The implications of empirical data for risk

Bibliographic Data

ID12597185
AuthorsDaniel Bilusich (Defence Science and Technology Group, corresponding author), Steven Lord (0000-0002-6142-5358, Defence Science and Technology Group), Rick Nunes‐Vaz (Defence Science and Technology Group), Rick Nunes-Vaz
Year2014
Volume18
Issue4
Pages521-538
Publication date2014-05-01
Open AccessNo
TypeARTICLE
VenueJournal of Risk Research (JOURNAL)
Journal identifiersISSN: 1366-9877 • E-ISSN: 1466-4461
PublisherRoutledge (PUBLISHER • GB)
DOI10.1080/13669877.2014.910682
OpenAlexW2119187760
LanguageEN
References cited28

It is of interest for national governments to assess strategic issues such as natural hazards and anthropogenic threats with some reference to risk, in order to support prioritisation of treatment solutions. With most threats of strategic relevance such as earthquakes, pandemics and terrorism following a distribution in size of events, representation of the risk for a threat as a single frequency– consequence pair is often inadequate as this single pair may exclude a significant portion of data and their contribution to total risk. Identifying the entire distribution of event sizes and their frequencies is better suited for understanding the relative contributions to total risk from high and low consequence events. If the distribution of event sizes does follow a law, the finite size of data-sets makes identifying the law difficult. This paper outlines the steps required to utilise empirical data to inform the risk of strategic threats and support decision-makers to prioritise treatment options according to their relative contributions to total risk. Potential pitfalls and limitations are also described

Actuarial science · Business · Econometrics · Economics · Event (particle physics · Hazard · Risk analysis (engineering · Variable (mathematics · Agricultural risk and resilience · Computer Science · Economic, financial, and policy analysis · Mathematics · Risk Perception and Management

Tools

Open DOISci-Hub