Evidence from the implementation of action plan of air pollution prevention and control

Journal of Environmental Management, Journal Year: 2021, Volume and Issue: 296, P. 113078 - 113078

Published: July 10, 2021

Language: Английский

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Role of environmental regulations, green finance, and investment in green technologies in green total factor productivity: Empirical evidence from Asian region

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 380, P. 134930 - 134930

Published: Nov. 3, 2022

Language: Английский

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How do heterogeneous R&D investments affect China's green productivity: Revisiting the Porter hypothesis

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 825, P. 154090 - 154090

Published: Feb. 24, 2022

Language: Английский

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Intelligent manufacturing, green technological innovation and environmental pollution

Journal of Innovation & Knowledge, Journal Year: 2023, Volume and Issue: 8(3), P. 100384 - 100384

Published: May 16, 2023

Intelligent manufacturing offers opportunities for green technology innovation at a low cost, helps eliminate outdated equipment, and improves pollution efficiency, which is essential environmental protection. From the perspective of industrial sector, based on data 269 Chinese cities, this study empirically examines impacts intelligent ecological environment using fixed effect model unconditional quantile model. The research results show that can significantly reduce concentration PM2.5 in air by optimizing resource allocation during production operation. external mechanism technological plays positive mediating role impact to improve quality. marginal nonlinear, main trend M-type distribution increasing first, then decreasing, rising. In particular, has greater welfare lower quantiles. provide viable path government actively plan strategic layout achieving goal high-quality economic development.

Language: Английский

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