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Analyzing the Influence of Philanthropy on Eco-Efficiency in 108 Countries

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  • Matheus Belucio

    (EoF Academy, Viale Guglielmo Marconi, 6, 06081 Assisi, Italy
    CEFAGE-UE, University of Évora, Largo Marquês de Marialva, 8, 7000-809 Évora, Portugal
    Department of Economics, University of Évora, Largo dos Colegiais, 2, 7000-803 Évora, Portugal)

  • Giulio Guarini

    (EoF Academy, Viale Guglielmo Marconi, 6, 06081 Assisi, Italy
    Department of Economics, Engineering, Society and Business Organizations, University of Tuscia, 01100 Viterbo, Italy)

Abstract

This paper analyzes philanthropy’s influence on countries’ eco-efficiency. The hypothesis to be verified is that philanthropy can favour the eco-efficiency. A data panel was built with statistical information from 2009 to 2018. Two methods were applied. First, a Data Envelopment Analysis model output oriented was estimated to identify the situation of overall efficiency in countries. We consider the relationship between Gross Domestic Product per capita and carbon dioxide per capita as our desirable and undesirable products, respectively. The second estimated method was a Stochastic Frontier, through which it was possible to assess the impact of philanthropy on eco-efficiency (rank of overall efficiency from DEA). Assessing the average eco-efficiency of countries around the world, it is possible to state that the results are worrying, since they reveal a fall in the average eco-efficiency of the countries over the years. Moreover, according to the second econometric model, the philanthropy index positively impacts on eco-efficiency. These empirical results fill a gap in the literature on donations’ effect on countries’ eco-efficiency. They allow policymakers to see how philanthropy can be one more tool to help countries improve their eco-efficiency. However, there is a warning that some attention is needed (control and regulation) for the best use of donations.

Suggested Citation

  • Matheus Belucio & Giulio Guarini, 2023. "Analyzing the Influence of Philanthropy on Eco-Efficiency in 108 Countries," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1085-:d:1027431
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    References listed on IDEAS

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    1. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    2. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    3. 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.
    4. Rodríguez-García, Martha del Pilar & Galindo-Manrique, Alicia Fernanda & Cortez-Alejandro, Klender Aimer & Méndez-Sáenz, Alma Berenice, 2022. "Eco-efficiency and financial performance in Latin American countries: An environmental intensity approach," Research in International Business and Finance, Elsevier, vol. 59(C).
    5. Renato Santiago & José Alberto Fuinhas & António Cardoso Marques, 2020. "The impact of globalization and economic freedom on economic growth: the case of the Latin America and Caribbean countries," Economic Change and Restructuring, Springer, vol. 53(1), pages 61-85, February.
    6. Yantuan Yu & Jianhuan Huang & Nengsheng Luo, 2018. "Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency? Evidence from China," Sustainability, MDPI, vol. 10(2), pages 1-20, February.
    7. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    8. Chia-Nan Wang & Han-Sung Lin & Hsien-Pin Hsu & Van-Tinh Le & Tsung-Fu Lin, 2016. "Applying Data Envelopment Analysis and Grey Model for the Productivity Evaluation of Vietnamese Agroforestry Industry," Sustainability, MDPI, vol. 8(11), pages 1-15, November.
    9. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
    10. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    11. Wu, Bao & Jin, Chenfei & Monfort, Abel & Hua, Danni, 2021. "Generous charity to preserve green image? Exploring linkage between strategic donations and environmental misconduct," Journal of Business Research, Elsevier, vol. 131(C), pages 839-850.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    13. Althouse, Jeffrey & Guarini, Giulio & Gabriel Porcile, Jose, 2020. "Ecological macroeconomics in the open economy: Sustainability, unequal exchange and policy coordination in a center-periphery model," Ecological Economics, Elsevier, vol. 172(C).
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