Elements of household income and income inequality in selected EU countries

Joanna Maria Kozak; Aldona Mrówczyńska-Kamińska; Andrzej Wołoszyn

Authors

Joanna Maria Kozak ✉️ Department of Economics and Economic Policy in Agribusiness, Faculty of Economics, Poznań University of Life Sciences
joanna.kozak@up.poznan.pl https://orcid.org/0000-0002-0500-2406
Aldona Mrówczyńska-Kamińska Department of Economics and Economic Policy in Agribusiness, Faculty of Economics, Poznań University of Life Sciences https://orcid.org/0000-0001-5439-7339
Andrzej Wołoszyn Department of Finance and Accounting, Faculty of Economics, Poznań University of Life Sciences https://orcid.org/0000-0001-8992-7379

Keywords:

Gini coefficient decomposition, income inequality, Gini coefficient semi-elasticity, pseudo-Gini index, total household gross income

Abstract

Aim: The aim of this study was to identify the most influential factors impacting the level and dynamics of general income inequalities in Poland, Denmark, Germany, Spain and Romania in the period 2007–2019.

Methodology: The study was based on unpublished individual data from the European Survey of Income and Living Conditions carried out by the European Commission. The research was conducted using the procedure of decomposing the Gini coefficient to the general assessment of inequalities as per income source.

Results: The study enabled the conclusion that the biggest inequalities in household gross income were present in Romania, and the smallest in Denmark. In Romania and Poland income inequalities are slowly but continuously rising, whilst in Denmark, Spain and Germany, they are in decline. The gross income in the analysed EU households was based on three main elements, namely paid employment, self-employment and pensions, which constituted 86-96% of household financial resources. The diversity of inequality was predominantly influenced by the income from paid employment, interests, dividends and profit from capital investments in unincorporated businesses, self-employment as well as old-age benefits; such benefits showed an equalising effect on income inequalities.

Implications and recommendations: Analyses carried out on the basis of microdata can contribute to the formulation of policies, the targeting of interventions, and the monitoring and measurement of the impact of ongoing interventions and policies on the situation of households.

Originality/value: This study contributes to the literature on income inequality by providing a comparative analysis of five European countries, By utilizing unpublished microdata from the European Survey of Income and Living Conditions (EU-SILC), this research offers a novel approach to identifying the distinct contributions of employment income, self-employment, capital income, and pensions to inequality levels. The study's cross-country comparison covering the period 2007-2019 also provides valuable insights into the heterogeneous impacts of socioeconomic policies across both Western and Eastern European countries. This original dataset and analytical approach support the development of more effective, evidence-based public policies aimed at reducing income disparities.

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