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Estimation of VAR Models: Computational Aspects

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Author Info
Paolo Foschi () (Institut d'informatique, UniversitÈ de Neuchatel, Rue Emile Argand 11, CH-2007 Neuchâtel, Switzerland)
Erricos J. Kontoghiorghes () (Institut d'informatique, UniversitÈ de Neuchatel, Rue Emile Argand 11, CH-2007 Neuchâtel, Switzerland)

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Abstract

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.

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Publisher Info
Article provided by Springer in its journal Computational Economics.

Volume (Year): 21 (2003)
Issue (Month): 1_2 (02)
Pages: 3-22
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Handle: RePEc:kap:compec:v:21:y:2003:i:1_2:p:3-22

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Web page: http://www.springerlink.com/link.asp?id=100248

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  1. 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. [Downloadable!] (restricted)
  2. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254. [Downloadable!] (restricted)
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This page was last updated on 2009-11-12.

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