Monte Carlo inference in econometric models with symmetric stable disturbances

Abstract

The paper develops Markov Chain Monte Carlo methods to perform exact posterior analysis in models with symmetric stable Paretian disturbances. It is shown how posterior moments and marginal densities of functions of parameters can be computed methodically by combining a Gibbs sampler with Metropolis independence chains. The new method is shown to perform satisfactorily in constructed examples. The method is also applied to a set of monthly real exchange rates and the question of difference versus trend stationarity is taken up jointly with the problem of inference about the parameter of the stable distribution.