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Estimating Monetary Policy Reaction Functions Using Quantile Regressions

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  • Wolters, Maik Hendrik

Abstract

Monetary policy rule parameters are usually estimated at the mean of the interest rate distribution conditional on inflation and an output gap. This is an incomplete description of monetary policy reactions when the parameters are not uniform over the conditional distribution of the interest rate. I use quantile regressions to estimate parameters over the whole conditional distribution of the Federal Funds Rate. Inverse quantile regressions are applied to deal with endogeneity. Realtime data of inflation forecasts and the output gap are used. I find significant and systematic variations of parameters over the conditional distribution of the interest rate.

Suggested Citation

  • Wolters, Maik Hendrik, 2010. "Estimating Monetary Policy Reaction Functions Using Quantile Regressions," MPRA Paper 23857, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:23857
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    Cited by:

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    2. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.
    3. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," AMSE Working Papers 1716, Aix-Marseille School of Economics, France.
    4. Ravn, Søren Hove, 2014. "Asymmetric monetary policy towards the stock market: A DSGE approach," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 24-41.
    5. Luís Francisco Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2014. "Analyzing the Taylor Rule with Wavelet Lenses," NIPE Working Papers 18/2014, NIPE - Universidade do Minho.
    6. Gabriela Bezerra Medeiros & Marcelo Savino Portugal & Edilean Kleber da Silva Bejarano Aragón, 2017. "Endogeneity and nonlinearities in Central Bank of Brazil’s reaction functions: an inverse quantile regression approach," Empirical Economics, Springer, vol. 53(4), pages 1503-1527, December.
    7. Tae-Hwan Kim & Christophe Muller, 2013. "A Test for Endogeneity in Conditional Quantiles," Working Papers halshs-00854527, HAL.
    8. Shen, Chung-Hua & Lin, Kun-Li & Guo, Na, 2016. "Hawk or dove: Switching regression model for the monetary policy reaction function in China," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 94-111.
    9. Sardor Sadykov, 2018. "The Modified Taylor Rule For Bank Of Uzbekistan On The Basis Of Mode Switching," Economics and Management, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 14(2), pages 100-110.
    10. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Christis Hassapis, 2019. "Monetary Policy Reaction to Uncertainty in Japan: Evidence from a Quantile-on-Quantile Interest Rate Rule," Working Papers 201929, University of Pretoria, Department of Economics.
    11. 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.
    12. Karamti, Chiraz, 2019. "Lopsided effects of telecom reforms on mobile markets in the enlarged EU: Evidence from dynamic quantile model," Telecommunications Policy, Elsevier, vol. 43(3), pages 238-261.
    13. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    14. Kiesel, Konstantin & Wolters, Maik H., 2014. "Estimating monetary policy rules when the zero lower bound on nominal interest rates is approached," Kiel Working Papers 1898, Kiel Institute for the World Economy (IfW).
    15. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Won Joong Kim, 2018. "Monetary Policy Reaction Functions of the TICKs: A Quantile Regression Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(15), pages 3552-3565, December.
    16. William Miles & Sam Schreyer, 2012. "Is monetary policy non-linear in Indonesia, Korea, Malaysia, and Thailand? A quantile regression analysis," Asian-Pacific Economic Literature, Asia Pacific School of Economics and Government, The Australian National University, vol. 26(2), pages 155-166, November.
    17. Jau-er Chen & Masanori Kashiwagi, 2017. "The Japanese Taylor rule estimated using censored quantile regressions," Empirical Economics, Springer, vol. 52(1), pages 357-371, February.
    18. Aguiar-Conraria, Luis & Martins, Manuel M.F. & Soares, Maria Joana, 2018. "Estimating the Taylor rule in the time-frequency domain," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 122-137.
    19. Apergis, Nicholas & Christou, Christina, 2015. "The behaviour of the bank lending channel when interest rates approach the zero lower bound: Evidence from quantile regressions," Economic Modelling, Elsevier, vol. 49(C), pages 296-307.
    20. 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.
    21. Chou, K.W., 2019. "Re-examining the time-varying nature and determinants of exchange rate pass-through into import prices," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 331-351.
    22. Zheng Qiao & Yangshu Liu, 2017. "Open Market Operation Effectiveness in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(8), pages 1706-1719, August.
    23. Sebastian Gechert & Ansgar Rannenberg, 2014. "Are Fiscal Multipliers Regime-Dependent? A Meta Regression Analysis," IMK Working Paper 139-2014, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    24. 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 Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    25. Xiaochun Liu, 2018. "How is the Taylor Rule Distributed under Endogenous Monetary Regimes?," International Review of Finance, International Review of Finance Ltd., vol. 18(2), pages 305-316, June.

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    More about this item

    Keywords

    monetary policy rules; IV quantile regression; real-time data;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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