This article investigates the contribution of regions to aggregate growth. We find a great degree of heterogeneity in the performance of Territorial Level 3 ( TL3) regions of the OECD (Organization for Economic Cooperation and Development). The regional contributions to aggregate growth follow a...

Our study focuses on the EU new members, which are transition countries. After a long period of privatization and restructuring, the ownership structure of firms in these countries takes a clearer form. This evolution of ownership structure has a considerable effect on firm performance. In using...

Our study focuses on the EU new members, which are transition countries. After a long period of privatization and restructuring, the ownership structure of firms in these countries takes a clearer form. This evolution of ownership structure has a considerable effect on firm performance. In using...

For numerous models, it is impossible to conduct an exact Bayesian inference. There are many cases where the derivation of the posterior distribution leads to intractable calculations (due to the fact that this generally involves intractable integrations). The Bayesian computational literature...

Abstract: In this paper, we review classical and advanced methodologies for analysing within-subject functional Magnetic Resonance Imaging (fMRI) data. Such data are usually acquired during sensory or cognitive experiments that aims at stimulating the subject in the scanner and eliciting evoked...

This introduction to Bayesian statistics presents the main concepts as well as the principal reasons advocated in favour of a Bayesian modelling. We cover the various approaches to prior determination as well as the basis asymptotic arguments in favour of using Bayes estimators. The testing...

In many different fields such as hydrology, telecommunications, physics of condensed matter and finance, the gaussian model results unsatisfactory and reveals difficulties in fitting data with skewness, heavy tails and multimodality. The use of stable distributions allows for modelling skewness...

This paper deals with some computational aspects in the Bayesian analysis of statistical models with intractable normalizing constants. In the presence of intractable normalizing constants in the likelihood function, traditional MCMC methods cannot be applied. We propose an approach to sample...

While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the current chapter details its practical aspects through a review of the computational methods available for approximating Bayesian procedures. Recent innovations like Monte Carlo Markov chain, sequential...