In this paper we compare the performance of a regional indicator of vulnerability in predicting, out of sample, the crisis events affecting the South East Asian region during the 1997-98 period. A Dynamic Factor method was used to retrieve the vulnerability indicator and stochastic simulation is...

In this paper we compared the performance of country specific and regional indicators of reserve adequacy in predicting, out of sample, the balance of payment crisis affecting the South East Asian region during the 1997-98 period. A Dynamic Factor method was used to retrieve reserve adequacy...

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments tends to infinity. We consider cases where the unobserved factors are the optimal instruments but also cases where the factors are not necessarily the optimal instruments but can...

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new methodology for estimating factors from large datasets based on state space models, discuss its...

In this paper we compared the performance of country specific and regional indicators of reserve adequacy in predicting, out of sample, the balance of payment crisis affecting the South East Asian region during the 1997-98 period. A Dynamic Factor method was used to retrieve reserve adequacy...

The estimation of structural dynamic factor models (DFMs) for large sets of variables is attracting considerable attention. In this paper we briefly review the underlying theory and then compare the impulse response functions resulting from two alternative estimation methods for the DFM....

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new parametric methodology for estimating factors from large datasets based on state space models and...

In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding...

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new methodology for estimating factors from large datasets based on state space models, discuss its...