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ORIGINAL RESEARCH article

Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
Volume 8 - 2024 | doi: 10.3389/fsufs.2024.1489448

The double-edged sword effect of agricultural technological progress on agricultural carbon emissions: Empirical evidence from China

Provisionally accepted
Shiying Zhu Shiying Zhu 1Jianxu Liu Jianxu Liu 1YanSong Li YanSong Li 1Siqi Wang Siqi Wang 1Jiande Cui Jiande Cui 1Woraphon Yamaka Woraphon Yamaka 2*
  • 1 Shandong University of Finance and Economics, Jinan, China
  • 2 Chiang Mai University, Chiang Mai, Thailand

The final, formatted version of the article will be published soon.

    As global climate change intensifies, mitigating agricultural carbon emissions has become a critical research focus. This study aims to explore the dual effects of agricultural technological progress on carbon emissions and its underlying mechanisms. Using panel data from 30 Chinese provinces from 2002 to 2021, we employ a two-tier stochastic frontier model for empirical analysis. Our key findings are: (1) Agricultural technological progress exhibits a significant dual effect on carbon emission intensity, with an average net reduction of 3.17%. (2) Different types of agricultural technologies have varying impacts on emission intensity: mechanical technologies increase emissions, while resource-saving and biochemical technologies reduce them. (3) The impact of technological progress on emission intensity shows notable regional heterogeneity. ( 4) Factors such as agricultural land management scale, fiscal support for agriculture, and agricultural human capital significantly influence the emission reduction effects of technological progress. Based on these results, we recommend implementing differentiated agricultural technology promotion strategies, developing "carbon-smart" agricultural management systems, and strengthening incentive mechanisms for low-carbon agricultural technology innovation and application.

    Keywords: TFP, agricultural technological progress, Agricultural carbon emissions, two-tier stochastic frontier models, carbon intensity ' include ATP, ey, sl, lnmp, ad, ed, fs, hc, ur, lnpi

    Received: 01 Sep 2024; Accepted: 29 Nov 2024.

    Copyright: © 2024 Zhu, Liu, Li, Wang, Cui and Yamaka. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Woraphon Yamaka, Chiang Mai University, Chiang Mai, 50200, Thailand

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