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 …

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 …

The term now-casting is a contraction for now and forecasting and has been used for a long-time in meteorology and …

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. …

aggregating weighted forecasts of the sub-component price indices, versus forecasting the aggregate consumer price index itself … aggregate CPI forecasts, and also offers substantial gains over forecasting using benchmark naïve models. The analysis also … contributes an improved understanding of sectoral inflationary pressures. This forecasting method should be more robust to the …