An optimum currency area index for BRICS: A Bayesian prediction model

This paper assesses the feasibility of monetary integration among BRICS economies, an issue that remains underexplored in the Optimum Currency Area (OCA) literature. Previous studies have typically relied on static indices or structural models that are not well-suited for forward-looking analysis. We develop a new OCA index using a Bayesian Seemingly Unrelated Regression (SUR) framework, which jointly estimates GDP growth and exchange rate volatility conditional on external macro-financial risks, including global uncertainty, oil prices, policy uncertainty, and sovereign risk. Using monthly data for the period 1998–2022, we analyse dynamics before and after the 2010 phase of institutional coordination. The results reveal persistent asymmetries in how BRICS economies respond to fundamentals and shocks, with India and China showing the greatest divergence. Elevated global uncertainty and financial risk are found to weaken macroeconomic alignment. The proposed index captures convergence patterns and facilitates scenario-based forecasting, offering a flexible framework for analysing monetary integration in both emerging and advanced economies. • The paper develops a new OCA index for BRICS economies. • The index is based on a Bayesian Seemingly Unrelated Regression model. • Exchange rate volatility and GDP growth are jointly estimated. • Global risks such as oil prices and policy uncertainty drive divergence. • Findings inform monetary integration debates in emerging and advanced economies.