Predicting the Texas Windstorm Insurance Association Payout for Commercial Property Loss Due to Ike Based on Weather, Geographical, and Building Variables

Hurricanes cause enormous loss to life and property worldwide. Predicting the damage caused by hurricane and figuring out what factors are responsible for the damage are important. This study utilizes multiple linear regression models to predict a hurricane ? induced Texas Windstorm Insurance Association (TWIA) payout or TWIA payout ratio using independent variables that could affect the hurricane intensity, including distance from the coastline, distance from the hurricane track, distance from the landfall center of Hurricane Ike, proportion in floodplain zone (100 year, 500 year, 100-500 year), building area, proportion in island, number of buildings per parcel, and building age.

The methodology of this study includes Pearson?s correlation and multiple linear regressions. First, Pearson?s correlation is used to examine whether there are any significant correlations between the dependent and independent variables. For TWIA payout, three independent variables, distance from the coastline, distance from the landfall center, and building area, are correlated to the TWIA payout at the 0.01 level. Distance from the coastline and distance from the landfall center have negative relations with the TWIA payout. The variable, building area, has a positive relation with the TWIA payout. Moreover, the improvement value is correlated to the TWIA payout at the 0.05 level. For TWIA payout ratio, distance from the coastline is correlated to the TWIA payout ratio at the level of 0.01 and distance from the landfall center is correlated to the TWIA payout ratio at the 0.05 level. These two variables have negative relations to the TWIA payout ratio.

Multiple linear regressions are applied to predict the TWIA payout and payout ratio. A regression model with an Adjusted R Square of 0.264 is presented to predict the TWIA payout. This model could explain 26.4 percent of the variability in TWIA payout using the variables, distance from coastline and building area. A regression model with an Adjusted R Square of 0.121 is presented to predict the TWIA payout ratio.