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Quota allocation rules in Romania assessed by a dynamic CGE model

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  • RODICA LOISEL

Abstract

Alternative mechanisms for EU ETS (European Union Emissions Trading Scheme) quota allocations within the Romanian economy were evaluated using a general equilibrium model within a dynamic intertemporal framework. Several distribution rules were simulated based on: the historical emissions, the least-cost approach, and the auctioning scheme with and without a preliminary selection of eligible sectors. We found that the resulting marginal abatement cost in ETS-eligible sectors is only €5.75/tCO 2 for reducing pollution by 20.7%. Such a low cost is explained by low energy prices and by substitution possibilities with low carbon content resources (nuclear and hydroelectricity). Including all sectors in the trade creates a more flexible market than in the ETS, since more reduction options are available. The ETS has high feasibility for monitoring. All eligible sectors (except refineries and metallurgy) present the lowest abatement costs in the economy. Auctioning introduces a strong carbon price signal, which reduces emission intensity but creates distortions in terms of trade and worsens the country's energy dependency. Environmental policy has modest macroeconomic results and tends to correct the resources allocation. The strong double dividend obtained under certain circumstances indicates Romania's potential for improving its energy efficiency and carbon intensity.

Suggested Citation

  • Rodica Loisel, 2010. "Quota allocation rules in Romania assessed by a dynamic CGE model," Climate Policy, Taylor & Francis Journals, vol. 10(1), pages 87-102, January.
    • Handle: RePEc:taf:tcpoxx:v:10:y:2010:i:1:p:87-102
    DOI: 10.3763/cpol.2008.0557
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    1. Hiro Lee & Joaquim Oliveira Martins & Dominique van der Mensbrugghe, 1994. "The OECD Green Model: An Updated Overview," OECD Development Centre Working Papers 97, OECD Publishing.
    2. McKibbin, Warwick J. & Wilcoxen, Peter J., 1998. "The theoretical and empirical structure of the G-Cubed model," Economic Modelling, Elsevier, vol. 16(1), pages 123-148, January.
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    Cited by:

    1. Pan, Xiongfeng & Wang, Mengyang & Li, Mengna, 2023. "Low-carbon policy and industrial structure upgrading: Based on the perspective of strategic interaction among local governments," Energy Policy, Elsevier, vol. 183(C).
    2. Yun-Fei Yao & Qiao-Mei Liang, 2016. "Approaches to carbon allowance allocation in China: a computable general equilibrium analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 333-351, November.
    3. Zheng, Xiaogui & Huang, Guohe & Liu, Lirong & Zhang, Xiaoyue, 2025. "Factorial equilibrium analyses for socio-economic implications of emission trading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 214(C).

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