多维深度贫困指数构建与分解

Construct and Decompose of Multidimensional Deep Poverty Index

文章将综合模糊集相对方法用于多维深度贫困识别与指标的权重系数确定,并引入贫困持续时间因素构建了一个具有维度和子群可分解性的多维深度贫困指数。该方法以贫困指标的分布函数为基础构造隶属函数,将多维一般性贫困测量A-F方法拓展到多维深度贫困测度。根据2015-2017年河南省深度贫困县入户调查数据,计算多维深度贫困指数并在不同区域和维度上进行分解,较为精确地测度了多维深度贫困的动态特征。

This paper applies the comprehensive fuzzy set relative approach to the determination on multidimensional deep poverty identification and weight coefficient, and also introduces the poverty duration factor to construct a multidimensional deep poverty index with dimension and subgroup decomposability. This method constructs subordinate functions based on the distribution function of poverty indicators, extending the A-F method of multidimensional general poverty measurement to multidimensional deep poverty measurement. According to the household survey data of deep poverty counties in Henan Province from 2015 to 2017, the paper calculates multidimensional deep poverty index and makes decomposition in different regions and dimensions,accurately measuring the dynamic characteristics of multidimensional deep poverty.