Methods for Economic Decision-Making under Uncertainty (MEDU)

The Methods for Economic Decision making under Uncertainty (MEDU) group aims to develop and improve a wide spectrum of modeling methodologies, with an emphasis on economic incentives and mechanisms for mitigation and adaptation, including market solutions for implementing REDD-based measures and a special focus on decision making under uncertainty.

MEDU

MEDU

The concept of optimality in classical integrated assessment tools such as GLOBIOM needs to be scrutinized given large scale uncertainties of basic input data as well as knowledge gaps. MEDU’s mission is to address these issues by fundamental research providing improved understanding of basic new concepts as well as by testing and implementing existing methodologies in ESM mainstream models. In particular, MEDU aims to develop and improve a wide spectrum of modeling methodologies, with an emphasis on economic incentives and mechanisms for mitigation and adaptation with special focus on decision-making under uncertainty and diffusion of technology. There is strong cooperation on methodological work with the IIASA ASA and RPV programmes.

MEDU employs the following major tools and methodologies:

- Stochastic optimization and simulation
- Dynamic and static portfolio selection
- Real options theory
- Model intercomparison, particularly in integrated assessment of climate change impacts
- Stylized economic modeling for understanding underlying dynamics and system effects
- Modeling of risk preferences.


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Last edited: 16 June 2016

CONTACT DETAILS

Nikolay Khabarov

Research Scholar
MEDU Group Leader

Ecosystems Service and Management

T +43(0) 2236 807 346

PUBLICATIONS

Krasovskii A, Khabarov N, & Obersteiner M (2016). Fair pricing of REDD-based emission offsets under risk preferences and benefit-sharing. Energy Policy 96: 193-205. DOI:10.1016/j.enpol.2016.05.040.

Deryng D, Elliott J, Folberth C, Müller C, Pugh TAM, Boote KJ, Conway D, Ruane AC, et al. (2016). Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity. Nature Climate Change 6 (4): 1-8. DOI:10.1038/NCLIMATE2995.

Khabarov N, Krasovskii AA, Obersteiner M, Swart R, Dosio A, San-Miguel-Ayanz J, Durrant T, Camia A, et al. (2016). Forest fires and adaptation options in Europe. Regional Environmental Change 16 (1): 21-30. DOI:10.1007/s10113-014-0621-0.

International Institute for Applied Systems Analysis (IIASA)
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Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313