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Investigating the nonlinear effects of climate change on agricultural green total factor productivity: findings from the PSTR approach

Author

Listed:
  • Deheng Zhou

    (Sichuan Agricultural University)

  • Mengqian Tang

    (Sichuan Agricultural University)

  • Houjian Li

    (Sichuan Agricultural University)

Abstract

Current climate issues pose a challenge to green development, so it is important to study the relationship between climate change and agricultural green total factor productivity (AGTFP). This paper constructs a panel smooth transition regression (PSTR) model using panel data from 2005 to 2019 in China to evaluate the relationship between climate change and agricultural green total factor productivity. Selecting agricultural operation scale, agricultural premium and green finance index as transfer variables, the PSTR model is constructed, respectively. The empirical results show that the impacts of different types of climate change on AGTFP have significant nonlinear characteristics. Smaller and larger agricultural operation scales can mitigate the negative impact of sunshine impact on AGTFP. Higher agricultural premiums and lower or higher green finance index can mitigate the negative impact of temperature shock and sunshine shock on AGTFP. Based on the research results, we put forward policy recommendations to encourage the expansion of agricultural operation scale, promote agricultural insurance and promote the construction of a green financial system.

Suggested Citation

  • Deheng Zhou & Mengqian Tang & Houjian Li, 2024. "Investigating the nonlinear effects of climate change on agricultural green total factor productivity: findings from the PSTR approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 24453-24471, September.
    • Handle: RePEc:spr:endesu:v:26:y:2024:i:9:d:10.1007_s10668-023-03650-x
    DOI: 10.1007/s10668-023-03650-x
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