Analysis of Poverty Through Educational Lag Using the Maximum Clique into the Complex

Abstract

AbstractIn this work, it is proposed to detect communities that share attributes in common, based on the attributes that quantify the indicator of deficiency due to educational lag, which is proposed by the National Council for the Evaluation of Social Development Policy (CONEVAL) in its multidimensional poverty analysis methodology in Mexico. The data obtained to carry out this work were recovered from the databases generated by the National Institute of Statistics and Geography (INEGI) from the National Survey of Household Income and Expenditure in 2018 (ENIGH-2018). The proposed methodology consists of 1) recovering the data of the indicator of lack due to educational lag, 2) a characterization was carried out on each of the variables by states of the Mexican Republic, 3) a complex network model was generated for the indicator of deficiency analysed, 4) the complex network was analysed using a genetic algorithm to detect the maximum click in the network, with this it was possible to detect communities made up of federative entities with similar attributes 5) the properties of the subgraph of statistical form. The objective of the proposed methodology aims to address the analysis of multidimensional poverty in Mexico from a complex network and optimization approach.KeywordsSocial networkCommunity analysisData analysis