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Eigenvalue filtering in VAR models with application to the Czech business cycle

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  • Beneš, Jaromír
  • Vávra, David

Abstract

We propose the method of eigenvalue filtering as a new tool to extract time series subcomponents (such as business-cycle or irregular) defined by properties of the underlying eigenvalues. We logically extend the Beveridge-Nelson decomposition of the VAR time-series models focusing on the transient component. We introduce the canonical state-space representation of the VAR models to facilitate this type of analysis. We illustrate the eigenvalue filtering by examining a stylized model of inflation determination estimated on the Czech data.We characterize the estimated components of CPI, WPI and import inflations, together with the real production wage and real output, survey their basic properties, and impose an identification scheme to calculate the structural innovations. We test the results in a simple bootstrap simulation experiment. We find two major areas for further research: first, verifying and improving the robustness of the method, and second, exploring the method’s potential for empirical validation of structural economic models. JEL Classification: C32, E32

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0549.

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Date of creation: Nov 2005
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Handle: RePEc:ecb:ecbwps:20050549

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Keywords: Beveridge-Nelson decomposition; business cycle; eigenvalues; filtering; inflation; time series analysis;

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  1. Charles Nelson & Eric Zivot, 2000. "Why are Beveridge-Nelson and Unobserved-Component Decompositions of GDP so Different?," Econometric Society World Congress 2000 Contributed Papers 0692, Econometric Society.
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  11. Hoffmann, Mathias, 2000. "Long run recursive VAR models and QR decompositions," Discussion Paper Series In Economics And Econometrics 0015, Economics Division, School of Social Sciences, University of Southampton.
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