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Nonlinear Taylor rules: evidence from a large dataset

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posted on 2018-05-08, 10:07 authored by Jun Ma, Eric Olson, Mark Wohar
In this paper we estimate nonlinear Taylor rules over the 1986-2008 sample time period and augment the traditional Taylor rule by including principal components to better model Federal Reserve policy. Including principal components is useful in that they extract information about the overall economy from multiple economic indicators in a statistically optimal way. Additionally, given that uncertainty may influence Federal Reserve decisions, we incorporate an uncertainty index in the reaction function of the Federal Reserve. We find substantial evidence that the Federal Reserve responded to increases in macroeconomic uncertainty by cutting the Federal Funds rate over the sample period. We also find evidence that the Federal Reserve responded aggressively to increases in capacity utilization, especially when the inflation rate was above 2%.

History

School

  • Business and Economics

Department

  • Business

Published in

Studies in Nonlinear Dynamics and Econometrics

Volume

22

Issue

1

Citation

MA, J., OLSON, E. and WOHAR, M.E., 2018. Nonlinear Taylor rules: evidence from a large dataset. Studies in Nonlinear Dynamics and Econometrics, 22 (1), 20160082.

Publisher

© Walter de Gruyter

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2018

Notes

This paper was accepted for publication in the journal Studies in Nonlinear Dynamics and Econometrics and the definitive published version is available at https://doi.org/10.1515/snde-2016-0082

ISSN

1081-1826

eISSN

1558-3708

Language

  • en

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