Inability to face unexpected expenses and monetary poverty in Poland: Are these two faces on the same coin?
DOI:
https://doi.org/10.24136/eq.3049Keywords:
financial distress, monetary poverty, household, Shapley-Owen decomposition, logit modelAbstract
Research background: The economic literature often states that monetary poverty does not coincide with other types of poverty. The paper examines monetary poverty and financial distress, which refer to distinct aspects of poverty. It addresses the issue by explaining how the same household characteristics affect these different types of poverty.
Purpose of the article: The paper aims to identify socioeconomic variables influencing financial distress and monetary poverty in Poland. In addition, the relative contribution of household-level variables in explaining McFadden’s R2 for the financial dimensions under consideration is assessed.
Methods: The study relies on data from the EU Statistics on Income and Living Conditions (EU-SILC) survey in 2022. Logistic regression analysis empirically tests the impact of socioeconomic variables on financial distress and income poverty. Moreover, the relative importance of regressors is determined using the Shapley-Owen decomposition analysis.
Findings & value added: The results have revealed that the smallest group consisted of only monetary poor households, followed by both monetary poor and financially distressed. The largest group was made up of households that experienced only financial distress. Such an incomplete overlap in experiencing the examined types of poverty implies the importance of studying financial distress alongside traditional income indicator. The study indicated a statistically significant role for characteristics such as disability, unemployment, education, the burden of the repayment of debts, household type, and tenure status in experiencing all the types of poverty considered. Furthermore, it was observed that the explanatory power of the models varied depending on the types of poverty under consideration. The results also revealed a substantial relative contribution of education to McFadden’s R2 in all models, indicating that education level substantially explains vulnerability to financial fragility. The contribution of other regressors varied among the models describing the types of poverty analyzed. These findings should stimulate policymakers, as effective policies are needed to alleviate different types of poverty.
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