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Parameter Uncertainty And Nonlinear Monetary Policy Rules

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  • Tillmann, Peter

Abstract

Empirical evidence suggests that the instrument rule describing the interest rate–setting behavior of the Federal Reserve is nonlinear. This paper shows that optimal monetary policy under parameter uncertainty can motivate this pattern. If the central bank is uncertain about the slope of the Phillips curve and follows a min–max strategy to formulate policy, the interest rate reacts more strongly to inflation when inflation is further away from target. The reason is that the worst case the central bank takes into account is endogenous and depends on the inflation rate and the output gap. As inflation increases, the worst-case perception of the Phillips curve slope becomes larger, thus requiring a stronger interest rate adjustment. Empirical evidence supports this form of nonlinearity for post-1982 U.S. data.

Suggested Citation

  • Tillmann, Peter, 2011. "Parameter Uncertainty And Nonlinear Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 15(02), pages 184-200, April.
  • Handle: RePEc:cup:macdyn:v:15:y:2011:i:02:p:184-200_99
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    Cited by:

    1. Creel, Jérôme & Hubert, Paul, 2015. "Has Inflation Targeting Changed The Conduct Of Monetary Policy?," Macroeconomic Dynamics, Cambridge University Press, vol. 19(01), pages 1-21, January.
    2. Luís Francisco Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, "undated". "Analyzing the Taylor Rule with Wavelet Lenses," NIPE Working Papers 18/2014, NIPE - Universidade do Minho.
    3. Roth, Markus & Bursian, Dirk, 2012. "Taylor rule cross-checking and selective monetary policy adjustment," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62078, Verein für Socialpolitik / German Economic Association.
    4. repec:spr:empeco:v:53:y:2017:i:4:d:10.1007_s00181-016-1195-0 is not listed on IDEAS
    5. Bursian, Dirk & Roth, Markus, 2013. "Optimal policy and taylor rule cross-checking under parameter uncertainty," SAFE Working Paper Series 30, Research Center SAFE - Sustainable Architecture for Finance in Europe, Goethe University Frankfurt.
    6. Neuenkirch, Matthias & Tillmann, Peter, 2014. "Inflation targeting, credibility, and non-linear Taylor rules," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 30-45.
    7. White, Halbert & Pettenuzzo, Davide, 2014. "Granger causality, exogeneity, cointegration, and economic policy analysis," Journal of Econometrics, Elsevier, vol. 178(P2), pages 316-330.
    8. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2016. "Estimating the Taylor Rule in the Time-Frequency Domain," CEF.UP Working Papers 1404, Universidade do Porto, Faculdade de Economia do Porto.
    9. repec:spr:joevec:v:27:y:2017:i:5:d:10.1007_s00191-017-0522-8 is not listed on IDEAS
    10. André P. Calmon & Thomas Vallée & João B. R. Do Val, 2009. "Monetary policy as a source of uncertainty," Working Papers hal-00422454, HAL.
    11. Gabriela Bezerra De Medeiros & Marcelo Savino Portugal & Edilean Kleber Da Silva Bejarano Aragon, 2016. "Endogeneity And Nonlinearities In Central Bank Of Brazil’S Reaction Functions: An Inverse Quantile Regression Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 061, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Thanaset Chevapatrakul & Juan Paez-Farrell, 2014. "Monetary Policy Reaction Functions in Small Open Economies: a Quantile Regression Approach," Manchester School, University of Manchester, vol. 82(2), pages 237-256, March.

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