摘要: |
在“双碳”目标的约束下,探究农作物种植结构对农业绿色全要素生产率的影响程度能够有效促进农业农村高质量发展。基于2000—2019年陕西省10个地市的面板数据,运用方向距离函数和Global Malmquist-Luenberger指数对“双碳”目标约束下的农业绿色全要素生产率进行测算,采用Tobit回归模型分析农作物种植结构变化对农业绿色全要素生产率的影响因子,并探讨影响农业绿色全要素生产率的其他潜在因素。研究表明:陕西省农业绿色全要素生产率在“双碳”目标的约束下,总体有所提升,但各地市间存在地区差异性;粮食作物种植面积的增长对农业绿色全要素生产率具有显著的积极影响;农户生计保障对农业绿色全要素生产率有显著的正向作用,农业机械化水平和自然环境条件均对农业绿色全要素生产率有显著的负向作用。优化农作物种植结构、减少农业碳排放量以及提升农业绿色全要素生产率,是全面促进乡村振兴、加快农业高质量发展的关键。 |
关键词: “双碳”目标 农业绿色全要素生产率 农作物种植结构 农业高质量发展 |
DOI:10.7515/JEE222023 |
CSTR:32259.14.JEE222023 |
分类号: |
基金项目:国家自然科学基金项目(42171281);国家社会科学基金项目(21BJY138);陕西省创新能力支撑计划(2022KRM045,2022KRM107) |
英文基金项目:National Natural Science Foundation of China (42171281); National Social Science Fund of China (21BJY138);
Innovation Capability Support Program of Shaanxi (2022KRM045, 2022KRM107) |
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Study on the impact of crop planting structure on agricultural green total factor productivity under the constraint of “dual carbon” goals: taking Shaanxi Province as an example |
FENG Ying, LIU Fan
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School of Management, Northwest University of Political Science and Law, Xi’an 710122, China
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Abstract: |
Background, aim, and scope Under the constraint of “dual carbon” goals, exploring the influence of crop planting structure on agricultural green total factor productivity can effectively promote the high-quality development of agriculture and rural areas. This paper mainly uses the panel data of 10 prefectures and cities in Shaanxi Province from 2000 to 2019 to investigate the influence of variations in crop planting structure on agricultural green total factor productivity, which will provide a theoretical basis for reducing agricultural carbon emissions and improving agricultural green total factor productivity. Materials and methods The data in this article derives from Shaanxi Statistical Yearbook (2001—2020), Shaanxi Water Resources Bulletin (2000—2019) and statistical yearbooks of various prefectures and cities. The directional distance function and Global Malmquist-Luenberger index are used to calculate the agricultural green total factor productivity under the constraint of “dual carbon” goals. Besides, Tobit regression model is adopted to analyze the influencing factors of the change of crop planting structure on agricultural green total factor productivity. In addition, other potential factors influencing agricultural green total factor productivity are discussed. Results Under the constraint of “dual carbon” goals, the agricultural green total factor productivity in Shaanxi Province has overall improved, but there are differences among prefectures and cities. The mix of crops planted has a more significant influence on agricultural green total factor productivity. Farmers’ livelihood security has a significant positive effect on agricultural green total factor productivity, and the level of agricultural mechanization and natural environment have a significant negative effect on agricultural green total factor productivity. Discussion In recent years, with the rapid development of agricultural economy in Shaanxi Province, the continuous rise of the total power of agricultural machinery, agricultural film and other agricultural intermediate input factors, and the annual growth of agricultural carbon emissions, the overall level of agricultural green total factor productivity is expected to improve. The adjustment of crop planting structure can not only improve the agricultural green total factor productivity, but also promote the agricultural economic development mode to transform from extensive to intensive. According to the research conclusion, the grain crop planting area significantly promotes the growth of agricultural green total factor productivity. Therefore, increasing the proportion of grain crop in the crop planting structure is an effective way to improve agricultural green total factor productivity, and also a necessary step to achieve agricultural scale, agricultural mechanization and agricultural informatization. Conclusions The increase in the grain crop planting area significantly improves the agricultural green total factor productivity. In addition, strengthening farmers’ low-carbon awareness, promoting farmers’ livelihood diversification, and focusing on agricultural scientific research and innovation can also effectively improve agricultural green total factor productivity. Recommendations and perspectives Optimizing crop planting structure, reducing agricultural carbon emissions, and improving agricultural green total factor productivity are the key to comprehensively promoting rural revitalization and accelerating high-quality agricultural development. |
Key words: “dual carbon” goals agricultural green total factor productivity crop planting structure agricultural
high-quality development |