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Autor:innen: 
Erscheinungsjahr: 
2003
Schriftenreihe/Nr.: 
Sveriges Riksbank Working Paper Series No. 150
Verlag: 
Sveriges Riksbank, Stockholm
Zusammenfassung: 
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.
Schlagwörter: 
Bayesian inference
Cointegration analysis
Estimation
Grassman manifold
Subspaces.
JEL: 
C11
C13
C32
Dokumentart: 
Working Paper
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