Working Paper Series,
Sveriges Riksbank (Central Bank of Sweden)

Abstract: 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.

JEL-codes: C11; C13; C32

16 pages, September 1, 2003

Full text files

WP_150.pdf  

Download statistics

• Sveriges Riksbank (Central Bank of Sweden)
• Ordering Working Papers
• Home page for this series

Questions (including download problems) about the papers in this series should be directed to Lena Löfgren ()
Report other problems with accessing this service to Sune Karlsson ().

RePEc:hhs:rbnkwp:0150This page generated on 2024-09-13 22:16:57.