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What Affects Agricultural Green Total Factor Productivity in China? A Configurational Perspective Based on Dynamic Fuzzy-Set Qualitative Comparative Analysis

Author

Listed:
  • Danni Lu

    (State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xinhuan Zhang

    (State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Degang Yang

    (State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Shubao Zhang

    (State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Agricultural production faces the dual challenge of increasing output while ensuring efficient resource utilization and environmental sustainability amid escalating global climate change and relentless increases in human demand. This study used provincial panel data from China from 2001 to 2022 to address these challenges. It systematically evaluated the dynamic evolution of agricultural green total factor productivity (AGTFP) by selecting “resources” and “energy” as core input factors and adopting a dual-output approach focused on “economic” and “low-carbon” outcomes. This study thoroughly analyzed the synergistic mechanisms of factors such as natural endowment, agricultural technology, economic development, and environmental regulation, exploring their impact on AGTFP enhancement through the innovative application of the dynamic fuzzy-set qualitative comparative analysis (fsQCA) method. There was a significant upward trend in AGTFP across China, indicating notable progress in green agricultural development. Additionally, three pathways promoting AGTFP improvement were identified: resource–economy-driven, technology–policy-guided, and multifactor-synergy. Simultaneously, two modes constraining AGTFP enhancement were uncovered: economy–policy suppression and human capital–economy suppression, highlighting the pivotal role of regional economic development and the conditionality of converting natural resource advantages. Moreover, the contributions of these pathways to AGTFP exhibited notable temporal dynamics. Major economic events, such as the 2008 financial crisis and policy shifts, including the 2012 “Ecological Civilization” strategy, significantly altered the effectiveness of existing configurations. Our analysis of regional heterogeneity revealed distinct geographical patterns, with the resource–economy-driven model predominantly observed in central regions and the technology–policy-guided and multi-factor-synergy models more prevalent in central and eastern regions. These findings highlight the importance of formulating differentiated policies tailored to the specific needs and stages of development in different regions. Specifically, enhancing the synergy between resource management and economic development, optimizing technology–policy integration, and promoting coordinated multisectoral development are critical to fostering sustainable agricultural practices. This research provides crucial empirical evidence for shaping targeted policies that can drive green agricultural development across diverse regional contexts.

Suggested Citation

  • Danni Lu & Xinhuan Zhang & Degang Yang & Shubao Zhang, 2025. "What Affects Agricultural Green Total Factor Productivity in China? A Configurational Perspective Based on Dynamic Fuzzy-Set Qualitative Comparative Analysis," Agriculture, MDPI, vol. 15(2), pages 1-25, January.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:2:p:136-:d:1563524
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