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

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.

KEYWORDS:

• Currency anchor
• RMB internationalization
• State space model
• Driving factors of currency anchor

JEL CLASSIFICATION:

• F830
• F832.1
• F831.0

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

¹ ‘The correct specification to estimate the weights of the anchor currencies in a currency basket is to use the rates of changes in exchange rates and to write exchange rates in quantity term.’.

² The model-free method primarily includes exchange rate volatility, foreign exchange reserve volatility and interest rate volatility. In light of the fact that China’s monetary policy is still quantitatively dominated and the interest rate transmission channel is relatively weak, so the interest rate fluctuations is excluded.

³ For space reason, detailed outcomes have been retained upon request.

⁴ The calculation is based on the data from IMF’s Direction of Trade Statistics (DOTS) database.

⁵ The method of Narayan and Popp (2010) is a Dicky-Fuller type test where the break date is obtained by maximizing the significance of the break date coefficient.

⁶ The exchange rate is against the U.S. dollar and is not used against New Zealand dollar because the U.S. dollar is a free-floating currency and in practice the currencies of economies are referenced to the U.S. dollar, which better reflects the reality..

Additional information

Funding

The work was supported by the R&D Program of Beijing Municipal Education Commission (Micro-impact and countermeasures of the sudden stop shock of international capital flows) [SZ202310038016]; Fundamental Research Funds for the Beijing Municipal Universities of CUEB [QNTD202206]; State Scholarship Fund of China Scholarship Council [202208110128]; Beijing Social Science Fund [20JJB018].