Modeling risks from natural hazards with generalized additive models for location, scale and shape
| Autor: | Stefan Trück, David Pitt, Wan Wah Wong, Rob van den Honert |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Generalized linear model
Environmental Engineering Climate 0208 environmental biotechnology 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences Risk Factors Natural hazard Covariate Generalized beta distribution Econometrics Weather Waste Management and Disposal Risk management 0105 earth and related environmental sciences business.industry Generalized additive model Linear model General Medicine Floods 020801 environmental engineering Linear Models business Scale parameter |
| Zdroj: | Journal of Environmental Management. 275:111075 |
| ISSN: | 0301-4797 |
| DOI: | 10.1016/j.jenvman.2020.111075 |
| Popis: | We investigate a new framework for estimating the frequency and severity of losses associated with catastrophic risks such as bushfires, storms and floods. We explore generalized additive models for location, scale and shape (GAMLSS) for the quantification of regional risk factors - geographical, weather and climate variables - with the aim of better quantifying the frequency and severity of catastrophic losses from natural perils. Due to the flexibility of the GAMLSS approach, we find a superior fit to empirical loss data for the applied models in comparison to generalized linear regression models typically applied in the literature. In particular the generalized beta distribution of the second kind (GB2) provides a good fit to the severity of losses. Including covariates in the calibration of the scale parameter, we obtain vastly differently shaped distributions for the predicted individual losses at different levels of the covariates. Testing the GAMLSS approach in an out-of-sample validation exercise, we also find support for a correct specification of the estimated models. More accurate models for the losses from natural hazards will help state and local government policy development, in particular for risk management and scenario planning for emergency services with respect to these perils. |
| Databáze: | OpenAIRE |
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