Uncertainty, cost-effectiveness and environmental safety of robust carbon trading: integrated approach

  • T. Ermolieva
  • Y. Ermoliev
  • M. Jonas
  • M. Obersteiner
  • F. Wagner
  • W. Winiwarter
Chapter

Abstract

Carbon markets, like other commodity markets, are volatile. They react to stochastic “disequilibrium” spot prices, which may be affected by inadequate policies, speculations and bubbles. The market-based emission trading, therefore, does not necessarily minimize abatement costs and achieve emission reduction goals. We introduce a basic stochastic model integrating emissions reduction, monitoring and trading costs allowing us to analyze the robustness of emission and uncertainty reduction policies under environmental safety constraints asymmetric information and other multiple anthropogenic and natural uncertainties. Explicit treatment of uncertainties provides incentives for reducing them before trading. We illustrate functioning of the robust market with numerical results involving such countries as the US, Australia, Canada, Japan, EU27, Russia, Ukraine. In particular, we analyze if the knowledge about uncertainties may affect portfolios of technological and trade policies or structure of the market and how uncertainty characteristics may affect market prices and change the market structure.

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References

  1. Amann M (2009) Integrated assessment tools: the greenhouse and air pollution interactions and synergies (GAINS) model. Pollut Atmosph Special Issue 73–76Google Scholar
  2. Baumol W, Oates W (1975) The theory of environmental policy. Cambridge University Press, Cambridge, New York, SydneyGoogle Scholar
  3. Betz R, Sato M (2006) Emissions trading: lessons learnt from the 1st phase of the EU ETS and prospects for the 2nd phase. Clim Pol 6:351–359CrossRefGoogle Scholar
  4. Dales JH (1968) Pollution property and prices: an essena in policy-making and economics. University of Toronto PressGoogle Scholar
  5. De Jong C, Walet K (eds) (2004) A guide for emission trading: risk management and business implications. Risk Books, LondonGoogle Scholar
  6. Ermoliev Y, von Winterfeldt D (2012) Systemic risk and security management. In: Ermoliev Y, Makowski M, Marti K (eds) Managing Safety of heterogeneous systems. Springer, Berlin, pp 19–49CrossRefGoogle Scholar
  7. Ermoliev Y, Wets R (eds) (1988) Numerical techniques of stochastic optimization. Computational mathematics. Springer Verlag, BerlinGoogle Scholar
  8. Ermoliev Y, Michalevich M, Nentjes A (2000) Markets for tradable emission and ambient permits: a dynamic approach. Environ Res Econ 15:39–56CrossRefGoogle Scholar
  9. Ermolieva T, Ermoliev Y (2005) Catastrophic risk management: flood and seismic risks case studies. In: Wallace SW, Ziemba WT (eds) Applications of stochastic programming. MPS-SIAM Series on Optimization, PhiladelphiaGoogle Scholar
  10. Ermolieva T, Ermoliev Y, Fischer G, Jonas M, Makowski M (2010a) Cost effective and environmentally safe emission trading under uncertainty. In: Marti K, Ermoliev Y, Makowski M (eds) Coping with uncertainty: robust solutions. Springer, Heidelberg, pp 79–99CrossRefGoogle Scholar
  11. Ermolieva T, Ermoliev Y, Fischer G, Jonas M, Makowski M, Wagner F (2010b) Carbon emission trading and carbon taxes under uncertainties. Clim Chang 103(1–2)Google Scholar
  12. Evstigneev I, Flam S (2001) Sharing nonconvex cost. J Glob Optim 20:257–271CrossRefGoogle Scholar
  13. Gillenwater M, Sussman F, Cohen J (2007) Practical policy applications of uncertainty analysis for national greenhouse gas inventories. In: Lieberman D, Jonas J, Nahorski Z, Nilson S (eds) Accounting for climate change: uncertainty in greenhouse gas inventories–verification, compliance, and trading. Springer VerlagGoogle Scholar
  14. Godal O, Ermoliev Y, Klassen G, Obersteiner M (2003) Carbon trading with imperfectly observable emissions. Environ Res Econ 25:151–169CrossRefGoogle Scholar
  15. IPCC (2000) Good practice guidance and uncertainty management in national greenhouse gas inventories. Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, HayamaGoogle Scholar
  16. Kerr S (ed) (2000) Global emissions trading: key issues for industrialized countries. Edward Elgar, Cheltenham, UK, Northampton, MA, USGoogle Scholar
  17. Lieberman D, Jonas M, Nahorski Z, Nilsson S (2007) Accounting for climate change: uncertainty in greenhouse gas inventories―verification, compliance, and trading. Springer Verlag, BerlinCrossRefGoogle Scholar
  18. McCain R (2010) Game theory: a nontechnical introduction to the analysis of strategy. World Scientific Publishing, ISBN-13 978-981-4289-65-8Google Scholar
  19. Milgrom P, Roberts J (1986) Price and advertising signals of product quality. J Polit Econ 94:796–821CrossRefGoogle Scholar
  20. Montgomery DW(1972)Markets in licenses and efficient pollution control programs. J Public Econ 75:273–291 Nahorski Z, Horabik J, Jonas M (2007) Compliance and emissions trading under the Kyoto protocol: rules for uncertain inventories. In: Lieberman D, Jonas M, Nahorski Z,Nilsson S (eds) Accounting for climate change: uncertainty in greenhouse gas inventories–verification, compliance, and trading. Springer Verlag 119–138Google Scholar
  21. Nahorski Z, Stanczak J, Palka P (2010) Multi-agent approach to simulation of the greenhouse gases emission permits market. In: Proceedings of the 3rd International Workshop on Uncertainty in Greenhouse Gas Inventories, 22–24 September 2010, Lvov, Ukraine, 183–195Google Scholar
  22. Obersteiner M, Ermoliev Y, Gluck M, Jonas M, Nilsson S, Shvidenko A (2000) Avoiding a lemons market by including uncertainty in the Kyoto protocol: same mechanism–improved rules. Interim report IR-00-043. International Institute for Applied Systems Analysis, LaxenburgGoogle Scholar
  23. Rockafellar T, Uryasev S (2000) Optimization of conditional value at risk. J Risk 2(3):21–41Google Scholar
  24. Roos J (2011) EU emissions trading triggered dash for coal. The Breakthrough Institute, http://breakthrougheurope.org/
  25. Stavins R (2010) The problem of the commons: still unsettled after 100 years. Discussion paper RFF DP 10– 46. Resources for the Future. Washington DC, www.rff.org
  26. Stikkelman R, Dijkema G, Chappin E (2010) Emissions trading fails to reduce CO2 emissions. Delft University of Technology. Faculty of Technology, Policy and ManagementGoogle Scholar
  27. Wagner F, Amann M(2009) GAINS contribution to ETMA request #2B-v1, International Institute for Applied Systems Analysis (IIASA)Google Scholar
  28. Wagner F, Amann M, Borken-Kleefeld J, Cofala J, Höglund-Isaksson L, Purohit P, Rafaj P, Schöpp W, Winiwarter W (2012) Sectoral marginal abatement cost curves: implications for mitigation pledges and air pollution co-benefits for Annex I countries. Sustain Sci 7:169–184Google Scholar
  29. Winiwarter W (2007) National greenhouse gas inventories: understanding uncertainties versus potential for improving reliability. Water Air Soil Pollut 7:443–450. doi:10.1007/s11267-006-9117-3 CrossRefGoogle Scholar
  30. Winiwarter W, Muik B (2010) Statistical dependence in input data of national greenhouse gas inventories: effects on the overall inventory uncertainty. Clim Chang 103:19–36. doi:10.1007/s10584-010-9921-7 CrossRefGoogle Scholar
  31. Winiwarter W, Rypdal K (2001) Assessing the uncertainty associated with national greenhouse gas emission inventories: a case study for Austria. Atmos Environ 35:5425–5440CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • T. Ermolieva
    • 1
  • Y. Ermoliev
    • 1
  • M. Jonas
    • 1
  • M. Obersteiner
    • 1
  • F. Wagner
    • 1
  • W. Winiwarter
    • 1
    • 2
  1. 1.International Institute for Applied Systems AnalysisLaxenburgAustria
  2. 2.Institute for Systems Sciences, Innovation & Sustainability Research (ISIS)University of GrazGrazAustria

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