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Computational Management Science

, Volume 5, Issue 1–2, pp 119–140 | Cite as

An oracle based method to compute a coupled equilibrium in a model of international climate policy

  • Laurent DrouetEmail author
  • Alain Haurie
  • Francesco Moresino
  • Jean-Philippe Vial
  • Marc Vielle
  • Laurent Viguier
Original Paper

Abstract

This paper proposes a computational game-theoretic model for the international negotiations that should take place at the end of the period covered by the Kyoto protocol. These negotiations could lead to a self-enforcing agreement on a burden sharing scheme given the necessary global emissions limit that will be imposed when the real extent of climate change is known. The model assumes a non-cooperative behavior of the parties except for the fact that they will be collectively committed to reach a target on total cumulative emissions by the year 2050. The concept of normalized equilibrium, introduced by J.B. Rosen for concave games with coupled constraints, is used to characterize a family of dynamic equilibrium solutions in an m-player game where the agents are (groups of) countries and the payoffs are the welfare gains obtained from a Computable General Equilibrium (CGE) model. The model deals with the uncertainty about climate sensitivity by computing an S-adapted equilibrium. These equilibria are computed using an oracle-based method permitting an implicit definition of the payoffs to the different players, obtained through simulations performed with the global CGE model GEMINI-E3.

Keywords

Climate change negotiations Dynamic game model Coupled constraints Stochastic modal jumps 

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References

  1. Armington PS (1969) A theory of demand for products distinguished by place of production. IMF Staff Papers 16:159–178Google Scholar
  2. Babonneau F, Beltran C, Haurie A, Tadonki C, Vial J-P (2006) Proximal-accpm: a versatile based optimization method. In: Kontoghiorghes EJ (ed) Optimisation, econometric and financial analysis.Advances in computational management science, vol 9. Springer, Boston, pp 3–23Google Scholar
  3. Bernard A, Haurie A, Vielle M, Viguier L (2005) A two-level dynamic game of carbon emissions trading between Russia, China, and Annex B countries. J Econ Dyn Control (submitted for publication)Google Scholar
  4. Bernard A, Paltsev S, Reilly JM, Vielle M, Viguier L (2003) Russia’s role in the Kyoto protocol. Report 98, MIT Joint Program on the Science and Policy of Global Change, Cambridge, MA, JuneGoogle Scholar
  5. Bernard A, Vielle M (1998) La structure du modèle GEMINI-E3. Econ Prévis 5(136)Google Scholar
  6. Bernard A, Vielle M (2000) Comment allouer un coût global d’environnement entre pays: permis négociables versus taxes ou permis négociables et taxes? Econ Int 2(82)Google Scholar
  7. Bernard A, Vielle M (2003) Measuring the welfare cost of climate change policies: a comparative assessment based on the computable general equilibrium model GEMINI-E3. Environ Model Assessm 8(3):199–217CrossRefGoogle Scholar
  8. Bernard A, Vielle M, Viguier L (2005) Carbon tax and international emissions trading: a swiss perspective. In: Haurie A, Viguier L (eds) Coupling climate and economic dynamics. Springer, HeidelbergGoogle Scholar
  9. Buchner B, Carraro C, Cersonimo I, Marchiori C (2005) Back to Kyoto? US participation and the linkage between R&D and climate cooperation. In: Haurie A, Viguier L (eds) The coupling of climate and economic dynamics. Springer, Dordrecht, pp 173–204CrossRefGoogle Scholar
  10. Carraro C, Siniscalco D (1996) R&D cooperation and the stability of international environmental agreements. In: Carraro C (ed) International environmental negotiations. Kluwer Academic PublishersGoogle Scholar
  11. Ferris MC, Munson TS (2000) Complementarity problems in GAMS and the PATH solver. J Econ Dyn Control 24:165–188CrossRefGoogle Scholar
  12. Ferris MC, Pang JS (1997) Complementarity and variational problems: state of the art. SIAM Publications, PhiladelphiaGoogle Scholar
  13. Goffin JL, Haurie A, Vial J-Ph (1992) Decomposition and nondifferentiable optimization with the projective algorithm. Manage Sci 37:284–302CrossRefGoogle Scholar
  14. Haurie A (1995) Environmental coordination in dynamic oligopolistic markets. Group Decis Negotiat 4:46–67Google Scholar
  15. Haurie A, Krawczyk J (1997) Optimal charges on river effluent from lumped and distributed sources. Environ Model Assessm 2:177–199CrossRefGoogle Scholar
  16. Haurie A, Moresino F (2002) S-adapted oligopoly equilibria and approximations in stochastic variational inequalities. Ann Oper Res 114:183–201CrossRefGoogle Scholar
  17. Haurie A, Moresino F, Viguier L (2005) A two-level differential game of international emissions trading. In: HAurie A, Raghavan TES (eds) Advances in dynamic games and applications, vol 8. Birkhäuser, Boston (in press)Google Scholar
  18. Haurie A, Smeers Y, Zaccour G (1990) Stochastic equilibrium programming for dynamic oligopolistic markets. J Optim Theory Appl 66:243–253CrossRefGoogle Scholar
  19. Haurie A, Viguier L (2003) A stochastic game of carbon emissions trading. Environ Model Assessm 8(3):239–248CrossRefGoogle Scholar
  20. Haurie A, Zaccour G (1995) Differential game models of global environmental management. In: Carraro C, Filar JA (eds) Game-theoretic models of the environment. Annals of the International Society of Dynamic Games, vol 3. Birkhäuser, Boston, pp 3–23Google Scholar
  21. Hertel TW (1997) Global trade analysis: modeling and applications. Cambridge University Press, CambridgeGoogle Scholar
  22. IEA (2002) Beyond Kyoto. Energy dynamics and climate stabilisation. OECD/IEA, ParisGoogle Scholar
  23. Luo Z-Q, Goffin J-L, Ye Y (1996) Complexity analysis of an interior cutting plane for convex feasibility problems. SIAM J Optim 6:284–302Google Scholar
  24. Knutti R, Meehl GA, Allen MR, Stainforth DA (2006) Constraining climate sensitivity from the seasonal cycle in surface temperature. J Climate 19(17):4224–4233CrossRefGoogle Scholar
  25. Nesterov Y, Nemirovskii A (1994) Interior point polynomial algorithm in convex programming. SIAM, PhiladelphiaGoogle Scholar
  26. Nesterov Y, Vial J-P (1999) Homogeneous analytic center cutting plane methods for convex problems and variational inequalities. SIAM J Optim 9(2):707–728CrossRefGoogle Scholar
  27. Philibert C (2000) How could emissions trading benefit developing countries? Energy Policy 28:947–956CrossRefGoogle Scholar
  28. Philibert C, Pershing J (2001) Considering the options: climate targets for all countries. Climate Policy 1:211–227CrossRefGoogle Scholar
  29. Rosen JB (1965) Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33(3):520–534CrossRefGoogle Scholar
  30. Stone JRN (1983) Linear expenditure systems and demand analysis: an application to the pattern of British demand. Econ J 64:511–527CrossRefGoogle Scholar
  31. Toth FL (2005) Coupling climate and economic dynamics: recent achievements and unresolved problems. In: Haurie A, Viguier L (eds) The coupling of climate and economic dynamics. Springer, Dordrecht, pp 35–68CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Laurent Drouet
    • 1
    Email author
  • Alain Haurie
    • 2
  • Francesco Moresino
    • 4
  • Jean-Philippe Vial
    • 2
  • Marc Vielle
    • 3
    • 4
  • Laurent Viguier
    • 4
    • 5
  1. 1.ORDECSYS and REME-EPFLEcole Polytechnique Fédérale de LausanneLausanneSwitzerland
  2. 2.ORDECSYS and University of GenevaGenevaSwitzerland
  3. 3.CEA-LERNAUniversity of Social SciencesToulouseFrance
  4. 4.REME-EPFLEcole Polytechnique Fédérale de LausanneLausanneSwitzerland
  5. 5.MIT Joint Program on the Science and Policy of Global ChangeCambridgeUSA

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