Multivariate Dynamic Probit Models: An Application to Financial Crises Mutation

In this paper we propose a multivariate dynamic probit model. Our model can be considered as a non-linear VAR model for the latent variables associated with correlated binary time-series data. To estimate it, we implement an exact maximum-likelihood approach, hence providing a solution to the problem generally encountered in the formulation of multivariate probit models. Our framework allows us to apprehend dynamics and causality in several ways. Furthermore, we propose an impulse-response analysis for such models. An empirical application on three nancial crises is nally proposed.