by Mattias Villani
Research Report 1998:2
Department of Statistics, Stockholm University, S-106 91 Stockholm, Sweden
A Bayesian analysis of the parameters
in the vector autoregressive model with a single cointegrating relationship
is presented. A mixture distribution is used as a prior for the cointegration
vector to allow for a proper representation of prior beliefs. The traditional
normalization coupled with a, intendedly uninformative, flat prior on the
free elements in the cointegration vector are shown to add unwanted information
into the analysis. Parametrization of the cointegration vector in polar
coordinates is argued to be a better alternative and a suitable procedure
We illustrate the method on a simple example with two interest rates.
Key words: Bayesian, Cointegration, Mixture prior, Polar coordinates.
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Last update: 1998-05-28 / KH