There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such … as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we … incorporate Google search data into a Bridge Equation Model, a version of which usually belongs to the suite of forecasting models …

inflation for estimating an area-wide measure of the output gap. In the proposed multi-country framework we moreover allow for … the common euro area output gap component as a means to explaining movements in both output and inflation over time, the … an out-of-sample forecasting exercise, the paper shows that the proposed approach performs well as compared to other well …

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

surface types. We finally show that our proposed model can also be effective in forecasting. We provide evidence that our … model significantly outperforms existing models in the forecasting of tennis match results. …

series forecasting models for economic variables. In these models, the reduction of the predictors and the modeling and … forecasting of the response y are carried out in two separate and independent phases. We introduce a potentially more attractive … of widely used macroeconomic series data with one or two sufficient reductions delivering similar forecasting performance …

variable selection and estimation in one step. We evaluate the forecasting accuracy of these estimators for a large set of …