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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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File URL: http://www.economia.puc.cl/docs/dt_426.pdf
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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
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Handle: RePEc:ioe:doctra:426
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  1. George Kapetanios & M. Hashem Pesaran & Takashi Yamagata, 2006. "Panels with Nonstationary Multifactor Error Structures," Working Papers 569, Queen Mary University of London, School of Economics and Finance.
  2. 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.).
  3. Troy Davig & Eric M. Leeper, 2005. "Generalizing the Taylor Principle," NBER Working Papers 11874, National Bureau of Economic Research, Inc.
  4. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
  5. 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.
  6. Francis Teal & Markus Eberhardt, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," Economics Series Working Papers WPS/2008-12, University of Oxford, Department of Economics.
  7. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
  8. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  9. Ansgar Belke & Jens Klose, 2010. "(How) Do the ECB and the Fed React to Financial Market Uncertainty?: The Taylor Rule in Times of Crisis," Discussion Papers of DIW Berlin 972, DIW Berlin, German Institute for Economic Research.
  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. Glenn D. Rudebusch, 2005. "Monetary policy inertia: fact or fiction?," Working Paper Series 2005-19, Federal Reserve Bank of San Francisco.
  12. G. Kapetanios & M. Hashem Pesaran & T. Yamagata, 2010. "Panels with nonstationary multifactor error structures," Post-Print peer-00768190, HAL.
  13. 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.
  14. 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.
  15. Frank Smets, 2002. "Output gap uncertainty: Does it matter for the Taylor rule?," Empirical Economics, Springer, vol. 27(1), pages 113-129.
  16. Markus Eberhardt & Francis Teal, 2010. "Productivity Analysis in Global Manufacturing Production," DEGIT Conference Papers c015_019, DEGIT, Dynamics, Economic Growth, and International Trade.
  17. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
  18. Markus Eberhardt & Francis Teal, 2008. "Modeling Technology and Technological Change in Manufacturing: How do Countries Differ?," CSAE Working Paper Series 2008-12, Centre for the Study of African Economies, University of Oxford.
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