Insured Loss Inflation: How Natural Catastrophes Affect Reconstruction Labor Wages

In the aftermath of a natural catastrophe there is an increased demand for skilled reconstruction labor, which leads to significant increases of reconstruction labor wages and hence insured losses. Such inflation effects are referred to as "Demand Surge" effects. It is important for insurance companies to properly account for these effects when calculating insurance premiums and determining the economic capital. The paper at hand presents the first econometric model of the Demand Surge effect. Based on 188 catastrophe events in the United States we find that the proposed model is able to explain more than 75 % of variance of the Demand Surge effect and should allow insurance companies to forecast future Demand Surge effects and to incorporate these results in their premium calculations. Demand Surge is positively influenced by the total amount of repair work, however, a possible reconstruction backlog from previous events worsens the situation additionally. The model also deduces a positive relationship between the number of insurance claims per event and the Demand Surge effect, which is due to a less restrictive regulation policy. Furthermore, the Demand Surge effect is more pronounced if the construction sector is in a growth stage. In contrast, a higher capacity of the construction sector has a restraining effect on Demand Surge. In addition, if we restrict the data to very severe catastrophes, we observe a saturation effect according to which an increase of reconstruction labor wages before a catastrophe reduces the Demand Surge effect. Moreover, the model results remain valid under different robustness checks, which confirms our measurement approach. JEL classification: G22, J23, J31, Q54, R23