Integrated Modeling Environment  
   

Robust emission trading under the Kyoto agreement


   

 

   There are similarities between management of emission uncertainties in Kyoto related mechanisms and catastrophic risks approaches: both have interdependencies in space and time. An appropriate analysis of these two classes of risks requires adaptation, integration, extension and further development of methodologies for quantitative modeling of uncertainty and risks that have emerged during recent decades in such fields as economics and finance, optimization, simulation of stochastic multicriteria and multiagent systems, emission detection. For more detailed treatment of emission uncertainties, we have selected three such methodologies: market under uncertainties, catastrophic risk management and stochastic emission detection, coupled with stochastic optimization (STO) approaches.
We propose to combine stochastic properties of emissions and emission changes with economic decision-making modeling in a new integrated simulation system. Namely, with practical examples using reported data for Europe/World we show how the stochastic emission detection techniques with schemes of sequential bilateral emission trading operating under uncertainties can be used in practice for deriving robust cost-efficient market policies, reducing the aggregate cost of mitigation, and achieving this outcome in a fair and mutually beneficial way, i.e., reducing individual costs of the participants that create the stable coalition. The proposed robust sequential trading mechanisms account for safety constraints typical for catastrophic risks management (Ermolieva et. al., 2005). Here, the safety constraints are adapted for handling the risks of underestimating and overestimating actual emissions and, therefore, represent the confidence of the parties about the correctness of the estimates as well as their concern about losses incurred if estimates are incorrect. In particular, the explicit introduction of safety constraints may enforce long-term investments in reducing emission uncertainties.
The novelty of the proposed approachis that the sequential trading mechanisms and emission prices explicitly depend on the safety constraints related to verifiability (verification time) of emissions/emission changes. With safety constraints, the parties set the level of their exposure towards uncertainties and risks, which serves as vulnerability indicators. In pricing Kyoto-related financial products, safety constraints/indicators discount the involved costs and benefits associated with risks' of the Parties. Thus, this type of induced endogenous discounting should become a key element in a proper definition of prices, and be exploited in forming stable coalitions of the Parties.

Three major tasks of the research are being carried out:

  1. analysis of EU ETS and other schemes (e.g., the UK ETS learning-by-doing voluntary scheme) with respect to their robustness against uncertainties (e.g., market stability, price volatility).
  2. development of robust trading schemes that operate under uncertainty and reduce the aggregate costs of GHG mitigation in fair and mutually beneficial way (i.e., minimize the costs of market participants that form a stable colaition); study sequential trading (pricing) mechanisms to account for safety constraints (e.g., the risks of underestimating and overestimating emmissions or the risks associated with price volatility).
  3. design and development of software adn database.

Selected references:  

  1. Ermoliev, Y., G. Klaassen and A. Nentjes (1996): The design of cost effective ambient charges under incomplete information and risk. In: E.C. van Ierland and K. Gorka (eds.) Economics of Atmospheric Pollution, NATO ASI Series, Partnership Sub-Series, 2. Environment, V. 14, 123-151, Springer, Berlin, Germany.
  2. Ermoliev, Y., M. Michalevich and A. Nentjes (2000); Markets for tradeable emission and ambients permits: A dynamic approach. environ. res. Econ., 15, 39-56.
  3. Godal O., Y. Ermoliev, G. Klassen and M. Obersteiner (2003): Carbon trading with imperfectly observable emissions. Environmental and Resources Economics, 25, 151-169.
  4. Makowski M., Ermolieva T, Jonas M, Ermoliev Y (2007): The difference between deterministic and probabilistic detection of emission changes: Toward the use of the probabilistic varification time concept. In: Proc. of the 2nd International Workshop on Uncertainty in Greenhouse Gas Inventories, IIASA - Systems Research Institute of the Polish Academy of Sciences, 27-28 September, 2007, further information: http://www.iiasa.ac.at/Research/FOR/unc_prep.html
  5. Gritsevskii A., Ermoliev, Y. (1999): An Energy Model Incorporating Techonological Uncertainty, Increasing Returns and Economic and Environmental Risks. In: Proceedings of the International Association for Energy Economics 1999 European Energy Conference "Technological Progress and the Energy Challenges", 30 september - 1 October, Paris, France.
  6. Ermolieva T, Jonas M, Makowski M, Ermoliev Y, Fischer G. (2008): Stochastic techniqus for the design of robust and efficient emission trading mechanisms. In: Proceedings of IFIP/IIASA/GAMM Workshop on Coping with Uncertainty: Robust Decisions, 10-12 December, 2007, Laxenburg, Austria (forthcoming).
  7. Ermolieva T, Jonas M, Ermoliev Y, Makowski M., Fischer G. (2008): Economic implications of stochastic detection techniques for the design of robust and efficient Kyoto flexible mechanisms. A paper in preparation for journal of Climate Change.

For more information, please contact Tatiana Ermolieva, Yuri Ermoliev and Marek Makowski.

 

Responsible for this page: Amalia Priyatna
Last updated: 17 Nov 2011

Go to top
International Institute for Applied Systems Analysis (IIASA) * Schlossplatz 1 * A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 * Fax: (+43 2236) 71 313 * Web: www.iiasa.ac.at * Contact Us
Copyright © 2009-2011 IIASA * ZVR-Nr: 524808900 * Disclaimer