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Financial and environmental efficiency of CDM projects: Analysis and classification for investment decisions

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  • Antônio Carlos Pacagnella Júnior
  • Henrique Luiz da Silva
  • Wagner Wilson Bortoletto
  • Paulo Sergio de Arruda Ignacio

Abstract

The main purpose of this paper is to analyze the efficiency of Clean Development Mechanism (CDM) projects implemented worldwide and understand their main characteristics, seeking to support investment decisions and expand the scientific understanding of the financial and environmental impact of these projects. To achieve this goal, a sample of 2352 CDM projects was selected from a United Nations Framework Convention on Climate Change (UNFCCC) database and analyzed first with a two‐stage data envelopment analysis (DEA) model that allowed the evaluation of the financial return and environmental efficiency of these projects. DEA results provide an efficiency ranking that was then analyzed with a classification tree (CHAID algorithm), revealing some main characteristics of the projects with higher efficiencies, like their sizes, locations, and type of CDM. CDMs are projects that demand a significant quantity of resources and effort to produce the expected outcomes, so it is crucial for public managers and investors to know the project profiles that generate the best financial and environmental results. In this sense, this study presents a completely original methodology for this kind of analysis and reveals important insights for these agents and researchers in this field.

Suggested Citation

  • Antônio Carlos Pacagnella Júnior & Henrique Luiz da Silva & Wagner Wilson Bortoletto & Paulo Sergio de Arruda Ignacio, 2023. "Financial and environmental efficiency of CDM projects: Analysis and classification for investment decisions," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 926-941, March.
    • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:2:p:926-941
    DOI: 10.1002/mde.3722
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    References listed on IDEAS

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    2. Chen, Tingqiang & Zheng, Xin & Wang, Lei, 2025. "Systemic risk among Chinese oil and petrochemical firms based on dynamic tail risk spillover networks," The North American Journal of Economics and Finance, Elsevier, vol. 77(C).

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