This dissertation consists of three economic questions relating to wildfire and homes. Each utilizes “big" data. Zillow’s ZTRAX data is combined with MTBS fire perimeter data
and LANDFIRE fire risk data to answer three economic questions. The first chapter examines the spatial relationship between fires and homes. The second evaluates homeowners’ attitudes towards wildfire risk. The third tests if property taxes reflect wildfire risk.
Fire managers have strong incentives to save homes. The first chapter examines the relationship between wildfire perimeters and unburned areas within fire in relation to home
locations. The connection is examined by measuring the density of homes around fire perimeters and by measuring the frequency of refugia around structures. The existing studies of refugia, defined as unburned areas within fire perimeters, have not yet evaluated structure presence or structure protection activities as potential causes for refugia. This chapter analyzes the spatial frequency of structures within fire perimeters and within refugia. A variety of datasets are utilized to show a correlation between refugia and structure locations. Furthermore, the findings indicate that structure density is 40% higher within 30 meters of fire perimeters than structure density between 30 and 60 meters. Structure density, the number of homes per unit of area, is a new measurement that is developed to county the number of homes at different distances from the fire perimeter. The increased density at the fire perimeter demonstrates that fires often burn immediately near to houses before being stopped. There is also evidence that wildfires are contained further away from homes where there is a larger number of homes. The results suggest that fire suppression mitigates fire spread.
In year 2020, there were 9,630 residences destroyed by wildfires in the United States. While living in the wildland urban interface (WUI) may be desirable for homeowners, the increased wildfire risk in some WUI locations may make certain homes less desirable. The second chapter examines the relationship that home materials have on house prices in fire prone areas. A hedonic model of housing prices based on housing attributes and wildfire risk is constructed to determine home buyer willingness to pay for home attributes that are vulnerable to wildfires, such as wooden roofs. Homebuyers initially appear willing to spend more to purchase homes in high fire risk areas. However, they value a home in a high fire risk area less if it has a flammable roof despite wooden roofs commanding a price premium in other locations. The results suggest that homeowners may be aware of how fire risk relates to their type of home but still place more value on the aesthetics than the associated fire risk. To fund wildfire protection, some states have required homes located in areas determined by the state to be at higher fire risk to pay a fee. From 2011 to 2017, California charged property owners a fee of approximately $150 for each habitable structure located in the state responsibility area. In states and counties that don’t charge a fee for living in a fire risk area, fire protection services are paid for by the entire group of taxpayers. This may result in an implicit subsidy to homeowners in high fire risk areas. The third chapter develops a model to determine if states and counties charge high fire risk homeowners more in taxes than non high-risk homeowners. A random forest estimator is used on cross county assessment data to back out county assessment models that determine the assessed value of properties. The resulting models are used to examine the assessed value of homes relative to fire risk.
Preliminary results indicate that high fire risk homeowners pay a slight premium to live in high fire risk areas but less than the amount spent on rural fire protection.
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Details
Title
Essays on Wildland Fire and Housing
Creators
Joshua Olsen
Contributors
Jonathan Yoder (Chair)
Randy Fortenbery (Committee Member)
Gregmar Galinato (Committee Member)
Awarding Institution
Washington State University
Academic Unit
School of Economic Sciences
Theses and Dissertations
Doctor of Philosophy (PhD), Washington State University