The European Union Structural Funds: The Impact on the Country’s Competitiveness

Growing economic volatility has renewed interest in whether EU cohesion instruments are associated with measurable improvements in macro-level competitiveness. This article examines the relationship between European Structural and Investment Funds (ESF) and EU competitiveness indicators, focusing on GDP, inflation, unemployment, imports, and exports. Using annual EU-level data from 2007 to 2022, the study employs descriptive statistics, Pearson correlation with Student’s t-tests, and pairwise and multivariate OLS regressions, all implemented in MS Excel. The results show strong correlations between ESF and GDP (r = 0.88), imports (r = 0.80), and exports (r = 0.79), a moderate correlation with inflation (r = 0.61), and a strong negative correlation with unemployment (r = –0.72), with all coefficients statistically significant (e.g., t = 9.98 for GDP and t = –5.6 for unemployment against a critical value of 2.145). Pairwise regressions indicate substantial explanatory power for GDP (R² = 0.78; slope +7,822.15 per ESF unit), imports (R² = 0.65; slope +1.85), and exports (R² = 0.64; slope +1.59), while inflation remains weaker but significant (R² = 0.38; slope +0.0077) and unemployment declines with higher ESF (R² = 0.53; slope –0.0072). In the multivariate model, overall fit is high (R² = 0.927; Significance F = 0.000022), and GDP (p = 0.0091) and inflation (p = 0.0036) remain significant predictors of ESF; a reduced specification including GDP, inflation, and imports retains strong fit (R² = 0.922; Significance F = 0.00000063) with all included predictors statistically significant. Policy implications suggest prioritising ESF allocations towards productivity-enhancing and trade-oriented investments (skills linked to labour demand, innovation diffusion, and export readiness) that align with the strongest GDP and trade associations observed. Given the positive co-movement with inflation (r = 0.61; p = 0.0036 in the multivariate model), programme implementation should also incorporate macro-stability safeguards, including smoother procurement scheduling and a greater emphasis on supply-expanding projects during inflationary episodes.

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Journal
Financial Markets Institutions and Risks
Published
2026-01-04
DOI
https://doi.org/10.61093/fmir.9(4).92-113.2025
Primary Topic
Regional Development and Policy
Type
article
Field-Weighted Citation Impact
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article

The European Union Structural Funds: The Impact on the Country’s Competitiveness

Olena Churikanova, Aygun Aliyeva, Oleh Blazhko
Financial Markets Institutions and Risks
Regional Development and Policy
article

The European Union Structural Funds: The Impact on the Country’s Competitiveness

Olena Churikanova, Aygun Aliyeva, Oleh Blazhko
article en

Abstract

Growing economic volatility has renewed interest in whether EU cohesion instruments are associated with measurable improvements in macro-level competitiveness. This article examines the relationship between European Structural and Investment Funds (ESF) and EU competitiveness indicators, focusing on GDP, inflation, unemployment, imports, and exports. Using annual EU-level data from 2007 to 2022, the study employs descriptive statistics, Pearson correlation with Student’s t-tests, and pairwise and multivariate OLS regressions, all implemented in MS Excel. The results show strong correlations between ESF and GDP (r = 0.88), imports (r = 0.80), and exports (r = 0.79), a moderate correlation with inflation (r = 0.61), and a strong negative correlation with unemployment (r = –0.72), with all coefficients statistically significant (e.g., t = 9.98 for GDP and t = –5.6 for unemployment against a critical value of 2.145). Pairwise regressions indicate substantial explanatory power for GDP (R² = 0.78; slope +7,822.15 per ESF unit), imports (R² = 0.65; slope +1.85), and exports (R² = 0.64; slope +1.59), while inflation remains weaker but significant (R² = 0.38; slope +0.0077) and unemployment declines with higher ESF (R² = 0.53; slope –0.0072). In the multivariate model, overall fit is high (R² = 0.927; Significance F = 0.000022), and GDP (p = 0.0091) and inflation (p = 0.0036) remain significant predictors of ESF; a reduced specification including GDP, inflation, and imports retains strong fit (R² = 0.922; Significance F = 0.00000063) with all included predictors statistically significant. Policy implications suggest prioritising ESF allocations towards productivity-enhancing and trade-oriented investments (skills linked to labour demand, innovation diffusion, and export readiness) that align with the strongest GDP and trade associations observed. Given the positive co-movement with inflation (r = 0.61; p = 0.0036 in the multivariate model), programme implementation should also incorporate macro-stability safeguards, including smoother procurement scheduling and a greater emphasis on supply-expanding projects during inflationary episodes.

Financial Markets Institutions and RisksVol. 9(4)
Vilnius Gediminas Technical University (LT), Azerbaijan University of Architecture and Construction (AZ), TU Bergakademie Freiberg (DE)
Decent work and economic growth
Openalex Percentile: Top 91%
Regional Development and Policy
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