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Estimation of Income Inequality and the Poverty Rate in Poland, by Region and Family Type

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  • Alina Jędrzejczak

  • Jan Kubacki

Abstract

High income inequality can be a source of serious socio-economic problems, such as increasing poverty, social stratification and polarization. Periods of pronounced economic growth or recession may impact different groups of earners differently. Growth may not be shared equally and economic crises may further widen gaps between the wealthiest and poorest sectors. Poverty affects all ages but children are disproportionately affected by it. The reliable inequality and poverty analysis of both total population of households and subpopulations by various family types can be a helpful piece of information for economists and social policy makers. The main objective of the paper was to present some income inequality and poverty estimates with the application to the Polish data coming from the Household Budget Survey. Besides direct estimation methods, the model based approach was taken into regard. Standard errors of estimates were also considered in the paper.

Suggested Citation

  • Alina Jędrzejczak & Jan Kubacki, 2013. "Estimation of Income Inequality and the Poverty Rate in Poland, by Region and Family Type," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(3), pages 359-378, September.
    • Handle: RePEc:csb:stintr:v:14:y:2013:i:3:p:359-378
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    References listed on IDEAS

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    1. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    2. Matti Langel & Yves Tillé, 2013. "Variance estimation of the Gini index: revisiting a result several times published," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 521-540, February.
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    Cited by:

    1. Alina Jędrzejczak, 2014. "Income Inequality and Income Stratification in Poland," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 269-282, March.
    2. Isabel Molina & Paul Corral & Minh Nguyen, 2022. "Estimation of poverty and inequality in small areas: review and discussion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1143-1166, December.
    3. Francesca Battisti & Francesco Porro, 2023. "A multi-decomposition of Zenga-84 inequality index: an application to the disparity in CO $$_2$$ 2 emissions in European countries," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 957-981, September.
    4. Alina Jędrzejczak & Dorota Pekasiewicz, 2020. "Changes in Income Distribution for Different Family Types in Poland," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(2), pages 135-146, May.
    5. Francesco Porro & Michele Zenga, 2020. "Decomposition by subpopulations of the Zenga-84 inequality curve and the related index $$\zeta $$ζ: an application to 2014 Bank of Italy survey," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 187-207, March.

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