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Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data

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  • Nikolsko-Rzhevskyy, Alex

Abstract

There is widespread agreement that monetary policy should be evaluated by using forward-looking Taylor rules estimated with real-time data. For the case of the U.S., this analysis can be performed using Greenbook data, but only through 2002. In countries outside the U.S., central banks do not regularly release their forecasts to the public. I propose a methodology for conducting monetary policy evaluation in real-time when forward-looking real-time data is unavailable. I then implement this methodology and estimate the resultant Taylor rules for the U.S., Canada, the U.K., and Germany. The methodology consists of calibrating models to closely replicate Greenbook forecasts, and then applying them to international real-time datasets. The results show that the U.S. output gap series is well described by quadratic detrending, while Greenbook inflation forecasts can be closely replicated using Bayesian model averaging over Autoregressive Distributed Lag models in inflation and the GDP growth rate. German and U.S. Taylor rules are characterized by inflation coefficients increasing with the forecast horizon and a positive output gap response. The U.K. and Canada interest rate reaction functions achieve maximum inflation response at middle-term horizons of about 1/2 year and the output gap coefficient enters the reaction functions insignificantly. Estimating the U.K. and Canadian Taylor rules as forward-looking is crucial, as backward-looking specifications produce nonsensical estimates. This is not the case for the U.S. and Germany.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 11352.

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Date of creation: 19 Oct 2008
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Handle: RePEc:pra:mprapa:11352

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Keywords: real-time data; Taylor rule; monetary rules; inflation forecasts; output gap;

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Citations

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Cited by:
  1. Adriana Z. Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2008. "The relative performance of alternative Taylor rule specifications," Staff Papers, Federal Reserve Bank of Dallas, Federal Reserve Bank of Dallas, issue Jun.
  2. Mandler, Martin, 2007. "Decomposing Federal Funds Rate forecast uncertainty using real-time data," MPRA Paper 13498, University Library of Munich, Germany, revised Jan 2009.
  3. Bernd Hayo & Matthias Neuenkirch, 2009. "Domestic or U.S. News: What Drives Canadian Financial Markets?," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung) 200908, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  4. Adriana Z. Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization and Monetary Policy Institute Working Paper, Federal Reserve Bank of Dallas 96, Federal Reserve Bank of Dallas.
  5. Lamarche Jean-Francois & Koustasy Zisimos, 2012. "Estimation of a Nonlinear Taylor Rule Using Real-Time U.S. Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, De Gruyter, vol. 16(5), pages 1-26, December.
  6. Mthuli Ncube & Mthokozisi M. Tshuma, 2010. "Working Paper 113 - Monetary Policy Conduct Based on Nonlinear Taylor Rule: Evidence from South Africa," Working Paper Series, African Development Bank 250, African Development Bank.

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