
on Econometrics 
By:  M.P. Wiper,; F.J. Giron; A. Pewsey 
Abstract:  In this article we consider approaches to Bayesian inference for the halfnormal and halft distributions. We show that a generalized version of the normalgamma distribution is conjugate to the halfnormal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the halft distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the halfnormal and halft models. 
Date:  2005–07 
URL:  http://d.repec.org/n?u=RePEc:cte:wsrepe:ws054709&r=ecm 
By:  Kim C. Border (California Institute of Technology); Paolo Ghirardato (Università da Torino); Uzi Segal (Boston College) 
Abstract:  This note shows that if the space of events is sufficiently rich and the subjective probability function of each individual is nonatomic, then there is a sigmaalgebra of events over which everyone will have the same probability function, and moreover, the range of these probabilities is the whole [0, 1] segment. 
Date:  2005–08–02 
URL:  http://d.repec.org/n?u=RePEc:boc:bocoec:616&r=ecm 