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Eigenvalue Decomposition of Time Series with Application to the Czech Business Cycle

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  • Jaromir Benes
  • David Vavra

Abstract

We follow a Beveridge-Nelson like time series decomposition method (into trend, business cycle and irregular components), and examine a stylized model of price inflation determination using the Czech data. We characterize the estimated components of CPI, IPPI and import inflations, together with the real production wage and real output, and survey their basic correlation properties; furthermore we compute structural innovations imposing restrictions on their long-run effects, draw the impulse responses, and test the results by means of bootstrap simulation. We conclude that major room for further refinement of the research is found in two areas, First, from an economist's perspective, in the construction of real marginal cost indicators, and second, from a statistiacian's perspective, in further investigation of the robustness of the method.

Suggested Citation

  • Jaromir Benes & David Vavra, 2004. "Eigenvalue Decomposition of Time Series with Application to the Czech Business Cycle," Working Papers 2004/08, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2004/08
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    References listed on IDEAS

    as
    1. Mr. Jaromir Benes & Mr. Papa M N'Diaye, 2004. "A Multivariate Filter for Measuring Potential Output and the NAIRU Application to the Czech Republic," IMF Working Papers 2004/045, International Monetary Fund.
    2. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    3. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    4. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    5. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    6. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    7. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    8. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    9. Hoffmann, Mathias, 2001. "Long run recursive VAR models and QR decompositions," Economics Letters, Elsevier, vol. 73(1), pages 15-20, October.
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    More about this item

    Keywords

    bootstrap; business cycle; inflation; structural VAR; time series decomposition;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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