Kociecki, Andrzej (2013): Towards Understanding the Normalization in Structural VAR Models.
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Abstract
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.
Item Type: | MPRA Paper |
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Original Title: | Towards Understanding the Normalization in Structural VAR Models |
Language: | English |
Keywords: | Normalization, Identification, Impulse Response Function |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C30 - General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation |
Item ID: | 47645 |
Depositing User: | Andrzej Kociecki |
Date Deposited: | 18 Jun 2013 13:16 |
Last Modified: | 28 Sep 2019 22:30 |
References: | Hamilton, J.D., D.F. Waggoner and T. Zha (2007), “Normalization in Econometrics”, Econometric Reviews, 26, pp. 221–252. Harville, D.A. (1997), Matrix Algebra from a Statistician’s Perspective, Springer–Verlag, New York. Kim, S. (1999), “Do Monetary Policy Shocks Matter in the G–7 Countries? Using Common Identifying Assumptions about Monetary Policy Across Countries”, Journal of International Economics, 48, pp. 387–412. Rohn, J. (1989), “Systems of Linear Interval Equations”, Linear Algebra and Its Applications, 126, pp. 39–78. Rubio–Ramírez, J.F, D.F. Waggoner and T. Zha (2010), “Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference”, The Review of Economic Studies, 77, pp. 665–696. Seber, G.A.F (2008), A Matrix Handbook for Statisticians, John Wiley & Sons, Inc., Hoboken, New Jersey. Uhlig, H. (2005), “What Are the Effects of Monetary Policy on Output? Results From an Agnostic Identification Procedure,” Journal of Monetary Economics, 52, pp. 381–419. Waggoner, D.F., and T. Zha (2003a), “Likelihood Preserving Normalization in Multiple Equation Models”, Journal of Econometrics, 114, pp. 329–347. Waggoner, D.F., and T. Zha (2003b), “A Gibbs Sampler for Structural Vector Autoregressions”, Journal of Economic Dynamics and Control, 28, pp. 349–366. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/47645 |