Towards Understanding the Normalization in Structural VAR Models
The aim of the paper is to study the nature of normalization in Structural VAR models. Noting that normalization is the integral part of identification of a model, we provide a general characterization of the normalization. In consequence some the easy–to–check conditions for a Structural VAR to be normalized are worked out. Extensive comparison between our approach and that of Waggoner and Zha (2003a) is made. Lastly we illustrate our approach with the help of five variables monetary Structural VAR model.
|Date of creation:||17 Jun 2013|
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- Waggoner, Daniel F. & Zha, Tao, 2003.
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- Daniel F. Waggoner & Tao Zha, 2000. "Likelihood-preserving normalization in multiple equation models," FRB Atlanta Working Paper 2000-8, Federal Reserve Bank of Atlanta.
- Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
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