A Multi-Dimensional Approach for Growth and Stability

The elaboration of the composite index of economic sovereignty is grounded in a broad understanding of the concept, defined as a country's ability to exert autonomous control over its natural resources, essential supplies, technologies, economic policies, and commercial choices. This capacity reflects its economic power and ability to advance national interests. Economic sovereignty is essential for ensuring stability, sustainable growth, and favorable positioning within global value chains while safeguarding the well-being of the population, social peace, justice, and continuity of essential services.

From this definition, three key components of economic sovereignty emerge:

• • Proactive Component: This aspect views economic sovereignty as a dynamic and positive force aimed at resilience and market engagement. It goes beyond passive protectionism, representing an active commitment to strengthen the country’s economic power and adaptability. Indicators in this category include innovation potential, product diversification and sophistication, and productive capacity.

  • Defensive Component: Independence is the cornerstone of economic sovereignty. A country achieves this when it can freely determine the means to pursue its development objectives. Key indicators include monetary sovereignty (the ability to manage monetary policy autonomously), budgetary sovereignty (control over financial decisions), and food sovereignty (ensuring access to adequate and culturally appropriate food). These elements can be threatened by public debt, international pressures, and reliance on imports.

  • Prosperity Component: Economic sovereignty serves to ensure national prosperity through autonomous decision-making that fosters growth, innovation, competitiveness, and local job protection. This component emphasizes indicators that reflect citizen welfare, focusing on good governance, entrepreneurial freedom, and quality of life.

Selecting the appropriate components and variables for constructing a composite index is a critical—and often debated—phase in the development process. This step involves identifying the key dimensions to include, as well as the corresponding subcategories and specific variables that accurately reflect the concept being measured. For the Economic Sovereignty Index (ECO-SOV), the framework is structured around three main components: the proactive, defensive, and prosperity dimensions, as depicted in the figure below. Each component is broken down into subcomponents, which in turn consist of individual measurable variables. In total, the index comprises 28 variables.

These variables were selected based on well-established criteria: validity, comparability, simplicity, and data availability. Only sources that are publicly accessible, reliable, and regularly updated were used to ensure the robustness and transparency of the data. The interpretation of economic sovereignty varies by context, especially in relation to a country’s position within the global economic system. For low- and middle-income nations, sovereignty is particularly salient because it touches on the ability to craft independent economic policies while managing the structural constraints imposed by global and domestic forces.

Yet, in today’s highly interconnected world, the concepts of “state overreach” and even “state dilution” have gained prominence. As economic and financial globalization intensifies, the regulatory power of states appears to be eroding—not only in traditional economic and monetary arenas but even in core sovereign functions like national security and defense. This erosion of authority impacts both affluent and developing countries.

To address the diverse conditions and varying levels of development across nations, the ECO-SOV Index categorizes countries into three groups based on income and data availability: 35 lower-middle-income countries, 29 upper-middle-income countries, and 37 high-income countries. This classification helps ensure a more tailored and meaningful comparison of economic sovereignty across different global contexts.

ECO-SOV Index Structure

Normalization, Variable Weights and Aggregation Procedure

Data normalization involves transforming data to ensure comparability and coherence, typically by adjusting it to a specific scale or common range. This process minimizes differences among variables, facilitating easier analysis and aggregation. For the Economic Sovereignty Index (ECO-SOV), the "Min-Max" normalization method is applied, scaling all data to a range between 0 and 100, where 100 indicates the best score and 0 the worst.

Cronbach's alpha is employed as a measure of internal consistency, assessing how closely related the variables in each subcategory are. A high alpha value (above 0.65) indicates strong coherence among the variables, reinforcing the reliability of the measurements. Additionally, the Kaiser-Meyer-Olkin (KMO) measure and Bartlett's test are used to evaluate the data's appropriateness for factor analysis. A significant result from the Bartlett test, coupled with a KMO value above 0.7, suggests that the data are suitable for this type of analysis.

High values for Cronbach's alpha confirm strong internal consistency among the variables, while KMO results validate the data's suitability for factor analysis. These positive findings enhance confidence in the quality of the data, supporting the composite index's construction.

The assignment of weights to the variables in the composite index is based on a rigorous approach using principal component analysis (PCA), which identifies the relationships among the variables. Weights are assigned according to the significance of each variable's contribution to the overall variance. This methodology ensures that the most impactful variables are adequately represented in the composite index, providing an objective and empirically grounded framework that enhances the index's validity and relevance.

The choice of aggregation method for the components of the composite index depends on the specific context, the objectives of the index, and the characteristics of the data. For the Economic Sovereignty Index, we opted for the geometric mean aggregation method. This choice provides several advantages, particularly its lower sensitivity to extreme values compared to other aggregation techniques. By minimizing the impact of outliers, this method ensures a more balanced representation of the various components, helping to avoid undue dominance by any single component.

The aggregation formula used calculates the index score based on the normalized values of the components and their respective weights, which are derived from principal component analysis.

101 COUNTRIES

Riadh Ben Jelili - IAE Bretagne Sud - University of South Brittany