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 …

While forecasting is a common practice in academia, government and business alike, practitioners are often left … wondering how to choose the sample for estimating forecasting models. When we forecast inflation in 2014, for example, should we … time series, and the forecasting performance is often quite sensitive to the choice of such window size. In this paper, we …

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

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the … choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over … the usefulness of the methodologies for evaluating exchange rate models' forecasting ability. …

Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into … examples, such as accounting identities, disaggregation and spatial restrictions when forecasting aggregate variables …, cointegration and forecasting with Dynamic Stochastic General Equilibrium (DSGE) models. We group the lessons into three themes. The …

DSGE models are a prominent tool for forecasting at central banks and the competitive forecasting performance of these … have the same implication. We therefore argue that forecasting ability during the Great Moderation is not a good metric to …