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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ECB Working Paper ; No. 549

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Business Fluctuations; Cycles
• Subject: Beveridge-Nelson decomposition ; business cycle ; eigenvalues ; filtering ; inflation ; time series analysis ; Konjunktur ; Zeitreihenanalyse ; VAR-Modell ; Tschechien

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Beneš, Jaromír ; Vávra, David
• Event: Veröffentlichung
• (who): European Central Bank (ECB)
• (where): Frankfurt a. M.
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/152983
• Last update: 10.03.2025, 11:42 AM CET