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Monetary Policy Inertia: More a Fiction than a fact?

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  • Consolo, Agostino
  • Favero, Carlo A.

Abstract

Empirical estimates of monetary policy reaction functions feature a very high estimated degree of monetary policy inertia. This evidence is very hard to reconcile with the alternative evidence of low predictability of monetary policy rates. In this paper we examine the potential relevance of the problem of weak instruments to correctly identify the degree of monetary policy inertia in forward looking monetary policy reaction function of the type originally proposed by Taylor (1993). After appropriately diagnosing and taking care of the weak instruments problem, we find an estimated degree of policy inertia which is significantly lower than the common value in the empirical literature on monetary policy rules.

Suggested Citation

  • Consolo, Agostino & Favero, Carlo A., 2009. "Monetary Policy Inertia: More a Fiction than a fact?," CEPR Discussion Papers 7341, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7341
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    9. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    10. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
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    Cited by:

    1. Ferland, René & Gauthier, Geneviève & Lalancette, Simon, 2010. "A regime-switching term structure model with observable state variables," Finance Research Letters, Elsevier, vol. 7(2), pages 103-109, June.
    2. Kobayashi Teruyoshi, 2010. "Policy Irreversibility and Interest Rate Smoothing," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-29, October.
    3. repec:eee:jimfin:v:77:y:2017:i:c:p:99-116 is not listed on IDEAS
    4. de Sá, Rodrigo & Savino Portugal, Marcelo, 2015. "Central bank and asymmetric preferences: An application of sieve estimators to the U.S. and Brazil," MPRA Paper 72746, University Library of Munich, Germany.
    5. Glenn D. Otto & Graham M. Voss, 2014. "Flexible inflation forecast targeting: Evidence from Canada," Canadian Journal of Economics, Canadian Economics Association, vol. 47(2), pages 398-421, May.
    6. Matthew Greenwood-Nimmo & Youngcheol Shin, 2011. "Shifting Preferences at the Fed: Evidence from Rolling Dynamic Multipliers and Impulse Response Analysis," Working Papers 2011-057, Madras School of Economics,Chennai,India.
    7. David Cobham & Yue Kang, 2013. "Time Horizons and Smoothing in the Bank of England's Reaction Function: The Contrast Between the Standard GMM and Ex Ante Forecast Approaches," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 662-679, October.
    8. Nucci, Francesco & Riggi, Marianna, 2013. "Performance pay and changes in U.S. labor market dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2796-2813.
    9. Favaretto, Federico & Masciandaro, Donato, 2016. "Doves, hawks and pigeons: Behavioral monetary policy and interest rate inertia," Journal of Financial Stability, Elsevier, vol. 27(C), pages 50-58.
    10. Bauer, Christian & Neuenkirch, Matthias, 2017. "Forecast uncertainty and the Taylor rule," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 99-116.
    11. Bayar Omer, 2015. "An ordered probit analysis of monetary policy inertia," The B.E. Journal of Macroeconomics, De Gruyter, vol. 15(2), pages 705-726, July.
    12. Zhang, Chengsi & Dang, Chao, 2018. "Is Chinese monetary policy forward-looking?," BOFIT Discussion Papers 6/2018, Bank of Finland, Institute for Economies in Transition.
    13. Olivier Coibion & Yuriy Gorodnichenko, 2012. "Why Are Target Interest Rate Changes So Persistent?," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(4), pages 126-162, October.
    14. Christian Aubin & Ibrahima Diouf & Dominique Pepin, 2010. "Inertie De La Politique Monétaire Dans La Zone Euro : Le Rôle De L'Hétérogénéité," Post-Print hal-00960030, HAL.
    15. repec:aea:jecper:v:31:y:2017:i:2:p:59-86 is not listed on IDEAS
    16. Inoue, Atsushi & Rossi, Barbara, 2011. "Testing for weak identification in possibly nonlinear models," Journal of Econometrics, Elsevier, vol. 161(2), pages 246-261, April.
    17. Nicolas Pinkwart, 2013. "Quantifying The European Central Bank'S Interest Rate Smoothing Behavior," Manchester School, University of Manchester, vol. 81(4), pages 470-492, July.
    18. de Sá, Rodrigo & Portugal, Marcelo S., 2015. "Central bank and asymmetric preferences: An application of sieve estimators to the U.S. and Brazil," Economic Modelling, Elsevier, vol. 51(C), pages 72-83.

    More about this item

    Keywords

    Monetary Policy Rulkes; Weak Identification;

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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