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

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the … forecasting performance of our proposed model relative to most of the existing alternative specifications. While most of the … and useful for forecasting. …

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we … propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the …

forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy …. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is …

This Paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a …

In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification … lag length and of both; compare alternative approaches to h-step ahead forecasting (direct, iterated and pseudo …

produce large reductions in the out-of-sample prediction mean squared error and provides a useful alternative to forecasting …

model forecast should become the benchmark for forecasting horse races. We compare the real-time forecasting accuracy of the … forecasting models is efficient. Our second finding is that there is no single best forecasting method. For example, typically … simple AR models are most accurate at short horizons and DSGE models are most accurate at long horizons when forecasting …