IDEAS home Printed from https://ideas.repec.org/p/zbw/vfsc20/224651.html
   My bibliography  Save this paper

A Joint Top Income and Wealth Distribution

Author

Listed:
  • Zhu, Junyi
  • Steiner, Viktor

Abstract

Top distributions of income and wealth are still incompletely measured in many national statistics, particularly when using survey data. This paper develops the technique of incorporating the joint distributional relationship to enhance the estimation of these two top distributions. We leverage the bivariate parametric/non-parametric copula to extrapolate both income and wealth distributions from German PHF (Panel on Household Finance) data. The copula modelling potentially reduces the ad hocery in choosing the estimation domain as well as in the parametric specification (eg Pareto family) imposed by almost all the marginal approaches. One distinct feature of our paper is to complement the model fit with external validation. The copula estimate can help us to perform out-of-sample prediction on the very top of the tail distribution from one margin conditional on the characteristics of the other. The validation exercises show that our copula-based approach can approximate much closer to the top tax data and wealth "rich list" than those unconditional marginal extrapolations. The properness of copula and conditioning criterion seems to convince the asymmetric joint association between (labor) income and wealth (capital income) distributions as recently evidenced by other countries.

Suggested Citation

  • Zhu, Junyi & Steiner, Viktor, 2020. "A Joint Top Income and Wealth Distribution," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224651, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc20:224651
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/224651/1/vfs-2020-pid-40557.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. B. Atkinson, 2017. "Pareto and the Upper Tail of the Income Distribution in the UK: 1799 to the Present," Economica, London School of Economics and Political Science, vol. 84(334), pages 129-156, April.
    2. Stephen P. Jenkins, 2017. "Pareto Models, Top Incomes and Recent Trends in UK Income Inequality," Economica, London School of Economics and Political Science, vol. 84(334), pages 261-289, April.
    3. Trivedi, Pravin K. & Zimmer, David M., 2007. "Copula Modeling: An Introduction for Practitioners," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(1), pages 1-111, April.
    4. Kojadinovic, Ivan, 2017. "Some copula inference procedures adapted to the presence of ties," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 24-41.
    5. Stefan Bach & Andreas Thiemann & Aline Zucco, 2015. "The Top Tail of the Wealth Distribution in Germany, France, Spain, and Greece," Discussion Papers of DIW Berlin 1502, DIW Berlin, German Institute for Economic Research.
    6. Charlotte Bartels & Maria Metzing, 2019. "An integrated approach for a top-corrected income distribution," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 125-143, June.
    7. Thomas Blanchet & Juliette Fournier & Thomas Piketty, 2022. "Generalized Pareto Curves: Theory and Applications," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(1), pages 263-288, March.
    8. Junyi Zhu, 2014. "Bracket Creep Revisited - with and without r > g: Evidence from Germany," Journal of Income Distribution, Ad libros publications inc., vol. 23(3), pages 106-158, November.
    9. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    10. Philip Vermeulen, 2018. "How Fat is the Top Tail of the Wealth Distribution?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 357-387, June.
    11. Rolf Aaberge & Anthony B. Atkinson & Sebastian Königs, 2018. "From classes to copulas: wages, capital, and top incomes," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 295-320, June.
    12. Kojadinovic, Ivan & Yan, Jun, 2010. "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i09).
    13. Yan, Jun, 2007. "Enjoy the Joy of Copulas: With a Package copula," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i04).
    14. Lieberknecht, Philipp & Vermeulen, Philip, 2018. "Inequality and relative saving rates at the top," Working Paper Series 2204, European Central Bank.
    15. Bach, Stefan & Corneo, Giacomo & Steiner, Viktor, 2012. "Optimal top marginal tax rates under income splitting for couples," European Economic Review, Elsevier, vol. 56(6), pages 1055-1069.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Steiner, Viktor & Zhu, Junyi, 2021. "A joint top income and wealth distribution," Discussion Papers 2021/3, Free University Berlin, School of Business & Economics.
    2. Mathias Silva & Michel Lubrano, 2023. "Bayesian correction for missing rich using a Pareto II tail with unknown threshold: Combining EU-SILC and WID data," AMSE Working Papers 2320, Aix-Marseille School of Economics, France.
    3. Michele Cantarella & Andrea Neri & Maria Giovanna Ranalli, 2021. "Mind the wealth gap: a new allocation method to match micro and macro statistics for household wealth," Papers 2101.01085, arXiv.org, revised Jan 2021.
    4. F. Marta L. Di Lascio & Andrea Menapace & Maurizio Righetti, 2020. "Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 373-395, June.
    5. Albers, Thilo & Bartels, Charlotte & Schularick, Moritz, 2022. "Wealth and its Distribution in Germany, 1895-2018," CEPR Discussion Papers 17269, C.E.P.R. Discussion Papers.
    6. Thomas Blanchet & Juliette Fournier & Thomas Piketty, 2022. "Generalized Pareto Curves: Theory and Applications," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(1), pages 263-288, March.
    7. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    8. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    9. François Bourguignon, 2018. "Simple adjustments of observed distributions for missing income and missing people," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 171-188, June.
    10. Bricker, Jesse & Hansen, Peter & Volz, Alice Henriques, 2019. "Wealth concentration in the U.S. after augmenting the upper tail of the survey of consumer finances," Economics Letters, Elsevier, vol. 184(C).
    11. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.
    12. Arthur Charpentier & Emmanuel Flachaire, 2022. "Pareto models for top incomes and wealth," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 1-25, March.
    13. Shofiqul Islam & Sonia Anand & Jemila Hamid & Lehana Thabane & Joseph Beyene, 2020. "A copula-based method of classifying individuals into binary disease categories using dependent biomarkers," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 871-897, December.
    14. Jordá, Vanesa & Niño-Zarazúa, Miguel, 2019. "Global inequality: How large is the effect of top incomes?," World Development, Elsevier, vol. 123(C), pages 1-1.
    15. Ines Heck & Anna Hornykewycz & Jakob Kapeller & Rafael Wildauer, 2024. "Vermögensverteilung in Österreich: eine Analyse auf Basis des HFCS 2021/22," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 255, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    16. Terhi Ravaska, 2020. "Gender-specific top incomes: are they Pareto distributed?," Economics Bulletin, AccessEcon, vol. 40(3), pages 1994-2004.
    17. Thilo N. H. Albers & Charlotte Bartels & Moritz Schularick, 2020. "The Distribution of Wealth in Germany, 1895-2018," ECONtribute Policy Brief Series 001, University of Bonn and University of Cologne, Germany.
    18. Engel, Janina & Riera, Pau Gayà & Grilli, Joseph & Sola, Pierre, 2022. "Developing reconciled quarterly distributional national wealth – insight into inequality and wealth structures," Working Paper Series 2687, European Central Bank.
    19. Ines Heck & Jakob Kapeller & Rafael Wildauer, 2020. "Vermögenskonzentration in Österreich," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 206, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    20. Heck, Ines & Kapeller, Jakob & Wildauer, Rafael, 2020. "Vermögenskonzentration in Österreich: Ein Update auf Basis des HFCS 2017," Greenwich Papers in Political Economy 30683, University of Greenwich, Greenwich Political Economy Research Centre.

    More about this item

    Keywords

    income and wealth joint distribution; copula; heavy-tailed distributions; external consistency;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:vfsc20:224651. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vfsocea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.