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Forecast Uncertainty and the Taylor Rule

Listed author(s):
  • Christian Bauer
  • Matthias Neuenkirch

In this paper, we derive a modification of a forward-looking Taylor rule, which integrates two variables measuring the uncertainty of inflation and GDP growth forecasts into an otherwise standard New Keynesian model. We show that certainty-equivalence in New Keynesian models is a consequence of log-linearization and that a second-order Taylor approximation leads to a reaction function which includes the uncertainty of macroeconomic expectations. To test the model empirically, we use the standard deviation of individual forecasts around the median Consensus Forecast as proxy for forecast uncertainty. Our sample covers the euro area, Sweden, and the United Kingdom and the period 1992Q4-2014Q2. We find that while all three central banks react significantly to inflation forecast uncertainty by reducing their policy rates in times of higher inflation expectation uncertainty with an average effect of more than 25 basis points, they do not have significant reactions to GDP growth forecast uncertainty. We conclude with some implications for optimal monetary policy rules and central bank watchers.

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File URL: http://www.uni-trier.de/fileadmin/fb4/prof/VWL/EWF/Research_Papers/2015-05.pdf
File Function: Third version, 2017
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Paper provided by University of Trier, Department of Economics in its series Research Papers in Economics with number 2015-05.

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Length: 36 pages
Date of creation: 2015
Handle: RePEc:trr:wpaper:201505
Contact details of provider: Postal:
B IV, VWL, D-54286 Trier

Phone: +49 (0) 651 201-2739
Fax: +49 (0) 651 201-3934
Web page: http://www.uni-trier.de/index.php?id=2118

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