Economic Efficiency Assessment of Sustainability Investment in EU Member States: A Data Envelopment Analysis with Crisis Impact Evaluation (2015-2024)
DOI:
https://doi.org/10.31181/ijes1512026278Keywords:
Economic efficiency, Sustainability investment, Financial resources, Data Envelopment Analysis (DEA), Efficiency ratio (ER), EU‑27 sustainability policy, Green public finance, Crisis resilience, Institutional quality, Climate and energy transitionAbstract
The article proposes an approach for assessing the efficiency of sustainability-related investments in the EU-27 member states over the period 2015–2024. This is achieved through a combination of a DEA-based approach, a composite efficiency coefficient, and cluster analysis. The composite coefficient measures the relationship between calibrated outcomes and inputs and, in essence, provides a “value-for-money” assessment of sustainable expenditures. The results show substantial differences between countries. The Baltic states and several Central and Eastern European economies display high efficiency, while some of the traditional “leaders” in sustainability exhibit more modest returns per unit of investment. The cluster analysis groups the countries into four clusters with similar characteristics. These range from groups in which investment volumes play the leading role to groups in which efficiency is the key driver, and clearly show differences in the outcomes of the policies pursued (including target-setting and the design of EU financial instruments). The analysis also takes into account the impact of COVID-19 and the war in Ukraine. The main finding is that institutional quality is a stronger factor in maintaining efficiency during crises than the level of economic development. This conclusion underlines that sustainability objectives should also include measurable indicators of administrative capacity in order to improve the system’s ability to adapt in times of crisis. The proposed model provides an empirical basis for improving the way European targets and instruments are formulated. It can help direct limited resources more effectively towards countries and regions with the greatest potential for efficiency improvement.
Downloads
References
European Commission. (2020). Finance and the Green Deal. Available at: https://commission.europa.eu/publications/finance-and-green-deal_en
European Environment Agency. (2024). Sustainable development in the European Union – 2024 monitoring report on progress towards the SDGs in an EU context. Available at: https://www.eea.europa.eu/publications/sustainable-development-in-the-european-union-2024
Huang, S., Zhang, Y., & Liu, W. (2023). The super slack-based measure network three-stage data envelopment analysis approach to assess comprehensive environmental efficiency. Journal of Cleaner Production, 398, 136564. https://doi.org/10.1016/j.jclepro.2023.136564
OECD. (2023). Environmental finance database. OECD Environmental Statistics, https://www.oecd.org/en/topics/environmental-statistics-accounts-and-indicators.html?utm_source=chatgpt.com (Accessed: 14 December 2025).
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Springer. https://doi.org/10.1007/978-0-387-45283-8
Marjanović, I., Radojević, P., & Stojanović, A. (2025). Insight into territorial efficiency of circular economy through data envelopment analysis: Evidence from European Union countries. Frontiers in Environmental Science, 13, 1494184. https://doi.org/10.3389/fenvs.2025.1494184
Electricity Mix Assessment Study. (2019). Sustainability efficiency assessment of the electricity mix of the 28 EU member countries combining data envelopment analysis and optimized projections. Energy Policy, 134, 110951.
Sustainability Clustering Analysis. (2024). ESG-driven corporate clustering and stock market efficiency. Journal of Corporate Finance Research.
Bosna, J. (2025). Examining regional economic differences in Europe: The power of ANFIS analysis. Journal of Decision Analytics and Intelligent Computing, 5(1), 1–13. https://doi.org/10.31181/jdaic10010022025b
Maity, S., & Majumder, A. (2025). A comparative study on the financial inclusion status of G20 countries. Journal of Decision Analytics and Intelligent Computing, 5(1), 14–24. https://www.jdaic-journal.org/index.php/about/issue/view/5
Eurostat. (2024). Sustainable Development Goals database (SDG indicators). https://ec.europa.eu/eurostat/web/sdi (Accessed: 14 December 2025).
European Commission. (2021). The European Green Deal Investment Plan and Just Transition Mechanism explained. European Commission.
Cohesion Policy Efficiency Study. (2022). Is the Cohesion Policy Efficient in Supporting the Transition to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis. Sustainability, 14(18), 11587. https://doi.org/10.3390/su141811587
EIB Climate Investment Report. (2025). Multilateral development banks hit record $137 billion in climate finance to drive sustainable development worldwide. European Investment Bank Press Release.
OECD. (2023). Did COVID-19 accelerate the green transition? OECD Economic Policy Papers No. 31. OECD Publishing. https://doi.org/10.1787/5c4f06b6-en
COVID Green Transition Study. (2022). Did COVID-19 accelerate the green transition? OECD Economic Policy Papers, No. 31, OECD Publishing. https://doi.org/10.1787/31e0c3c9-en
European Commission. (2024). REPowerEU – Energy. https://commission.europa.eu/topics/energy/repowereu_en
Eastern EU Crisis Vulnerability Study. (2023). The EU's response to the war-induced energy crisis: legal foundations and political implications. CSF Research Paper.
Crisis Management in Sustainability Policy. (2024). Climate, conflict and COVID-19: How does the pandemic affect EU policies on climate-fragility? Cascades Project Report. https://www.cascades.eu/publication/climate-conflict-and-covid-19
World Bank. (2024). Governance and resilience review. World Bank. https://www.worldbank.org/en/publication/worldwide-governance-indicators
Sequential Crisis Impact Analysis. (2024). The Relationship of the Russia-Ukraine War with Energy Security and Sustainability. Sustainability Research Journal.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A, 120(3), 253–290. https://doi.org/10.2307/2343100
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Springer. https://doi.org/10.1007/978-0-387-45283-8
European Commission. (2019). The European Green Deal (COM(2019) 640 final). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640 (Accessed: 14 December 2025)
Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129–137. https://doi.org/10.1109/TIT.1982.1056489
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., … Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. https://jmlr.org/papers/v12/pedregosa11a.html
Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65. https://doi.org/10.1016/0377-0427(87)90125-7
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates. https://www.routledge.com/Statistical-Power-Analysis-for-the-Behavioral-Sciences/Cohen/p/book/9780805802832
OECD. (2024). Environmental performance reviews: Sustainability investment efficiency trends. OECD, https://www.oecd.org/en/topics/environmental-statistics-accounts-and-indicators.html?utm_source=chatgpt.com
EIB. (2024). Climate Investment Database. European Investment Bank Environmental and Climate Finance Statistics. https://www.eib.org/en/publications/climate-investment-report
Kaufmann, Daniel & Aart C. Kraay. (2024). “The Worldwide Governance Indicators: Methodology and 2024 Update.” Policy Research Working Paper. Washington, DC: World Bank Group. https://www.worldbank.org/en/publication/worldwide-governance-indicators (Accessed: 14 December 2025)
Corruption Perceptions Index, Transparency International – Corruption Perceptions Index 2024, https://www.transparency.org/en/cpi/2024 (Accessed: 14 December 2025)
Eurostat. (2024). Eurostat – SDG 08_10: GDP per capita, current prices (EUR) https://ec.europa.eu/eurostat/databrowser/view/sdg_08_10/default/table (Accessed: 14 December 2025)
United Nations Development Programme – Human Development Report 2024 https://hdr.undp.org/data-center/human-development-index (Accessed: 14 December 2025)
Eurostat – SDG 07_50: Energy dependency rate (net imports / gross inland consumption) https://ec.europa.eu/eurostat/databrowser/view/sdg_07_50/default/table
Eurostat – SDG 07_20: Renewable energy share in gross final energy consumption https://ec.europa.eu/eurostat/databrowser/view/sdg_07_20/default/table
European Investment Bank – Green Bond Database https://www.eib.org/en/publications/green-bond-impact-report (Accessed: 14 December 2025)
European Commission – Cohesion Policy Data (Cohesion Fund receipts 2015–2024, % of GDP) https://cohesiondata.ec.europa.eu/ (Accessed: 14 December 2025)
Regional coordinates (NUTS2, NUTS3), https://ec.europa.eu/eurostat (Accessed: 14 December 2025)
Emrouznejad, A., & Yang, G. L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4–8. https://doi.org/10.1016/j.seps.2017.01.008
Sustainable Development Solutions Network. (2024). Europe sustainable development report 2024: Performance rankings and policy implications. SDSN Europe. https://www.sdsn.eu/reports/europe-sustainable-development-report-2024/ (Accessed: 14 December 2025)
Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124–131. https://doi.org/10.1016/j.omega.2013.04.003
Porter, M. E., & van der Linde, C. (1995). Toward a new conception of the environment–competitiveness relationship. Journal of Economic Perspectives, 9(4), 97–118. https://doi.org/10.1257/jep.9.4.97
Folke, C., Carpenter, S. R., Walker, B., Scheffer, M., Chapin, T., & Rockström, J. (2010). Resilience thinking: Integrating resilience, adaptability and transformability. Ecology and Society, 15(4), 20. https://doi.org/10.5751/ES-03610-150420
Simms, B. (2022). European geopolitical vulnerabilities: Structural dependencies and crisis exposure patterns. International Security Review, 45(3), 78–95.
Borrás, S., & Radaelli, C. M. (2011). The politics of governance architectures: Creation, change and effects of the EU Lisbon Strategy. Journal of European Public Policy, 18(4), 463–484. https://doi.org/10.1080/13501763.2011.560490
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Stefan Petrov (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.


All site content, except where otherwise noted, is licensed under the