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Economic Decision Guide Software (EDGe$) with Loss Amplification and Risk Aversion: Wildfire Urban Interface (WUI) Case Studies

Published

Author(s)

Sherief Elsibaie, Bilal Ayyub, Jennifer Helgeson, Christina Gore, David Butry

Abstract

This report demonstrates by examples and case study as a proof of concept the use of loss amplification and risk aversion in benefit cost analysis (BCA) for community resilience planning. The report uses the NIST Economic Decision Guide Software (EDGe$) Online Tool, which assesses the economic feasibility of community resilience alternatives. Loss amplification arises from a catastrophe modeling method used to represent the increased costs associated with repair activity during a demand surge after a large catastrophe. Risk aversion is a measure of a community's (or other entity's) preference to avoid uncertainty. Risk aversion parameters can be used to compute certainty equivalent payoffs from uncertain payoffs and specific levels of risk aversion. A fictitious case study of wildfire disaster planning of a wildland-urban interface (WUI) is employed to demonstrate these two model enhancements (i.e., loss amplification and risk aversion) and their effects on the economic indicator outputs from EDGe$. The presented case study evaluates a binary development choice related to the resilience of a large presidential library from the perspective of two neighboring communities.
Citation
Special Publication (NIST SP) - 1296
Report Number
1296

Keywords

Benefit-cost analysis, community resilience, economic analysis, economic decision tool, loss amplification, demand surge, risk attitude, risk aversion, online application, online app, resilience, wildland urban interface

Citation

Elsibaie, S. , Ayyub, B. , Helgeson, J. , Gore, C. and Butry, D. (2023), Economic Decision Guide Software (EDGe$) with Loss Amplification and Risk Aversion: Wildfire Urban Interface (WUI) Case Studies, Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.SP.1296, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956723 (Accessed December 3, 2023)
Created November 1, 2023