Child Poverty in Rural China: Multidimensional Perspective

Abstract

This paper describes a pilot study on child multidimensional poverty in rural China by introducing the Alkire-Foster method based on survey data collected from five provinces/autonomous regions. Results showed that the headcount ratio of child multidimensional poverty was 14.29%. On average, multidimensionally poor children were deprived in 37.62% of all the dimensions, and their adjusted headcount ratio (multidimensional poverty) index was 0.054. Health was the most deprived dimension, followed by the subsistence and participation dimensions. Disabled children, children influenced by HIV/AIDS, and ethnic minority children were severely deprived. This study not only adds to the current literature on child poverty in China, but also provides policy suggestions for future action plans.

Multidimensional poverty measure and analysis: a case study from Hechi City, China

“…In regards to the weight of these dimensions in A–F method, considering that the policy-related criterion that each aspect of households’ living conditions should be synchronously improved to keep the same pace with building national moderately prosperous society of China, as well as that the equal weighting method is also a commonly adopted scheme in international MPI (Wang et al 2015 ), this paper assigned equal weight to all four dimensions as well as the indicators within each dimension. To be specified, each dimension has the same weight value of 1/4, and each indicator within each dimension shares the same weights of the dimension.…”

“…Wang et al ( 2013 ) conducted the village-level case study of multidimensional poverty. Multidimensional child poverty index and its dynamic changes in China were also studied by Qi and Wu ( 2015 ), and Wang et al ( 2015 ). Maasoumi and Xu ( 2015 ) combined multidimensional welfare analysis and entropy metrics to derive not only the best relative weights but also substitution degree among different attributes to construct multidimensional indices of well-being with CHIPS 2002 data.…”

“…On the other hand, according to some authors (UNDP 1997 ; Wang et al 2013 ; Wang et al 2015 ), these weights of the indicators should be equal while the composite welfare index is an average of the responses to the different variables. On the other hand, some others suggested that the weights allocated to the indicators must vary as a function of their contribution to welfare, and they developed such methodologies to response to this view, e.g., entropy approach (Maasoumi 1999 ), multiple correspondence analysis (Ningaye and Njong 2015 ), fuzzy set approach (Cheli and Lemmi 1995 ; Njong and Baye 2010 ; Betti et al 2015 ), and so on.…”

“…Alkire and Foster ( 2011 ) attempted to offer a practical A–F approach as the methodology of measurement and analysis multidimensional poverty, identifying people as poor depending upon achievements of household members. A–F measure with desirable axiomatic properties could reflect the breadth, intensity and components of deprivations and improve the counting-based headcount measures of multidimensional poverty, presenting indicators of multiple dimensions with a single summary index that can be broken down among the dimensions and different groups (Alkire and Roche 2011 ; Wang et al 2015 ). It has also been widely applied to the investigations of the multidimensional poverty status in India, China and Latin American countries (Alkire and Seth 2013 ; Yu 2013 ; Battiston et al 2013 ).…”

“…It has also been widely applied to the investigations of the multidimensional poverty status in India, China and Latin American countries (Alkire and Seth 2013 ; Yu 2013 ; Battiston et al 2013 ). In regards to the weight of these dimensions, most of the indexes apply equal weights implicitly or explicitly (Alkire and Roche 2011 ; Wang et al 2013 ; Qi and Wu 2015 ; Wang et al 2015 ). To simplify interpretation, Alkire and Roche ( 2011 ) argued that equal weight was plausible and commonly adopted.…”