Specification of discount rates is crucial in the evaluation of mitigation and adaptation measures. However, methodologies for evaluation and development of these measures should not be based on traditional approaches such as the concept of net present value (NPV) and others. Traditional approaches typically depend on discounting defined by the prevailing market interest rate. In fact, the NPV does not account for the temporal variability of random cash flows. Two cash flows may exhibit the same NPV although one flow can be clustered over a short time period while the other flow is spread evenly over a longer time interval. This type of temporal heterogeneity is critically important when dealing with benefits and extreme losses of measures as a result of uncertain emissions in the future. Among the essential shortcomings of NPV is that evaluation horizons do not relate to the (average) time of occurrence and to the likelihood of critical events, e.g., when emission changes are detected or market volatility passes vital thresholds.
Innovative approaches are required for the evaluation of precautionary, mitigation and adaptation measures under uncertainty. These approaches have been proposed by and are intensively developed at IIASA  (Ermoliev et al., 2008). In our research for evaluation of Kyoto mechanisms we suggest to use the so-called undiscounted stopping time criterion and rely on the concept of safety constraints that induce internal social discounting. That is, they rely on the optimal allocation of resources and actions over time, with the focus on arrival times of potentially extreme events rather than on horizons of capital markets. The undiscounted stopping time criterion depends on feasible decisions, the spatio-temporal variability of emission uncertainties, and on the balance of losses and gains. Safety constraints identify the level of risk and vulnerability that involved parties can or want to bear and they impose stability requirements on measures.
The use of safety constraints is a rather standard concept for coping with risks in the insurance (Ermolieva and Ermoliev, 2005), finance, and nuclear industries. For example, the safety regulations of nuclear plants assume that the violation of safety constraints may occur only once in 10 7 years. The concept of induced endogenous discounting associated with vulnerability and safety constraints was recently proposed for catastrophic risks management (Ermolieva, T. and Y. Ermoliev, 2005). With respect to emission trading markets, the safety constraints can impose restrictions on price volatility or market robustness.

In short, this approach fundamentally expands the traditional approach where a discount rate is chosen exogenously. An inappropriate discount rate leads to underestimated losses in the future and might even induce market disruptions.

Three major tasks of the research are being carried out:

1. consider methodologies for evaluating flexible mechanisms under Kyoto (e.g., EU ETS, CDM, JI) and analyse the compliance of identified projects in consideration of emissions uncertainties.
2. propose revisions to the methodologies relying on safety constraints imposed by “stopping” events and stability requirements, e.g., emissions verifiability horizon or price volatility exceeding vital threshold.
3. establish connections between the safety constraints, stopping time criterion, and value-at-risk and conditional value-at-risk risk measures from catastrophic risk management and financial modeling.

1. Ermoliev, Y., T. Ermolieva, G. Fischer, M. Makowski, S. Nillson and M. Obersteiner (2008): Discounting, catastrophic risks management and vulnerability modeling. Mathematics and Computers in Simulation, doi:10.1016/j.matcom.2008.02.004 (forthcoming).
2. Ermoliev, Y., Hordijk, L. (2006): Global Changes: Facets of Robust Decisions, in K. Marti, Y. Ermoliev, M. Makowski, G. Pflug (eds.) Coping With Uncertainty: Modeling and Policy Issue, Springer Verlag, Berlin, New York.
3. Ermolieva, T. and Y. Ermoliev (2005): Catastrophic Risk Management: Flood and Seismic Risks Case Studies. In: Applications of Stochastic Programming [S.W. Wallace and W.T. Ziemba (eds.)]. MPS-SIAM Series on Optimization, Philadelphia, PA, USA.
4. Gritsevskii, A., Ermoliev, Y. (1999): An Energy Model Incorporating Technological 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.
5. Ermolieva T, Jonas M, Makowski, M, Ermoliev Y, Ficher G. (2008): Stochastic techniques for the design of robust and effiecient emission trading mechanisms. In: Proceedings of IFIP/IIASA/GAMM Workshop on Coping with Uncertainty: Robust Decisions, 10-12 December, 2007, Laxenburg, Austria (forthcoming).
6. Ermolieva T, Jonas M. Errmoliev Y (2007): The difference between deterministic and probabilistic detection of emission changes: Toward the use of the probabilistic verification time concept. In: Proc. of the 2nd International Workshop on Uncertainty in Greenhouse Gas Inventories, IIAS - Systems Research Institute of the Polish Academy of Sciences, 27-28 September, 2007, for further information: http://www.iiasa.ac.at/Research/FOR/unc_prep.html .
7. Makowski, M. (2007): Rational Governance of Conflicting Goals, Uncertainties Risks. In: Y. Nakamori, Z. Wang, J. Gu & T. Ma (eds.): Proceedings of the 2007 IEEE International Conference on Systems, Man and Cybernetics, IEEE Omnipress, Montreal, Canada, Pages: 1812-1817, [ISBN 1-4244-0991-8].

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

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