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...

We present an algorithm, based on a differential evolution MCMC method, for Bayesian inference in AR-GARCH models subject to an unknown number of structural breaks at unknown dates. Break dates are directly treated as parameters and the number of breaks is determined by the marginal likelihood...

We develop a theory of marriage and fertility, distinguishing the choice to have children from the choice of the number of children. The deep parameters of the model are identified from the 1990 US Census. We measure voluntary and involuntary childlessness, and explain why (1) single women are...

Dynamic volatility and correlation models with fixed parameters are restrictive for time series subject to breaks. GARCH and DCC models with changing parameters are specified using the sticky infinite hidden Markov-chain framework. Estimation by Bayesian inference determines the adequate number...