Identification of relevant factors and assessment of their impact on various forms of poverty and social exclusion of slovak households by means of logistic regression

Erik Šoltés, Faculty of Economic Informatics, University of Economics in Bratislava, Slovak Republic

Pages: 3 – 22

Abstract

The article is based on a 3-dimensional concept of poverty and social exclusion used in the Europe 2020 strategy in connection to monitoring progress in the area of social inclusion and poverty reduction. The paper analyzes 5 logistic regression models that model various forms of poverty and social exclusion characterized by aggregating sub-indicators into the headline indicator – AROPE (at-risk-of-poverty-or-socialexclusion rate). The presented analyzes identify factors that affect the threat that a household will have to face the risk of poverty or social exclusion at least in 1 dimension and in all the 3 dimensions simultaneously as well as factors that have an impact on individual dimensions – risk of income poverty, severe material deprivation and very low work intensity. The estimated models allowed us to quantify the impact of relevant factors (through odds ratios) on mentioned forms of poverty and social exclusion and to predict probabilities of occurrence of these forms within individual groups of Slovak households. Statistical analyses were carried out in the analytics software SAS Enterprise Guide based on data from the survey EU-SILC 2016.

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