IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/201929.html
   My bibliography  Save this paper

Monetary Policy Reaction to Uncertainty in Japan: Evidence from a Quantile-on-Quantile Interest Rate Rule

Author

Listed:
  • Christina Christou

    () (Open University of Cyprus, School of Economics and Finance, 2220 Latsia, Cyprus.)

  • Ruthira Naraidoo

    () (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Christis Hassapis

    () (Department of Economics, University of Cyprus, 1678 Nicosia, Cyprus)

Abstract

Japan’s episodes of lower bound of interest rates together with macroeconomic uncertainty for over the past two decades stands as a tremendous hurdle for the estimation of Taylor-type rule models. We demarcate our study from previous literature by conducting the estimations not only at various points on the conditional distribution of the interest rate but also at various quantiles of an additional regressor on top of inflation and output, viz., an uncertainty measure, by adopting a quantile nonseparable triangular system estimation. The results show that the reaction to uncertainty seems to have substituted the Bank’s reaction to inflation and output, lending support to the Brainard attenuation principle. In essence, faced with higher uncertainty, the monetary authority reacts by cutting (attenuating) its policy rate across all quantiles of uncertainty at all conditional quantiles of interest rate, with an increased response of the Bank of Japan to uncertainty at its lower quantiles when interest rate is at its lower conditional quantiles. A possible explanation is the greater concern of getting out from the lower bounds of interest rate.

Suggested Citation

  • 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.
  • Handle: RePEc:pre:wpaper:201929
    as

    Download full text from publisher

    File URL: http://www.up.ac.za/media/shared/61/WP/wp_2019_29.zp171140.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. 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.
    3. Ruge-Murcia, Francisco J., 2003. "Does the Barro-Gordon model explain the behavior of US inflation? A reexamination of the empirical evidence," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1375-1390, September.
    4. 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.
    5. Jun, Sung Jae, 2009. "Local structural quantile effects in a model with a nonseparable control variable," Journal of Econometrics, Elsevier, vol. 151(1), pages 82-97, July.
    6. 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.
    7. Alex Cukierman & Stefan Gerlach, 2003. "The inflation bias revisited: theory and some international evidence," Manchester School, University of Manchester, vol. 71(5), pages 541-565, September.
    8. Ben S. Bernanke & Vincent R. Reinhart, 2004. "Conducting Monetary Policy at Very Low Short-Term Interest Rates," American Economic Review, American Economic Association, vol. 94(2), pages 85-90, May.
    9. Svensson, Lars E. O., 1999. "Inflation targeting as a monetary policy rule," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 607-654, June.
    10. Arturo Estrella & Frederic S. Mishkin, 1999. "Rethinking the Role of NAIRU in Monetary Policy: Implications of Model Formulation and Uncertainty," NBER Chapters,in: Monetary Policy Rules, pages 405-436 National Bureau of Economic Research, Inc.
    11. 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.
    12. repec:ime:imemes:v:35:y:2017:p:23-38 is not listed on IDEAS
    13. Christopher Martin & Costas Milas, 2009. "Uncertainty And Monetary Policy Rules In The United States," Economic Inquiry, Western Economic Association International, vol. 47(2), pages 206-215, April.
    14. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    15. Swamy, P.A.V.B. & Tavlas, George S. & Chang, I-Lok, 2005. "How stable are monetary policy rules: estimating the time-varying coefficients in monetary policy reaction function for the US," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 575-590, April.
    16. Aksoy, Yunus & Orphanides, Athanasios & Small, David & Wieland, Volker & Wilcox, David, 2006. "A quantitative exploration of the opportunistic approach to disinflation," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1877-1893, November.
    17. 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.
    18. A. Robert Nobay & David A. Peel, 2003. "Optimal Discretionary Monetary Policy in a Model of Asymmetric Central Bank Preferences," Economic Journal, Royal Economic Society, vol. 113(489), pages 657-665, July.
    19. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
    20. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    21. 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.
    22. Jung, Taehun & Teranishi, Yuki & Watanabe, Tsutomu, 2005. "Optimal Monetary Policy at the Zero-Interest-Rate Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(5), pages 813-835, October.
    23. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2009. "Unconditional Quantile Regressions," Econometrica, Econometric Society, vol. 77(3), pages 953-973, May.
    24. Mishkin, Frederic S., 2010. "Monetary policy flexibility, risk management, and financial disruptions," Journal of Asian Economics, Elsevier, vol. 21(3), pages 242-246, June.
    25. Gauti B. Eggertsson & Michael Woodford, 2003. "The Zero Bound on Interest Rates and Optimal Monetary Policy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(1), pages 139-235.
    26. Donald L. Kohn, 1996. "What operating procedures should be adopted to maintain price stability? practical issues (commentary)," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 297-306.
    27. Giannoni, Marc P., 2002. "Does Model Uncertainty Justify Caution? Robust Optimal Monetary Policy In A Forward-Looking Model," Macroeconomic Dynamics, Cambridge University Press, vol. 6(01), pages 111-144, February.
    28. Orphanides, Athanasios & Porter, Richard D. & Reifschneider, David & Tetlow, Robert & Finan, Frederico, 2000. "Errors in the measurement of the output gap and the design of monetary policy," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 117-141.
    29. Ehrmann, Michael & Smets, Frank, 2003. "Uncertain potential output: implications for monetary policy," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1611-1638, July.
    30. Wolters, Maik H., 2012. "Estimating monetary policy reaction functions using quantile regressions," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 342-361.
    31. Peersman, Gert & Smets, Frank, 1999. "The Taylor Rule: A Useful Monetary Policy Benchmark for the Euro Area?," International Finance, Wiley Blackwell, vol. 2(1), pages 85-116, April.
    32. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    33. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    34. William Miles & Samuel Schreyer, 2014. "Is monetary policy non-linear in Latin America? a quantile regression approach to Brazil, Chile, Mexico and Peru," Journal of Developing Areas, Tennessee State University, College of Business, vol. 48(2), pages 169-183, April-Jun.
    35. 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.
    36. repec:bla:irvfin:v:18:y:2018:i:2:p:305-316 is not listed on IDEAS
    37. Alan S. Blinder, 1999. "Central Banking in Theory and Practice," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522608, March.
    38. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Conditional quantile on quantile regressions; interest rate rule; zero lower bound; shadow rate of interest; uncertainty; Japan;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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:pre:wpaper:201929. 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: (Rangan Gupta). General contact details of provider: http://edirc.repec.org/data/decupza.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.