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长江经济带物流业效率测度及因素分解
引用本文:张泽华,刘维琦.长江经济带物流业效率测度及因素分解[J].西部经济管理论坛,2022,33(4):48-56, 80.
作者姓名:张泽华  刘维琦
作者单位:重庆邮电大学经济管理学院 重庆 400000
摘    要:文章采用超效率DEA模型和Malmquist指数分别从静态、动态视角对2010—2019年长江经济带11个省市的物流产业效率进行实证研究,最后利用Tobit模型分析物流产业效率的影响因素及影响程度。研究结果表明:从静态分析结果看,长江经济带2010—2019年物流产业效率整体达到有效水平,但呈现波动上升后下降的态势,并在空间区域呈现“下游>中游>上游”的阶梯状分布;从动态分析结果看,技术进步的下降是导致长江经济带全要素生产率下降的主要因素;从影响因素分析结果看,政府支持对物流产业效率提升具有制约作用,地区发展水平、对外开放程度、信息化水平对长江经济带物流产业效率提升均具有显著的推动作用。

关 键 词:物流效率    长江经济带    超效率DEA模型    Malmquist指数    Tobit模型
收稿时间:2022-01-22

Efficiency Measurement and Factor Decomposition of Logistics Industry in the Yangtze River Economic Belt: Based on super-efficiency DeA-Malmquist-Tobit Method
Authors:Zhang Zehua  Liu Weiqi
Institution:School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, 400000, China
Abstract:This paper uses the super-efficiency DEA model and Malmquist index to make an empirical study on the logistics industry efficiency of 11 provinces and cities in the Yangtze River Economic Belt from the static and dynamic perspectives respectively. The Tobit model is used to analyze the influencing factors and degree of logistics industry efficiency. The results show that from the static analysis results, the efficiency of logistics industry in the Yangtze River Economic Belt has reached an effective level in 2010-2019 as a whole, but it shows a trend of fluctuation rising and then falling, and presents a step-like distribution of “downstream > midstream > upstream” in the spatial region; From the results of dynamic analysis, the decline of technological progress is the main factor leading to the decline of total factor productivity in the Yangtze River Economic Belt; From the analysis results of influencing factors, the government support has a restrictive effect on the efficiency improvement of logistics industry, and the regional development level, opening-up degree and informatization level have a significant role in promoting the efficiency improvement of logistics industry in the Yangtze River Economic Belt.
Keywords:
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