Bayes Estimators of the Cointegration Space
No 150, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)
A neglected aspect of the otherwise fairly well developed Bayesian analysis of cointegration is the point estimation of the cointegration space. It is pointed out here that, due to the well known non-identification of the cointegration vectors, the parameter space is not an inner product space and conventional Bayes estimators therefore stand without their usual decision theoretic foundation. We present a Bayes estimator of the cointegration space which takes the curved geometry of the parameter space into account. Contrary to many of the Bayes estimators used in the literature, this estimator is invariant to the ordering of the time series. A dimension invariant overall measure of cointegration space uncertainty is also proposed. A small simulation study shows that the Bayes estimator compares favorably to the maximum likelihood estimator.
Keywords: Bayesian inference; Cointegration analysis; Estimation; Grassman manifold; Subspaces. (search for similar items in EconPapers)
JEL-codes: C11 C13 C32 (search for similar items in EconPapers)
Pages: 16 pages
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:rbnkwp:0150
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