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

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  • Casey Quinn

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.

Suggested Citation

  • Casey Quinn, 2007. "The health-economic applications of copulas: methods in applied econometric research," Health, Econometrics and Data Group (HEDG) Working Papers 07/22, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:07/22
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    Cited by:

    1. Noemi Kreif & Richard Grieve & Rosalba Radice & Zia Sadique & Roland Ramsahai & Jasjeet S. Sekhon, 2012. "Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data," Medical Decision Making, , vol. 32(6), pages 750-763, November.
    2. 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.
    3. Wei-Jhih Wang & Aasthaa Bansal & Caroline Savage Bennette & Anirban Basu, 2023. "Mimicking Clinical Trials Using Real-World Data: A Novel Method and Applications," Medical Decision Making, , vol. 43(3), pages 275-287, April.
    4. Ji, Xiangfeng & Chu, Yanyu, 2020. "A target-oriented bi-attribute user equilibrium model with travelers’ perception errors on the tolled traffic network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    5. José Murteira & Óscar Lourenço, 2011. "Health care utilization and self-assessed health: specification of bivariate models using copulas," Empirical Economics, Springer, vol. 41(2), pages 447-472, October.
    6. Ipek N Sener & Chandra R Bhat, 2011. "A Copula-Based Sample Selection Model of Telecommuting Choice and Frequency," Environment and Planning A, , vol. 43(1), pages 126-145, January.
    7. 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.
    8. Dardati, Evangelina & Saygili, Meryem, 2020. "Aggregate impacts of cap-and-trade programs with heterogeneous firms," Energy Economics, Elsevier, vol. 92(C).
    9. Sener, Ipek N. & Reeder, Phillip R., 2014. "An integrated analysis of workers’ physically active activity and active travel choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 381-393.

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    Keywords

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I10 - Health, Education, and Welfare - - Health - - - General

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