🌍 BRICS Economic Convergence Analysis

📊 Economic Development and Convergence Analysis of BRICS using the Principal Component Analysis (PCA) Method

• 📊 In this project, we compare the economic performance of the five main BRICS member states (🇧🇷 Brazil, 🇨🇳 China, 🇮🇳 India, 🇷🇺 Russia, 🇿🇦 South Africa) and identify patterns of convergence.
• 🧮 The comparison runs from 1990 to 2023, uses Principal Component Analysis (PCA), and covers key economic indicators.
• 🤝 The project was done together with my friend Jason Kehagias (@JasonKeha).

📚 Data Sources

• 🌐 WDI (World Development Indicators)

📈 Economic Indicators

• 📉 GDP Growth (%)
• 💵 GDP per Capita (US$)
• 💰 GDP per Capita, PPP (US$)
• 🌍 FDI Inflows (% of GDP)
• 🔥 Inflation (%)
• 🪖 Military Expenditure (% of GDP)

🔍 Main Findings

🧠 Interpretation of the Correlation of Variables:

• ➡️ The variables GDP_capita and GDP_capita_PPP tend to be in Principal Component 1 (PC1).
• ↗️ The GDP_growth and FDI variables tend to be in Principal Component 2 (PC2).
• ⚠️ Inflation does not trend positively in either PC.
• 🪖 Military Expenditure (Military_Expenditure) has an intermediate relationship with the PCs.

📉 Interpretation of Variance by Principal Components (PCs):

• PC1 covers 35.1% of the total volume of information, while PC2 covers 24.7%.
• In sum, the two PCs cover 59.8% of the indicators, a satisfactory percentage.
• PC3 covers around 18.9% and mainly concerns inflation, while the other PCs do not concern important data.

📊 Interpretation of the indicators in PC1:

• 🥇 GDP_capita_PPP (40%): Largest contribution to PC1, suggesting that fluctuations in GDP per capita explain a significant part of the overall variation in PC1.
• 🥈 GDP_capita (35%): Second strongest indicator, closely related to PC1, but less so than the PPP estimate.
• 🥉 GDP_growth (15%): Significant but minor influence; annual growth rates do not dominate the PC1 axis.

📊 Interpretation of the indicators in PC2:

• 🥇 FDI (33%): Largest contribution to PC2, suggesting that FDI fluctuations explain a significant part of the overall variation in PC2.
• 🥈 Inflation (21%): Second strongest indicator, closely related to PC2, but less so than FDI.
• 🥉 Military_Expenditure (15%): Significant but secondary influence; military expenditure does not dominate the PC2 axis.

🌐 Interpretation of indicators by country:

• 🇧🇷 Brazil performs positively in PC1, records balanced growth rates in all indicators, has a broad cloud and year-to-year volatility.
• 🇨🇳 China is in PC2 and particularly on the GDP growth axis, reflecting the country's high growth rates.
• 🇮🇳 India tends towards PC2 and negatively in PC1, showing concentration in GDP growth (small cloud) and indicating high growth but low incomes.
• 🇷🇺 Russia is positioned in PC1 and leads in a wide range of indicators (GDP per capita, Inflation, Military Expenditure), indicating strong volatility.
• 🇿🇦 South Africa is intermediate in the PCs, recording modest figures in the indicators and positioned closer to FDI.

🧾 Conclusion

• ❗ BRICS is not a homogeneous organisation in terms of economic growth: different rates per country and strong volatility.
• 📌 The comparison highlights the difference between developing countries (Russia, Brazil/South Africa, India/China).
• 🔄 The divergence between states has an impact on the policies of the organisation and affects the convergence potential of its member states.