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has been cited by the following article:

• TITLE: Using Multiple Correspondence Analysis to Measure Multidimensional Poverty in Congo

  AUTHORS: Samuel Ambapour

  KEYWORDS: Multiple Correspondence Analysis, Basic Needs, Composite Indicator of Multidimensional Poverty

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.8 No.4, October 12, 2020

  ABSTRACT: The following analysis is based on a multidimensional understanding of poverty using a nonmonetary basic needs approach. It is ground on data from the first survey on household living conditions for poverty assessment, conducted by the National Institute of Statistics of Congo in 2005. Multiple Correspondence Analysis is applied to construct a composite indicator by aggregating several attributes likely to reflect the poverty of individuals or households. The application shows that Congolese households are not affected by the same type of poverty. Three types of non-monetary poverty are identified: infrastructure poverty, vulnerability of human existence and poverty of comfort. These households were then classified according to the composite indicator of Poverty. The results show that the incidence of poverty corresponds to the weight of poor class of about 70.67%.