The Vector Autoregressive (VAR) model with zero coefficient restrictions canbe formulated as a Seemingly Unrelated Regression Equation (SURE) model. Boththe response vectors and the coefficient matrix of the regression equationscomprise columns from a Toeplitz matrix. Efficient numerical and computationalmethods which exploit the Toeplitz and Kronecker product structure of thematrices are proposed. The methods are also adapted to provide numericallystable algorithms for the estimation of VAR(p) models with Granger-causedvariables. © 2003 Kluwer Academic Publishers.
Foschi, P., Kontoghiorghes, E.J. (2003). Estimation of VAR Models Computational Aspects. COMPUTATIONAL ECONOMICS (DORDRECHT., 21(1-2), 3-22 [10.1023/A:1022281319272].
Estimation of VAR Models Computational Aspects
Foschi, P.;
2003
Abstract
The Vector Autoregressive (VAR) model with zero coefficient restrictions canbe formulated as a Seemingly Unrelated Regression Equation (SURE) model. Boththe response vectors and the coefficient matrix of the regression equationscomprise columns from a Toeplitz matrix. Efficient numerical and computationalmethods which exploit the Toeplitz and Kronecker product structure of thematrices are proposed. The methods are also adapted to provide numericallystable algorithms for the estimation of VAR(p) models with Granger-causedvariables. © 2003 Kluwer Academic Publishers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
