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Does energy aid reduce CO2 emission intensities in developing countries?

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  • Masako Ikegami
  • Zijian Wang

Abstract

Whether energy aid contributes to the reduction of CO2 emissions in developing countries is an unresolved question. We investigate whether the OECD Development Assistance Committee members’ energy aid can help reduce CO2 emission intensities in 64 recipient countries over the period 1995–2014. We find that once lagged energy aid – when measured in terms of once lagged GDP, in absolute terms, or in terms of once lagged total sectoral aid – is effective in reducing the recipients’ subsequent CO2 emission intensities. Importantly, we find highly varied effects of energy aid on the recipients’ CO2 emission intensities – fossil fuel-rich (poor) countries stand to benefit least (most) from receiving energy aid. Our findings point towards the merit of energy aid as a policy tool in achieving the CO2 emission reduction goals and the necessity for bilateral aid donors to take into account the recipients’ fossil fuel abundance when making provisions for energy aid.

Suggested Citation

  • Masako Ikegami & Zijian Wang, 2021. "Does energy aid reduce CO2 emission intensities in developing countries?," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 10(4), pages 343-358, October.
  • Handle: RePEc:taf:teepxx:v:10:y:2021:i:4:p:343-358
    DOI: 10.1080/21606544.2021.1882342
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    Citations

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    Cited by:

    1. Jeong Won Kim & Jae-Seung Lee, 2021. "Greening Energy Finance of Multilateral Development Banks: Review of the World Bank’s Energy Project Investment (1985–2019)," Energies, MDPI, vol. 14(9), pages 1-23, May.
    2. Liu, Yang & Dong, Kangyin & Taghizadeh-Hesary, Farhad, 2023. "How does energy aid mitigate the recipient countries’ carbon emissions?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 359-375.
    3. Simplice A. Asongu & Barbara D. Mensah & Judith C. M. Ngoungou, 2022. "Thresholds of external flows in financial development for environmental sustainability in sub-Saharan Africa," Working Papers 22/082, European Xtramile Centre of African Studies (EXCAS).
    4. Mahdieh Parsaeian & Mohammad Rahimi & Abbas Rohani & Shaneka S. Lawson, 2022. "Towards the Modeling and Prediction of the Yield of Oilseed Crops: A Multi-Machine Learning Approach," Agriculture, MDPI, vol. 12(10), pages 1-23, October.

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