Using Matching Methods to Estimate Impacts of Wildfire and Postwildfire Flooding on House Prices

The increasing frequency and severity of landscape-scale wildfire poses new challenges for forested watershed management. The Schultz Fire burned 6,100 ha on the steep slopes of San Francisco Mountain near Flagstaff, AZ, USA in 2010. Within a month of the wildfire, summer monsoon rains created flooding and debris flows 1–2 orders of magnitude greater than prewildfire rainfall events. We estimate a hedonic property model to determine the loss in house prices from the wildfire and postwildfire flooding. While several studies examine the effects of wildfires and flooding on housing prices separately, to our knowledge, no study has determined the effects of postwildfire flooding in a fire-adapted watershed. Most hedonic property models estimating impacts of wildfire or flooding use regression analysis to predict impacts. We also contribute to the hedonic property model literature by using nonparametric matching techniques. We find a negative and statistically significant average treatment effect of wildfire and post-wildfire flooding. The treatment effect, however, differs relative to distance to wildfire perimeter and distance to flood zones. For example, houses located within 5 km of the Schultz Fire perimeter have an estimated 31% loss, while houses within 20 km have an estimated 6% loss. In addition, prices for houses located within 100 m of the 5-year flood drop by 10% after the flood, whereas prices for houses within 2 km drop by 5%. Our results indicate that careful consideration of the impacts of both wildfire and postwildfire flooding is essential for understanding the net benefits of forested watershed restoration.