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Estimation of income distribution and detection of subpopulations: an explanatory model

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  • Emmanuel Flachaire

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Olivier Nunez

    (UC3M - Universidad Carlos III de Madrid [Madrid])

Abstract

Empirical evidence, obtained from nonparametric estimation of the income distribution, exhibits strong heterogeneity in most populations of interest. It is common, therefore, to suspect that the population is composed of several homogeneous subpopulations. Such an assumption leads us to consider mixed income distributions whose components feature the distributions of the incomes of a particular homogeneous subpopulation. A model with mixing probabilities that are allowed to vary with exogenous individual variables that characterize each subpopulation is developed. This model simultaneously provides a flexible estimation of the income distribution, a breakdown into several subpopulations and an explanation of income heterogeneity.

Suggested Citation

  • Emmanuel Flachaire & Olivier Nunez, 2007. "Estimation of income distribution and detection of subpopulations: an explanatory model," Post-Print halshs-00175923, HAL.
  • Handle: RePEc:hal:journl:halshs-00175923
    DOI: 10.1016/j.csda.2006.07.004
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00175923
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    2. Dorothée Boccanfuso & Bernard Decaluwé & Luc Savard, 2008. "Poverty, income distribution and CGE micro-simulation modeling: Does the functional form of distribution matter?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(2), pages 149-184, June.
    3. Ivana Malá, 2015. "Vícerozměrný pravděpodobnostní model rozdělení příjmů českých domácností [Multivariate Probability Model For Incomes of the Czech Households]," Politická ekonomie, Prague University of Economics and Business, vol. 2015(7), pages 895-908.
    4. Stéphane Guerrier & Samuel Orso & Maria-Pia Victoria-Feser, 2018. "Parametric Inference for Index Functionals," Econometrics, MDPI, vol. 6(2), pages 1-11, April.
    5. Ivana Malá, 2012. "The Use of Finite Mixtures of Lognormal Distribution for the Modelling of Income Distributions [Použití konečných směsí pro modelování příjmových rozdělení]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2012(4), pages 26-39.
    6. William E. Griffiths and Gholamreza Hajargasht, 2012. "GMM Estimation of Mixtures from Grouped Data:," Department of Economics - Working Papers Series 1148, The University of Melbourne.
    7. Nartikoev, Alan & Peresetsky, Anatoly, 2019. "Modeling the dynamics of income distribution in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 54, pages 105-125.
    8. Longford, N.T. & Pittau, M.G., 2006. "Stability of household income in European countries in the 1990s," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1364-1383, November.
    9. Nartikoev, Alan & Peresetsky, Anatoly, 2020. "Эндогенная Классификация Домохозяйств В Регионах России [Endogenous household classification: Russian regions]," MPRA Paper 104351, University Library of Munich, Germany.
    10. Ivana Malá, 2013. "Použití konečných směsí logaritmicko-normálních rozdělení pro modelování příjmů českých domácností [The Use of Finite Mixtures of Lognormal Distribution for the Modelling of Household Income Distri," Politická ekonomie, Prague University of Economics and Business, vol. 2013(3), pages 356-372.

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    income distribution; mixture models;

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