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传统DEA-Malmquist生产率指数的测量与分析都建立在精确的投入产出数据基础之上,缺乏对非精确数据的分析与应用研究。针对投入为确定性而产出为区间型数据的情形,构建了基于有效前沿面的区间DEA-Malmquist指数,探讨了区间Malmquist指数及其分解部分的性质,并提出了一种综合可能度所有位次重要性的区间数排序方法,将构建的理论应用于2006年至2009年间全国11个主要沿海省市工业行业的全要素生产率分析,结果表明:天津和海南的工业行业全要素生产率呈现增长态势,其余省市则落在降低与增长的区间内,其中技术效率对全要素生产率的贡献起主导作用的有海南,辽宁,河北,广西,山东,广东,福建7个省份,而技术进步对全要素生产率的贡献起主导作用的地区有浙江,天津,上海,江苏省的技术进步和技术效率的作用相当.
Traditional DEA-Malmquist productivity index measurement and analysis are based on accurate input-output data and lack of analysis and application of inaccurate data. For the case that the input is deterministic and the output is interval data, an interval DEA-Malmquist index based on effective frontiers is constructed, the properties of the interval Malmquist index and its decomposition parts are discussed, and a comprehensive probability all bit is proposed. The sub-important interval number ranking method applies the theory of construction to the analysis of total factor productivity of the industrial sectors in the 11 major coastal provinces and cities across the country from 2006 to 2009. The results show that the total factor productivity of the industrial sectors in Tianjin and Hainan is growing. Other provinces and cities fall within the range of reduction and growth. Among them, seven provinces of Hainan, Liaoning, Hebei, Guangxi, Shandong, Guangdong, and Fujian have a leading role in the contribution of technological efficiency to total factor productivity. The areas where the contribution of factor productivity plays a leading role include Zhejiang, Tianjin, Shanghai, and Jiangsu provinces. The technical progress and technical efficiency are quite similar.