Two new use cases have been written for the Economic Decision Guide Software (EDGe$) Online Tool V 1.0. These new Special Publications highlight functionalities available in the EDGe$ Online Tool and also highlight key considerations in benefit cost analysis (BCA). Specifically, the two new NIST Special Publications help EDGe$ users to think through capabilities of EDGe$ that have not typically been highlighted in BCA practice:
1. Considering the point-of-view from which a BCA is determined and how this affects the valuation and associated externalities and
2. Highlighting sustainability and resilience co-benefits.
Economic Decision Guide Software (EDGe$) Online Tutorial:
Wildfire Urban Interface (WUI) Case Study
This NIST Special Publication introduces features of the Economic Decision Guide Software (EDGe$) Online Tool V 1.0 and presents a fictitious case study of wildfire planning in the wildland-urban interface (WUI). This example highlights the competing interests of two neighboring communities by evaluating the same project alternatives from the point of view of each community as the primary stakeholder. This WUI case study also demonstrates the importance of considering co-benefits and approaches to incorporating nonmarket valuation.
https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1260.pdf
Economic Decision Guide Software (EDGe$) Online Tutorial:
University Pandemic Planning Analysis Use Case
This NIST Special Publication addresses a major issue relevant to the current COVID-19 Pandemic situation. This use case highlights potential mitigation actions a higher education institution may take to mitigating some of the negative economic, social, and health effects of an infectious disease. This use case demonstrates the value of considering co-benefits that may impact the resilience and sustainability of built infrastructure in addition to the mitigation of pandemic disease spread.
https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1261.pdf
It should be noted that each of the two use cases are drawn from real-life data, but the details are fictious in nature.