This paper examines the problem of weak identification in maximum likelihood, motivated by problems with estimation and inference a multi-dimensional, non-linear DSGE model. We suggest a test for a simple hypothesis concerning the full parameter vector which is robust to weak identification. We...

The degree of empirical support of a priori plausible structures on the cointegration vectors has a central role in the analysis of cointegration. Villani (2000) and Strachan and van Dijk (2003) have recently proposed finite sample Bayesian procedures to calculate the posterior probability of...

Este artículo presenta una colección de funciones computacionales que son utilizadas en la implementación de un análisis bayesiano exhaustivo para la diferencia de dos proporciones. Con este fin, se discute la estimación puntual, la estimación mediante intervalos de credibilidad y la...

This paper considers a vector autoregressive model or a vector error correction model with multiple structural breaks in any subset of parameters, using a Bayesian approach with Markov chain Monte Carlo simulation technique. The number of structural breaks is determined as a sort of model...

This paper introduces Bayesian inference in a Markov switching partial cointegration model. The partial cointegration allows the cointegration relationships to be switched on and off depending on the regime, unlike conventional cointegration analysis that assumes linear adjustment toward...

In this essay, I argue about the relevance and the ultimate unity of the Bayesian approach in a neutral and agnostic manner. My main theme is that Bayesian data analysis is an effective tool for handling complex models, as proven by the increasing proportion of Bayesian studies in the applied...

The degree of empirical support of a priori plausible structures on the cointegration vectors has a central role in the analysis of cointegration. Villani (2000) and Strachan and van Dijk (2003) have recently proposed finite sample Bayesian procedures to calculate the posterior probability of...

Bayesian empirical approaches appear frequently in fields such as engineering, computer science, political science and medicine, but almost never in law. This article illustrates how such approaches might be very useful in empirical legal studies. In particular, Bayesian approaches enable a much...

A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity. In addition, we define the concept of behaviorally distinguishable...