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Combining Top-Down and Bottom-up in Energy Policy Analysis: A Decomposition Approach

Author

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  • Rutherford, Thomas F.
  • Böhringer, Christoph

Abstract

The formulation of market equilibrium problems as mixed complementarity problems (MCP) permits integration of bottom-up programming models of the energy system into top-down general equilibrium models of the overall economy. Despite the coherence and logical appeal of the integrated MCP approach, implementation cost and dimensionality both impose limitations on its practical application. A complementarity representation involves both primal and dual relationships, often doubling the number of equations and the scope for error. When an underlying optimization model of the energy system includes upper and lower bounds on many decision variables the MCP formulation may suffer in robustness and efficiency. While bounds can be included in the MCP framework, the treatment of associated income effects is awkward. We present a decomposition of the integrated MCP formulation that permits a convenient combination of top-down general equilibrium models and bottom-up energy system models for energy policy analysis. We advocate the use of complementarity methods to solve the top-down economic equilibrium model and quadratic programming to solve the underlying bottom-up energy supply model. A simple iterative procedure reconciles the equilibrium prices and quantities between both models. We illustrate this approach using a simple stylized model.

Suggested Citation

  • Rutherford, Thomas F. & Böhringer, Christoph, 2006. "Combining Top-Down and Bottom-up in Energy Policy Analysis: A Decomposition Approach," ZEW Discussion Papers 06-007, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  • Handle: RePEc:zbw:zewdip:4586
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    File URL: https://www.econstor.eu/bitstream/10419/24199/1/dp06007.pdf
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    References listed on IDEAS

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    1. 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.
    2. Bohringer, Christoph, 1998. "The synthesis of bottom-up and top-down in energy policy modeling," Energy Economics, Elsevier, vol. 20(3), pages 233-248, June.
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    Cited by:

    1. Sarica, Kemal & Tyner, Wallace E., 2013. "Alternative policy impacts on US GHG emissions and energy security: A hybrid modeling approach," Energy Economics, Elsevier, vol. 40(C), pages 40-50.
    2. Deppermann, Andre & Grethe, Harald & Offermann, Frank, 2010. "Effekte Einer Eu-Agrarmarktliberalisierung Auf Betriebsebene: Simulationen Anhand Eines Europäischen Agrarsektormodells Und Eines Angebotsmodells Für Den Deutschen Agrarsektor," 50st Annual Conference, Braunschweig, Germany, September 29-October 1, 2010 93958, German Association of Agricultural Economists (GEWISOLA).
    3. Grant, Jason H. & Hertel, Thomas W. & Rutherford, Thomas F., 2006. "Extending General Equilibrium to the Tariff Line: U.S. Dairy in the DOHA Development Agenda," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25305, International Association of Agricultural Economists.
    4. Susana Silva & Isabel Soares & Óscar Afonso, 2010. "E3 Models Revisited," FEP Working Papers 393, Universidade do Porto, Faculdade de Economia do Porto.
    5. Andreas Peichl, 2009. "The benefits and problems of linking micro and macromodels - Evidence from a flat tax analysis," Journal of Applied Economics, Universidad del CEMA, vol. 12, pages 301-329, November.
    6. Theodoridou, Ifigeneia & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "A feasibility evaluation tool for sustainable cities – A case study for Greece," Energy Policy, Elsevier, vol. 44(C), pages 207-216.
    7. Andreas PEICHL, "undated". "The Benefits of Linking CGE and Microsimulation Models - Evidence from a Flat Tax analysis," EcoMod2008 23800106, EcoMod.
    8. Kiyama, Shoichi & Akira, Kobayashi, 2015. "Roles of payments for ecosystem services in agro-food demands and welfare," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202724, European Association of Agricultural Economists.
    9. Tabatabaei, Sharareh Majdzadeh & Hadian, Ebrahim & Marzban, Hossein & Zibaei, Mansour, 2017. "Economic, welfare and environmental impact of feed-in tariff policy: A case study in Iran," Energy Policy, Elsevier, vol. 102(C), pages 164-169.
    10. Peichl, Andreas, 2009. "Benefits and problems of linking micro and macro models - evidence from a flat tax analysis," ISER Working Paper Series 2009-02, Institute for Social and Economic Research.
    11. Deppermann, Andre & Grethe, Harald & Offermann, Frank, 2010. "Farm level effects of EU policy liberalization: Simulations based on an EU-wide agricultural sector model and a supply model of the German agricultural sector," 114th Seminar, April 15-16, 2010, Berlin, Germany 61083, European Association of Agricultural Economists.
    12. Schaefer, Thilo & Peichl, Andreas, 2006. "Documentation FiFoSiM: integrated tax benefit microsimulation and CGE model," FiFo Discussion Papers - Finanzwissenschaftliche Diskussionsbeiträge 06-10, University of Cologne, FiFo Institute for Public Economics.

    More about this item

    Keywords

    Mathematical Programming; Mixed Complementarity; Top-Down/Bottom-Up;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • 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
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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