Modeling Regional ESG Performance in the European Union: A Partial Least Squares Approach to Sustainable Economic Systems

Ioana Birlan (), Adriana AnaMaria Davidescu, Catalina-Elena Tita and Tamara Maria Nae
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Ioana Birlan: Doctoral School of Economic Cybernetics and Statistics, The Bucharest University of Economic Studies, 010552 Bucharest, Romania
Adriana AnaMaria Davidescu: Department of Statistics and Econometrics, The Bucharest University of Economic Studies, 010552 Bucharest, Romania
Catalina-Elena Tita: Faculty of Cybernetics, Statistics and Economic Informatics, The Bucharest University of Economic Studies, 010552 Bucharest, Romania
Tamara Maria Nae: Department of Economics and Economic Policy, Bucharest University of Economic Studies, 010552 Bucharest, Romania

Mathematics, 2025, vol. 13, issue 15, 1-42

Abstract: This study aims to evaluate the sustainability performance of EU regions through a comprehensive and data-driven Environmental, Social, Governance (ESG) framework, addressing the increasing demand for regional-level analysis in sustainable finance and policy design. Leveraging Partial Least Squares (PLS) regression and cluster analysis, we construct composite ESG indicators that adjust for economic size using GDP normalization and LOESS smoothing. Drawing on panel data from 2010 to 2023 and over 170 indicators, we model the determinants of ESG performance at both the national and regional levels across the EU-27. Time-based ESG trajectories are assessed using Compound Annual Growth Rates (CAGR), capturing resilience to shocks such as the COVID-19 pandemic and geopolitical instability. Our findings reveal clear spatial disparities in ESG performance, highlighting the structural gaps in governance, environmental quality, and social cohesion. The model captures patterns of convergence and divergence across EU regions and identifies common drivers influencing sustainability outcomes. This paper introduces an integrated framework that combines PLS regression, clustering, and time-based trend analysis to assess ESG performance at the subnational level. The originality of this study lies in its multi-layered approach, offering a replicable and scalable model for evaluating sustainability with direct implications for green finance, policy prioritization, and regional development. This study contributes to the literature by applying advanced data-driven techniques to assess ESG dynamics in complex economic systems.

Keywords: ESG modeling; partial least squares regression; sustainable economic systems; panel data analysis; regional sustainability; econometric modeling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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