Euro area GDP and components are nowcast and forecast one quarter ahead. Based on a dataset of 163 series comprising the relevant monthly indicators, simple bridge equations with one explanatory variable are estimated for each. The individual forecasts generated by each equation are then pooled,...

Several factor-based models are estimated to investigate the role of country-specific trade and survey data in forecasting euro areamanufacturing production. Following Boivin and Ng (2006), the emphasis is put on the role of dataset selection on the empirical performance of factor models. First,...

We suggest an alternative use of disaggregate information to forecast the aggregate variable of interest, that is to include disaggregate information or disaggregate variables in the aggregate model as opposed to first forecasting the disaggregate variables separately and then aggregating those...

We use a newly available dataset of euro area quarterly national accounts fiscal data and construct multivariate, state-space mixed-frequencies models for the government deficit, revenue and expenditure in order to assess its information content and its potential use for fiscal forecasting and...

This paper evaluates models that exploit timely monthly releases to compute early estimates of current quarter GDP (now-casting) in the euro area. We compare traditional methods used at institutions with a new method proposed by Giannone, Reichlin, and Small (2005). The method consists in...

We evaluate residual projection strategies in the context of a large-scale macro model of the euro area and smaller benchmark time-series models. The exercises attempt to measure the accuracy of model-based forecasts simulated both out-of-sample and in-sample. Both exercises incorporate...

This paper provides evidence on the reliability of euro area real-time output gap estimates. A genuine real-time data set for the euro area is used, including vintages of several sets of euro area output gap estimates available from 1999 to 2006. It turns out that real-time estimates of the...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...

In this paper we propose a methodology to estimate a dynamic factor model on data sets with an arbitrary pattern of missing data. We modify the Expectation Maximisation (EM) algorithm as proposed for a dynamic factor model by Watson and Engle (1983) to the case with general pattern of missing...