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Quantifying Catastrophic and Climate Impacted Hazards Based on Local Expert Opinions

Tim Keighley, Thomas Longden, Supriya Mathew and Stefan Trück
Additional contact information
Tim Keighley: Faculty of Business and Economics, Macquarie University
Supriya Mathew: Northern Institute, Charles Darwin University
Stefan Trück: Faculty of Business and Economics, Macquarie University

Authors registered in the RePEc Author Service: Stefan Trueck (stefan.trueck@mq.edu.au)

No 2014.93, Working Papers from Fondazione Eni Enrico Mattei

Abstract: The analysis of catastrophic and climate impacted hazards is a challenging but important exercise, as the occurrence of such events is usually associated with high damage and uncertainty. Often, at the local level, there is a lack of information on rare extreme events, such that available data is not sufficient to fit a distribution and derive parameter values for the frequency and severity distributions. This paper discusses local assessments of extreme events and examines the potential of using expert opinions in order to obtain values for the distribution parameters. In particular, we illustrate a simple approach, where a local expert is required to only specify two percentiles of the loss distribution in order to provide an estimate for the severity distribution of climate impacted hazards. In our approach, we focus on so-called heavy-tailed distributions for the severity, such as the Lognormal, Weibull and Burr XII distribution. These distributions are widely used to fit data from catastrophic events and can also represent extreme losses or the so-called tail of the distribution. An illustration of the method is provided utilising an example that quantifies the risk of bushfires in a local area in Northern Sydney.

Keywords: Catastrophic Risks; Climate Impacted Hazards; Expert Opinions; Local Level Decision Making; Loss Distribution Approach (search for similar items in EconPapers)
JEL-codes: Q5 Q54 Q58 (search for similar items in EconPapers)
Date: 2014-11
New Economics Papers: this item is included in nep-agr, nep-env and nep-rmg
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