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An Unobserved Components Model of the Monetary Transmission Mechanism in a Closed Economy

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  • Francis Vitek

    (University of British Columbia)

Abstract

This paper develops and estimates an unobserved components model for purposes of monetary policy analysis in a closed economy. Cyclical components are modeled as a multivariate linear rational expectations model of the monetary transmission mechanism, while trend components are modeled as unobserved components while ensuring the existence of a well defined balanced growth path. Full information maximum likelihood estimation of this unobserved components model, conditional on prior information concerning the values of trend components, provides a quantitative description of the monetary transmission mechanism in a closed economy, yields a mutually consistent set of indicators of inflationary pressure together with confidence intervals, and facilitates the generation of relatively accurate forecasts.

Suggested Citation

  • Francis Vitek, 2005. "An Unobserved Components Model of the Monetary Transmission Mechanism in a Closed Economy," Macroeconomics 0512018, University Library of Munich, Germany, revised 06 Feb 2006.
  • Handle: RePEc:wpa:wuwpma:0512018
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/0512/0512018.pdf
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    References listed on IDEAS

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    1. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    3. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, December.
    4. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809.
    5. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1228-1247, December.
    6. 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.
    7. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    8. Thomas Laubach & John C. Williams, 2003. "Measuring the Natural Rate of Interest," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1063-1070, November.
    9. Sims, Christopher A. & Zha, Tao, 2006. "Does Monetary Policy Generate Recessions?," Macroeconomic Dynamics, Cambridge University Press, vol. 10(2), pages 231-272, April.
    10. Watson, Mark W., 1989. "Recursive solution methods for dynamic linear rational expectations models," Journal of Econometrics, Elsevier, vol. 41(1), pages 65-89, May.
    11. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    12. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423.
    13. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    14. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    Cited by:

    1. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 802, University Library of Munich, Germany.
    2. Richard Harrison & George Kapetanios & Alasdair Scott & Jana Eklund, 2008. "Breaks in DSGE models," 2008 Meeting Papers 657, Society for Economic Dynamics.
    3. Vitek, Francis, 2006. "Monetary Policy Analysis in a Closed Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 797, University Library of Munich, Germany.
    4. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Closed Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 801, University Library of Munich, Germany.
    5. Vitek, Francis, 2006. "Monetary Policy Analysis in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 800, University Library of Munich, Germany.

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    More about this item

    Keywords

    Monetary policy analysis; Unobserved components model; Indicators of inflationary pressure; Monetary transmission mechanism; Forecast performance evaluation;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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