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Effects of Marginal Speci cations on Copula Estimation

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  • Azam, Kazim

    (Vrije Universiteit, Amsterdam)

Abstract

This paper studies the effect of marginal distributions on a copula, in the case of mixed discrete-continuous random variables. The existing literature has proposed various methods to deal with mixed marginals: this paper is the rst to quantify their e ect in a uni ed Bayesian setting. Using order statistics based information for the marginals, as proposed by Ho (2007), we find that in small samples the bias and mean square error are at least half in size as compared to those of empirical or misspecified marginal distributions. The difference in the bias and mean square error enlarges with increasing sample size, especially for low count discrete variables. We employ the order statistics method on firm-level patents data, containing both discrete and continuous random variables, and consistently estimate their correlation. JEL classification: C11 ; C14 ; C52

Suggested Citation

  • Azam, Kazim, 2014. "Effects of Marginal Speci cations on Copula Estimation," The Warwick Economics Research Paper Series (TWERPS) 1053, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:1053
    as

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    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/2014/twerp_1053_azam.pdf
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    References listed on IDEAS

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    1. Eckel, Carsten & Iacovone, Leonardo & Javorcik, Beata & Neary, J. Peter, 2015. "Multi-product firms at home and away: Cost- versus quality-based competence," Journal of International Economics, Elsevier, vol. 95(2), pages 216-232.
    2. Cockburn, Iain & Griliches, Zvi, 1988. "Industry Effects and Appropriability Measures in the Stock Market's Valuation of R&D and Patents," American Economic Review, American Economic Association, vol. 78(2), pages 419-423, May.
    3. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    4. Michael Pitt & David Chan & Robert Kohn, 2006. "Efficient Bayesian inference for Gaussian copula regression models," Biometrika, Biometrika Trust, vol. 93(3), pages 537-554, September.
    5. Peter Xue‐Kun Song, 2000. "Multivariate Dispersion Models Generated From Gaussian Copula," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(2), pages 305-320, June.
    6. Sandner, Philipp G. & Block, Joern, 2011. "The market value of R&D, patents, and trademarks," Research Policy, Elsevier, vol. 40(7), pages 969-985, September.
    7. Gilroy, Bernard Michael, 1993. "Book Review: John H. Dunning Multinational Enterprises and the Global Economy," MPRA Paper 18660, University Library of Munich, Germany.
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    More about this item

    Keywords

    Bayesian copula ; discrete data ; order statistics ; semi-parametriccreation-date: 2014;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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