IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i21p9229-d440854.html
   My bibliography  Save this article

Sustainable Approach to the Normalization Process of the UK’s Monetary Policy

Author

Listed:
  • Aleksandra Nocoń

    (Department of Banking and Financial Markets, College of Finance, University of Economics in Katowice, 40-287 Katowice, Poland)

Abstract

It has been more than a decade since central banks, in the face of the global financial crisis, implemented a set of unconventional initiatives that included a rapid and significant decrease in their main interest rates and an unprecedented balance sheet policy. Thus far, they still have not returned their monetary policy to the pre-crisis framework and have not implemented a normalization process. Currently, a trend of using econometric models in monetary policy for forecasting purposes has been observed. Among these models, Bayesian vector autoregression models (BVAR models) are increasingly being used by central banks. The main aim of this study was to conduct an empirical verification of the BVAR model’s usage for short-term prediction which could then be used for a sustainable (ordered) normalization process for the UK’s monetary policy. This study verifies a research hypothesis which states that the BVAR model might be a useful tool in the Bank of England’s decision-making process regarding the normalization of its monetary policy. Additionally, the cause and effect analysis, observation method, document analysis method, and synthesis method were also considered. The conducted research indicates that a large BVAR model has a significant predictive value for short-term forecasting.

Suggested Citation

  • Aleksandra Nocoń, 2020. "Sustainable Approach to the Normalization Process of the UK’s Monetary Policy," Sustainability, MDPI, vol. 12(21), pages 1-14, November.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9229-:d:440854
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/21/9229/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/21/9229/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic Factor Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 3, pages 25-40, Springer.
    3. Arahuetes García, Alfredo & Gómez Bengoechea, Gonzalo, 2020. "Fiscal Union, Monetary Policy Normalization and Populism in the Eurozone," European Review, Cambridge University Press, vol. 28(2), pages 238-257, April.
    4. Troy D. Matheson, 2006. "Factor Model Forecasts for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 2(2), May.
    5. Bagliano, Fabio C. & Favero, Carlo A., 1998. "Measuring monetary policy with VAR models: An evaluation," European Economic Review, Elsevier, vol. 42(6), pages 1069-1112, June.
    6. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    7. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    8. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    9. Kuschnig, Nikolas & Vashold, Lukas, 2019. "BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R," Department of Economics Working Paper Series 296, WU Vienna University of Economics and Business.
    10. Kjell Hausken & Mthuli Ncube, 2013. "Quantitative Easing and Its Impact in the US, Japan, the UK and Europe," SpringerBriefs in Economics, Springer, edition 127, number 978-1-4614-9646-5, October.
    11. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
    12. George Kapetanios & Haroon Mumtaz & Ibrahim Stevens & Konstantinos Theodoridis, 2012. "Assessing the Economy‐wide Effects of Quantitative Easing," Economic Journal, Royal Economic Society, vol. 122(564), pages 316-347, November.
    13. Fabio Canova & Joaquim Pires Pina, 1998. "Monetary policy misspecification in VAR models," Economics Working Papers 420, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 1999.
    14. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 8(Fall).
    15. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    16. Jacob A. Bikker, 1999. "Macro-economie forecasting for the major four EU countries two-step Bayesian VAR approach," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 162, pages 203-231.
    17. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
    18. 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.
    19. Michele Lenza & Huw Pill & Lucrezia Reichlin, 2010. "Monetary policy in exceptional times [Preventing deflation: Lessons from Japan’s experience in the 1990s]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 25(62), pages 295-339.
    20. Artis, M. J. & Zhang, W., 1990. "BVAR forecasts for the G-7," International Journal of Forecasting, Elsevier, vol. 6(3), pages 349-362, October.
    21. Sturm, Jan Egbert & de Haan, Jakob, 1995. "Is public expenditure really productive?: New evidence for the USA and The Netherlands," Economic Modelling, Elsevier, vol. 12(1), pages 60-72, January.
    22. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    23. Barreto,Humberto & Howland,Frank, 2006. "Introductory Econometrics," Cambridge Books, Cambridge University Press, number 9780521843195.
    24. Michael Artis & Anindya Banerjee & Massimiliano Marcellino, "undated". "Factor forecasts for the UK," Working Papers 203, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    25. Mr. Matteo Ciccarelli & Mr. Alessandro Rebucci, 2003. "Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System," IMF Working Papers 2003/102, International Monetary Fund.
    26. Claude Diebolt & Catherine Kyrtsou (ed.), 2005. "New Trends in Macroeconomics," Springer Books, Springer, number 978-3-540-28556-4, December.
    27. Munehisa Kasuya & Tomoki Tanemura, 2000. "Small Scale Bayesian VAR Modeling of the Japanese Macro Economy Using the Posterior Information Criterion and Monte Carlo Experiments," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    28. Mr. Murtaza H Syed & Hiromi Yamaoka, 2010. "Managing the Exit: Lessons from Japan's Reversal of Unconventional Monetary Policy," IMF Working Papers 2010/114, International Monetary Fund.
    29. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    30. Robert B. Litterman, 1984. "Specifying vector autoregressions for macroeconomic forecasting," Staff Report 92, Federal Reserve Bank of Minneapolis.
    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. Irena Pyka & Aleksandra Nocoń, 2021. "Banks’ Capital Requirements in Terms of Implementation of the Concept of Sustainable Finance," Sustainability, MDPI, vol. 13(6), pages 1-17, March.

    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. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    2. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    3. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
    4. Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
    5. Churm, Rohan & Joyce, Michael & Kapetanios, George & Theodoridis, Konstantinos, 2021. "Unconventional monetary policies and the macroeconomy: The impact of the UK's QE2 and funding for lending scheme," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 721-736.
    6. Churm, Rohan & Joyce, Mike & Kapetanios, George & Theodoridis, Konstantinos, 2015. "Unconventional monetary policies and the macroeconomy: the impact of the United Kingdom's QE2 and Funding for Lending Scheme," Bank of England working papers 542, Bank of England.
    7. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    8. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    9. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    10. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    11. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    12. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    13. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
    14. Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023. "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper 116827, University Library of Munich, Germany.
    15. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    16. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    17. Kemal Bagzibagli, 2014. "Monetary transmission mechanism and time variation in the Euro area," Empirical Economics, Springer, vol. 47(3), pages 781-823, November.
    18. Boubaker, Sabri & Gounopoulos, Dimitrios & Nguyen, Duc Khuong & Paltalidis, Nikos, 2017. "Assessing the effects of unconventional monetary policy and low interest rates on pension fund risk incentives," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 35-52.
    19. Stelios D. Bekiros & Alessia Paccagnini, 2016. "Policy‐Oriented Macroeconomic Forecasting with Hybrid DGSE and Time‐Varying Parameter VAR Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 613-632, November.
    20. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.

    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:gam:jsusta:v:12:y:2020:i:21:p:9229-:d:440854. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.