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Uncertainty and Monetary Policy Rules in the United States

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  • Christopher Martin
  • Costas Milas

Abstract

This paper analyses the impact of uncertainty about the true state of the economy on monetary policy rules in the US since the early 1980s. Extending the Taylor rule to allow for this type of uncertainty, we find evidence that the predictions of the theoretical literature on responses to uncertainty are reflected in the behaviour of policymakers, suggesting that policymakers are adhering to prescriptions for optimal policy. We find that the impact of uncertainty was most marked in 1983, when uncertainty increased interest rates by up to 140 basis points, in 1989-90, when uncertainty increased interest rates by up to 50 basis points and in 1996-2001 when uncertainty reduced interest rates by up to 50 basis points over five years.

Suggested Citation

  • Christopher Martin & Costas Milas, 2005. "Uncertainty and Monetary Policy Rules in the United States," Economics and Finance Discussion Papers 05-22, Economics and Finance Section, School of Social Sciences, Brunel University.
  • Handle: RePEc:bru:bruedp:05-22
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    Cited by:

    1. Greene, William H. & Gillman, Max & Harris, Mark N. & Spencer, Christopher, 2013. "The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy," CEI Working Paper Series 2013-04, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    2. Flamini Alessandro & Milas Costas, 2011. "Real-Time Optimal Monetary Policy with Undistinguishable Model Parameters and Shock Processes Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-43, March.
    3. Bauer, Christian & Neuenkirch, Matthias, 2017. "Forecast uncertainty and the Taylor rule," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 99-116.
    4. Cinzia Alcidi & Alessandro Flamini & Andrea Fracasso, 2011. "Policy Regime Changes, Judgment and Taylor rules in the Greenspan Era," Economica, London School of Economics and Political Science, vol. 78(309), pages 89-107, January.
    5. Ruthira Naraidoo & Leroi Raputsoane, 2015. "Financial markets and the response of monetary policy to uncertainty in South Africa," Empirical Economics, Springer, vol. 49(1), pages 255-278, August.
    6. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    7. Christou Christina & Naraidoo Ruthira & Gupta Rangan, 2020. "Conventional and unconventional monetary policy reaction to uncertainty in advanced economies: evidence from quantile regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-17, June.
    8. Belderbos, Rene & Ikeuchi, Kenta & Fukao, Kyoji & Kim, Young Gak & Kwon, Hyeog Ug, 2013. "Plant Productivity Dynamics and Private and Public R&D Spillovers: Technological, Geographic and Relational Proximity," CEI Working Paper Series 2013-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    9. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Christis Hassapis, 2022. "Monetary policy reaction to uncertainty in Japan: Evidence from a quantile‐on‐quantile interest rate rule," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2041-2053, April.

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    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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