IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v29y2023i7p780-799.html
   My bibliography  Save this article

Do Divisia monetary aggregates help forecast exchange rates in a negative interest rate environment?

Author

Listed:
  • Luis Antonio Molinas
  • Jane M. Binner
  • Meng Tong

Abstract

This paper contributes to the literature as the first work of its kind to examine the role and importance of Divisia monetary aggregates and concomitant User Cost Price indices as superior monetary policy forecasting tools in a negative interest rate environment. We compare the performance of Divisia monetary aggregates with traditional simple-sum aggregates in several theoretical models and in a Bayesian VAR to forecast the exchange rates between the euro, the dollar and yuan at various horizons using quarterly data. We evaluate their performance against that of a random walk using two criteria: Root Mean Square Error ratios and the Clark-West statistic. We find that, under a free-floating exchange regime, superior Divisia monetary aggregates outperform their simple sum counterparts and the benchmark random walk in a negative interest rate environment, consistently.

Suggested Citation

  • Luis Antonio Molinas & Jane M. Binner & Meng Tong, 2023. "Do Divisia monetary aggregates help forecast exchange rates in a negative interest rate environment?," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 780-799, May.
  • Handle: RePEc:taf:eurjfi:v:29:y:2023:i:7:p:780-799
    DOI: 10.1080/1351847X.2022.2124120
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1351847X.2022.2124120
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1351847X.2022.2124120?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 search for a different version of it.

    More about this item

    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:taf:eurjfi:v:29:y:2023:i:7:p:780-799. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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.