We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a...

This study analyses persistence in growth rates of the entire population of Dutch manufacturing firms. Previous literature on firm growth rates shows that extreme growth events are likely to be negatively correlated over time. A rebound effect following an extreme growth event questions the...

This study investigates the effects of a monetary policy shock on real output and prices, by means of a novel distribution-free nonrecursive identification scheme for structural vector autoregressions. Structural shocks are assumed to be mutually independent. The identification procedure is...

We study a Large-Dimensional Non-Stationary Dynamic Factor Model where (1) the factors Ft are I (1) and singular, that is Ft has dimension r and is driven by q dynamic shocks with q less than r, (2) the idiosyncratic components are either I (0) or I (1). Under these assumption the factors Ft are...

By representing a system of budget shares as an approximate factor model we determine its rank, i.e. the number of common functional forms, or factors, spanning the space of Engel curves. Once the common factors are estimated via approximate principal components, we identify them by imposing...