This paper provides a unified simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the …

We estabilsh the relationships between certain Bayesian and classical approaches to instrumental variables regression … classical 2SLS and LIML and in doing so provide some new insight to the small sample behavior of Bayesian and classical … Bayesian and classical procedures in linear regression models: i.e., Bayesian analysis with a diffuse prior leads to posteriors …

framework of Bayesian ARFIMA class of models. The results conclude that Canadian unemployment exhibits persistence in the short …

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC … methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software. General …

}$ are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with …

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA …

adoption of a Bayesian inference framework. We find that this approach has several attractive features, when comparing it to …

practically relevant inference methods for such models, within the Bayesian paradigm. The algorithm is based on Markov chain Monte …