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干旱区地理 ›› 2023, Vol. 46 ›› Issue (12): 2029-2041.doi: 10.12118/j.issn.1000-6060.2023.169

• 生态与环境 • 上一篇    下一篇

“双碳”目标下新疆粮食绿色全要素生产率的时空分异及驱动因素分析

马文江1(),白妙琴1,阿迪力·艾合买提1,张德平1,杨忠娜1,2()   

  1. 1.塔里木大学经济与管理学院,新疆 阿拉尔 843300
    2.华中农业大学经济管理学院,湖北 武汉 430070
  • 收稿日期:2023-04-13 修回日期:2023-10-10 出版日期:2023-12-25 发布日期:2024-01-05
  • 通讯作者: 杨忠娜(1983-),女,副教授,硕士生导师,主要从事特色农业经济研究. E-mail: yangzhongna@126.com
  • 作者简介:马文江(2001-),女,硕士研究生,主要从事特色农业经济研究. E-mail: 1137089614@qq.com
  • 基金资助:
    塔里木大学研究生科研创新项目(TDGRI202267);塔里木大学研究生教育教学改革研究项目(TDETR202218);农业经济管理教改委项目(NJX22141)

Spatial-temporal differentiation and driving factors analysis of green total factor productivity of Xinjiang grain under the carbon peaking and carbon neutrality goals

MA Wenjiang1(),BAI Miaoqin1,Adili AIHEMAITI1,ZHANG Deping1,YANG Zhongna1,2()   

  1. 1. School of Economics and Management, Tarim University, Aral 843300, Xinjiang China
    2. College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, Hubei, China
  • Received:2023-04-13 Revised:2023-10-10 Online:2023-12-25 Published:2024-01-05

摘要:

新疆粮食生产潜力巨大,是我国重要的后备耕地资源供给区。双碳目标下测算新疆粮食绿色全要素生产率(GTFP)对于新疆农业绿色转型发展及粮食安全均具有重要意义。将非期望产出粮食生产碳排放纳入粮食GTFP测度框架,基于SBM-GML模型对新疆14个地州市2000—2020年的粮食GTFP进行测算;并利用核密度估计法和Dagum基尼系数分解法对新疆各地区的粮食GTFP进行时空演进态势分析;最后运用固定效应模型甄别出影响新疆粮食GTFP的驱动因素。结果表明:(1) 2000—2020年新疆粮食GTFP呈上升趋势,年均增长率为0.7%,主要受益于粮食绿色技术效率(GEC)变化,掣肘于粮食绿色技术进步(GTC)。(2) 新疆粮食GTFP的增长存在区域异质性,从三大区域划分视角来看,北疆>东疆>南疆。(3) 时间上地区差距大致呈先缩小后增大的变化进程,空间差异主要来源于区域内差异。此外,粮食种植结构的变化显著促进了新疆粮食GTFP的增长,而城镇化水平和农村用电量则产生了显著的抑制作用。

关键词: 粮食GTFP, 动态演变, 驱动因素, 碳排放, 新疆

Abstract:

Xinjiang plays a crucial role as a significant grain production area and a key reservoir of arable land resources in China. Evaluating the green total factor productivity (GTFP) of grain in Xinjiang within the context of the carbon peaking and carbon neutrality goals holds substantial importance for advancing the green transformation of agriculture and ensuring food security in the region. This study incorporates carbon emissions from nondesired output in grain production into a framework for measuring grain GTFP. Using the SBM-GML model, we assessed the grain GTFP for 14 prefectures and municipalities in Xinjiang spanning the years 2000 to 2020. The analysis includes an examination of the spatial and temporal evolution of grain GTFP in each Xinjiang region (the North Xinjiang, East Xinjiang and South Xinjiang) using the kernel density estimation method and Dagum’s Gini coefficient decomposition. Moreover, we employ a fixed effects model to identify the impacts on the total factor productivity of Xinjiang’s agriculture. Subsequently, the fixed effects model is used to pinpoint the driving factors influencing grain GTFP in Xinjiang. The findings reveal several key insights: (1) Xinjiang’s grain GTFP exhibits an upward trajectory from 2000 to 2020, with an average annual growth rate of 0.7%. This growth is primarily attributed to advancements in grain green technology efficiency (GEC), while progress in grain green technology (GTC) acts as a constraining factor. (2) Notable regional heterogeneity characterizes the growth of Xinjiang’s grain GTFP, with the North Xinjiang region surpassing East Xinjiang and South Xinjiang in this regard. (3) Temporal regional disparities demonstrate a pattern of initial narrowing followed by an expansion, with intra-regional distinctions being the primary source of spatial differences. In addition, changes in the structure of grain cultivation significantly contribute to the growth of grain GTFP in Xinjiang, whereas urbanization levels and rural electricity consumption exert a notable dampening effect.

Key words: grain GTFP, dynamic evolution, drivers, carbon emissions, Xinjiang