Quantitative risk analysis links models of event severity, exposure and vulnerability of system components (people, assets, environment), and system linkages.
Understanding the physical events involved in extreme events and natural disasters, as well as their consequences, is becoming increasingly complex due to socioeconomic shifts, climate change, and the systemic and dependent nature of the hazards.
Social and governance complexities make effective risk-management even more challenging.
The major focus of the Risk Analysis and Modeling lies on:
The latest applications of risk modeling tools include:
Last edited: 01 March 2018
Gaupp F, Pflug G, Hochrainer-Stigler S, Hall J, & Dadson S (2017). Dependency of Crop Production between Global Breadbaskets: A Copula Approach for the Assessment of Global and Regional Risk Pools. Risk Analysis 37 (11): 2212-2228. DOI:10.1111/risa.12761.
Naqvi A ORCID: https://orcid.org/0000-0002-0986-6009 (2017). Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters. World Development 99: 395-418. DOI:10.1016/j.worlddev.2017.05.015.
Poledna S, Bochmann O, & Thurner S (2017). Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based, systemic risk-dependent financial transaction taxes. Journal of Economic Dynamics and Control 77: 230-246. DOI:10.1016/j.jedc.2017.02.004.
Pflug G, Timonina-Farkas A, & Hochrainer-Stigler S (2017). Incorporating model uncertainty into optimal insurance contract design. Insurance: Mathematics and Economics 73: 68-74. DOI:10.1016/j.insmatheco.2016.11.008.
International Institute for Applied Systems Analysis (IIASA)
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