Computational Economics

, Volume 18, Issue 2, pp 159–172 | Cite as

Climate Coalitions in an Integrated Assessment Model

  • Richard S.J. Tol


An analytically tractable approximation of a numerical model is used toinvestigate coalition formation between nine major world regions withregard to their policies for greenhouse gas emission reduction. Fullcooperation is not individually rational. Assuming non-transferableutility, side payments do not ensure full cooperation either. Withoutside payments, the largest stable coalitions are small and consist ofsimilar regions. With side payments, the largest stable coalitionsexclude either the main culprits or the main victims of climate change.In all cases, optimal emission control is modest.

climate change coalition formation LQ games optimal emission control 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Barrett, S. (1990). The problem of global environmental protection. Oxford Review of Economic Policy, 6(1), 68–79.Google Scholar
  2. Barrett, S. (1994). Self-enforcing international environmental agreements. Oxford Economic Papers, 46, 878–894.Google Scholar
  3. Botteon, M. and Carraro, C. (1997). Environmental Coalitions with Heterogenous Countries: Burden Sharing and Carbon Leakage. Fondazione Eni Enrico Mattei, Milan.Google Scholar
  4. Carraro, C. and Moricone, F. (1997). International Games on Climate Change Control. Fondazione Eni Enrico Mattei, Milan.Google Scholar
  5. Carraro, C. and Siniscalco, D. (1992). The international dimension of environmental policy. European Economic Review, 36, 379–387.Google Scholar
  6. Carraro, C. and Siniscalco, D. (1993). Strategies for the international protection of the environment. Journal of Public Economics, 52, 309–328.Google Scholar
  7. Chander, P. and Tulkens, H. (1992). Theoretical foundations of negotiations and cost sharing in transfrontier pollution problems. European Economic Review, 36, 388–398.Google Scholar
  8. Chenz, Z. (1997). Negotiating an agreement on global warming: A theoretical analysis. Journal of Environmental Economics and Management, 32, 170–188.Google Scholar
  9. Escapa, M. and Gutierrez, M.J. (1997). Distribution of potential gains from international environmental agreements: The case of the greenhouse effect. Journal of Environmental Economics and Management, 33, 1–16.Google Scholar
  10. Eykmans, J., Proost, S. and Schokkaert, E. (1993). Efficiency and distribution in greenhouse negotiations. Kyklos, 46(3), 363–398. Fankhauser, S. (1995), Valuing Climate Change – The Economics of the Greenhouse, EarthScan, London.Google Scholar
  11. Fankhauser, S. and Kverndokk, S. (1996). The global warming game – simulations of a CO2 reduction agreement. Resource and Energy Economics, 18, 83–102.Google Scholar
  12. Friedman, J.W. (1991). Game Theory with Applications to Economics, 2nd edn. Oxford University Press, Oxford.Google Scholar
  13. Hoel, M. (1994), Efficient climate policy in the presence of free riders. Journal of Environmental Economics and Management, 27, 259–274.Google Scholar
  14. Kaufmann, R.K. (1997). Assessing the DICE model: Uncertainty associated with the emission and retention of greenhouse gases. Climatic Change, 35, 435–448.Google Scholar
  15. Nordhaus, W.D. and Yang, Z. (1996). RICE: A regional dynamic general equilibrium model of optimal climate change policy. American Economic Review, 86(4), 741–765.Google Scholar
  16. Peck, S.C. and Teisberg, T.J. (1999). CO2 emission control agreements: Incentives for regional participation. Energy Journal Special Issue on the Costs of the Kyoto Protocol: A Multi-Model Evaluation, 367–390.Google Scholar
  17. Tol, R.S.J. (1995). The damage costs of climate change: Toward more comprehensive calculations. Environmental and Resource Economics, 5, 353–374.Google Scholar
  18. Tol, R.S.J. (1996). The damage costs of climate change: Towards a dynamic representation. Ecological Economics, 19, 67–90.Google Scholar
  19. Tol, R.S.J. (1997a). A Decision-Analytic Treatise on the Enhanced Greenhouse Effect. Vrije Universiteit, Amsterdam.Google Scholar
  20. Tol, R.S.J. (1997b). On the optimal control of carbon dioxide emissions: An application of FUND. Environmental Modeling and Assessment, 2, 151–163.Google Scholar
  21. Tol, R.S.J. (1999a). Kyoto, efficiency, and cost-effectiveness: Applications of FUND. Energy Journal Special Issue on the Costs of the Kyoto Protocol: A Multi-Model Evaluation, 130–156.Google Scholar
  22. Tol, R.S.J. (1999b). Time discounting and optimal control of climate change – application of FUND. Climatic Change, 41(3–4), 351–362.Google Scholar
  23. Weyant, J., Davidson, O., Dowlatabadi, H., Edmonds, J.A., Grubb, M.J., Parson, E.A., Richels, R.G., Rotmans, J., Shukla, P.R., Tol, R.S.J., Cline, W.R. and Fankhauser, S. (1996). Integrated assessment of climate change: An overview and comparison of approaches and results, in Bruce, J.P., Lee, H. and Haites, E.F. (eds). Climate Change 1995: Economic and Social Dimensions – Contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Richard S.J. Tol
    • 1
    • 2
    • 3
  1. 1.Centre for Marine and Climate ResearchHamburg UniversityHamburgGermany
  2. 2.Institute for Environmental StudiesVrije Universiteit AmsterdamThe Netherlands
  3. 3.Center for Integrated Study of the Human Dimensions of Global ChangeCarnegie Mellon UniversityPittsburghU.S.A.

Personalised recommendations