PL EN


2020 | 63 | 210-232
Article title

Gender differences in income distributions in Poland

Content
Title variants
PL
Różnice w rozkładach dochodów kobiet i mężczyzn w Polsce
Languages of publication
EN
Abstracts
The paper presents results of a descriptive analysis of income distributions as well as top income inequality among women and men in Poland. The analysis is based on the dataset provided by the Council for Social Monitoring (2019). Throughout 2003–2015 their panel survey included, for example, a question on individual net monthly income in the past three months. In order to reduce differences associated with the age of entering and exiting the labour market on declared income levels (especially pensions), the calculations include only women and men aged 25–60 years. The analysis of income distributions of women and men in Poland is based on standard measures such as mean income, median income and related measures, as well as the Gini coefficient, Theil index and entropy index. It is supplemented by kernel density estimates and results of simultaneous quantile regressions that demonstrate differences between women and men across income groups. The analysis of top income inequality includes comparisons of subsamples consisting of top 3% earners in each group. The share of women in the top percentiles is then calculated and discussed. The analysis shows different dynamics related to the incomes of women and men, which provides support for including business cycle considerations in the analysis of income inequalities and their gender aspects.
PL
W artykule przedstawiono wyniki analizy opisowej rozkładów dochodów kobiet i mężczyzn w Polsce ze szczególnym uwzględnieniem nierówności w grupie osób o najwyższych dochodach. Analizę oparto o bazę danych opracowaną przez Radę Monitoringu Społecznego (w ramach projektu Diagnoza Społeczna). W latach 2003–2015 jedno z pytań zadawanych respondentom dotyczyło indywidualnego miesięcznego dochodu netto z ostatnich trzech miesięcy. W celu zmniejszenia wpływu różnic związanych z momentem wchodzenia na rynek pracy i przechodzenia na emeryturę analizę ograniczono do osób w wieku 25–60 lat. W analizie rozkładów dochodów kobiet i mężczyzn w Polsce wykorzystano m.in. standardowe miary, takie jak średni dochód lub mediana dochodu oraz wskaźniki oparte na tych miarach, jak również współczynniki Giniego, Theila oraz entropii. Poza tym wykorzystano jądrowe estymatory gęstości i przedstawiono wyniki estymacji regresji kwantylowej pokazującej różnice dochodowe między kobietami i mężczyznami w różnych grupach dochodowych. Następnie dokonano porównania między podpróbami kobiet i mężczyzn uzyskujących najwyższe dochody (przyjęto próg 3% dla każdej płci). Przedstawiono również udział kobiet w grupie osób o najwyższych dochodach. Przeprowadzona analiza ujawniła m.in. zróżnicowanie dynamiki dochodów kobiet i mężczyzn, co stanowi argument za uwzględnieniem w analizie nierówności dochodowych także czynników cyklicznych, które mogą odmiennie oddziaływać na obie płci.
Year
Issue
63
Pages
210-232
Physical description
Contributors
  • Department of Economics University of Economics in Katowice
References
  • Atkinson, A. B., Casarico, A., Voitchovsky, S. (2018). Top incomes and the gender divide. The Journal of Economic Inequality, 16(2), 225–256. DOI: 10.1007/s10888-018-9384-z.
  • Bakker, A., Creedy, J. (2000). Macroeconomic variables and income distribution: Conditional modelling with the generalised exponential. Journal of Income Distribution, 9(2), 183–197. DOI: 10.1016/S0926-6437(00)00006-8.
  • Barlevy, G., Tsiddon, D. (2006). Earnings inequality and the business cycle. European Economic Review, 50(1), 55–89. DOI: 10.1016/j.euroecorev.2004.08.001.
  • Bertrand, M., Kamenica, E., Pan, J. (2015). Gender Identity and Relative Income within Households. The Quarterly Journal of Economics, 130(2), 571–614. DOI: 10.1093/qje/qjv001.
  • Black, S. E., Brainerd, E. (2004). Importing Equality? The Impact of Globalization on Gender Discrimination. Industrial and Labor Relations Review, 57(4), 540–559. DOI: 10.3386/w9110.
  • Bobilev, R., Boschini, A., Roine, J. (2020). Women in the Top of the Income Distribution: What Can We Learn From LIS-Data? Italian Economic Journal, 6, 63–107. DOI:10.1007/s40797-019-00108-w.
  • Bonhomme, S. Hospido, L. (2017). The Cycle of Earnings Inequality: Evidence from Spanish Social Security Data. The Economic Journal, 127(603), 1244–1278. DOI:10.1111/ecoj.12368.
  • Boschini, A., Gunnarsson, K., Roine, J. (2017). Women in top incomes: evidence from Sweden 1974–2013. Working Paper No. 10979. Bonn: Institute of Labor Economics.
  • Costa, M. (2019). The evaluation of gender income inequality by means of the Gini index decomposition. Working Paper DSE No.1130. Quaderni, Bologna: University of Bologna.
  • Council for Social Monitoring (2019). Integrated database. Retrieved from: http://www. diagnoza.com/ (2019.7.2).
  • Czapiński, J. (2015). Indywidualna jakość i styl życia. Contemporary Economics, 9(4), 200–331. DOI: 10.5709/ce.1897-9254.190.
  • Fiaschi, D., Marsili, M. (2012). Distribution of wealth and incomplete markets: Theory and empirical evidence. Journal of Economic Behavior & Organization, 81(1),243–267. DOI: 10.1016/j.jebo.2011.10.015.
  • Fritzell, J. (1999). Incorporating Gender Inequality into Income Distribution Research. International Journal of Social Welfare, 8, 56–66. DOI: 10.1111/1468-2397.00062.
  • Goldin, C. (2014). A Grand Gender Convergence: Its Last Chapter. American Economic Review, 104(4), 1091–1119. DOI: 10.1257/aer.104.4.1091.
  • Goraus, K., Tyrowicz, J., van der Velde, L. (2017). Which Gender Wage Gap Estimates to Trust? A Comparative Analysis. Review of Income and Wealth, 63, 118–146. DOI: 10.1111/roiw.12209.
  • Gregory, M. (2009). Gender and Economic Inequality. In: W. Salverda, B. Nolan, T. M. Smeeding (Eds.), The Oxford Handbook of Economic Inequality (pp. 284–312). Oxford – New York: Oxford University Press.
  • Hederos Eriksson, K., Stenberg, A. (2015). Gender Identity and Relative Income within Households: Evidence from Sweden. IZA Discussion Paper No. 9533. Bonn: The Institute for the Study of Labor (IZA).
  • Heinz, M., Normann, H.-T., Rau, H. A. (2016). How competitiveness may cause a gender wage gap: Experimental evidence. European Economic Review, 90, 336–349. DOI:10.1016/j.euroecorev.2016.02.011.
  • Hoover, G. A., Giedeman, D. C., Dibooglu, S. (2009). Income inequality and the business cycle: A threshold cointegration approach. Economic Systems, 33(3), 278–292. DOI:10.1016/j.ecosys.2009.04.002.
  • Jagielski, M., Kutner, R. (2013). Modelling of income distribution in the European Union with the Fokker–Planck equation. Physica A, 392, 2130–2138. DOI: 10.1016/j.physa.2013.01.028.
  • Kandil, M., Woods, J. G. (2002). Convergence of the gender gap over the business cycle: a sectoral investigation. Journal of Economics and Business, 54(3), 271–292. DOI:10.1016/S0148-6195(02)00061-9.
  • Lantican, C. P., Gladwin, C. H., Seale, Jr., J. L. (1996). Income and gender inequalities in Asia: Testing alternative theories of development. Economic Development and Cultural Change, 44(2), 235–263. DOI: 10.1086/452212.
  • Litchfield, J.A. (1999). Inequality: Method and Tools. Washington D.C: The World Bank. Retrieved from: http://www.worldbank.org/poverty/inequal/index.htm (2019.09.17).
  • O’Neill, J. (1985). The Trend in the Male-Female Wage Gap in the United States. Journal of Labor Economics, 3(1), S91–S116.
  • Panek, T., Czapiński, J. (2015). Wykluczenie społeczne. Contemporary Economics, 9(4), 396–432. DOI: 10.5709/ce.1897-9254.193.
  • Périvier, H. (2018). Recession, austerity and gender: A comparison of eight European labour markets. International Labour Review, 157(1), 1–37. DOI: 10.1111/ ilr.12032.
  • Piketty, T., Saez, E., Zucman, G. (2018). Distributional national accounts: methods and estimates for the United States, 1913–2013. The Quarterly Journal of Economics, 133(2), 553–609. DOI: 10.1093/qje/qjx043.
  • Ravaska, T. (2018). Top incomes and income dynamics from a gender perspective: evidence from Finland 1995–2012. ECINEQ WP Society for the Study of Economy Inequality, 469, 2–47.
  • Razzu, G., Singleton, C. (2016). Gender and the business cycle: An analysis of labour markets in the US and UK. Journal of Macroeconomics, 47 (Part B), 131–146. DOI:10.1016/j.jmacro.2015.12.006.
  • Shaikh, A., Papanikolaou, N., Wiener, N. (2014). Race, gender and the econophysics of income distribution in the USA. Physica A, 415, 54–60. DOI: 10.1016/ j.physa.2014.07.043/.
  • Włodarczyk, J. (2013). Nierówności dochodowe w Polsce według rozkładów Pareto i Boltzmanna-Gibbsa. Studia Ekonomiczne, 130, 76–87.
  • Yakovenko, V. M., Rosser, J. B. (2009). Colloquium: Statistical mechanics of money, wealth, and income. Reviews of Modern Physics, 81(4), 1703–1725. DOI: 10.1103/RevModPhys.81.1703.
  • Yavorsky, J. E., Keister, L. A., Qian, Y., Nau, M. (2019). Women in the One Percent: Gender Dynamics in Top Income Positions. American Sociological Review, 84(1), 54–81. DOI: 10.1177/0003122418820702.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-037e8b15-f9ba-4826-a4a1-ef0bd5d55bd3
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