Mixed Marginal Copula Modeling. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Gunawan, David; Khaled, Mohamad A.; Kohn, Robert
• Is Part Of: Journal of business & economic statistics. Volume 38:Issue 1(2020)
• Page Start: 137
• Page End: 147
• Publication Date: 2020-01-02
• Subjects: Bayesian analysis -- Markov chain Monte Carlo -- Mixtures of copulas -- Multivariate income dynamics.; Economics -- Statistical methods -- Periodicals; Commercial statistics -- Periodicals; Économie politique -- Méthodes statistiques -- Périodiques; Statistique commerciale -- Périodiques; 330.015195
• DOI: 10.1080/07350015.2018.1469998
• Languages: English
• ISSNs: 0735-0015

Abstract

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.