-term predictions. Due to the characteristics of the residuals, a bootstrapping method of forecasting was also used, yielding even …

This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The …

incorporate Google search data into a Bridge Equation Model, a version of which usually belongs to the suite of forecasting models … this respect. As the choice of which Google search terms to add to which equation is crucial - for the forecasting …There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such …

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …

forecasting volatility model with the most appropriate error distribution. The results suggest the presence of leverage effect … forecasting model that could guarantee a sound policy decisions. …

This paper is concerned with problem of variable selection and forecasting in the presence of parameter instability …. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or … variable selection and forecasting stages. In this study, we investigate whether or not we should use weighted observations at …

years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide … occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches … drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater …

DSGE models have recently received considerable attention in macroeconomic analysis and forecasting. They are usually …