We compare the forecasting performances of the classical and the Minnesota-type Bayesian vector autoregressive (VAR … algorithm for variable selection, estimated using Markov Chain Monte Carlo methods. In this regard, we analyze the forecasting … the linear fixed coefficients classical VAR. However, we do not observe marked gains in forecasting power across the …

This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs … Carlo experiment, and in forecasting 4 macroeconomic series of the UK using time-varying parameters vector autoregressions … (TVP-VARs). Restricted models consistently improve upon their unrestricted counterparts in forecasting, showing the merits …

is assessed in forecasting three major macroeconomic time series of the UK economy. Data-based restrictions of VAR … coefficients can help improve upon their unrestricted counterparts in forecasting, and in many cases they compare favorably to … shrinkage estimators. …

-of-sample forecasting, and accuracy in the estimation of impulse response functions. …

This paper studies the role of non-pervasive shocks when forecasting with factor models. To this end, we first … model for the idiosyncratic component. Then, we test the forecasting performance of this model both in simulations, and on a …

– 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal …-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered …

-- 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal …-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered …