, produces a degree of forecasting accuracy of the federal funds rate similar to that of the markets, and, for output and …

and Small, 2005. The method consists in bridging quarterly GDP with monthly data via a regression on factors extracted …This paper evaluates models that exploit timely monthly releases to compute early estimates of current quarter GDP (now … from a large panel of monthly series with different publication lags. We show that bridging via factors produces more …

sizeable. Prices and quantities affect the precision of the estimates of GDP while inflation is only affected by nominal …

. To illustrate our ideas, we study the nowcast of euro area GDP in the fourth quarter of 2008. …

information set used to extract factors. Using US yield curve data, we find that: a. macro factors are very useful in forecasting … at medium/long forecasting horizon; b. financial factors are useful in short run forecasting; c. no-arbitrage models are …This paper addresses the issue of forecasting the term structure. We provide a unified state-space modelling framework …

forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy …. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for …

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we … propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the …

In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification … lag length and of both; compare alternative approaches to h-step ahead forecasting (direct, iterated and pseudo …

We defend the forecasting performance of the FOMC from the recent criticism of Christina and David Romer. Our argument …