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Trade openness and green total factor productivity: testing the role of environment regulation based on dynamic panel threshold model

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  • Qinghua Huang

    (Southwest University)

  • Min Liu

    (Southwest University)

Abstract

As an ecological barrier to ensure the high-quality development of China’s economy, the Yangtze River Economic Belt has attracted more and more attention from academic circles on how to promote the green development of the Yangtze River Economic Belt. This paper uses the SBM directional distance function and the Malmquist–Luenberger index to measure the green total factor productivity of 110 cities in the Yangtze River Economic Belt from 2006 to 2018, and then based on the panel threshold model to empirically explore the intensity of environmental regulations that induce trade openness and promote green total factor productivity. Studies have shown that: Firstly, trade openness has significantly inhibited the increase in green total factor productivity, but environmental regulations can play a positive regulatory role, that is increasing the intensity of environmental regulation can alleviate the adverse effects of trade openness, and it is mainly to improve the adverse effects by promoting the progress of green technology. Secondly, the results of the panel threshold model show that environmental regulations have a nonlinear regulatory effect on trade openness and green total factor productivity. When the intensity of environmental regulations crosses the second threshold, trade openness has a significant positive effect on the impact of green total factor productivity. Finally, the heterogeneity results show that in order to reverse the adverse impact of trade openness on green total factor productivity, the upper, middle and lower reaches of the Yangtze River Economic Belt should formulate relatively strict environmental regulations.

Suggested Citation

  • Qinghua Huang & Min Liu, 2022. "Trade openness and green total factor productivity: testing the role of environment regulation based on dynamic panel threshold model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9304-9329, July.
    • Handle: RePEc:spr:endesu:v:24:y:2022:i:7:d:10.1007_s10668-021-01825-y
    DOI: 10.1007/s10668-021-01825-y
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    5. Xiong, Su & Luo, Rong, 2023. "Investigating the relationship between digital trade, natural resources, energy transition, and green productivity: Moderating role of R&D investment," Resources Policy, Elsevier, vol. 86(PB).
    6. Lee, Chien-Chiang & Wang, Fuhao & Lou, Runchi & Wang, Keying, 2023. "How does green finance drive the decarbonization of the economy? Empirical evidence from China," Renewable Energy, Elsevier, vol. 204(C), pages 671-684.
    7. Huiling Liu & Jianhua Zhang & Hongyun Huang & Haitao Wu & Yu Hao, 2023. "Environmental good exports and green total factor productivity: Lessons from China," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1681-1703, June.
    8. Yue Zhang & Hui Zhang & Haozhaoxing Liao & Xiang Sun & Lisi Jiang & Yufeng Wang & Yue Wang, 2024. "Heterogeneous Porter Effect or Crowded-Out Effect: Nonlinear Impact of Environmental Regulation on County-Level Green Total Factor Productivity of Pigs in the Yangtze River Basin of China," Agriculture, MDPI, vol. 14(9), pages 1-33, September.
    9. Min Liu & Yamei Li & Jiangfeng Hu, 2024. "Does the Yangtze River Protection Strategy help heavily polluting corporates deleverage? Evidence from corporates in the Yangtze River Economic Belt," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-30, April.

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