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Extreme Risk Analysis of Interdependent Economic and Infrastructure Sectors

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  • Chenyang Lian
  • Joost R. Santos
  • Yacov Y. Haimes

Abstract

Willful attacks or natural disasters pose extreme risks to sectors of the economy. An extreme‐event analysis extension is proposed for the Inoperability Input‐Output Model (IIM) and the Dynamic IIM (DIIM), which are analytical methodologies for assessing the propagated consequences of initial disruptions to a set of sectors. The article discusses two major risk categories that the economy typically experiences following extreme events: (i) significant changes in consumption patterns due to lingering public fear and (ii) adjustments to the production outputs of the interdependent economic sectors that are necessary to match prevailing consumption levels during the recovery period. Probability distributions associated with changes in the consumption of directly affected sectors are generated based on trends, forecasts, and expert evidence to assess the expected losses of the economy. Analytical formulations are derived to quantify the extreme risks associated with a set of initially affected sectors. In addition, Monte Carlo simulation is used to handle the more complex calculations required for a larger set of sectors and general types of probability distributions. A two‐sector example is provided at the end of the article to illustrate the proposed extreme risk model formulations.

Suggested Citation

  • Chenyang Lian & Joost R. Santos & Yacov Y. Haimes, 2007. "Extreme Risk Analysis of Interdependent Economic and Infrastructure Sectors," Risk Analysis, John Wiley & Sons, vol. 27(4), pages 1053-1064, August.
    • Handle: RePEc:wly:riskan:v:27:y:2007:i:4:p:1053-1064
    DOI: 10.1111/j.1539-6924.2007.00943.x
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    Citations

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    Cited by:

    1. Armbruster, Ginger & Endicott-Popovsky, Barbara & Whittington, Jan, 2012. "Are we prepared for the economic risk resulting from telecom hotel disruptions?," International Journal of Critical Infrastructure Protection, Elsevier, vol. 5(2), pages 55-65.
    2. Kenneth G. Crowther & Yacov Y. Haimes, 2010. "Development of the multiregional inoperability input‐output model (MRIIM) for spatial explicitness in preparedness of interdependent regions," Systems Engineering, John Wiley & Sons, vol. 13(1), pages 28-46, March.
    3. Kenneth G. Crowther & Yacov Y. Haimes & Gideon Taub, 2007. "Systemic Valuation of Strategic Preparedness Through Application of the Inoperability Input‐Output Model with Lessons Learned from Hurricane Katrina," Risk Analysis, John Wiley & Sons, vol. 27(5), pages 1345-1364, October.
    4. Joanna Resurreccion & Joost R. Santos, 2012. "Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1673-1692, October.
    5. Marco Percoco, 2011. "On the Local Sensitivity Analysis of the Inoperability Input‐Output Model," Risk Analysis, John Wiley & Sons, vol. 31(7), pages 1038-1042, July.
    6. Stephanie E. Chang & Timothy McDaniels & Jana Fox & Rajan Dhariwal & Holly Longstaff, 2014. "Toward Disaster‐Resilient Cities: Characterizing Resilience of Infrastructure Systems with Expert Judgments," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 416-434, March.
    7. Wenping Xu & Zongjun Wang & Liu Hong & Ligang He & Xueguang Chen, 2015. "The uncertainty recovery analysis for interdependent infrastructure systems using the dynamic inoperability input–output model," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1299-1306, May.
    8. 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.
    9. Stéphane Hallegatte, 2008. "An Adaptive Regional Input‐Output Model and its Application to the Assessment of the Economic Cost of Katrina," Risk Analysis, John Wiley & Sons, vol. 28(3), pages 779-799, June.
    10. Amine El Haimar & Joost R. Santos, 2014. "Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 401-415, March.
    11. Nan, Cen & Sansavini, Giovanni, 2015. "Multilayer hybrid modeling framework for the performance assessment of interdependent critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 18-33.
    12. Muhammad Abdullah Khalid & Yousaf Ali, 2020. "Economic impact assessment of natural disaster with multi-criteria decision making for interdependent infrastructures," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7287-7311, December.
    13. Jalal Ali & Joost R. Santos, 2015. "Modeling the Ripple Effects of IT‐Based Incidents on Interdependent Economic Systems," Systems Engineering, John Wiley & Sons, vol. 18(2), pages 146-161, March.

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