Forecast Uncertainty and the Taylor Rule

Christian Bauer and Matthias Neuenkirch

No 2015-05, Research Papers in Economics from University of Trier, Department of Economics

Abstract: 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.

Keywords: Certainty-Equivalence; Consensus Forecasts; Forecast Uncertainty; Global Financial Crisis; Optimal Monetary Policy; Taylor Rule (search for similar items in EconPapers)
JEL-codes: E52 E58 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2015
New Economics Papers: this item is included in nep-cba, nep-for, nep-mac and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Forecast uncertainty and the Taylor rule (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:trr:wpaper:201505

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