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Using copulas to estimate reduced-form systems of equations

Author

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  • Casey Quinn

Abstract

This paper introduces a new approach to measuring the association between health and socioeconomic status. Measuring inequalities in health is difficult when health is measured qualitatively, specifically on an ordinal scale. This paper demonstrates a rank-based dependence measure - the copula - that is invariant to both the scale and any monotonic transformations of its dimensions. Accordingly, the copula measure of association between health and income is robust under different cardinal scales for health as well as different income distributions, and can be used for ordering countries. The copula is also used to generate contingency tables of joint probability, which illustrate how this ordering can be due to polarity in the distributions of health and income, as well as stronger association between the distributions of health and income.

Suggested Citation

  • Casey Quinn, 2007. "Using copulas to estimate reduced-form systems of equations," Health, Econometrics and Data Group (HEDG) Working Papers 07/25, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:07/25
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    Cited by:

    1. 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.

    More about this item

    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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