We show that the use of prior information derived from former empirical findings and/or subject matter theory regarding the lag structure of the observable variables together with an AR process for the error terms can produce univariate and single equation models that are intuitively appealing,...

The occurrence of decision problems with changing roles of null and alternative hypotheses has increased interest in extending the classical hypothesis testing setup. Particularly, confirmation analysis has been in the focus of some recent contributions in econometrics. We emphasize that...

We analyse the volatility structure of Asian currencies against the U.S. dollar (USD) for the Thai Baht THB, the Philippine Peso PHP, the Indonesian Rupiah IDR and the South Korean Won KRW. Our goal is to check if the characteristics of the volatility dynamics have changed in a K-state switching...

This paper analyzes long-run co-movements between international real estate stock markets and between regions based on bivariate and multivariate tests for cointegration. While the topic has been analyzed in previous studies such as Gallo and Zhang (2009) and Yunus (2009) among others, this...

Inflation persistence has been put forward as one of the potential reasons of divergence among euro area members. It has also been proposed that the new EU Member States (NMS) may struggle with even higher persistence due to convergence factors. We argue that persistence may not be as different...

In this paper we introduce two general non-parametric first-order stationary time-series models for which marginal (invariant) and transition distributions are expressed as infinite-dimensional mixtures. That feature makes them the first Bayesian stationary fully non-parametric models developed...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to the...

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series....