IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/23857.html
   My bibliography  Save this paper

Estimating Monetary Policy Reaction Functions Using Quantile Regressions

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/23857/2/MPRA_paper_23857.pdf
    File Function: original version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Amemiya, Takeshi, 1982. "Two Stage Least Absolute Deviations Estimators," Econometrica, Econometric Society, vol. 50(3), pages 689-711, May.
    2. Adam, Klaus & Billi, Roberto M., 2006. "Optimal Monetary Policy under Commitment with a Zero Bound on Nominal Interest Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(7), pages 1877-1905, October.
    3. Orphanides, Athanasios & Wieland, Volker, 2000. "Efficient Monetary Policy Design near Price Stability," Journal of the Japanese and International Economies, Elsevier, vol. 14(4), pages 327-365, December.
    4. Kato, Ryo & Nishiyama, Shin-Ichi, 2005. "Optimal monetary policy when interest rates are bounded at zero," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 97-133, January.
    5. Florio, Anna, 2006. "Asymmetric interest rate smoothing: The Fed approach," Economics Letters, Elsevier, vol. 93(2), pages 190-195, November.
    6. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    7. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    8. John B. Taylor, 2007. "Housing and Monetary Policy," NBER Working Papers 13682, National Bureau of Economic Research, Inc.
    9. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2009. "The Taylor Principle and Monetary Policy Approaching a Zero Bound on Nominal Rates: Quantile Regression Results for the United States and Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1705-1723, December.
    10. Sugo, Tomohiro & Teranishi, Yuki, 2005. "The optimal monetary policy rule under the non-negativity constraint on nominal interest rates," Economics Letters, Elsevier, vol. 89(1), pages 95-100, October.
    11. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
    12. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    13. Athanasios Orphanides & Volker W. Wieland, 2008. "Economic projections and rules of thumb for monetary policy," Review, Federal Reserve Bank of St. Louis, vol. 90(Jul), pages 307-324.
    14. Helle Bunzel & Walter Enders, 2010. "The Taylor Rule and "Opportunistic" Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(5), pages 931-949, August.
    15. Clarida, Richard & Gali, Jordi & Gertler, Mark, 1998. "Monetary policy rules in practice Some international evidence," European Economic Review, Elsevier, vol. 42(6), pages 1033-1067, June.
    16. Castelnuovo, Efrem, 2003. "Taylor rules, omitted variables, and interest rate smoothing in the US," Economics Letters, Elsevier, vol. 81(1), pages 55-59, October.
    17. Qu, Zhongjun, 2008. "Testing for structural change in regression quantiles," Journal of Econometrics, Elsevier, vol. 146(1), pages 170-184, September.
    18. Dolado, Juan J. & Maria-Dolores, Ramon & Naveira, Manuel, 2005. "Are monetary-policy reaction functions asymmetric?: The role of nonlinearity in the Phillips curve," European Economic Review, Elsevier, vol. 49(2), pages 485-503, February.
    19. Laurence H. Meyer & Eric T. Swanson & Volker W. Wieland, 2001. "NAIRU Uncertainty and Nonlinear Policy Rules," American Economic Review, American Economic Association, vol. 91(2), pages 226-231, May.
    20. Orphanides, Athanasios, 2004. "Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 151-175, April.
    21. Rudebusch, Glenn D., 2002. "Term structure evidence on interest rate smoothing and monetary policy inertia," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1161-1187, September.
    22. English William B. & Nelson William R. & Sack Brian P., 2003. "Interpreting the Significance of the Lagged Interest Rate in Estimated Monetary Policy Rules," The B.E. Journal of Macroeconomics, De Gruyter, vol. 3(1), pages 1-18, April.
    23. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    24. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    25. William Poole, 2007. "Understanding the Fed," Review, Federal Reserve Bank of St. Louis, vol. 89(Jan), pages 3-14.
    26. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    27. Gerlach-Kristen Petra, 2004. "Interest-Rate Smoothing: Monetary Policy Inertia or Unobserved Variables?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-19, March.
    28. Powell, James L, 1983. "The Asymptotic Normality of Two-Stage Least Absolute Deviations Estimators," Econometrica, Econometric Society, vol. 51(5), pages 1569-1575, September.
    29. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    30. Cukierman Alex & Muscatelli Anton, 2008. "Nonlinear Taylor Rules and Asymmetric Preferences in Central Banking: Evidence from the United Kingdom and the United States," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-31, February.
    31. Eric Schaling, 1999. "The non-linear Phillips curve and inflation forecast targeting," Bank of England working papers 98, Bank of England.
    32. Pau Rabanal, 2004. "Monetary Policy Rules and the U.S. Business Cycle; Evidence and Implications," IMF Working Papers 04/164, International Monetary Fund.
    33. repec:fip:fedgsq:y:2010:x:4 is not listed on IDEAS
    34. John B. Taylor, "undated". "Housing and monetary policy," Proceedings - Economic Policy Symposium - Jackson Hole y:2007:p:463-476, Federal Reserve Bank of Kansas City.
    35. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    36. Surico, Paolo, 2007. "The Fed's monetary policy rule and U.S. inflation: The case of asymmetric preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 305-324, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Ravn, Søren Hove, 2014. "Asymmetric monetary policy towards the stock market: A DSGE approach," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 24-41.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    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. 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.
    16. Tae-Hwan Kim & Christophe Muller, 2013. "A Test for Endogeneity in Conditional Quantiles," AMSE Working Papers 1342, Aix-Marseille School of Economics, France, revised Aug 2013.
    17. 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.
    18. 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.
    19. 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.
    20. 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].
    21. 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.
    22. 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.
    23. 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.

    More about this item

    Keywords

    monetary policy rules; IV quantile regression; real-time data;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:23857. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.