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

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Author Info
Jaromír Beneš () (Czech National Bank, Monetary and Statistics Department, Prague, Czech Republic)
David Vávra (Czech National Bank, Monetary and Statistics Department, Prague, Czech Republic)

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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.

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Publisher Info
Paper provided by European Central Bank in its series Working Paper Series with number 549.

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Length: 33 pages
Date of creation: Nov 2005
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Handle: RePEc:ecb:ecbwps:20050549

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Related research
Keywords: Business cycle; inflation; eigenvalues; filtering; Beveridge-Nelson decomposition; time series analysis.;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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References listed on IDEAS
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