IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03861139.html
   My bibliography  Save this paper

On the Use of General Equilibrium Model to Assess the Impact of Climate Policy in Latvia

Author

Listed:
  • Olegs Krasnopjorovs

    (LU - University of Latvia)

  • Daniels Jukna

    (LU - University of Latvia)

  • Konstantins Kovalovs

    (LU - University of Latvia)

Abstract

Ambitious climate policy targets by developed countries towards carbon neutrality created a necessity to model the impact of climate policy on macroeconomic and socioeconomic indicators. Academic literature suggests that Computable General Equilibrium (CGE) model representing the entire economy, linked with a TIMES model reflecting the energy sector in detail, proved to be an effective tool for such modelling. This article contributes to the starting point for creating such a modelling system in the University of Latvia (CGE model) and the Institute of Physical Energetics (TIMES model), focusing on the CGE model. First, it reviews the literature on the use of the CGE model and its effective link with the TIMES model to assess the economic impact of climate policy. Second, it reviews the features of the current Latvian CGE model owned by the University of Latvia, compared to its ORANI-G model prototype. Third, as a list of recommendations, it proposes a roadmap for the future development of the Latvian CGE model to be effectively linked with the TIMES model to assess the impact of climate policy on macroeconomic and socioeconomic indicators.

Suggested Citation

  • Olegs Krasnopjorovs & Daniels Jukna & Konstantins Kovalovs, 2022. "On the Use of General Equilibrium Model to Assess the Impact of Climate Policy in Latvia," Post-Print hal-03861139, HAL.
    • Handle: RePEc:hal:journl:hal-03861139
    Note: View the original document on HAL open archive server: https://hal.science/hal-03861139
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03861139/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Valentina Bosetti & Carlo Carraro & Marzio Galeotti & Emanuele Massetti & Massimo Tavoni, 2006. "WITCH. A World Induced Technical Change Hybrid Model," Working Papers 2006_46, Department of Economics, University of Venice "Ca' Foscari".
    2. Krook-Riekkola, Anna & Berg, Charlotte & Ahlgren, Erik O. & Söderholm, Patrik, 2017. "Challenges in top-down and bottom-up soft-linking: Lessons from linking a Swedish energy system model with a CGE model," Energy, Elsevier, vol. 141(C), pages 803-817.
    3. Fortes, Patrícia & Pereira, Rui & Pereira, Alfredo & Seixas, Júlia, 2014. "Integrated technological-economic modeling platform for energy and climate policy analysis," Energy, Elsevier, vol. 73(C), pages 716-730.
    4. Abrell, Jan & Rausch, Sebastian, 2016. "Cross-country electricity trade, renewable energy and European transmission infrastructure policy," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 87-113.
    5. van Vuuren, Detlef P. & Hoogwijk, Monique & Barker, Terry & Riahi, Keywan & Boeters, Stefan & Chateau, Jean & Scrieciu, Serban & van Vliet, Jasper & Masui, Toshihiko & Blok, Kornelis & Blomen, Eliane , 2009. "Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials," Energy Policy, Elsevier, vol. 37(12), pages 5125-5139, December.
    6. Frei, Christoph W. & Haldi, Pierre-Andre & Sarlos, Gerard, 2003. "Dynamic formulation of a top-down and bottom-up merging energy policy model," Energy Policy, Elsevier, vol. 31(10), pages 1017-1031, August.
    7. Martin L. Weitzman, 2012. "GHG Targets as Insurance Against Catastrophic Climate Damages," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 14(2), pages 221-244, March.
    8. Schafer, Andreas & Jacoby, Henry D., 2005. "Technology detail in a multisector CGE model: transport under climate policy," Energy Economics, Elsevier, vol. 27(1), pages 1-24, January.
    9. Andersen, Kristoffer S. & Termansen, Lars B. & Gargiulo, Maurizio & Ó Gallachóirc, Brian P., 2019. "Bridging the gap using energy services: Demonstrating a novel framework for soft linking top-down and bottom-up models," Energy, Elsevier, vol. 169(C), pages 277-293.
    10. Valentina Bosetti, Carlo Carraro, Marzio Galeotti, Emanuele Massetti, Massimo Tavoni, 2006. "A World induced Technical Change Hybrid Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 13-38.
    11. Devarajan, Shantayanan & Go, Delfin S., 1998. "The Simplest Dynamic General-Equilibrium Model of an Open Economy," Journal of Policy Modeling, Elsevier, vol. 20(6), pages 677-714, December.
    12. Giraudet, Louis-Gaëtan & Guivarch, Céline & Quirion, Philippe, 2012. "Exploring the potential for energy conservation in French households through hybrid modeling," Energy Economics, Elsevier, vol. 34(2), pages 426-445.
    13. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(II), pages 111-135, June.
    14. Bohringer, Christoph & Rutherford, Thomas F., 2008. "Combining bottom-up and top-down," Energy Economics, Elsevier, vol. 30(2), pages 574-596, March.
    15. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    16. Böhringer, Christoph & Rutherford, Thomos F., 2009. "Integrated assessment of energy policies: Decomposing top-down and bottom-up," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1648-1661, September.
    17. Van Ha, Pham & Kompas, Tom, 2016. "Solving intertemporal CGE models in parallel using a singly bordered block diagonal ordering technique," Economic Modelling, Elsevier, vol. 52(PA), pages 3-12.
    18. Wong, Grace Y. & Alavalapati, Janaki R. R., 2003. "The land-use effects of a forest carbon policy in the US," Forest Policy and Economics, Elsevier, vol. 5(3), pages 249-263, September.
    19. Martinsen, Thomas, 2011. "Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models," Energy Policy, Elsevier, vol. 39(6), pages 3327-3336, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lee, Hwarang & Kang, Sung Won & Koo, Yoonmo, 2020. "A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects," Energy, Elsevier, vol. 212(C).
    2. Andersen, Kristoffer S. & Termansen, Lars B. & Gargiulo, Maurizio & Ó Gallachóirc, Brian P., 2019. "Bridging the gap using energy services: Demonstrating a novel framework for soft linking top-down and bottom-up models," Energy, Elsevier, vol. 169(C), pages 277-293.
    3. Fortes, Patrícia & Pereira, Rui & Pereira, Alfredo & Seixas, Júlia, 2014. "Integrated technological-economic modeling platform for energy and climate policy analysis," Energy, Elsevier, vol. 73(C), pages 716-730.
    4. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Pisciella, Paolo & van Beesten, E. Ruben & Tomasgard, Asgeir, 2023. "Efficient coordination of top-down and bottom-up models for energy system design: An algorithmic approach," Energy, Elsevier, vol. 284(C).
    6. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    7. Laha, Priyanka & Chakraborty, Basab, 2017. "Energy model – A tool for preventing energy dysfunction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 95-114.
    8. Gjorgiev, Blazhe & Garrison, Jared B. & Han, Xuejiao & Landis, Florian & van Nieuwkoop, Renger & Raycheva, Elena & Schwarz, Marius & Yan, Xuqian & Demiray, Turhan & Hug, Gabriela & Sansavini, Giovanni, 2022. "Nexus-e: A platform of interfaced high-resolution models for energy-economic assessments of future electricity systems," Applied Energy, Elsevier, vol. 307(C).
    9. Helgesen, Per Ivar & Tomasgard, Asgeir, 2018. "From linking to integration of energy system models and computational general equilibrium models – Effects on equilibria and convergence," Energy, Elsevier, vol. 159(C), pages 1218-1233.
    10. Durand-Lasserve, Olivier & Almutairi, Hossa & Aljarboua, Abdullah & Pierru, Axel & Pradhan, Shreekar & Murphy, Frederic, 2023. "Hard-linking a top-down economic model with a bottom-up energy system for an oil-exporting country with price controls," Energy, Elsevier, vol. 266(C).
    11. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    12. Ruth Delzeit & Robert Beach & Ruben Bibas & Wolfgang Britz & Jean Chateau & Florian Freund & Julien Lefevre & Franziska Schuenemann & Timothy Sulser & Hugo Valin & Bas van Ruijven & Matthias Weitzel &, 2020. "Linking Global CGE Models with Sectoral Models to Generate Baseline Scenarios: Approaches, Challenges, and Opportunities," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 5(1), pages 162-195, June.
    13. Ruth Delzeit & Roberto Beach & Ruben Bibas & Wolfgang Britz & Jean Chateau & Florian Freund & Julien Lefevre & Franziska Schuenemann & Timothy Sulser & Hugo Valin & Bas van Ruijven & Matthias Weitzel , 2020. "Linking global CGE models with sectoral models to generate baseline scenarios: Approaches, opportunities and pitfalls," Post-Print hal-03128285, HAL.
    14. Mier, Mathias & Siala, Kais & Govorukha, Kristina & Mayer, Philip, 2023. "Collaboration, decarbonization, and distributional effects," Applied Energy, Elsevier, vol. 341(C).
    15. Milad Maralani & Milad Maralani & Basil Sharp & Golbon Zakeri, 2016. "The Potential Impact of Industrial Energy Savings on The New Zealand Economy," EcoMod2016 9308, EcoMod.
    16. Krook-Riekkola, Anna & Berg, Charlotte & Ahlgren, Erik O. & Söderholm, Patrik, 2017. "Challenges in top-down and bottom-up soft-linking: Lessons from linking a Swedish energy system model with a CGE model," Energy, Elsevier, vol. 141(C), pages 803-817.
    17. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
    18. van den Broek, Machteld & Veenendaal, Paul & Koutstaal, Paul & Turkenburg, Wim & Faaij, André, 2011. "Impact of international climate policies on CO2 capture and storage deployment: Illustrated in the Dutch energy system," Energy Policy, Elsevier, vol. 39(4), pages 2000-2019, April.
    19. Böhringer, Christoph & Rutherford, Thomos F., 2009. "Integrated assessment of energy policies: Decomposing top-down and bottom-up," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1648-1661, September.
    20. Sophie Maire & Philippe Thalmann & Frank Vöhringer, 2019. "Welfare effects of technology-based climate policies in liberalized electricity markets: seeing beyond total system cost," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-12, December.

    More about this item

    Keywords

    Computable General Equilibrium model; climate policy modelling; soft-link;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-03861139. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.