In the specification of linear regression models it is common to indicate a list of candidate variables from which a subset enters the model with nonzero coefficients. This paper interprets this specification as a mixed continuous-discrete prior distribution for coefficient values. It then...

This paper generalizes the normal probit model of dichotomous choice by introducing mixtures of normals distributions for the disturbance term. By mixing on both the mean and variance parameters and by increasing the number of distributions in the mixture these models effectively remove the...

This paper provides a general and efficient method for computing density ratio class bounds on posterior moments, given the output of a posterior simulator. It shows how density ratio class bounds for posterior odds ratios may be formed in many situations, also on the basis of posterior...

This paper surveys recently developed methods for Bayesian inference and their use in economic time series models. It begins by reviewing aspects of Bayesian inference essential to understanding the implications of the Bayesian paradigm for time series analysis. It next describes the use of...

This paper presents a new method for predicting turning points. The paper formally defines a turning point; develops a probit model for estimating the probability of a turning point; and then examines both the in-sample and out-of-sample forecasting performance of the model. The model performs...

The reduced rank regression model arises repeatedly in theoretical and applied econometrics. To date the only general treatments of this model have been frequentist. This paper develops general methods for Bayesian inference with noninformative reference priors in this model, based on a Markov...

The normal linear model, with sign or other linear inequality constraints on its coefficients, arises very commonly in many scientific applications. Given inequality constraints Bayesian inference is much simpler than classical inference, but standard Bayesian computational methods become...