Abstract
This paper examines the evolution of income affluence (richness) in Poland during 1998–2007. Using household survey data, the paper estimates several statistical indices of income affluence including income share of the top percentiles, population share of individuals receiving incomes higher than the richness line, and measures that take into account both the extent and the intensity of affluence. Results show that over the period under study there was a statistically significant and socio-economically sizable rise in income affluence by between 9 and 50%, depending on the index used. The overall income distribution in the period has shifted in favour of the rich as relative poverty and relative size and income share of the middle class have declined.
Similar content being viewed by others
Notes
Long run high-quality estimates of the income shares of the top p% of the population have been produced for at least fourteen developed countries and at least four developing economies (Atkinson and Piketty 2007; Leigh 2009). An almost exhaustive reference list of recent papers devoted to the empirical measurement of top incomes can be found in Leigh (2009). These papers usually rely on incomes reported for tax purposes, but the number of studies based on household survey data grows as well.
In this paper terms richness and affluence are used interchangeably. They are used in a neutral sense to denote ‘top incomes’ in the population.
The group included also Estonia, Greece, Lithuania, Latvia, Hungary, Ireland, Italy, Portugal, Spain, and the United Kingdom.
This is the longest period for which the consistent data series can be constructed.
An early contribution to the first strand of this literature was offered by Drewnowski (1978).
This reasoning assumes, of course, that these transfers would be efficient (i.e., there would be no leakage in the transfer or the process would not impede economic growth).
This measure bears resemblance to the well-known poverty headcount ratio, which is defined s a proportion of the population with incomes below the poverty line.
Peichl et al. (2008) present five arguments in favour of the axiom T1, but such arguments are much less persuasive in the debate on measuring richness than analogous ones put forward in the poverty measurement debate.
However, incomes reported for tax purposes may also fail to reflect real incomes accurately because of tax evasion or tax avoidance.
Kordos et al. (2002) provide detailed description of HBS.
As shown by Howes and Lanjouw (1998), ignoring the sample design leads to calculated standard errors of poverty indices, which can be smaller by as much as a third than the correctly calculated standard errors.
A detailed exposition of the bootstrap approach is given by Efron and Tibshirani (1993).
Poland joined the European Union on 1 May 2004.
Affluence indices were calculated using a modified version of user-written STATA module richness (Peichl and Schaefer 2006).
These definitions of the size of the ‘middle class’ were used, among others, by Wolfson (1994).
References
Atkinson, A., & Piketty, T. (Eds.). (2007). Top incomes over the twentieth century. Oxford: Oxford University Press.
Chakravarty, S. R. (1983). A new index of poverty. Mathematical Social Sciences, 6, 307–313.
Chakravarty, S., & Muliere, P. (2004). Welfare indicators: A review and new perspectives. Metron—International Journal of Statistics, 62, 247–281.
Drewnowski, J. (1978). The affluence line. Social Indicators Research, 5, 263–278.
Efron, B., & Tibshirani, R. J. (1993). An introduction to bootstrap. New York: Chapman and Hall.
Esteban, J., & Ray, D. (2008). Polarization, fractionalization and conflict. Journal of Peace Research, 45, 163–182.
Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52, 761–766.
Foster, J. E., & Shorrocks, A. F. (1991). Subgroup consistent poverty indices. Econometrica, 59, 687–709.
Frank, R. (2007). Falling behind: How rising inequality harms the middle class. Berkeley: University of California Press.
Gutierrez, R. G. (2008). Analyzing survey data using Stata 10. Summer North American Stata Users’ Group Meetings 2008 18, Stata Users Group.
Heynes, B. (2005). Emerging inequalities in Central and Eastern Europe. Annual Review of Sociology, 31, 163–197.
Howes, S., & Lanjouw, J. (1998). Does sample design matter for poverty rate comparisons? Review of Income and Wealth, 44, 99–109.
Keane, M. P., & Prasad, E. S. (2002). Inequality, transfers, and growth: New evidence from the economic transition in Poland. The Review of Economics and Statistics, 84, 324–341.
Kolenikov, S. (2008). Survey bootstrap and bootstrap weights. Summer North American Stata Users’ Group Meetings 2008 19, Stata Users Group.
Kordos, J., Lednicki, B., & Zyra, M. (2002). The household sample surveys in Poland. Statistics in Transition, 5, 555–589.
Leigh, A. (2009). Top incomes. In W. Salverda, B. Nolan & T. Smeeding (Eds.), The Oxford handbook of economic inequality. Oxford: Oxford University Press (in press).
Medeiros, M. (2006). The rich and the poor: The construction of an affluence line from the poverty line. Social Indicators Research, 78, 1–18.
Mitra, P., & Yemtsov, R. (2006). Increasing inequality in transition economies: Is there more to come?, Policy Research Working Paper Series 4007, The World Bank.
Moore, J. C., Stinson, L. L., & Welniak, E. J., Jr. (2000). Income measurement error in surveys: A review. Journal of Official Statistics, 16, 331–361.
Moran, T. P. (2006). Statistical inference for measures of inequality with a cross-national bootstrap application. Sociological Methods & Research, 34, 296–333.
Peichl, A., & Schaefer, T. (2006). RICHNESS: Stata module to compute measures of income richness. Statistical Software Components S456778. Boston College Department of Economics.
Peichl, A., Schaefer, T., & Scheicher, C. (2006). Measuring richness and poverty—A micro data application to Germany and the EU-15. CPE Discussion Papers No. 06-11. University of Cologne.
Peichl, A., Schaefer, T., & Scheicher, C. (2008). Measuring richness and poverty—A micro data application to Europe and Germany. IZA Discussion Papers No. 3790. Institute for the Study of Labor (IZA).
Piketty, T. (2001). Les hauts revenus en France au 20 ème siècle. Paris: Grasset.
Rao, J. N. K., & Wu, C. F. J. (1988). Resampling inference with complex survey data. Journal of the American Statistical Association, 83, 231–241.
Rao, J. N. K., Wu, C. F. J., & Yue, K. (1992). Some recent work on resampling methods for complex surveys. Survey Methodology, 18, 209–217.
Szulc, A. (2000). Economic transition, poverty and inequality: Poland in the 1990s. Statistics in Transition, 4, 997–1017.
Szulc, A. (2006). Poverty in Poland during the 1990s: Are the results robust? Review of Income and Wealth, 52, 423–448.
Szulc, A. (2008). Checking the consistency of poverty in Poland: 1997–2003 evidence. Post-Communist Economies, 20, 33–55.
Wolfson, M. (1994). When inequalities diverge. The American Economic Review, 84, 353–358.
World Bank. (2000). Making transition work for everyone: Poverty and inequality in Europe and Central Asia. Washington, DC: World Bank.
World Bank. (2005). Growth, poverty, and inequality: Eastern Europe and the Former Soviet Union. Washington, DC: World Bank.
Zheng, B. (1997). Aggregate poverty measures. Journal of Economic Surveys, 11, 123–162.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Brzezinski, M. Income Affluence in Poland. Soc Indic Res 99, 285–299 (2010). https://doi.org/10.1007/s11205-010-9580-0
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11205-010-9580-0