Estimation of VAR Models: Computational Aspects
The Vector Autoregressive (VAR) model with zero coefficient restrictions can be formulated as a Seemingly Unrelated Regression Equation (SURE) model. Both the response vectors and the coefficient matrix of the regression equations comprise columns from a Toeplitz matrix. Efficient numerical and computational methods which exploit the Toeplitz and Kronecker product structure of the matrices are proposed. The methods are also adapted to provide numerically stable algorithms for the estimation of VAR(p) models with Granger-caused variables.
Volume (Year): 21 (2003)
Issue (Month): 1_2 (02)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=100248|
More information through EDIRC
References listed on IDEAS
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.:
- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, March.
- Kontoghiorghes, E. J. & Clarke, M. R. B., 1995. "An alternative approach for the numerical solution of seemingly unrelated regression equations models," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 369-377, April.
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:3-22. 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: (Guenther Eichhorn)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.