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This study seeks to identify the extent to which global oil and food price volatilities affected the interdependence of the Brazilian and Russian economies in the period from 1996 to 2021. The ARCH/GARCH framework was used to model the volatility of oil and food prices. The Structural Vector Autoregressive (SVAR) approach was used to ascertain the sensitivity of key economic indicators to oil and food shocks. The Impulse Response Function (IRF) was usedto trace short-term effects over a period of 12 months. Subsequently, the multivariate dynamic conditional correlation DCC-GARCH model, created by Engle &amp; Sheppard (2001), was used to model time-varying correlations of paired macroeconomic variables. This study contributes to the empirical literature in two fundamental ways. Firstly, it pairs the two largest oil and food producers in the BRICS bloc. Secondly, unlike some earlier studies, the applied methodology ensures the effectiveness of the results by using stationary time series data. The results show that Brazil and Russia have long-run spillover effects for all macroeconomic variables in response to both oil and food price shocks. Furthermore, money supply and exchange rate variables exhibited declining positive correlation coefficients during the global financial crisis of 2008–2009, but peaked in early 2020 due to the Covid-19 pandemic. As a corollary of the main findings, the researchers recommend that investors should diversify their portfolios beyond these two economies in order to minimize the risk of contagion during severe global crises.

The impact of world oil and food price shocks on the interdependence of Brazil and Russia: SVAR-DCC-GARCH model