Bayes Estimators of the Cointegration Space
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.
|Date of creation:||01 Sep 2003|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: 08 - 787 00 00
Fax: 08-21 05 31
Web page: http://www.riksbank.com/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kleibergen, Frank & Paap, Richard, 2002.
"Priors, posteriors and bayes factors for a Bayesian analysis of cointegration,"
Journal of Econometrics,
Elsevier, vol. 111(2), pages 223-249, December.
- Kleibergen, F.R. & Paap, R., 1998. "Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration," Econometric Institute Research Papers EI 9821, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Phillips, P C B, 1991.
"Optimal Inference in Cointegrated Systems,"
Econometric Society, vol. 59(2), pages 283-306, March.
- Strachan, R., 2000.
"Valid Bayesian Estimation of the Cointegrating Error Correction Model,"
Monash Econometrics and Business Statistics Working Papers
6/00, Monash University, Department of Econometrics and Business Statistics.
- Strachan, Rodney W, 2003. "Valid Bayesian Estimation of the Cointegrating Error Correction Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 185-95, January.
- Geweke, John, 1996.
"Bayesian reduced rank regression in econometrics,"
Journal of Econometrics,
Elsevier, vol. 75(1), pages 121-146, November.
- BAUWENS, Luc & LUBRANOÂ , Michel, 1994. "Identification Restrictions and Posterior Densities in Cointegrated Gaussian VAR Systems," CORE Discussion Papers 1994018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
- Kleibergen, Frank & van Dijk, Herman K., 1994. "On the Shape of the Likelihood/Posterior in Cointegration Models," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 514-551, August.
- Kleibergen, Frank & van Dijk, Herman K., 1998.
"Bayesian Simultaneous Equations Analysis Using Reduced Rank Structures,"
Cambridge University Press, vol. 14(06), pages 701-743, December.
- Kleibergen, F.R. & van Dijk, H.K., 1997. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Econometric Institute Research Papers EI 9714/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, March.
When requesting a correction, please mention this item's handle: RePEc:hhs:rbnkwp:0150. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lena Löfgren)
If references are entirely missing, you can add them using this form.