We study the performance of Bayesian model averaging as a forecasting method for a large panel of time series and … correlated implying similar mean-square forecast errors. Applied to forecasting Industrial production and inflation in the United … the average global out-of-sample performance hides important changes in the local forecasting power of the two approaches …

resulting model is competitive with standard benchmarks in terms of forecasting and can be used for policy analysis …

other sources of information. The combination weights are time-varying and may depend on past predictive forecasting …

forecasting US inflation by mixing density forecasts from an autoregressive model and the Survey of Professional Forecasters …

forecasting. The empirical results serve as a preliminary guide to understanding the behaviour of BMA under double asymptotics, i …

This thesis utilizes modern Bayesian tools to evaluate the forecasting performance of two of the most widely used …, but also in the choice of the best model according to its forecasting potential. To our knowledge, the literature avoids … welcoming existing Bayesian methods in forecasting and comparison of nonlinear time series models; all known attempts from a …

such a models. It alsoprovides procedures for forecasting (unconditional and conditional),dimension reduction (canonical …

problem to tackle with a traditional Bayesian approach. Our solution is to focus on the forecasting performance for the …