2013 | 11(17) | 179-200
Article title

Rekonstrukcja światowego rozkładu dochodów na podstawie minimalnej informacji statystycznej

Title variants
Reconstruction of world income distribution based on minimal statistical information
Languages of publication
The aim of this paper is to obtain a sample from the world income distribution (WID). We assumed log-logistic form of countries’ income distributions with unit means. This implies that such distributions are fully described by their corresponding Gini indices. Gini estimates came from Deninger-Squire, WID2, and other databases for 119 countries in the years 1990-2005. We generated random sample for every distribution and multiplied its values by GDP/capita. Sample size was controlled by sequential ratio test. The world sample consisted of country samples weighted by population shares. We have found that WID is bimodal with diminishing inequality and poverty during analyzed period.
Physical description
  • Politechnika Gdańska
  • Politechnika Gdańska
  • Atkinson A.B., Brandolini A., Promise and pitfalls in the use of ‘secondary’ data-sets: income inequality in OECD Countries, “Journal of Economic Literature” 2001, 39, s. 771-99.
  • Deninger K., Squire L., A new data set measuring income inequality, “The World Bank Economic Review” 1996, 10, s. 565-591.
  • DS World Bank database, Fisk P.R., The graduation of income distributions, “Econometrica” 1961, 29, s. 171-185.
  • Fisz M., Rachunek prawdopodobieństwa i statystyka matematyczna, PWN, Warszawa 1969.
  • Foster J.E., Greer J., Thorbecke E., A class of decomposable poverty indices, "Econometrica” 1984, 52, s. 761-766.
  • Kendall M.G., Stuart A., The advanced theory of statistics, Vol. 2, Griffin & Co. Ltd., London 1961.
  • Kleiber Ch., Kotz S., Statistical Size Distributions in Economics and Actuarial Sciences, Wiley and Sons Publications, New Jersey 2003.
  • McDonald J.B., Some generalized functions for the size distribution of income, ”Econometrica” 1984, 52, s. 647-663.
  • McDonald J.B., Xu Y.J., A generalization of the beta distribution with applications, “Journal of Econometrics” 1995, 66, s. 133-152: erratum: “Journal of Econometrics” 1995, 69, s. 427-428.
  • Pinkovskiy M., Sala-i-Martin X., Parametric estimations of the Word distribution of income, “NBER Working Paper” 2009, No. 15433.
  • Ravallion M., The debate on globalization, poverty and inequality: Why measurement matters, “Policy Research Working Papers”, WPS3031, The World Bank, May 2003.
  • Sala-i-Martin X., The world distribution of income: Falling poverty and… convergence, period, “Quarterly Journal of Economics” 2006, 121(2), s. 351-397.
  • Shorrocks A., Wan G., Ungrouping income distributions: Synthesising samples for inequality and poverty analysis, [w:] K. Basu, R. Kanbur (red.), Arguments for a Better World: Essays in Honor of Amartya Sen, Vol. I: Ethics, Welfare and Measurement, Oxford University Press, Oxford, 2009, s. 414-434.
  • Van Kerm P., Extreme incomes and the estimation of poverty and inequality indicators from EU-SILC, “IRISS Working Paper” 2007-01, CEPS/INSTEAD, Differdange, Luxembourg 2007.
  • WIID2 World income inequality database, UNU-WIDER, Helsinki, May 2005.
  • World Development Indicators, World Bank, Washington 2012.
  • Yitzhaki S., Gini’s mean difference: A superior measure of variability for non-normal distributions, “METRON − International Journal of Statistics” 2003, 41(2), s. 285-316.
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Publication order reference
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