Abstract: This paper introduces the ``compound confluent hypergeometric'' (CCH)
distribution. The CCH unifies and generalizes three recently
introduced generalizations of the beta distribution: the Gauss
hypergeometric (GH) distribution of Armero and Bayarri (1994), the
generalized beta (GB) distribution of McDonald and Xu (1995), and the
confluent hypergeometric (CH) distribution of Gordy (forthcoming).
Unlike the beta, GB and GH, the CCH allows for conditioning on
explanatory variables in a natural and convenient way. The CCH family
is conjugate for gamma distributed signals, and so may also prove
useful in Bayesian analysis. Application of the CCH is demonstrated
with two measures of household liquid assets. In each case, the CCH
yields a statistically significant improvement in fit over the more
restrictive alternatives.
Keywords: Beta distribution, hypergeometric functions
Full paper (301 KB PDF)
 Full paper (339 KB Postscript)
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