The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marginalization, for any subset of the observables in linear Gaussian state-space models. We compare macroeconomic density forecasts for the euro area of a DSGE model to those of a DSGE-VAR, a BVAR, and a multivariate random walk over ...

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes Factor, which is obtained without any additional computational effort, can be used to assess the plausibility of the restrictions imposed on the VAR parameter vector by competing DSGE models. In other words, it is possible to rank the amount of abstraction implied by each DSGE mode...

In this paper we treat the issue of forecasting with DSGE and DSGE-VAR models, with particular attention to Bayesian estimation of the predictive distribution and its mean and covariance. As a novel contribution to the forecasting literature, which extends beyond (log-linearized) DSGE models and DSGE-VARs, we show how the value of the h-step-ahead marginal and joint predictive likelihood for a ...

This paper develops a forecasting model for important macroeconomic variables in the state of Indiana. In this study, we specify a Bayesian Vector Autoregression (BVAR) model with Litterman’s prior. A comparison with the Vector Autoregression (VAR) model shows that BVAR improves forecast by reducing root mean square

The general pattern of estimated volatilities of macroeconomic and financial variables is often broadly similar. We propose two models in which conditional volatilities feature comovement and study them using U.S. macroeconomic data. The first model specifies the conditional volatilities as driven by a single common unobserved factor, plus an idiosyncratic component. We label this model BVAR wi...

Integrins connect the extracellular matrix with the cell interior, and transduce signals through interactions of their cytoplasmic tails with cytoskeletal and signaling proteins. Using the yeast two-hybrid system, we isolated a novel splice variant (filamin-Bvar-1) of the filamentous actin cross-linking protein, filamin-B, that interacts with the cytoplasmic domain of the integrin beta1A and be...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-steps ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area-Wide Model (NAWM) that has been designed f...