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

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  • Núñez, Olivier
  • Flachaire, Emmanuel

Abstract

Inequality and polarization analyses are complementary but conceptually different. They are usually implemented independently in practic e, with different a priori assumptions and different tools. In this paper, we develop a unique method to study simultaneously these different and complementary concerns. Based on mixture models, the method we develop includes at the same time : an estimation of income distribution with no a priori assumptions - a decomposition in several homogeneous subpopulations - an explanatory model to study the structure of the income distribution. Length: 20 pages

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  • Núñez, Olivier & Flachaire, Emmanuel, 2003. "Estimation of income distribution and detection of subpopulations: an explanatory model," DES - Working Papers. Statistics and Econometrics. WS ws030201, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:ws030201
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    Cited by:

    1. 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.
    2. Edwin Fourrier-Nicolaï & Michel Lubrano, 2020. "Bayesian inference for TIP curves: an application to child poverty in Germany," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 91-111, March.
    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. 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.
    5. 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.
    6. Stéphane Guerrier & Samuel Orso & Maria-Pia Victoria-Feser, 2018. "Parametric Inference for Index Functionals," Econometrics, MDPI, Open Access Journal, vol. 6(2), pages 1-11, April.
    7. 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.
    8. 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.
    9. 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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