交通扶贫效率测度可为乡村振兴阶段区域交通规划方案制定提供重要的理论依据。以滇西边境山区56个县域四年间交通与经济发展面板数据为样本，构建交通扶贫效率投入产出指标体系，运用DEA模型、Malmquist指数测度滇西边境山区各县交通扶贫效率，并分析其时空分布特征。同时，构建Tobit回归模型，探究县域交通扶贫效率的影响因素。研究表明：滇西边境山区县域交通扶贫效率整体呈逐步增长态势，在乡村振兴阶段仍然有较大提升空间，且交通扶贫综合效率主要受到规模效率的影响；滇西边境山区县域交通扶贫效率大幅提升；依据交通扶贫综合效率的平均值和Malmquist指数值两个维度，滇西边境山区56个县可划分为潜力型、发展型、成熟型及巩固型4种类型，而发展型和成熟型是滇西边境山区交通扶贫效率的主要形态；县域规模、产业结构对交通扶贫效率的提升具有反向抑制作用，就业支持、消费水平、区位优势、投资规模均在不同程度上对滇西边境山区交通扶贫效率产生正向促进作用；各影响因素对不同发展阶段的县域交通扶贫效率在影响强度和作用路径上存在差异。因此，应进一步优化县城交通基础设施空间布局，强化劳动力就业等因素与交通运输发展的“联动效应”，针对不同交通扶贫发展阶段及影响因素短板，采取差异化、合理化发展策略。

The study on the efficiency of transport-driven poverty alleviation can provide an important theoretical basis for the formulation of regional poverty alleviation-oriented transport policies in the stage of rural revitalization. Panel data of transportation and economic development in 56 counties in the border mountainous areas of western Yunnan from 2016-2019 are used as samples to construct a transport-driven poverty alleviation efficiency input-output index system. The DEA model and Malmquist index are used to measure the transport-driven poverty alleviation efficiency of counties， and analyze their spatial and temporal distribution characteristics. At the same time， Tobit regression model is constructed to explore the factors influencing the efficiency of county-level transport-driven poverty alleviation. The results show that： 1） The overall efficiency of transport-driven poverty alleviation in the mountainous counties along the border of western Yunnan shows a gradual growth. There is still large room for improvement in the stage of rural revitalization， and the comprehensive efficiency of transport-driven poverty alleviation is mainly influenced by the scale efficiency. 2） According to two dimensions of comprehensive efficiency average of transport-driven poverty alleviation and Malmquist index value， the 56 counties in western Yunnan can be divided into four types： potential， developmental， mature and consolidation types. The developmental and mature types are main types of efficiency for transport-driven poverty alleviation in the border mountainous areas of western Yunnan. 3） County size and industrial structure have a reverse inhibitory effect on the improvement of transport-driven poverty alleviation efficiency， while employment support， consumption level， location advantage， and investment scale all have a certain positive promoting effect on transport-driven poverty alleviation efficiency in the border mountainous areas of western Yunnan to different degrees. Each influencing factor shows differences in terms of its influence intensity and effect path on the county transport-driven poverty alleviation efficiency in different development stages. Therefore， we should further optimize the spatial layout of the county transportation infrastructure， attach importance to the development of digital and intelligent transportation， strengthen the “linkage effect” between labor employment and transportation development， and adopt differentiated and rational development strategies based on different development stages of transport-driven poverty alleviation and characteristics of influencing factors.