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...

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...

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...

It has increasingly become standard practice to supplement point macroeconomic forecasts with an appraisal of the degree of uncertainty and the prevailing direction of risks. Several alternative approaches have been proposed in the literature to compute the probability distribution of...

We present a mixed-frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real-time is compared...

In this paper a dynamic factor model with mixed frequency is proposed (FaMIDAS), where the past observations of high frequency indicators are used following the MIDAS approach. This structure is able to represent with richer dynamics the information content of the economic indicators and...

The paper assesses the performance of medium-term forecasts of euro-area GDP and inflation obtained with a DSGE model and a BVARX model currently in use at the Bank of Italy. The performance is compared with that of simple univariate models and with the Eurosystem projections; the same real time...