Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts
AbstractThis paper makes three contributions. Firstly, it uses copula functions to obtain a flexible bivariate parametric model for non-negative integer-valued data (counts). Secondly, it recovers the distribution of the difference in the two counts from a specified bivariate count distribution. Thirdly, 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). Copyright Royal Economic Socciety 2004
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Bibliographic InfoArticle provided by Royal Economic Society in its journal The Econometrics Journal.
Volume (Year): 7 (2004)
Issue (Month): 2 (December)
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Other versions of this item:
- 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 43, University of California, Davis, Department of Economics.
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