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The health-economic applications of copulas: methods in applied econometric research

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  • Casey Quinn
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    Abstract

    A copula is best described, as in Joe (1997), as a multivariate distribution function that is used to bind each marginal distribution function to form the joint. The copula parameterises the dependence between the margins, while the parameters of each marginal distribution function can be estimated separately. This is a brief introduction to copulas and multivariate dependence issues within a health economics context. The research presented here will make its own contributions to the development of copulas as a methodology, but more importantly will make deliberate inroads into health economic applications of copulas. To do this, common analytic problems faced by health economists are considered. Some of the differences between the copula methodology and existing alternatives are discussed, and a generalisable, systematic approach to estimation is provided.

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    Bibliographic Info

    Paper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 07/22.

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    Date of creation: Oct 2007
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    Handle: RePEc:yor:hectdg:07/22

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    Cited by:
    1. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    2. José M. R. Murteira & Óscar D. Lourenço, 2007. "Health Care Utilization and Self-Assessed Health Specification of Bivariate Models Using Copulas," Health, Econometrics and Data Group (HEDG) Working Papers 07/27, HEDG, c/o Department of Economics, University of York.
    3. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.

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