In this paper we consider the value of Google Trends search data for nowcasting (and forecasting) GDP growth for a …

-term inflation target, and the incidence of recession and slow growth. The forecasting performance of the GVAR model in relation to …-of-sample forecasting performance is substantiated by a raft of statistical tests which indicate that the predictive accuracy of the GVAR …. Hence we conclude that GVAR models may be a useful forecasting tool for institutions operating at both the national and …

specification is most effective in its forecasting performance. Furthermore, the forecast performances of the different … short-term forecasting models. These empirical findings have been established for different macroeconomic data sets and … different forecast horizons. However, various specifications of the factor model exist and it is a topic of debate which …

spread significantly contributes to the forecast performance of simple growth regressions in Europe, but not in the US in …

. After ten prosperous years with an average GDP growth of 3.7%, the current recession places non-judgemental forecasting …-sized linear dynamic regressions with priors originating in the Bayesian VAR literature. Our forecasting procedure can be … agencies to construct aggregate GDP figures. The real time forecast evaluation conducted over the most severe phase of the …

that the Bayesian Dynamic Factor Model performs well both in terms of point forecast, and in terms of density forecasts …

uses these in simple time-series models to construct out-of-sample forecasts for GDP growth. Over short forecast horizons …

This study develops a framework to forecast India's gross domestic product growth on a quarterly frequency from 2004 to … targeting. The predictive ability of over 3,000 BVAR models is assessed through a set of forecast evaluation statistics and … compared with the forecasting accuracy of alternate econometric models including unrestricted and structural VARs. Key findings …