Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/125830
Authors: 
Zadrozny, Peter A.
Year of Publication: 
2015
Series/Report no.: 
CFS Working Paper Series 526
Abstract: 
Chen and Zadrozny (1998) developed the linear extended Yule-Walker (XYW) method for determining the parameters of a vector autoregressive (VAR) model with available covariances of mixed-frequency observations on the variables of the model. If the parameters are determined uniquely for available population covariances, then, the VAR model is identified. The present paper extends the original XYW method to an extended XYW method for determining all ARMA parameters of a vector autoregressive moving-average (VARMA) model with available covariances of single- or mixed-frequency observations on the variables of the model. The paper proves that under conditions of stationarity, regularity, miniphaseness, controllability, observability, and diagonalizability on the parameters of the model, the parameters are determined uniquely with available population covariances of single- or mixed-frequency observations on the variables of the model, so that the VARMA model is identified with the single- or mixed-frequency covariances.
Subjects: 
block-Vandermonde eigenvectors of block-companion state-transition
matrix of state-space representation
matrix spectral factorization
JEL: 
C32
C80
Document Type: 
Working Paper

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