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Is the Cohesion Policy Efficient in Supporting the Transition to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis

Author

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  • Maria Gouveia

    (Polytechnic of Coimbra, Coimbra Business School|ISCAC, 3045-601 Coimbra, Portugal
    INESC Coimbra, DEEC, Rua Sílvio Lima, Polo II, 3030-290 Coimbra, Portugal
    CeBER, Faculty of Economics, University of Coimbra, Av Dias da Silva 165, 3004-512 Coimbra, Portugal)

  • Carla Henriques

    (Polytechnic of Coimbra, Coimbra Business School|ISCAC, 3045-601 Coimbra, Portugal
    INESC Coimbra, DEEC, Rua Sílvio Lima, Polo II, 3030-290 Coimbra, Portugal
    CeBER, Faculty of Economics, University of Coimbra, Av Dias da Silva 165, 3004-512 Coimbra, Portugal)

  • Ana Amaro

    (Polytechnic of Coimbra, Coimbra Business School|ISCAC, 3045-601 Coimbra, Portugal
    CEGIST-IST-UL, 1049-001 Lisboa, Portugal)

Abstract

We evaluated the implementation of European Regional Development Funds (ERDF) devoted to Thematic Objective (TO) 4 in 23 beneficiary European Union (EU) Member States (MS). The assessment of each country was made through the value-based data envelopment analysis (VBDEA) approach in three phases. In the first phase, it was possible to conclude that 43% of the MS were efficient in the implementation of the ERDF devoted to a low-carbon economy (LCE), and the reasons for their efficiency were mainly explained by their execution rate. After running the second phase for the inefficient countries, it was possible to obtain the improvements that must be made for these countries to “emulate” their peers at the efficient frontier. Finally, in the third stage, we incorporated political concerns in the evaluation of the implementation of the ERDF by including constraints on the ranking order of the weights. A robustness analysis was also carried out, according to which it was found that only 22% of the MS under evaluation remained surely efficient for tolerances of δ = 5% and δ = 10%, with Spain being the most robust country. Other countries such as Romania (surely inefficient for δ = 5%), Hungary, and the Czech Republic (the most inefficient) did not manage to implement these funds efficiently. Considering these findings, the EU needs to further promote policies that ensure economic benefits from investing in an LCE, specifically for countries with fewer resources, while also providing them with better financial conditions and know-how.

Suggested Citation

  • Maria Gouveia & Carla Henriques & Ana Amaro, 2022. "Is the Cohesion Policy Efficient in Supporting the Transition to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis," Sustainability, MDPI, vol. 14(18), pages 1-24, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11587-:d:915860
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    References listed on IDEAS

    as
    1. Yanhong Ding & Yu Han & Zaoli Yang, 2022. "Low Carbon Economy Assessment in China Using the Super-SBM Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-9, May.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Chenet, Hugues & Ryan-Collins, Josh & van Lerven, Frank, 2021. "Finance, climate-change and radical uncertainty: Towards a precautionary approach to financial policy," Ecological Economics, Elsevier, vol. 183(C).
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. M C Gouveia & L C Dias & C H Antunes, 2008. "Additive DEA based on MCDA with imprecise information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 54-63, January.
    6. Xiangshuo He & Jian Zhang, 2018. "Supplier Selection Study under the Respective of Low-Carbon Supply Chain: A Hybrid Evaluation Model Based on FA-DEA-AHP," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    7. Gouveia, M.C. & Henriques, C.O. & Costa, P., 2021. "Evaluating the efficiency of structural funds: An application in the competitiveness of SMEs across different EU beneficiary regions," Omega, Elsevier, vol. 101(C).
    8. Meng, Ming & Qu, Danlei, 2022. "Understanding the green energy efficiencies of provinces in China: A Super-SBM and GML analysis," Energy, Elsevier, vol. 239(PA).
    9. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834.
    10. Xiang Liu & Jia Liu, 2016. "Measurement of Low Carbon Economy Efficiency with a Three-Stage Data Envelopment Analysis: A Comparison of the Largest Twenty CO 2 Emitting Countries," IJERPH, MDPI, vol. 13(11), pages 1-14, November.
    11. M C Gouveia & L C Dias & C H Antunes, 2013. "Super-efficiency and stability intervals in additive DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(1), pages 86-96, January.
    12. Ryan Hanna & Yangyang Xu & David G. Victor, 2020. "After COVID-19, green investment must deliver jobs to get political traction," Nature, Nature, vol. 582(7811), pages 178-180, June.
    13. Ali, Agha Iqbal & Lerme, Catherine S. & Seiford, Lawrence M., 1995. "Components of efficiency evaluation in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 80(3), pages 462-473, February.
    14. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    15. Song, Yanwu & Zhang, Jinrui & Song, Yingkang & Fan, Xinran & Zhu, Yuqing & Zhang, Chen, 2020. "Can industry-university-research collaborative innovation efficiency reduce carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    16. Iwona Bąk & Anna Barwińska-Małajowicz & Grażyna Wolska & Paweł Walawender & Paweł Hydzik, 2021. "Is the European Union Making Progress on Energy Decarbonisation While Moving towards Sustainable Development?," Energies, MDPI, vol. 14(13), pages 1-18, June.
    17. Gefu Liang & Dajia Yu & Lifei Ke, 2021. "An Empirical Study on Dynamic Evolution of Industrial Structure and Green Economic Growth—Based on Data from China’s Underdeveloped Areas," Sustainability, MDPI, vol. 13(15), pages 1-16, July.
    18. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    19. Weijuan Li & Pengcheng Zhang, 2021. "Developing the transformation of scientific and technological achievements in colleges and universities to boost the development of low-carbon economy [Social stability risk assessment of land expr," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 16(2), pages 305-316.
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