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A literature review on the use of expert opinion in probabilistic risk analysis


  • Ouchi, Fumika


Risk assessment is part of the decision making process in many fields of discipline, such as engineering, public health, environment, program management, regulatory policy, and finance. There has been considerable debate over the philosophical and methodological treatment of risk in the past few decades, ranging from its definition and classification to methods of its assessment. Probabilistic risk analysis (PRA) specifically deals with events represented by low probabilities of occurring with high levels of unfavorable consequences. Expert judgment is often a critical source of information in PRA, since empirical data on the variables of interest are rarely available. The author reviews the literature on the use of expert opinion in PRA, in particular on the approaches to eliciting and aggregating experts'assessments. The literature suggests that the methods by which expert opinions are collected and combined have a significant effect on the resulting estimates. The author discusses two types of approaches to eliciting and aggregating expert judgments-behavioral and mathematical approaches, with the emphasis on the latter. It is generally agreed that mathematical approaches tend to yield more accurate estimates than behavioral approaches. After a short description of behavioral approaches, the author discusses mathematical approaches in detail, presenting three aggregation models: non-Bayesian axiomatic models, Bayesian models, andpsychological scaling models. She also discusses issues of stochastic dependence.

Suggested Citation

  • Ouchi, Fumika, 2004. "A literature review on the use of expert opinion in probabilistic risk analysis," Policy Research Working Paper Series 3201, The World Bank.
  • Handle: RePEc:wbk:wbrwps:3201

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    References listed on IDEAS

    1. Carmen M. Reinhart & Kenneth S. Rogoff & Miguel A. Savastano, 2003. "Debt Intolerance," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(1), pages 1-74.
    2. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
    3. Carmen M. Reinhart, 2002. "Default, Currency Crises, and Sovereign Credit Ratings," World Bank Economic Review, World Bank Group, vol. 16(2), pages 151-170, August.
    4. repec:rus:hseeco:123922 is not listed on IDEAS
    5. Nancy Birdsall & Stijn Claessens & Ishac Diwan, 2003. "Policy Selectivity Forgone: Debt and Donor Behavior in Africa," World Bank Economic Review, World Bank Group, vol. 17(3), pages 409-435, December.
    6. Enrica Detragiache & Antonio Spilimbergo, 2001. "Crises and Liquidity; Evidence and Interpretation," IMF Working Papers 01/2, International Monetary Fund.
    7. Berg, Andrew & Sachs, Jeffrey, 1988. "The debt crisis structural explanations of country performance," Journal of Development Economics, Elsevier, vol. 29(3), pages 271-306, November.
    8. Lynn Aylward & Rupert Thorne, 1998. "An Econometric Analysis of Countries' Repayment Performance to the International Monetary Fund," IMF Working Papers 98/32, International Monetary Fund.
    9. Lloyd-Ellis, H. & McKenzie, G. W. & Thomas, S. H., 1990. "Predicting the quantity of LDC debt rescheduling," Economics Letters, Elsevier, vol. 32(1), pages 67-73, January.
    10. Axel Schimmelpfennig & Nouriel Roubini & Paolo Manasse, 2003. "Predicting Sovereign Debt Crises," IMF Working Papers 03/221, International Monetary Fund.
    11. Cohen, Daniel, 1996. "The sustainability of African debt," Policy Research Working Paper Series 1621, The World Bank.
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    Cited by:

    1. Werner, Christoph & Bedford, Tim & Cooke, Roger M. & Hanea, Anca M. & Morales-NĂ¡poles, Oswaldo, 2017. "Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions," European Journal of Operational Research, Elsevier, vol. 258(3), pages 801-819.
    2. repec:eee:reensy:v:95:y:2010:i:7:p:729-741 is not listed on IDEAS
    3. L. Joe Moffitt & John K. Stranlund & Barry C. Field, 2005. "Inspections To Avert Terrorism: Robustness Under Severe Uncertainty," Working Papers 2005-3, University of Massachusetts Amherst, Department of Resource Economics.


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