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 …

It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean …

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 …

indices over the period 1995-2003. We find strong evidence in support of ‘thick’ modelling proposed in the forecasting …

Time series models are often adopted for forecasting because of their simplicity and good performance. The number of … potentially useful when forecasting. Hence, in this Paper we construct a large macroeconomic data-set for the UK, with about 80 …

This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple …