The work studies the processes of growth of the world top 150 pharmaceutical firms, on the grounds of an original database which allows also disaggregate analysis at the level of single therapeutical classes and chemical entities.Our findings show that the industry -whose long-term evolution is...

This paper uses a dynamic factor model recently studied by Forni, Hallin, Lippi and Reichlin (2000) to analyze the response of 21 U.S. interest rates to news. Using daily data, we find that the news that affects interest rates daily can be summarized by two common factors. This finding is robust...

This paper proposes a new forecasting method that exploits information from a largepanel of time series. The method is based on the generalized dynamic factor model proposedin Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information onthe dynamic covariance structure of...

In many important textbooks the formal statement of the Spectral RepresentationTheorem is followed by a process version, usually informal, stating thatany stationary stochastic process g is the limit in quadratic mean of asequence of processes, each consisting of a finite sum of...

The work studies the processes of growth of the world top 150 pharmaceutical firms, on the grounds of an original database which allows also disaggregate analysis at the level of single therapeutical classes and chemical entities.Our findings show that the industry -whose long-term evolution is...

This paper explores the statistical properties of household consumption-expenditure budget shares distributions (HBSDs) ---defined as the share of household total expenditure spent for purchasing a specific category of commodities--- for a large sample of Italian households in the period...

We propose a new method for multivariate forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the multivariate Generalized Autoregressive Conditionally Heteroskedastic (GARCH) model. We assume that the dynamic common factors are conditionally heteroskedastic. The GDFM,...

We test the importance of multivariate information for modelling and forecasting in- flation's conditional mean and variance. In the literature, the existence of inflation's conditional heteroskedasticity has been debated for years, as it seemed to appear only in some datasets and for some lag...

We propose a refinement of the criterion by Bai and Ng [2002] for determining the number of static factors in factor models with large datasets. It consists in multiplying the penalty function times a constant which tunes the penalizing power of the function itself as in the Hallin and Liska...

We study the topological properties of the multi-network of commodity-specific trade relations among world countries over the 1992-2003 period, comparing them with those of the aggregate-trade network, known in the literature as the international trade network (ITN). We show that link-weight...