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Monetary Policy Rules with Model and Data Uncertainty

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  • Myles Callan
  • Eric Ghysels

    ()

  • Norman R. Swanson

Abstract

We examine the prevalence of data, specification, and parameter uncertainty in the formation of simple rules which mimic monetary policy-making decisions. Our approach is to build real-time datasets, simulate a real-time policy-setting environment, and provide a set of prescriptions and diagnoses which are useful not only within the context on monetary policy rules, but also within the context of the application of real-time data to macroeconomics in general. Some of our findings can be summarized as follows. First, while our version of calibration is better than naive estimation, both are dominated by an approach to rule formation based on adaptive least squares learning using real-time data. Second, it appears that rules based on seasonally unadjusted data are more reliable than when seasonally adjusted data are used. Finally, it does not pay to use data which are too preliminary. Indeed, it appears that it would be in the best interest of policymakers to wait until some of the data uncertainty associated with preliminary data has been removed by the revision process. Although some rules require more patience than others, a prescription based on our best-performing rule points to a waiting period of 9 months for monthly data, which in turn leads to around a 50% increase in precision. Nous étudions l'impact de l'incertitude par rapport aux données, la spécification du modèle ainsi que les paramètres sur des règles de décisions de politique monétaire. Notre analyse est fondée sur le modèle de Taylor et les règles de politique monétaire qui en découlent. Nous utilisons une banque de données qui contient l'historique des données macro-économique telles qu'elles ont été publiées et révisées à travers le temps. Ainsi notre étude est en temps réel et respecte la chronologie des données que les protagonistes de la politique avaient à leur disposition à travers le temps. Nous étudions différents mécanismes de calibrage et d'apprentisage par moyen d'estimation.

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Bibliographic Info

Paper provided by CIRANO in its series CIRANO Working Papers with number 98s-40.

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Date of creation: 01 Nov 1998
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Handle: RePEc:cir:cirwor:98s-40

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Keywords: Data revision process; monetary authority credibility; predictive ability; adaptive and rational expectations; real-time data; Révision des données; crédibilité des politiques monétaires; attentes rationelles et adaptives; données en temps réel;

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Cited by:
  1. Peter Christoffersen & Eric Ghysels & Norman Swanson, 2000. "Let's Get "Real" About Using Economic Data," Econometric Society World Congress 2000 Contributed Papers 1004, Econometric Society.
  2. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
  3. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
  4. María-Dolores, Ramón & Londoño, Juan M. & Vázquez Pérez, Jesús, 2012. "The Effect of Data Revisions on the Basic New Keynesian Model," DFAEII Working Papers 2012-05, University of the Basque Country - Department of Foundations of Economic Analysis II.
  5. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting industrial production: the role of information and methods," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 227-235 Bank for International Settlements.
  6. Ruben Atoyan & Patrick Conway, 2011. "Projecting macroeconomic outcomes: Evidence from the IMF," The Review of International Organizations, Springer, vol. 6(3), pages 415-441, September.
  7. Q. Farooq Akram, 2010. "Policy analysis in real time using IMF's monetary model," Working Paper 2010/10, Norges Bank.
  8. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
  9. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
  10. Söderström, Ulf, 1999. "Should central banks be more aggressive?," Working Paper Series 84, Sveriges Riksbank (Central Bank of Sweden).
  11. Felipe Morandé Lavín & Mauricio Tejada, 2008. "Sources of Uncertainty for Conducting Monetary Policy in Chile," Working Papers wp285, University of Chile, Department of Economics.

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