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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- Uhlig, Harald, 1999.
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2137, C.E.P.R. Discussion Papers.
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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.
- Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2008.
"Structural vector autoregressions: theory of identification and algorithms for inference,"
FRB Atlanta Working Paper
2008-18, Federal Reserve Bank of Atlanta.
- Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
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