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作 者:张瑞[1] 孙夏令 ZHANG Rui;SUN Xia-ling(School of Management,China University of Mining and Technology,Beijing 100083,China)
机构地区:[1]中国矿业大学(北京)管理学院,北京100083
出 处:《商业研究》2020年第3期29-38,共10页Commercial Research
基 金:山西省科技重大专项课题,项目编号:20181102017;国家自然科学基金面上项目,项目编号:71774161;中国矿业大学(北京)越崎青年学者资助项目,项目编号:800015Z1121。
摘 要:本文运用包含非期望产出的SBM—ML模型对全国30省2004—2016年的物流业绿色全要素生产率进行测度,通过核密度估计和马尔科夫链探讨其时空演进特征,并借助空间面板计量模型分析物流业绿色全要素生产率的影响因素和空间溢出效应。结果表明:物流业绿色全要素生产率具有显著的动态演进规律,省域间物流发展协调度有待提高;物流业绿色全要素生产率存在显著的正空间自相关特征,表现为生产率较高的省份趋于相邻,生产率较低的省份趋于相邻;物流业绿色全要素生产率的主要驱动因素包括交通网络密度、物流能源强度、交通运输强度和人均GDP,各影响因素具有显著的空间溢出效应,其中市场化进程的正向溢出效应最高,对外开放程度和地区产业结构的溢出效应为负。In this paper,SBM-ML model including unexpected output is used to measure the green total factor productivity of logistics industry in 30 provinces of China from 2004 to 2016.By using kernel density estimation and Markov chain,this paper discusses its spatial and temporal evolution characteristics,and analyzes the influence factors and spatial spillover effects of green total factor productivity of logistics industry with the help of spatial panel econometric model.The results show that the green total factor productivity of logistics industry has a significant dynamic evolution law,and the coordination degree of logistics development among provinces needs to be improved;there is a significant positive spatial autocorrelation in green TFP of logistics industry,which shows that provinces with higher productivity tend to be adjacent,while provinces with lower productivity tend to be adjacent;the main driving factors of green total factor productivity of logistics industry include traffic network density,logistics energy intensity,traffic intensity and per capita GDP,and each influence factor has significant spatial spillover effect,among which the market-oriented process has the highest positive spillover effect,while the degree of opening to the outside world and regional industrial structure have negative spillover effect.
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