This paper introduces an upgraded version of MSVARlib, a Gauss and Ox- Gauss compliant library, focusing on Multivariate Markov Switching Regressions in their most general specification. This new set of procedures allows to estimate, through classical optimization methods, models belonging to...

A methodology based on the multivariate generalized Butterwoth filter for extracting the business cycles of the whole economy and of its productive sectors is developed. The method is then illustrated through an application to the Italian gross value added time series of the main economic sectors.

This paper explores 35 years of the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series, which offer reliable information to detect recessions in real time. It also assesses the performances of different and...

This paper explores the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series which offer reliable information to detect recessions in real time. It also proposes and assesses the performances of different and...

We proposed clear, methodologically sound framework for analyzing SVAR with priors on impulse responses. We showed it poses no difficulties in deriving the posterior which even in case of unidentified SVAR with flat prior on impulse functions (under the appropriate requirement tying number of...

The structural vector autoregression (SVAR) has become a central tool for research in empirical macroeconomics. Because the vast majority of these models are exactly identified, researchers have traditionally relied upon the informal use of prior information to compare alternative...

A welfare analysis of a risky policy is impossible within a linear or linearized model and its certainty equivalence property. The presented algorithms are designed as a toolbox for a general model class. The computational challenges are considerable and I concentrate on the numerics and...

This paper develops a Bayesian vector autoregressive model(BVAR) for the leader of the Portuguese car market to forecast the market share. The model includes five marketing decision variables.The Bayesian prior is selected on the basis of the accuracy of the out-of-sample forecasts. We find that...

Using Markov Chain Monte Carlo algorithms within the limited information Bayesian framework, we estimate the parameters of the structural equation of interest and test weak exogeneity in a simultaneous equation model with white noise as well as autocorrelated error terms. A numerical example and...

I use numerical methods to test for the presence of one-time structural breaks in the conditional variance of nominal interest rate spreads in four European countries over a period of eleven years (Jan 1988 to Dec 1998). I start with an intuitive approach consisting of a sequence of breakpoint...