Article ID: | iaor20173423 |
Volume: | 84 |
Issue: | 3 |
Start Page Number: | 851 |
End Page Number: | 879 |
Publication Date: | Sep 2017 |
Journal: | Journal of Risk and Insurance |
Authors: | Grtler Marc, Hibbeln Martin, Dhrmann David |
Keywords: | risk, financial, investment, construction & architecture, demand, statistics: regression |
In the aftermath of a natural catastrophe, there is increased demand for skilled reconstruction labor, which leads to significant increases in reconstruction labor wages and hence insured losses. Such inflation effects are known as ‘Demand Surge’ effects. It is important for insurance companies to properly account for these effects when calculating insurance premiums and determining economic capital. We propose an approach to quantifying the Demand Surge effect and present an econometric model for the effect that is based on 192 catastrophe events in the United States. Our model explains more than 75 percent of the variance of the Demand Surge effect and is thus able to identify the key drivers of the phenomenon.