This paper presents an application of neural network models to predictive classification for data quality control. Our aim is to identify data affected by measurement error in the Bank of Italy�s business surveys. We build an architecture consisting of three feed-forward networks for...

In this paper we consider several time-varying volatility and/or heavy-tailed models to explain the dynamics of return time series and to fit the volatility smile for exchange-traded options where the underlying is the main �Borsa Italiana� stock index. Given observed prices for the...

Most of the important models in finance rest on the assumption that randomness is explained through a normal random variable because, in general, the use of alternative models is obstructed by the difficulty of calibrating and simulating them. In this paper, we empirically study models for...

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...

Business investment is a very important variable for short- and medium-term economic analysis, but it is volatile and difficult to predict. Qualitative business survey data are widely used to provide indicators of economic activity ahead of the publication of official data. Traditional...

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...

We quantitatively assess the macroeconomic effects of country-specific supply-side reforms in the euro area by simulating EAGLE, a multi-country dynamic general equilibrium model. We consider reforms in the labor and services markets of Germany (or, alternatively, Portugal) and the rest of the...

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...

The available empirical evidence suggests that non-negligible differences in economic structures persist among euro area countries. Because of these asymmetries, an area-wide modelling approach is arguably less reliable, from a strictly statistical viewpoint, than a multi-country one. This paper...

This paper deals with the usefulness of several measures of financial spreads (the slope of the yield curve, the reverse yield gap, the credit quality spread) for fore-casting real economic activity and inflation in the euro area. A quarterly Bayesian vector autoregression model is used to...