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Estimation of monetary policy preferences in a forward-looking model : a Bayesian approach

  • Pelin Ilbas

    ()

    (Center for Economic Studies, Catholic University of Leuven)

In this paper we adopt a Bayesian approach towards the estimation of the monetary policy preference parameters in a general equilibrium framework. We start from the model presented by Smets and Wouters (2003) for the euro area where, in the original set up, monetary policy behaviour is described by an empirical Taylor rule. We abandon this way of representing monetary policy behaviour and assume, instead, that monetary policy authorities optimize an intertemporal quadratic loss function under commitment. We consider two alternative specifications for the loss function. The first specification includes inflation, output gap and difference in the interest rate as target variables. The second loss function includes an additional wage inflation target. The weights assigned to the target variables in the loss functions, i.e. the preferences of monetary policy, are estimated jointly with the structural parameters in the model. The results imply that inflation variability remains the main concern of optimal monetary policy. In addition, interest rate smoothing and the output gap appear to be, to a lesser extent, important target variables as well. Comparing the marginal likelihood of the original Smets and Wouters (2003) model to our specification with optimal monetary policy indicates that the latter performs only slightly worse. Since we are faced with the time-inconsistency problem under commitment, we initialize our estimates by considering a presample period of 40 quarters. This allows us to approach, empirically, the timeless perspective framework.

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Paper provided by National Bank of Belgium in its series Working Paper Research with number 129.

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Length: 51 pages
Date of creation: Mar 2008
Date of revision:
Handle: RePEc:nbb:reswpp:200803-12
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  1. Ulf Söderström & Paul Söderlind & Anders Vredin, 2005. "New-Keynesian Models and Monetary Policy: A Re-examination of the Stylized Facts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 107(3), pages 521-546, 09.
  2. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," CEPR Discussion Papers 2139, C.E.P.R. Discussion Papers.
  3. Michael Ehrmann and Frank Smets, 2001. "Uncertain Potential Output: Implications for Monetary Policy," Computing in Economics and Finance 2001 8, Society for Computational Economics.
  4. Timothy Kam & Kirdan Lees & Philip Liu, 2006. "Uncovering The Hit-List For Small Inflation Targeters: A Bayesian Structural Analysis," ANU Working Papers in Economics and Econometrics 2006-473, Australian National University, College of Business and Economics, School of Economics.
  5. Florian Pelgrin & Michel Juillard, 2005. "Computing optimal policy functions in a timeless perspective: An application," Computing in Economics and Finance 2005 271, Society for Computational Economics.
  6. Söderlind, Paul, 1998. "Solution and Estimation of RE Macromodels with Optimal Policy," SSE/EFI Working Paper Series in Economics and Finance 256, Stockholm School of Economics.
  7. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  8. Richard Dennis, 2001. "The policy preferences of the U.S. Federal Reserve," Working Paper Series 2001-08, Federal Reserve Bank of San Francisco.
  9. Svensson, L.E.O., 1998. "Inflation Targeting as a Monetary Policy Rule," Papers 646, Stockholm - International Economic Studies.
  10. Julio J. Rotemberg & Michael Woodford, 1998. "Interest-Rate Rules in an Estimated Sticky Price Model," NBER Working Papers 6618, National Bureau of Economic Research, Inc.
  11. Sungbae An & Frank Schorfheide, 2006. "Bayesian analysis of DSGE models," Working Papers 06-5, Federal Reserve Bank of Philadelphia.
  12. Lars E. O. Svensson, 2003. "What Is Wrong with Taylor Rules? Using Judgment in Monetary Policy through Targeting Rules," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 426-477, June.
  13. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
  14. Christian Jensen & Bennett C. McCallum, 2002. "The Non-Optimality of Proposed Monetary Policy Rules Under Timeless-Perspective Commitment," NBER Working Papers 8882, National Bureau of Economic Research, Inc.
  15. Bennett T. McCallum & Edward Nelson, 2000. "Timeless Perspectives vs. Discretionary Monetary Policy In Forward-Looking Models," NBER Working Papers 7915, National Bureau of Economic Research, Inc.
  16. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
  17. Ozlale, Umit, 2003. "Price stability vs. output stability: tales of federal reserve administrations," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1595-1610, July.
  18. Alexei Onatski & Noah Williams, 2010. "Empirical and policy performance of a forward-looking monetary model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 145-176.
  19. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
  20. Richard Dennis, 2000. "Solving for optimal simple rules in rational expectations models," Working Paper Series 2000-14, Federal Reserve Bank of San Francisco.
  21. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139.
  22. Frank Smets & Rafael Wouters, 2005. "Bayesian New Neoclassical Synthesis (NNS) Models: Modern Tools for Central Banks," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 422-433, 04/05.
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