modeling, we construct the area-wide indicators by utilizing weights that minimize the variance of the out-of-sample forecast … errors of the area-wide target variable. In an out-of-sample forecast experiment we find that our optimal pooling of … information approach outperforms alternative forecasting methods in terms of forecast accuracy …

rates approach forecasting from a different perspective. Rather than focus on forecast errors for bilateral exchange rates …

This paper explores a range of different forecast methods for Brent oil prices and analyses their performance relative … across forecast horizons. To address this instability, we propose a forecast combination for predicting quarterly real Brent … generates forecasts whose performance is robust over time. The improvements in forecast accuracy and stability are noticeable in …

quite rapidly with the forecast horizon, and (b) AugGVAR forecasts do as well as other data-rich forecasting techniques for … short horizons, and tend to do better for longer forecast horizons …

This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks …

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when … the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast … optimally does not improve forecast accuracy; (e) all variants except the large BVAR tend to be well calibrated for inflation …