Strategic partner election: proposal for a Binary Logistic Model for the European Union

The EU, a unique supranational actor, has navigated enlargements, Brexit, and multiple internal and external challenges (e.g., financial crises, terrorism, COVID-19, and Russia’s aggression against Ukraine). In light of recent events, the EU’s Strategic Compass emphasizes building stronger, diverse partnerships and aligning security policies. Historically, the 2003 European Security Strategy first framed strategic partnerships (notably with the USA and Russia, and with Canada, Japan, China, India), yet without clear definitions or criteria. The EU subsequently granted strategic partner status to the USA, Canada, Japan, Brazil, Russia, India, China, South Korea, Mexico, and South Africa. Despite large differences among them, the EU pursued similar frameworks and action plans. However, no official definition or agreed criteria exist. This study’s purpose is to analyze the phenomenon of strategic partnerships in EU foreign policy, offer an operative definition underpinned by measurable indicators, and construct a Binary Logistic Model (built on components from CATPCA and PCA) to assess which countries are or should be EU strategic partners. The research questions/hypotheses are: (1) whether political and economic weight and common commercial interests dominate partner selection over shared values; (2) whether all of the EU’s “Special Ten” are truly strategic; and (3) whether other countries outside the official list merit strategic partner status.

The term “strategic partnership” proliferated post–Cold War as states adapted to a unipolar order. Early uses and definitions varied: Lessa (1998) framed it as priority political-economic relations built on accumulated bilateral ties; Emerson (2001) saw powerful actors capable of joint strategic action; encyclopedic entries described it as a political tool for intensifying economic relations. National interpretations also diverged: China emphasized long-term, comprehensive, equal, and mutually beneficial cooperation; Russia stressed equality, pragmatism, and respect for interests. Scholars highlighted multidimensionality across political, economic, social, and security domains (Gupta and Azad, 2011; Quevedo, 2012), the role of geographic proximity (Vasiliev, 2014), and the need for clarity to avoid conceptual dilution (Biscop and Renard, 2010; Grevi, 2010). The EU’s application has faced inconsistencies, particularly where “common values” are challenged (e.g., China, Russia). Based on the review, the authors propose an operative definition: Strategic Partnership is long-term bilateral cooperation for mutual benefits and equality of rights and respect among states, international organizations, and blocs with relevant economic and geopolitical weight at regional and/or international levels, based on common economic and/or geopolitical interests and preferably (though not necessarily) shared values and cultural-historical roots, aiming at common strategic objectives.

Design: Quantitative, multi-criteria model for identifying EU strategic partners using CATPCA to derive dimensions from indicators across categories, followed by PCA to extract principal components, and a Binary Logistic Model to estimate the probability a country is or should be an EU strategic partner. Sample: 143 countries (including official EU strategic partners), 2010–2019. Data sources: World Bank, ESPO, Eurostat, economic forums, official information. Software: SPSS. Indicator framework: Variables grouped into economic, commercial, political, social, geographical-cultural, common values, common jurisdictional basis, institutional basis, and discriminative actions. CATPCA produced 14 dimensions with acceptable-to-excellent reliability (Cronbach’s alpha, many totals >0.8 or >0.9). PCA and adequacy: KMO = 0.796; Bartlett’s test significant (p < 0.001). PCA extracted three components explaining about 67% of variance (COMP1 ~36.0%, COMP2 ~20.4%, COMP3 ~10.5%). Rotated structure (Varimax): COMP1 loads on economic and political weight, common commercial interests, social development, and some institutional basis—interpreted as the Strategic Partnership Component. COMP2 loads on sustainable governance, economic freedom, shared values, and absence of discriminative actions—interpreted as the Partnership in Spirit Component. COMP3 loads on geographical proximity and jurisdictional-institutional basis—interpreted as the Good Neighbor Component. Logistic regression: Dependent variable is binary (1 if a country is or should be an EU strategic partner; 0 otherwise). Significant predictors: COMP1 (positive) and COMP2 (negative); COMP3 not significant. Final model: F(x) = 1/(1 + e^-( -6.079 + 3.010*COMP1 - 3.104*COMP2 )). Selection and data reduction: Countries and indicators contributing less than 80% of information by Pareto rule were excluded.

- PCA structure: Three components explain ~67% of total variance (36.05%, 20.45%, 10.50%). KMO = 0.796; Bartlett’s p < 0.001. - Component meanings: COMP1 (Strategic Partnership Component) reflects a country’s economic and political weight plus common commercial interests with the EU; COMP2 (Partnership in Spirit) reflects governance, economic freedom, shared values, and absence of discrimination; COMP3 (Good Neighbor) reflects geographic proximity and legal-institutional ties. - Logistic model: Significant predictors are COMP1 (β ≈ +3.010, p ≈ 0.003, OR ≈ 20.3) and COMP2 (β ≈ −3.104, p ≈ 0.012, OR ≈ 0.045); constant ≈ −6.079 (p < 0.001). Thus, higher economic/political/commercial weight increases probability, while higher value/governance alignment (COMP2) decreases probability in the observed selection. - Rankings: On COMP1, official EU strategic partners cluster at the top (e.g., USA, China, Canada, Japan, Russia), evidencing that economic/political weight and trade ties drove status. On COMP2, Canada ranks favorably, whereas Russia and China perform poorly. On COMP3, neighbors and potential EU members dominate (e.g., Ukraine, Western Balkans; Russia relatively high due to proximity and institutional-legal engagement). - Partner probabilities: The model identifies as most critical partners (probability >99%): USA, China, Russia, Japan, India, Brazil. A revised list with probability >50% includes USA, China, Russia, Japan, India, Brazil, Canada, and Mexico; Argentina also attains ≈63% and should be awarded strategic partner status. Indonesia and Switzerland, along with South Korea, fall into a potential partner tier (~25–30%). South Africa does not reach strategic or potential thresholds in the model. - Hypotheses: (1) Confirmed—partner selection correlates primarily with economic/political weight and trade, not shared values; (2) Confirmed—not all “Special Ten” are truly strategic; (3) Confirmed—Argentina emerges as a candidate strategic partner.

The findings address the lack of formal EU criteria by operationalizing strategic partnership through measurable indicators and a probabilistic model. The strong, positive impact of COMP1 indicates that, in practice, the EU’s strategic partner choices align with states wielding significant economic and political power and extensive EU trade linkages. The negative coefficient for COMP2 reveals a gap between EU rhetoric about values and actual partner selection, where governance and value alignment have not historically increased the likelihood of strategic designation. COMP3 highlights proximity and institutional-legal cooperation as complementary but not decisive factors. The model thus provides an evidence-based framework that can clarify partner status, reduce ambiguity, and guide rebalancing toward partners that are both strategically significant and values-aligned if the EU chooses to prioritize the “Partnership in Spirit” dimension in future selections.

The paper contributes an operative definition of strategic partnership, a multi-dimensional indicator framework, and a combined CATPCA–PCA–Binary Logistic methodology for the EU’s strategic partner selection. Three components were identified: Strategic Partnership, Partnership in Spirit, and Good Neighbor. Only the first two significantly predicted partner status, with the values/governance component having a negative sign, indicating a mismatch between EU rhetoric and practice. Empirically, eight of the official “Special Ten” are truly strategic, Argentina should be added, and South Korea and South Africa are not sufficiently strategic under the model. The authors recommend continuous monitoring, greater diversification to enhance EU autonomy in economy and security, and elevating values/human rights (the Partnership in Spirit Component) in future selections, especially in the post-Ukraine invasion environment.

- The study proposes a methodology rather than a finalized, static list; partner status should be continuously monitored given changing geopolitical and economic contexts. - Data coverage and selection: 2010–2019 period; countries and indicators providing less than 80% information (Pareto rule) were excluded, potentially omitting some cases/variables. - Model dependence: Results depend on the chosen indicators, dimensionality reduction, and logistic specification; COMP3 (proximity/institutional basis) was not significant in prediction despite its policy relevance. - The analysis focuses on quantifiable indicators and may not capture dynamic political events or qualitative nuances occurring after the study period.