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中国种植业碳生产率空间关联格局及影响因素分析
引用本文:伍国勇,孙小钧,于福波,杨丽莎.中国种植业碳生产率空间关联格局及影响因素分析[J].中国人口.资源与环境,2020(5):46-57.
作者姓名:伍国勇  孙小钧  于福波  杨丽莎
作者单位:贵州大学经济学院;贵州大学中国喀斯特地区乡村振兴研究院;西南大学经济管理学院
基金项目:贵州大学文科重点学科特色学科项目“贵州农业生态安全的经济学研究”(批准号:GZZT201401);贵州大学一流学科建设项目“农林经济管理国内一流学科建设”(批准号:GNYL[2017]002);国家社科基金项目“多重排斥与西部特困地区包容性发展机制生成研究”(批准号:18BGL222)。
摘    要:农业碳排放已经成为我国农业低碳、循环经济发展的掣肘,探究种植业碳生产率现状及其内生增长动力,以期为我国农业继续实现绿色低碳发展目标提供指引。基于2001—2017年我国大陆31省面板数据,测算了我国种植业碳生产率,并分析其动态演化过程;运用ESDA方法分析了种植业碳生产率的空间态势,进一步引入时空跃迁测度法分析其跃迁过程;借助SEM模型探究了种植业碳生产率的影响因素。结果表明:①2017年我国种植业碳生产率高达6.98万元/t,较之于2001年的2.58万元/t增长了170.54%,尽管其总体呈上升趋势,但区域差异依然存在。整体表现为:西部地区>东部地区>全国层面>中部地区;在研究后期,东部、中部地区的种植业碳生产率开始下降。②2001—2017年我国种植业碳生产率总体呈高-高、低-低集聚态势分布,且该趋势不断加强,表明存在较强的空间相关性。时空跃迁测度分析表明,我国种植业碳生产率跃迁类型主要为类型Ⅳ,类型Ⅲ分布最少,表明其总体稳态与局部极不稳态特征并存。③研究期内农业产业结构、农村受教育水平、农业经济发展水平、农村电力基础设施对提高种植业碳生产率有显著的促进作用;农业机械化水平与种植业碳生产率呈“U”型关系;农作物受灾程度和家庭农地经营规模则显著抑制了种植业碳生产率的上升。未来继续深化农业供给侧改革,促进农业经济高质量发展是提高碳生产率的关键。

关 键 词:种植业  碳排放  碳生产率  空间格局  空间计量

Spatial correlation pattern and influencing factors of China s crop production carbon productivity
WU Guo-yong,SUN Xiao-jun,YU Fu-bo,YANG Li-sha.Spatial correlation pattern and influencing factors of China s crop production carbon productivity[J].China Polulation.Resources and Environment,2020(5):46-57.
Authors:WU Guo-yong  SUN Xiao-jun  YU Fu-bo  YANG Li-sha
Institution:(School of Economics,Guizhou University,Guiyang Guizhou 550025,China;Institute of China Karst Region Rural Revitalization,Guizhou University,Guiyang Guizhou 550025,China;School of Economics and Management,Southwest University,Beibei Chongqing 400715,China)
Abstract:Agricultural carbon emissions have become a constraint to the development of low-carbon and circular economy in China’s agriculture.This paper explored the current status of carbon productivity in crop production and its endogenous growth momentum,in order to provide guidance for China s agriculture to achieve green and low carbon development goals.Based on the panel data of 31 provinces in China's Mainland from 2001 to 2017,this paper calculated the carbon productivity of China’s crop production and analyzed its dynamic evolution process.The ESDA method was used to analyze the spatial situation of carbon productivity in crop production,and space-time transition measurement was further introduced to analyze its transition process.At the same time,the SEM model was used to explore the factors affecting the carbon productivity of crop production.The results showed that:①China s crop production carbon productivity reached 69.8 thousand yuan per ton in 2017,which was 170.54%higher than that of 25.8 thousand yuan per ton in 2001.Although it showed an overall upward trend,regional differences still existed.Among them,the carbon productivity in the eastern region and western region was generally higher than the national average;the central region was significantly lower than the national average;the western region was higher than the eastern region as a whole.In the later stage of the study,carbon productivity began to decline in the eastern and central regions;②From 2001 to 2017,China s crop production carbon productivity generally showed a high-high,low-low agglomeration situation,and this trend continued to strengthen,indicating a strong spatial correlation.The analysis of space-time transition measurement showed that the type of carbon productivity transition in China s crop production was mainly type IV,and the type III distribution was the least,indicating that the overall steady state and local extreme unsteady characteristics coexisted;③During the research period,the structure of agricultural industry,the level of education in rural areas,the level of agricultural economic development and rural power infrastructure played a significant role in promoting the carbon productivity of crop production.There was a U-type relationship between the level of agricultural mechanization and the carbon productivity of crop production.The extent of crop damage and the scale of family farmland management significantly inhibited the rise of carbon productivity in crop production.In the future,continuing to deepen the agricultural supply-side structural reform to promote the high-quality development of agricultural economy is the key to improving carbon productivity in crop production.
Keywords:crop production  carbon emission  carbon productivity  spatial pattern  spatial econometrics
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