In this paper, we exploit the heterogeneity in the forecasts obtained by estimating different factor models to measure forecast uncertainty. Our approach is simple and intuitive. It consists first in selecting all the models that outperform some benchmark model, and then in constructing an...

The aim of the present work is to obtain short-term predictions of the monthly volume of the industrial production of the euro area. Preliminary information on the behaviour of this variable is needed, since the index is released with a lag of about two months. A model based on the US industrial...

In this paper we explore the performance of bridge and factor models in forecasting quarterly aggregates in the very short-term subject to a pre-selection of monthly indicators. Starting from a large information set, we select a subset of targeted predictors using data reduction techniques as in...

Assessing the global economic outlook is a fundamentally important task of international financial institutions, governments and central banks. In this paper we focus on the consequences of the rapid growth of emerging markets for monitoring and forecasting the global outlook. Our main results...

This paper proposes a simple procedure to obtain monthly assessments of short-run perspectives for quarterly world GDP and trade. It combines emerging and advanced countries� high frequency information to explain quarterly national accounts variables through bridge models. The union of all...

We suggest the use of an index of Internet job-search intensity (the Google Index, GI) as the best leading indicator to predict the US monthly unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt our preferred leading indicator (GI), the more...

Quantitative information on the current state of the economy is crucial to economic policy-making, but the quarterly national accounts data for GDP in the euro area are released with a significant delay. This paper presents alternative models for the real-time forecasting of euro area GDP and...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

The aim of the paper is to estimate a reliable quarterly time-series of potential output for the Italian economy, exploiting four alternative approaches: a Bayesian unobserved component method, a univariate time-varying autoregressive model, a production function approach and a structural VAR....

Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a �Generalized� Kalman Filter to deal effectively with this problem: our method connects to and innovates upon data-filtering techniques...