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A Survey of Approaches for Assessing and Managing the Risk of Extremes

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  • Vicki M. Bier
  • Yacov Y. Haimes
  • James H. Lambert
  • Nicholas C. Matalas
  • Rae Zimmerman

Abstract

In this paper, we review methods for assessing and managing the risk of extreme events, where “extreme events” are defined to be rare, severe, and outside the normal range of experience of the system in question. First, we discuss several systematic approaches for identifying possible extreme events. We then discuss some issues related to risk assessment of extreme events, including what type of output is needed (e.g., a single probability vs. a probability distribution), and alternatives to the probabilistic approach. Next, we present a number of probabilistic methods. These include : guidelines for eliciting informative probability distributions from experts; maximum entropy distributions; extreme value theory; other approaches for constructing prior distributions (such as reference or noninformative priors); the use of modeling and decomposition to estimate the probability (or distribution) of interest; and bounding methods. Finally, we briefly discuss several approaches for managing the risk of extreme events, and conclude with recommendations and directions for future research.

Suggested Citation

  • Vicki M. Bier & Yacov Y. Haimes & James H. Lambert & Nicholas C. Matalas & Rae Zimmerman, 1999. "A Survey of Approaches for Assessing and Managing the Risk of Extremes," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 83-94, February.
    • Handle: RePEc:wly:riskan:v:19:y:1999:i:1:p:83-94
    DOI: 10.1111/j.1539-6924.1999.tb00391.x
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    References listed on IDEAS

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    1. Ali Mosleh & Vicki Bier, 1992. "On Decomposition and Aggregation Error in Estimation: Some Basic Principles and Examples," Risk Analysis, John Wiley & Sons, vol. 12(2), pages 203-214, June.
    2. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
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    2. Qian Zhou & James H. Lambert & Christopher W. Karvetski & Jeffrey M. Keisler & Igor Linkov, 2012. "Flood Protection Diversification to Reduce Probabilities of Extreme Losses," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1873-1887, November.
    3. Riccardo Minciardi & Roberto Sacile & Eva Trasforini, 2009. "Resource Allocation in Integrated Preoperational and Operational Management of Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 29(1), pages 62-75, January.
    4. James D. Englehardt, 2002. "Scale Invariance of Incident Size Distributions in Response to Sizes of Their Causes," Risk Analysis, John Wiley & Sons, vol. 22(2), pages 369-381, April.
    5. Hongyang Yu & Faisal Khan & Brian Veitch, 2017. "A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1668-1682, September.
    6. Maria Iglesias-Mendoza & Akilu Yunusa-Kaltungo & Sara Hadleigh-Dunn & Ashraf Labib, 2021. "Learning How to Learn from Disasters through a Comparative Dichotomy Analysis: Grenfell Tower and Hurricane Katrina Case Studies," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    7. Nima Khakzad & Faisal Khan & Paul Amyotte, 2015. "Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1336-1347, July.
    8. Smith, Curtis L., 2020. "Representing external hazard initiating events using a Bayesian approach and a generalized extreme value model," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    9. Pietro Turati & Nicola Pedroni & Enrico Zio, 2017. "An Adaptive Simulation Framework for the Exploration of Extreme and Unexpected Events in Dynamic Engineered Systems," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 147-159, January.
    10. Seth D. Baum, 2015. "Risk and resilience for unknown, unquantifiable, systemic, and unlikely/catastrophic threats," Environment Systems and Decisions, Springer, vol. 35(2), pages 229-236, June.
    11. Rebello, Sinda & Yu, Hongyang & Ma, Lin, 2019. "An integrated approach for real-time hazard mitigation in complex industrial processes," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 297-309.
    12. Elisabeth Paté‐Cornell, 2012. "On “Black Swans” and “Perfect Storms”: Risk Analysis and Management When Statistics Are Not Enough," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1823-1833, November.
    13. Convertino, Matteo & Annis, Antonio & Nardi, Fernando, 2019. "Information-theoretic Portfolio Decision Model for Optimal Flood Management," Earth Arxiv k5aut, Center for Open Science.

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