straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations …, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of …

This paper addresses the issue of improving the forecasting performance of vector autoregressions (VARs) when the set …

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 …

-- 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 …

forecasting one-month ahead, especially with Bayesian VARs. Furthermore, for both real and nominal variables, the direct pooling …

shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool … for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time …