The degree of RMB as an international anchor currency and its driving factors: an exchange rate perspective

Fengxian Chen and Tianruo Hao

Applied Economics, 2024, vol. 56, issue 4, 462-482

Abstract: This paper provides an alternative method to estimate the degree of RMB internationalization by combining the modified Frankel-Wei’s (1994, 2008) weight-inference technique and the state space model. Using a large sample of monthly exchange rate data of 54 economies, we estimate the dynamic currency weights of the U.S. dollar, Euro, RMB, Japanese yen and British pound. Results show that RMB has markedly increased since August 2015 as an international anchor currency, and then gradually decreased from June 2016 to December 2018. The currency weights ranked from highest to lowest are the U.S. dollar, Euro, RMB, British pound and Japanese yen for now. Furthermore, we also find that relative trade openness, capital account openness and exchange rate stability are the key drivers promoting the weight of the RMB. The above findings are robust to a battery of robustness tests. Our research contributes to the literature by providing a dynamic anchor currency weight estimation method and presenting a preliminary explanation for the changes of currency weight.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2023.2168611 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:56:y:2024:i:4:p:462-482

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2023.2168611

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().