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Divergence of BRICS economies: cluster analysis and growth factors

https://doi.org/10.17073/2072-1633-2026-1-1584

Abstract

In the context of global economic transformation and the growing role of emerging market countries, the BRICS group is often viewed as a monolithic actor capable of offering an alternative development model. However, the hypothesis of this study is that, despite shared geopolitical goals, the economic strategies of BRICS member countries diverge significantly under the influence of national fiscal and trade policy choices. To test this hypothesis, a cluster analysis method was used based on 15 indicators (mean values, standard deviation, and trend) for 22 countries.

The results of the analysis confirmed the divergence hypothesis. The BRICS countries were divided into different clusters, reflecting fundamentally different development models. China and India were included in the cluster of dynamically growing economies with moderate tax burdens and trade liberalization policies. Meanwhile, Brazil and South Africa were classified as countries in the “middle-income trap”, characterized by high tax burdens, complex regulations, and, consequently, a large shadow economy (over 40% of GDP). Russia and South Africa, while high-income, exhibit high growth volatility due to dependence on commodity markets and institutional weaknesses.

The clustering conducted in the study allowed us to identify the determinants of the BRICS countries’ inclusion in various strata of the global economic hierarchy. Development models largely depend on fiscal factors (tax and customs-tariff policies), which in turn influence the scale of the shadow economy and, ultimately, determine growth rates. Five fundamentally different patterns of economic growth were identified, refuting the hypothesis of a monolithic BRICS bloc. Cluster 0 demonstrates a “dynamic development” pattern – an export-oriented model with high investments in human capital, which ensures sustainable growth with a moderate shadow economy. Cluster 1 is characterized by a “protectionist stagnation” pattern: despite high customs barriers, weak fiscal institutions lead to the formation of a gigantic shadow sector, limiting the potential for sustainable growth. Cluster 2 represents a “middle-income trap” pattern, where excessive tax burdens suppress business activity, resulting in minimal growth rates and the scale of the shadow economy. Cluster 3 exhibits a “rent volatility” pattern: high per capita GDP is combined with growth instability due to dependence on commodity markets. Low tariffs and tax burdens do not compensate for institutional vulnerability, manifested in a moderately high level of shadow economy.

Thus, the optimal model is a balance of taxation, trade openness, and investment in human capital, while protectionism, excessive tax burdens, and dependence on commodity markets contribute to slower growth.

The study demonstrates that the key determinants of economic success and sustainability are not formal membership in an integration bloc, but specific national choices regarding tax and tariff policies. The effectiveness of these choices directly impacts the growth rate and scale of the shadow economy, determining a country’s place in the global economic hierarchy.

About the Authors

A. A. Zavorykin
Financial University under the Government of the Russian Federation
Russian Federation

Alexei A. Zavorykin – PhD (Econ.), Lecturer of the Department of Taxes and Tax Administration of the Faculty of Taxes, Audit and Business Analysis

49/2 Leningradsky Ave., Moscow 125167



I. A. Zhuravleva
Financial University under the Government of the Russian Federation
Russian Federation

Irina A. Zhuravleva – Dr.Sci. (Philos.), PhD (Econ.), Associate Professor, Associate Professor of the Department of Taxes and Tax Administration of the Faculty of Taxes, Audit and Business Analysis

49/2 Leningradsky Ave., Moscow 125167



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Review

For citations:


Zavorykin A.A., Zhuravleva I.A. Divergence of BRICS economies: cluster analysis and growth factors. Russian Journal of Industrial Economics. 2026;19(1):7-25. (In Russ.) https://doi.org/10.17073/2072-1633-2026-1-1584

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ISSN 2072-1633 (Print)
ISSN 2413-662X (Online)