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Monetary policy decisions by the world's central banks using real-time data

  • Klaus Schmidt-Hebbel
  • Francisco Muñoz

This paper contributes to the empirical understanding of monetary policy in five dimensions. First, specifiying a generalized Taylor equation that nests backward and forward-looking inflation and activity variables in setting policy rates. Second, using real-time data. Third, estimating the model on a world panel of monthly 1994-2011 data for 28 advanced and emerging economies. Fourth, using alternative panel data estimators to test for robustness. Fifth, testing for differences in monetary policy over time and across country groups. The findings are very supportive of the nested model and generally show that the Taylor principle is satisfied by the world's central banks.

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Paper provided by Instituto de Economia. Pontificia Universidad Católica de Chile. in its series Documentos de Trabajo with number 426.

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Date of creation: 2012
Date of revision:
Handle: RePEc:ioe:doctra:426
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  1. repec:rwi:repape:0166 is not listed on IDEAS
  2. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  3. George Kapetanios & M. Hashem Pesaran & Takashi Yamagata, 2006. "Panels with Nonstationary Multifactor Error Structures," CESifo Working Paper Series 1788, CESifo Group Munich.
  4. Francis Teal & Markus Eberhardt, 2010. "Productivity Analysis in Global Manufacturing Production," Economics Series Working Papers 515, University of Oxford, Department of Economics.
  5. Troy Davig & Eric M. Leeper, 2007. "Generalizing the Taylor Principle," American Economic Review, American Economic Association, vol. 97(3), pages 607-635, June.
  6. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  7. Brian Sack & Volker Wieland, 1999. "Interest-rate smoothing and optimal monetary policy: a review of recent empirical evidence," Finance and Economics Discussion Series 1999-39, Board of Governors of the Federal Reserve System (U.S.).
  8. Markus Eberhardt & Christian Helmers & Hubert Strauss, . "Do Spillovers Matter When Estimating Private Returns to R&D?," Discussion Papers 11/22, University of Nottingham, GEP.
  9. M. Hashem Pesaran, 2004. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," CESifo Working Paper Series 1331, CESifo Group Munich.
  10. George A. Kahn, 2012. "The Taylor Rule and the Practice of Central Banking," Book Chapters, in: Evan F. Koenig & Robert Leeson & George A. Kahn (ed.), The Taylor Rule and the Transformation of Monetary Policy, chapter 3 Hoover Institution, Stanford University.
  11. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
  12. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages S63-S79, October.
  13. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
  14. Frank Smets, 1998. "Output gap uncertainty: does it matter for the Taylor rule?," BIS Working Papers 60, Bank for International Settlements.
  15. Glenn D. Rudebusch, 2006. "Monetary Policy Inertia: Fact or Fiction?," International Journal of Central Banking, International Journal of Central Banking, vol. 2(4), December.
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