Bootstrap aggregating or Bagging, introduced by Breiman (1996a), has been proved to be effective to improve on unstable forecast. Theoretical and empirical works using classification, regression trees, variable selection in linear and non-linear regression have shown that bagging can generate...

A common problem in out-of-sample prediction is that there are potentially many relevant predictors that individually have only weak explanatory power. We propose bootstrap aggregation of pre-test predictors (or bagging for short) as a means of constructing forecasts from multiple regression...

The paper examines the processes underlying economic fluctuations by investigating the volatility moderation of U.S. economy in the early 1980's. We decompose the volatility decline using a dynamic factor framework into a common stochastic trend, common transitory component and idiosyncratic...

This paper aims at identifying the main shocks, which cause movements in real GNP. It does so by searching for two shocks in the context of a VAR model, which explain the majority of the k-step ahead prediction error variances in real GNP for horizons between 0 and 5 years. We find that two...