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Modeling the Joint Distribution of Income and Wealth

In: Measurement of Poverty, Deprivation, and Economic Mobility

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  • Markus Jäntti
  • Eva M. Sierminska
  • Philippe Van Kerm

Abstract

Abstract This paper considers a parametric model for the joint distribution of income and wealth. The model is used to analyze income and wealth inequality in five OECD countries using comparable household-level survey data. We focus on the dependence parameter between the two variables and study whether accounting for wealth and income jointly reveals a different pattern of social inequality than the traditional “income only” approach. We find that cross-country variations in the dependence parameter effectively account only for a small fraction of cross-country differences in a bivariate measure of inequality. The index appears primarily driven by differences in inequality in the wealth distribution.

Suggested Citation

  • Markus Jäntti & Eva M. Sierminska & Philippe Van Kerm, 2015. "Modeling the Joint Distribution of Income and Wealth," Research on Economic Inequality,in: Measurement of Poverty, Deprivation, and Economic Mobility, volume 23, pages 301-327 Emerald Publishing Ltd.
  • Handle: RePEc:eme:reinzz:s1049-258520150000023010
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    References listed on IDEAS

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    1. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
    2. Stéphane Bonhomme & Jean-Marc Robin, 2009. "Assessing the Equalizing Force of Mobility Using Short Panels: France, 1990-2000," Review of Economic Studies, Oxford University Press, vol. 76(1), pages 63-92.
    3. Jenkins, Stephen P. & Jantti, Markus, 2005. "Methods for summarizing and comparing wealth distributions," ISER Working Paper Series 2005-05, Institute for Social and Economic Research.
    4. Singh, S K & Maddala, G S, 1976. "A Function for Size Distribution of Incomes," Econometrica, Econometric Society, vol. 44(5), pages 963-970, September.
    5. Christophe Croux & Catherine Dehon, 2010. "Influence functions of the Spearman and Kendall correlation measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 497-515, November.
    6. Koshevoy, G. A. & Mosler, K., 1997. "Multivariate Gini Indices," Journal of Multivariate Analysis, Elsevier, vol. 60(2), pages 252-276, February.
    7. Markus Jantti & Eva Sierminska & Tim Smeeding, 2008. "The Joint Distribution of Household Income and Wealth: Evidence from the Luxembourg Wealth Study," OECD Social, Employment and Migration Working Papers 65, OECD Publishing.
    8. Eva Sierminska & Andrea Brandolini & Timothy Smeeding, 2006. "The Luxembourg Wealth Study – A cross-country comparable database for household wealth research," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(3), pages 375-383, December.
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    Cited by:

    1. repec:eee:wdevel:v:107:y:2018:i:c:p:75-86 is not listed on IDEAS
    2. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    3. Graciela Sanroman & Guillermo Santos, 2017. "The Joint Distribution of Income and Wealth in Uruguay," Documentos de Trabajo (working papers) 0717, Department of Economics - dECON.

    More about this item

    Keywords

    Income; wealth; inequality; copula; multivariate Gini; C1; D31; J10;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General

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