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Modeling the Differences in Counted Outcomes using Bivariate Copula Models: with Application to Mismeasured Counts

Author

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  • A. Colin Cameron
  • Tong Li
  • Pravin K. Trivedi
  • David M. Zimmer

    (Department of Economics, University of California Davis)

Abstract

This paper makes three contributions. First, it uses copula functions to obtain a flexible bivariate parametric model for nonnegative integer-valued data (counts). Second, it recovers the distribution of the difference in the two counts from a specifed bivariate count distribution. Third, the methods are applied to counts that are measured with error. Specifically we model the determinants of the difference between the self-reported number of doctor visits (measured with error) and true number of doctor visits (also available in the data used).

Suggested Citation

  • A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modeling the Differences in Counted Outcomes using Bivariate Copula Models: with Application to Mismeasured Counts," Working Papers 109, University of California, Davis, Department of Economics.
    • Handle: RePEc:cda:wpaper:109
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    References listed on IDEAS

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