IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v24y2020i3p17n1.html
   My bibliography  Save this article

Conventional and unconventional monetary policy reaction to uncertainty in advanced economies: evidence from quantile regressions

Author

Listed:
  • Christou Christina

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

  • Naraidoo Ruthira
  • Gupta Rangan

    (Department of Economics, University of Pretoria, Pretoria 0002, South Africa)

Abstract

This paper investigates how the Federal Reserve (Fed) and the Bank of England, Bank of Japan and the European Central Bank reacted in the aftermath of the financial crisis by making use of both conditional and unconditional interest rate quantiles regressions and data on shadow short rate of interest and a measure of uncertainty. Firstly, the unconditional quantile regression offers some support for increased reaction by the Fed as the ZLB is approached. Secondly, the decreased reaction of the Fed and other monetary policy makers towards uncertainty particularly at lower conditional quantiles of interest rates lends support to expansionary mechanism in place during this time. Hence uncertainty is key to policy reaction, and more so during episodes of crisis.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:sndecm:v:24:y:2020:i:3:p:17:n:1
    DOI: 10.1515/snde-2018-0056
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2018-0056
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2018-0056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    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. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    3. 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.
    4. 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.
    5. 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.
    6. Svensson, Lars E. O., 1999. "Inflation targeting as a monetary policy rule," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 607-654, June.
    7. 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.
    8. 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.
    9. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    10. Castro, Vítor & Sousa, Ricardo M., 2012. "How do central banks react to wealth composition and asset prices?," Economic Modelling, Elsevier, vol. 29(3), pages 641-653.
    11. Colombo, Valentina, 2013. "Economic policy uncertainty in the US: Does it matter for the Euro area?," Economics Letters, Elsevier, vol. 121(1), pages 39-42.
    12. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    13. 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.
    14. Lee, Ji Hyung, 2016. "Predictive quantile regression with persistent covariates: IVX-QR approach," Journal of Econometrics, Elsevier, vol. 192(1), pages 105-118.
    15. 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.
    16. 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.
    17. Mishkin, Frederic S., 2010. "Monetary policy flexibility, risk management, and financial disruptions," Journal of Asian Economics, Elsevier, vol. 21(3), pages 242-246, June.
    18. Francois Gourio & Jonas Fisher, 2015. "Risk Management for Monetary Policy at the Zero Lower Bound," 2015 Meeting Papers 665, Society for Economic Dynamics.
    19. Leo Krippner, 2013. "A tractable framework for zero lower bound Gaussian term structure models," Reserve Bank of New Zealand Discussion Paper Series DP2013/02, Reserve Bank of New Zealand.
    20. Conley, Timothy G. & Galenson, David W., 1998. "Nativity and Wealth in Mid-Nineteenth-Century Cities," The Journal of Economic History, Cambridge University Press, vol. 58(2), pages 468-493, June.
    21. 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(1), pages 111-144, February.
    22. 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.
    23. Charles Evans & Jonas Fisher & Francois Gourio & Spencer Krane, 2015. "Risk Management for Monetary Policy Near the Zero Lower Bound," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(1 (Spring), pages 141-219.
    24. Wolters, Maik H., 2012. "Estimating monetary policy reaction functions using quantile regressions," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 342-361.
    25. Jawadi, Fredj & Sousa, Ricardo M., 2013. "Money demand in the euro area, the US and the UK: Assessing the role of nonlinearity," Economic Modelling, Elsevier, vol. 32(C), pages 507-515.
    26. Gert Peersman & Frank Smets, 1999. "The Taylor Rule: A Useful Monetary Policy Benchmark for the Euro Area?," International Finance, Wiley Blackwell, vol. 2(1), pages 85-116, April.
    27. Sousa, João & Sousa, Ricardo M., 2017. "Predicting risk premium under changes in the conditional distribution of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 204-218.
    28. Fredj Jawadi & Sushanta Kumar Mallick & Ricardo Magalhães Sousa, 2014. "Nonlinear monetary policy reaction functions in large emerging economies: the case of Brazil and China," Applied Economics, Taylor & Francis Journals, vol. 46(9), pages 973-984, March.
    29. Alan Greenspan, 2003. "Opening remarks : monetary policy and uncertainty : adapting to a changing economy," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 1-7.
    30. William Miles & Sam Schreyer, 2012. "Is monetary policy non-linear in Indonesia, Korea, Malaysia, and Thailand? A quantile regression analysis," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 26(2), pages 155-166, November.
    31. 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.
    32. 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.
    33. Ma Jun & Olson Eric & Wohar Mark E., 2018. "Nonlinear Taylor rules: evidence from a large dataset," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-14, February.
    34. Chen Jau-er, 2015. "Factor instrumental variable quantile regression," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 71-92, February.
    35. Alan S. Blinder, 1999. "Central Banking in Theory and Practice," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522608, April.
    36. 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.
    37. 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. Long, Shaobo & Zuo, Yulan & Tian, Hao, 2023. "Asymmetries in multi-target monetary policy rule and the role of uncertainty: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 278-296.
    2. Plakandaras, Vasilios & Gupta, Rangan & Balcilar, Mehmet & Ji, Qiang, 2022. "Evolving United States stock market volatility: The role of conventional and unconventional monetary policies," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    3. 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.
    4. Çekin, Semih Emre & Hkiri, Besma & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "The relationship between monetary policy and uncertainty in advanced economies: Evidence from time- and frequency-domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 70-87.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    3. 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.
    4. Caporale, Guglielmo Maria & Helmi, Mohamad Husam & Çatık, Abdurrahman Nazif & Menla Ali, Faek & Akdeniz, Coşkun, 2018. "Monetary policy rules in emerging countries: Is there an augmented nonlinear taylor rule?," Economic Modelling, Elsevier, vol. 72(C), pages 306-319.
    5. 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.
    6. Moccero, Diego & Gnabo, Jean-Yves, 2015. "The risk management approach to monetary policy, nonlinearity and aggressiveness: the case of the US Fed," Working Paper Series 1792, European Central Bank.
    7. Paolo Surico, 2002. "Inflation Targeting and Nonlinear Policy Rules: the Case of Asymmetric Preferences," Macroeconomics 0210002, University Library of Munich, Germany, revised 23 Feb 2004.
    8. 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].
    9. 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.
    10. Gnabo, Jean-Yves & Moccero, Diego Nicolas, 2015. "Risk management, nonlinearity and aggressiveness in monetary policy: The case of the US Fed," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 281-294.
    11. Giovanni Pellegrino, 2021. "Uncertainty and monetary policy in the US: A journey into nonlinear territory," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1106-1128, July.
    12. Nidhal Mgadmi & Slim Chaouachi & Wajdi Moussa & Azza Bejaoui, 2021. "Does the Tunisian Central Bank follow an augmented nonlinear Taylor rule?," SN Business & Economics, Springer, vol. 1(1), pages 1-15, January.
    13. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    14. Wolters, Maik H., 2012. "Estimating monetary policy reaction functions using quantile regressions," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 342-361.
    15. Shawn Chen‐Yu Leu & Jeffrey Sheen, 2006. "Asymmetric Monetary Policy in Australia," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages 85-96, September.
    16. 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.
    17. William H.Greene & Max Gillman & Mark N. Harris & Christopher Spencer, 2013. "The Tempered Ordered Probit (TOP) model with an application to monetary policy," Discussion Paper Series 2013_10, Department of Economics, Loughborough University, revised Sep 2013.
    18. Doyle, Matthew & Falk, Barry, 2010. "Do asymmetric central bank preferences help explain observed inflation outcomes?," Journal of Macroeconomics, Elsevier, vol. 32(2), pages 527-540, June.
    19. Efrem Castelnuovo, 2019. "Domestic and global uncertainty: A survey and some new results," CAMA Working Papers 2019-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. 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.

    More about this item

    Keywords

    advanced economies; conditional and unconditional quantile regressions; interest rate rule; shadow rate of interest; uncertainty; zero lower bound;
    All these keywords.

    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

    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:bpj:sndecm:v:24:y:2020:i:3:p:17:n:1. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.