Dependence Measures in Bivariate Gamma Frailty Models

Gerard van den Berg and Georgios Effraimidis ()
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Georgios Effraimidis: University of Southern Denmark

No 8083, IZA Discussion Papers from IZA Network @ LISER

Abstract: Bivariate duration data frequently arise in economics, biostatistics and other areas. In "bivariate frailty models", dependence between the frailties (i.e., unobserved determinants) induces dependence between the durations. Using notions of quadrant dependence, we study restrictions that this imposes on the implied dependence of the durations, if the frailty terms act multiplicatively on the corresponding hazard rates. Marginal frailty distributions are often taken to be gamma distributions. For such cases we calculate general bounds for two association measures, Pearson's correlation coefficient and Kendall's tau. The results are employed to compare the flexibility of specific families of bivariate gamma frailty distributions.

Keywords: bivariate gamma distribution; duration models; competing risks; Kendall's tau; negative and positive quadrant dependence; Pearson's correlation coefficient; unobserved heterogeneity; survival analysis (search for similar items in EconPapers)
JEL-codes: C32 C33 C34 C41 C51 J64 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2014-03
New Economics Papers: this item is included in nep-ecm and nep-ger
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