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Modelling of distributional impacts of energy subsidy reforms: an illustration with Indonesia

Author

Listed:
  • Olivier Durand-Lasserve

    (OECD)

  • Lorenza Campagnolo

    (University of Venice)

  • Jean Chateau

    (OECD)

  • Rob Dellink

    (OECD)

Abstract

This report develops an analytical framework that assesses the macroeconomic, environmental and distributional consequences of energy subsidy reforms. The framework is applied to the case of Indonesia to study the consequences in this country of a gradual phase out of all energy consumption subsidies between 2012 and 2020. The energy subsidy estimates used as inputs to this modelling analysis are those calculated by the International Energy Agency, using a synthetic indicator known as “price gaps”. The analysis relies on simulations made with an extended version of the OECD’s ENV-Linkages model. The phase out of energy consumption subsidies was simulated under three stylised redistribution schemes: direct payment on a per household basis, support to labour incomes, and subsidies on food products. The modelling results in this report indicate that if Indonesia were to remove its fossil fuel and electricity consumption subsidies, it would record real GDP gains of 0.4% to 0.7% in 2020, according to the redistribution scheme envisaged. The redistribution through direct payment on a per household basis performs best in terms of GDP gains. The aggregate gains for consumers in terms of welfare are higher, ranging from 0.8% to 1.6% in 2020. Both GDP and welfare gains arise from a more efficient allocation of resources across sectors resulting from phasing out energy subsidies. Meanwhile, a redistribution scheme through food subsidies tends to create other inefficiencies. The simulations show that the redistribution scheme ultimately matters in determining the overall distributional performance of the reform. Cash transfers, and to a lesser extent food subsidies, can make the reform more attractive for poorer households and reduce poverty. Mechanisms that compensate households via payments proportional to labour income are, on the contrary, more beneficial to higher income households and increase poverty. This is because households with informal labour earnings, which are not eligible for these payments, are more represented among the poor. The analysis also shows that phasing out energy subsidies is projected to reduce Indonesian CO2 emissions from fuel combustion by 10.8% to 12.6% and GHG emissions by 7.9% to 8.3%, in 2020 in the various scenarios, with respect to the baseline. These emission reductions exclude emissions from deforestation, which are large but highly uncertain and for which the model cannot make reliable projections. Ce rapport élabore un cadre analytique qui évalue les effets macroéconomiques, environnementaux et redistributifs des réformes des subventions énergétiques. Il applique ce cadre au cas de l’Indonésie afin d’étudier les conséquences dans ce pays d’une suppression progressive de toutes les subventions à la consommation d’énergie entre 2012 et 2020. Les estimations des subventions à l’énergie sur lesquelles se base cette analyse par modélisation sont celles calculées par l’Agence internationale de l’énergie, à l’aide d’un indicateur synthétique appelé « différentiel de prix ». L’analyse repose sur des simulations réalisées avec une version enrichie du modèle ENV-Linkages de l’OCDE, modèle dynamique d’équilibre général calculable (EGC) mondial. La suppression des subventions à la consommation d’énergie a été simulée en retenant trois types de dispositifs de redistribution : un paiement direct au niveau des ménages, un soutien aux revenus du travail et des subventions aux produits alimentaires. Les résultats de la modélisation réalisée dans ce rapport indiquent que si l’Indonésie venait à supprimer ses subventions à la consommation des combustibles fossiles et d’électricité, elle enregistrerait des gains de PIB réel de 0.4 % à 0.7 % en 2020, selon le dispositif de redistribution retenu. La redistribution sous forme de paiements directs au niveau des ménages donne les meilleurs résultats en termes de gains de PIB. Le gain global pour les consommateurs en termes de bien-être est plus élevé, allant de 0.8 % à 1.6 % en 2020. Les gains en matière de PIB et de bien-être sont obtenus grâce à une répartition des ressources entre les secteurs de façon plus efficiente à la suite de l’élimination des subventions énergétiques. Dans l’intervalle, un dispositif de redistribution sous forme de subventions alimentaires tend à créer d’autres inefficacités, qui compensent en partie les avantages macroéconomiques de la suppression des subventions à la consommation d’énergie. Les simulations montrent aussi qu’à terme, le dispositif de redistribution joue un rôle en déterminant l’effet redistributif global de la réforme. Les transferts monétaires, et dans une moindre mesure les subventions alimentaires, peuvent rendre la réforme plus profitable pour les ménages pauvres et faire reculer la pauvreté. À l’inverse, les mécanismes qui compensent les ménages à l’aide de paiements proportionnels aux revenus du travail bénéficient davantage aux ménages à revenu élevé et accroissent la pauvreté. En effet, les ménages qui reçoivent des revenus du travail dans le secteur informel et qui ne peuvent prétendre à ces paiements, sont plus nombreux chez les pauvres. L’analyse montre aussi que d’après les prévisions, la suppression des subventions énergétiques en Indonésie devrait réduire les émissions de CO2 dues à la combustion des énergies fossiles de 10.8 % à 12.6 % et les émissions de GES de 7.9 % à 8.3 % en 2020 selon les différents scénarios, par rapport au scénario de référence. Ces réductions d’émissions ne tiennent pas compte des émissions dues à la déforestation, qui sont élevées mais restent très mal connues, et au sujet desquelles le modèle ne peut pas faire de projections fiables.

Suggested Citation

  • Olivier Durand-Lasserve & Lorenza Campagnolo & Jean Chateau & Rob Dellink, 2015. "Modelling of distributional impacts of energy subsidy reforms: an illustration with Indonesia," OECD Environment Working Papers 86, OECD Publishing.
  • Handle: RePEc:oec:envaaa:86-en
    DOI: 10.1787/5js4k0scrqq5-en
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    Cited by:

    1. Herwig Immervoll & Cathal O’Donoghue & Jules Linden & Denisa Sologon, 2023. "Who pays for higher carbon prices?: Illustration for Lithuania and a research agenda," OECD Social, Employment and Migration Working Papers 283, OECD Publishing.
    2. Jon Sampedro & Iñaki Arto & Mikel González-Eguino, 2017. "Implications of Switching Fossil Fuel Subsidies to Solar: A Case Study for the European Union," Sustainability, MDPI, vol. 10(1), pages 1-12, December.
    3. Ben Westmore, 2017. "Sharing the Benefits of China’s Growth by Providing Opportunities to All," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-33, October.
    4. Robert J. R. Elliott & Toshihiro Okubo, 2016. "Ecological Modernization in Japan: The Role of Interest Rate Subsidies and Voluntary Pollution Control Agreements," Asian Economic Papers, MIT Press, vol. 15(3), pages 66-88, Fall.
    5. Filippo Maria D’Arcangelo & Ilai Levin & Alessia Pagani & Mauro Pisu & Åsa Johansson, 2022. "A framework to decarbonise the economy," OECD Economic Policy Papers 31, OECD Publishing.
    6. Hübler, Michael & Wiese, Malin & Braun, Marius & Damster, Johannes, 2024. "The distributional effects of CO2 pricing at home and at the border on German income groups," Resource and Energy Economics, Elsevier, vol. 77(C).
    7. José M. Labeaga & Xavier Labandeira & Xiral López-Otero, 2018. "Energy Tax Reform and Poverty Alleviation in Mexico," Working Papers 1801, Universidade de Vigo, Departamento de Economía Aplicada.
    8. van Ruijven, Bas J. & O’Neill, Brian C. & Chateau, Jean, 2015. "Methods for including income distribution in global CGE models for long-term climate change research," Energy Economics, Elsevier, vol. 51(C), pages 530-543.
    9. Lekavičius, V. & Bobinaitė, V. & Galinis, A. & Pažėraitė, A., 2020. "Distributional impacts of investment subsidies for residential energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    10. Rentschler, Jun & Kornejew, Martin, 2017. "Energy price variation and competitiveness: Firm level evidence from Indonesia," Energy Economics, Elsevier, vol. 67(C), pages 242-254.
    11. Stefan Bakker & Gary Haq & Karl Peet & Sudhir Gota & Nikola Medimorec & Alice Yiu & Gail Jennings & John Rogers, 2019. "Low-Carbon Quick Wins: Integrating Short-Term Sustainable Transport Options in Climate Policy in Low-Income Countries," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    12. Agboje, A., 2018. "Implication of Switching Fuel Subsidy on Households Welfare in Nigeria," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275938, International Association of Agricultural Economists.
    13. Jun E Rentschler & Nobuhiro Hosoe, 2017. "Illicit dealings: Fossil fuel subsidy reforms and the role of tax evasion and smuggling," GRIPS Discussion Papers 17-05, National Graduate Institute for Policy Studies.
    14. Maulidia, Martha & Dargusch, Paul & Ashworth, Peta & Ardiansyah, Fitrian, 2019. "Rethinking renewable energy targets and electricity sector reform in Indonesia: A private sector perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 231-247.
    15. Rentschler, Jun & Kornejew, Martin & Bazilian, Morgan, 2017. "Fossil fuel subsidy reforms and their impacts on firms," Energy Policy, Elsevier, vol. 108(C), pages 617-623.
    16. Maruyama Rentschler,Jun Erik & Hosoe,Nobuhiro, 2022. "Illicit Schemes : Fossil Fuel Subsidy Reforms and the Role of Tax Evasion and Smuggling," Policy Research Working Paper Series 9907, The World Bank.
    17. Roman Mendelevitch, 2018. "Testing supply-side climate policies for the global steam coal market—can they curb coal consumption?," Climatic Change, Springer, vol. 150(1), pages 57-72, September.

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    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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