We propose a Bayesian infinite hidden Markov model to estimate time- varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...

We consider the measures of jointness proposed by Doppelhofer and Weeks (2009) and Strachan (2009) in the context of variable selection. Using the general criteria suggested in Ley and Steel (2007), we identify some shortcomings of these measures, which are illustrated with empirically relevant...

This paper examines the robustness of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible combination of included...

In this paper, we explore Bayesian inference in models with many instrumental variables that are potentially weakly correlated with the endogenous regressor. The prior distribution has a hierarchical (nested) structure. We apply the methods to the Angrist-Krueger (AK, 1991) analysis of returns...

A Bayesian approach is used to investigate a sample's information about a portfolio's degree of inefficiency. With standard diffuse priors, posterior distributions for measures of portfolio inefficiency can concentrate well away from values consistent with efficiency, even when the portfolio is...

We present a model of the time-allocation decision of spouses in order to study the role of heterogeneity in preferences and wages for couples' labor supply. Spouses differ in their tastes for market consumption and non-market goods and activities, and also in their offered or earned wages. They...