Title: DETERMINING POVERTY FACTORS USING LOGIT MODELS
Authors:
Dimitrios Theodoridis and Stefanos G. Giakoumatos
Abstract:
This study examines the factors of poverty across six European countries—three in Southern Europe (Greece, Spain, Portugal) and three in Central/Northern Europe (Germany, the Netherlands, Belgium)—using 2023 cross-sectional data from the EU Statistics on Income and Living Conditions (EU-SILC). Focusing on individuals aged 30 to 65, the analysis applies logistic regression to assess the impact of nine socioeconomic variables on the probability of living below the poverty line. The findings reveal that four factors—ability to afford a holiday, ability to cover unexpected expenses, access to a car, and participation in leisure activities—are statistically significant predictors of poverty in all countries examined. Notable differences are observed in the significance and magnitude of other variables, such as education level and social activity, highlighting the influence of national socioeconomic contexts. The results underscore the value of targeted, evidence-based social policies that address both shared and country-specific drivers of poverty.
Keywords: Poverty, Income, Economic Factorss, Logistic Regression, EU Silc.
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