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Mixed Marginal Copula Modeling

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  • David Gunawan
  • Mohamad A. Khaled
  • Robert Kohn

Abstract

This article extends the literature on copulas with discrete or continuous marginals to the case where some of the marginals are a mixture of discrete and continuous components. We do so by carefully defining the likelihood as the density of the observations with respect to a mixed measure. The treatment is quite general, although we focus on mixtures of Gaussian and Archimedean copulas. The inference is Bayesian with the estimation carried out by Markov chain Monte Carlo. We illustrate the methodology and algorithms by applying them to estimate a multivariate income dynamics model. Supplementary materials for this article are available online.

Suggested Citation

  • David Gunawan & Mohamad A. Khaled & Robert Kohn, 2020. "Mixed Marginal Copula Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 137-147, January.
    • Handle: RePEc:taf:jnlbes:v:38:y:2020:i:1:p:137-147
    DOI: 10.1080/07350015.2018.1469998
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    Cited by:

    1. Mohamad Khaled & Paul Makdissi & Prasada Rao & Myra Yazbeck, 2023. "A Unidimensional Representation of Multidimensional Inequality: An Econometric Analysis of Inequalities in the Arab Region," Working Papers 2304E Classification- D63, University of Ottawa, Department of Economics.
    2. Mohamad A. Khaled & Paul Makdissi & D.S. Prasada Rao & Myra Yazbeck, 2023. "A unidimensional representation of multidimensional inequality, with an application to the Arab region," Discussion Papers Series 659, School of Economics, University of Queensland, Australia.
    3. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
    4. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.

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