Advertisement

Climatic Change

, Volume 65, Issue 1–2, pp 39–71 | Cite as

A Sensitivity Analysis of Timing and Costs of Greenhouse Gas Emission Reductions

  • Reyer Gerlagh
  • Bob van der Zwaan
Article

Abstract

This paper analyses the optimal timing and macro-economic costs of carbon emission reductions that mitigate the global average atmospheric temperature increase. We use a macro-economic model in which there are two competing energy sources, fossil-fuelled and non-fossil-fuelled. Technological change is represented endogenously through learning curves, and niche markets exist implying positive demand for the relatively expensive non-fossil-fuelled energy source. Under these conditions, with a temperature increase constraint of 2 ° C, early abatement is found to be optimal, and, comparedto the results of many existing top-down models, the costs of this strategy prove to be low. We perform an extensive sensitivity analysis of our results regarding the uncertainties that dominate various economic and technological modeling parameters. Uncertainties in the learning rate and the elasticity of substitution between the two different energy sources most significantly affect the robustness of our findings.

Keywords

Carbon Emission Emission Reduction Learning Rate Atmospheric Temperature Technological Modeling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abler, D. G., Rodriguez, A. G., and Shortle, J. S.: 1999, ‘Parameter Uncertainty, CGE Modelling of the Environmental Impacts of Economic Policies’, Environ. Resour. Econ. 14, 75–94.Google Scholar
  2. Anderson, D. and Bird, C. D.: 1992, ‘Carbon Accumulation and Technical Progress–A Simulation Study of Costs’, Oxford Bulletin of Economics and Statistics 54, 1–27.Google Scholar
  3. Arrow, K. J.: 1961, ‘The Economic Implications of Learning by Doing’, Review of Economic Studies 29, 155–173.Google Scholar
  4. Arthur, W. B., Ermoliev, Y. M., and Kanjovski, Y. M.: 1987, ‘Path-Dependent Processes and the Emergence of Macro-Structure’, European J. Operational Research 30, 294–303.Google Scholar
  5. Berry, R. S., Heal, G., and Salomon P.: 1978, ‘On a Relation between Economic and Thermodynamic Optima’, Resources and Energy 1, 125–137.Google Scholar
  6. Carraro, C., Gerlagh, R., and van der Zwaan, B.: 2003, ‘Endogenous Technical Change in Environmental Macroeconomics’, Editorial, Resource and Energy Economics 25, 1–10.Google Scholar
  7. Chakravorty, U., Roumasset, J., and Tse, K.: 1997, ‘Endogenous Substitution among Energy Resources and Global Warming’, J. Political Economy 105, 1201–1234.Google Scholar
  8. Chen, B.-L. and Shimomura, K.: 1998, ‘Self-Fulfilling Expectations and Economic Growth: A Model of Technology Adoption and Industrialization’, International Economic Review 39, 151–170.Google Scholar
  9. Dosi, G., Ermoliev, Y. M., and Kaniovski, Y.: 1994, ‘Generalized Urn Schemes and Technological Dynamics’, J. Mathematical Economics 23, 1–19.Google Scholar
  10. Gerlagh, R., van der Zwaan, B. C. C., Hofkes, M.W., and Klaassen, G.: 2004, ‘Impacts of CO2-Taxes when there are NicheMarkets and Learning-by-Doing’, Environmental and Resource Economics, in press.Google Scholar
  11. Gerlagh, R. and van der Zwaan, B. C. C.: 2003, ‘Gross World Product and Consumption in a Global Warming Model with Endogenous Technological Change’, Resource and Energy Economics 25, 35–57.Google Scholar
  12. Goulder, L. H. and Schneider, S. H.: 1999, ‘Induced Technological Change and the Attractiveness of CO2 Abatement Policies’, Resource and Energy Economics 21, 211–253.Google Scholar
  13. Grübler, A. and Messner, S.: 1998, ‘Technological Change and the Timing of Mitigation Measures’, Energy Economics 20, 495–512.Google Scholar
  14. Harrison, G. W., Jones, R., Kimbell, L. J., and Wigle, R.: 1993, ‘How Robust is Applied General Equilibrium Analysis?’, J. Policy Modeling 15, 99–115.Google Scholar
  15. Hasselmann, K., Hasselmann, S., Giering, R., Ocana V., and v. Storch, H.: 1997, ‘Sensitivity Study of Optimal CO2 Emission Paths Using a Simplified Structural Integrated Assessment Model (SIAM)’, Clim. Change 37, 345–386.Google Scholar
  16. IEA/OECD: 1999, Key World Energy Statistics, International Energy Agency, OECD, Paris.Google Scholar
  17. IEA/OECD: 2000, Experience Curves for Energy Technology Policy, International Energy Agency, OECD, Paris.Google Scholar
  18. Knapp, K. E.: 1999, ‘Exploring Energy Technology Substitution for Reducing Atmospheric Carbon Emissions’, Energy J. 20, 121–143.Google Scholar
  19. Kremer, M. and Marcom C.: 2000, ‘Elephants’, American Economic Review 90, 212–234.Google Scholar
  20. Krugman, P.: 1991, ‘History versus Expectations’, Quarterly J. Economics 106, 651–667.Google Scholar
  21. Mankiw, N. G., Romer, D., and Weil, D. N.: 1992, ‘A Contribution to the Empirics of Economic Growth’, Quarterly J. Economics 107, 407–437.Google Scholar
  22. Manne, A. S., Mendelsohn, R., and Richels R.: 1995, ‘MERGE, A Model for Evaluating Regional and Global Effects of GHG Reduction Policies’, Energy Policy 23, 17–34.Google Scholar
  23. McDonald, A. and Schrattenholzer, L.: 2001, ‘Learning Rates for Energy Technologies’, Energy Policy 29, 255–261.Google Scholar
  24. Messner, S.: 1995, Endogenized Technological Learning, An Energy Systems Model, WP-95–114, IIASA, Laxenburg, Austria.Google Scholar
  25. Nelson, R. R.: 1995, ‘Recent Evolutionary Theorizing about Economic Change’, J. Economic Literature 33, 48–90.Google Scholar
  26. Nordhaus, W. D.: 1994, Managing the Global Commons, MIT Press, Cambridge, Massachusetts.Google Scholar
  27. Nordhaus, W. D. and Yang, Z.: 1996, ‘A Regional Dynamic General Equilibrium Model of Alternative Climate-Change Strategies’, American Economic Review 86, 741–765.Google Scholar
  28. Peck, S. C. and Teisberg, T. J.: 1992, ‘CETA, AModel for Carbon Emissions Trajectory Assessment’, Energy J. 13, 55–77.Google Scholar
  29. Portney, P. R. and Weyant, J. P. (eds.): 1999, Discounting and Intergenerational Equity, Resources for the Future, Washington, D.C.Google Scholar
  30. Romer, P. M.: 1989, ‘Capital Accumulation and Long-Term Growth’, in Barro, R. J. (ed.), Modern Business Cycles Theory, Blackwell, Oxford, U.K.Google Scholar
  31. Schneider, S. H. and Azar, C.: 2001, ‘Are Uncertainties in Climate and Energy Systems A Justi-fication for Stronger Near-Term Mitigation Policies?’, Pew Center on Global Climate Change, www.pewclimate.org/events, Workshop Paper, October 2001.Google Scholar
  32. Tol, R. S. J.: 1999, ‘Spatial and Temporal Efficiency, Climate Policy, Applications of FUND’, Environ. Resour. Econ. 14, 33–49.Google Scholar
  33. Wigley, T. M. L., Richels, R., and Edmonds, J. A.: 1996, ‘Economic and Environmental Choices, the Stabilization of Atmospheric CO2 Concentrations’, Nature 379, 240–379.Google Scholar
  34. Wright, T. P.: 1936, ‘Factors Affecting the Cost of Airplanes’, J. Aeronautical Sciences 3, 122.Google Scholar
  35. van der Zwaan, B. C. C., Gerlagh, R., Klaassen, G., and Schrattenholzer L.: 2002, ‘Endogenous Technological Change in Climate Change Modelling’, Energy Economics 24, 1.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Reyer Gerlagh
    • 1
  • Bob van der Zwaan
    • 2
    • 3
  1. 1.IVMVrije University AmsterdamThe Netherlands
  2. 2.ECNEnergy research Centre of the NetherlandsThe Netherlands
  3. 3.BCSIA, John F. Kennedy School of GovernmentHarvard UniversityU.S.A

Personalised recommendations