National accounts statistics undergo a process of revisions over time because of the accumulation of information and … preliminary releases vis a vis an intermediate vintage supposed to embody all statistical information (or no longer revisable as …. The analysis of the news models in differences is based on the comparison of the forecasting performance of the …

We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need … in forecasting the price of oil? How useful are survey forecasts? How does one evaluate the sensitivity of a baseline oil …

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the … information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an … forecasting performance of our proposed model relative to most of the existing alternative specifications. While most of the …

process is to use timely monthly information in order to nowcast quarterly variables that are published with long delays. We …

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

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 … this finding is confirmed by a Monte Carlo experiment based on bootstrapped data. We also provide a consistency result for …

forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets …

statistical benchmarks, and revisit the forecasting performance of changes in commodity currencies as efficient predictors of …-augmented models that use information from a large data set containing a variety of indicators of supply and demand conditions across … least squares (PLS) regression to extract dynamic factors from the data set. Our forecasting analysis considers ten …

produce large reductions in the out-of-sample prediction mean squared error and provides a useful alternative to forecasting …