Prospects of BRICS currency dominance in international trade

TL;DR

This study asks whether a BRICS-backed currency (BRI) could come to dominate international trade when considering only the structure of the World Trade Network (WTN) derived from UN Comtrade data (2010–2020). It extends a previously proposed two-currency Ising-style Monte Carlo framework to three currencies (USD, EUR, BRI), with fixed seed groups and a stochastic update rule that assigns each country a trade-currency preference based on local and global trade weights. The analysis finds that BRRI’s influence grows over time, achieving 60% of countries by TCP in 2020, though its share of total trade volume remains below EUR and USD; this suggests BRRI could become a dominant trade currency under network effects alone. However, the study intentionally omits political and policy dynamics, implying that real-world constraints could dampen or modify the predicted dominance in practice.

Abstract

During his state visit to China in April 2023, Brazilian President Lula proposed the creation of a trade currency supported by the BRICS countries. Using the United Nations Comtrade database, providing the frame of the world trade network associated to 194 UN countries during the decade 2010 - 2020, we study a mathematical model of influence battle of three currencies, namely, the US dollar, the euro, and such a hypothetical BRICS currency. In this model, a country trade preference for one of the three currencies is determined by a multiplicative factor based on trade flows between countries and their relative weights in the global international trade. The three currency seed groups are formed by 9 eurozone countries for the euro, 5 Anglo-Saxon countries for the US dollar and the 5 BRICS countries for the new proposed currency. The countries belonging to these 3 currency seed groups trade only with their own associated currency whereas the other countries choose their preferred trade currency as a function of the trade relations with their commercial partners. The trade currency preferences of countries are determined on the basis of a Monte Carlo modeling of Ising type interactions in magnetic spin systems commonly used to model opinion formation in social networks. We adapt here these models to the world trade network analysis. The results obtained from our mathematical modeling of the structure of the global trade network show that as early as 2012 about 58 percent of countries would have preferred to trade with the BRICS currency, 23 percent with the euro and 19 percent with the US dollar. Our results announce favorable prospects for a dominance of the BRICS currency in international trade, if only trade relations are taken into account, whereas political and other aspects are neglected.

Figures (7)

• Figure 1: World distribution of the trade currency preferences, TCP, for 2010 (top panel) and 2019 (bottom panel). Countries with a trade preference for USD are colored in blue, for EUR in gold, and for BRI in red. Countries colored in grey have no trade data reported in the UN Comtrade database comtrade.
• Figure 2: Distribution of the countries' trade currency ternary scores $\left(Z_{\hbox{\tiny USD}},Z_{\hbox{\tiny EUR}},Z_{\hbox{\tiny BRI}}\right)$ for 2010 (top panel) and 2019 (bottom panel). A country is represented by a circle. Colors are associated to TCPs, blue for USD, gold for EUR, and red for BRI. The $Z_{\hbox{\tiny USD}}$ coordinate is read along the dashed blue horizontal lines, the $Z_{\hbox{\tiny EUR}}$ coordinate along the gold dashed oblique lines, and the $Z_{\hbox{\tiny BRI}}$ coordinate along the red dashed oblique lines.
• Figure 3: Evolution of the size of the trade currency groups with time. The height of each band corresponds to the corresponding fraction of world countries (left panel) and to the corresponding fraction of the total trade volume (right panel). The group of countries preferring to trade in USD is colored in blue, EUR in gold, and BRI in red. In the right panel, the fractions of the total trade volume associated to the currency seed groups are shown: Anglo-Saxon group (dark blue), the EU9 group (dark gold), BRICS countries (dark red).
• Figure A1: Examples of evolutions of the fraction $f$ of countries with USD trade preference ($f^{\hbox{\tiny USD}}$, solid line) and EUR trade preference ($f^{\hbox{\tiny EUR}}$, dashed line) as a function of the Monte-Carlo process step $\tau$ in 2010 (top panels) and 2019 (bottom panels). The complementary fraction $f^{\hbox{\tiny BRI}}=1-f^{\hbox{\tiny USD}}-f^{\hbox{\tiny EUR}}$ gives the fraction of countries with a BRI trade preference. The fractions $f$ are averaged over $10^4$ random simulations. In left panels, $f_i^{\hbox{\tiny BRI}}=0.5$, we show four configurations such as $f_i^{\hbox{\tiny USD}}+f_i^{\hbox{\tiny EUR}}=0.5$. In right panels, $f_i^{\hbox{\tiny BRI}}=0.8$, we show one configuration such as $f_i^{\hbox{\tiny USD}}+f_i^{\hbox{\tiny EUR}}=0.2$. In 2010, the steady state fractions of countries with a USD, EUR, or BRI TCP are $f_f^{\hbox{\tiny USD}}=0.24$, $f_f^{\hbox{\tiny EUR}}=0.27$, and $f_f^{\hbox{\tiny BRI}}=0.49$. In 2019, the steady state fractions of countries with a USD, EUR, or BRI TCP are $f_f^{\hbox{\tiny USD}}=0.19$, $f_f^{\hbox{\tiny EUR}}=0.22$, and $f_f^{\hbox{\tiny BRI}}=0.59$.
• Figure A2: World distribution of the trade currency preferences for the years 2010, 2012, 2014, 2016, 2018, 2019, and 2020. Countries with a trade preference for USD are colored in blue, for EUR in gold, and for BRI in red. Countries colored in grey have no trade data reported in the UN Comtrade database comtrade.