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Electricity load level detail in computational general equilibrium – Part I – Data and calibration

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  • Rodrigues, Renato
  • Linares, Pedro

Abstract

The growing importance of the electricity sector in many economies, and of energy and environmental policies, requires a detailed consideration of these sectors and policies in computable general equilibrium (CGE) models, including both technological and temporal aspects. This paper presents the first attempt to our knowledge at building temporal disaggregation into a CGE model, while keeping technological detail. This contribution is coupled with some methodological improvements over existing technology-rich CGE models. The model is able to account for the indirect effects characteristic of CGE models while also mimicking the detailed behavior of the electricity operation and investment present before only in bottom-up detailed models. The present paper is the first of two parts and focuses on the bottom-up top-down calibration methodology needed to build such a model. Part II will present the CGE model applied to the evaluation of an energy policy with temporal consequences.

Suggested Citation

  • Rodrigues, Renato & Linares, Pedro, 2014. "Electricity load level detail in computational general equilibrium – Part I – Data and calibration," Energy Economics, Elsevier, vol. 46(C), pages 258-266.
    • Handle: RePEc:eee:eneeco:v:46:y:2014:i:c:p:258-266
    DOI: 10.1016/j.eneco.2014.09.016
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    References listed on IDEAS

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    1. McFarland, J. R. & Reilly, J. M. & Herzog, H. J., 2004. "Representing energy technologies in top-down economic models using bottom-up information," Energy Economics, Elsevier, vol. 26(4), pages 685-707, July.
    2. Jean-Marc Burniaux & John P. Martin & Giuseppe Nicoletti & Joaquim Oliveira Martins, 1992. "GREEN a Multi-Sector, Multi-Region General Equilibrium Model for Quantifying the Costs of Curbing CO2 Emissions: A Technical Manual," OECD Economics Department Working Papers 116, OECD Publishing.
    3. Frederic Ghersi and Jean-Charles Hourcade, 2006. "Macroeconomic Consistency issues in E3 Modeling: The Continued Fable of the Elephant and the Rabbit," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 39-62.
    4. Rausch, Sebastian & Metcalf, Gilbert E. & Reilly, John M., 2011. "Distributional impacts of carbon pricing: A general equilibrium approach with micro-data for households," Energy Economics, Elsevier, vol. 33(S1), pages 20-33.
    5. McFarland, James R. & Herzog, Howard J., 2006. "Incorporating carbon capture and storage technologies in integrated assessment models," Energy Economics, Elsevier, vol. 28(5-6), pages 632-652, November.
    6. Sue Wing, Ian, 2008. "The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technology detail in a social accounting framework," Energy Economics, Elsevier, vol. 30(2), pages 547-573, March.
    7. F. Ghersi & Jean Charles Hourcade, 2006. "Macroeconomic consistency issues in E3 modeling: The continued fable of the elephant and the rabbit," Post-Print hal-00716324, HAL.
    8. Rodrigues, Renato & Linares, Pedro, 2015. "Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program," Energy Economics, Elsevier, vol. 47(C), pages 52-67.
    9. Keppo, Ilkka & Strubegger, Manfred, 2010. "Short term decisions for long term problems – The effect of foresight on model based energy systems analysis," Energy, Elsevier, vol. 35(5), pages 2033-2042.
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    Cited by:

    1. Rodrigues, Renato & Linares, Pedro, 2015. "Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program," Energy Economics, Elsevier, vol. 47(C), pages 52-67.
    2. Pablo Pintos & Pedro Linares, 2016. "Assessing the EU ETS with an Integrated Model," Working Papers 01-2016, Economics for Energy.
    3. Jieting Yin & Qingyou Yan & Kaijie Lei & Tomas Baležentis & Dalia Streimikiene, 2019. "Economic and Efficiency Analysis of China Electricity Market Reform Using Computable General Equilibrium Model," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    4. Carlos Benavides & Luis Gonzales & Manuel Diaz & Rodrigo Fuentes & Gonzalo García & Rodrigo Palma-Behnke & Catalina Ravizza, 2015. "The Impact of a Carbon Tax on the Chilean Electricity Generation Sector," Energies, MDPI, vol. 8(4), pages 1-27, April.
    5. Xavier Labandeira & José M. Labeaga & Xiral López-Otero, 2019. "New Green Tax Reforms: Ex-Ante Assessments for Spain," Sustainability, MDPI, vol. 11(20), pages 1-25, October.

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    More about this item

    Keywords

    Computable general equilibrium (CGE); Calibration;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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