This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We...

This paper shows how one can compute option prices from a Bayesian inference viewpoint, using an econometric model for the dynamics of the return and of the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The...

We provide a ranking of economics departments in Europe and we discuss the methodsused to obtain it. The JEL CD-ROM serves as a database for a period covering 10years. Journals are ranked using a combination of expert opinions and citation data toproduce a scale from 1 to 10. The publication...

We derive the postenor density of the cointegrating coetficients in a Gaussian VAR system. The density does not belong in general to a family of densities with known properties. If there is one cointegrating vector, the density belongs to the class of poly-t densities. It is integrable if the...

We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the diffculties of simulating dynamic latent variables in a Gibbs sampler. We propose an alternative specification of the dynamic disequilibrium model which leads to a simple...

This paper is concerned with the empirical investigation of models of the US short term interest rate, using a mixture of classical non-parametric methods and of Bayesian parametric methods. The shape of the drift and volatility functions of the usual diffusion equation are first investigated...