This Paper proposes a new forecasting method that exploits information from a large panel of time series. The method is based on the generalized dynamic factor model proposed in Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information on the dynamic covariance structure...

In this paper we examine whether data from business tendency surveys are useful for forecasting the macro economy in the short run. Our analyses primarily concern the growth rates of real GDP but we also evaluate forecasts of other variables such as unemployment, price and wage inflation,...

This paper studies the international business cycle behaviour across 25 advanced and emerging market economies for which 125 years of annual GDP data are available. The picture that emerges is more fragmented than the one drawn by studies that focused on a narrower set of advanced market...

We derive forecast weights and uncertainty measures for assessing the roles of individual series in a dynamic factor model (DFM) for forecasting the euro area GDP from monthly indicators. The use of the Kalman smoother allows us to deal with publication lags when calculating the above measures....

We estimate and forecast growth in euro area monthly GDP and its components from the dynamic factor model of Doz et al. (2006), which handles unbalanced data sets in an efficient way. We extend the model to integrate interpolation and forecasting with cross-equation accounting identities. A...