Bayesian Treatment of the Independent Student- t Linear Model

John Geweke

Journal of Applied Econometrics, 1993, vol. 8, issue S, S19-40

Abstract: This article takes up methods for Bayesian inference in a linear model in which the disturbances are independent and have identical Student-t distributions. It exploits the equivalence of the Student-t distribution and an appropriate scale mixture of normals, and uses a Gibbs sampler to perform the computations. The new method is applied to some well-known macroeconomic time series. It is found that posterior odds ratios favour the independent Student-t linear model over the normal linear model, and that the posterior odds ratio in favour of difference stationarity over trend stationarity is often substantially less in the favored Student-t models. Copyright 1993 by John Wiley & Sons, Ltd.

Date: 1993
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