Essays on the economic valuation of wildfires

Gonzalez Valencia, Maria Teresa (2024). Essays on the economic valuation of wildfires. University of Birmingham. Ph.D.

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Abstract

This thesis studies changes and differences in safety preferences as revealed by the housing market through the capitalisation of wildfire risk into property prices. To explain changes or differences in property prices, we implement the hedonic price method using high-quality geographic information system data on utility-bearing attributes specific to the property and its location. For this purpose, we focus on Western Australia during 2010-2019, a region of high wildfire risk with recent policy changes. CHAPTER 1 studies the near-miss effect of wildfires, i.e., the impact of a wildfire disaster on the area free from damage but subject to information effects. These information effects may alter households’ risk perception depending on their experience during the event. The wildfire disaster that we analyse is the Waroona Fire of 2016. To identify the near-miss effect, we rely on the use of difference-in-differences and a multidimensional near-miss area defined by proximity to the burn scar and receiving warnings during the fire event. Our findings suggest that the proximity treatment effect is positive due to a risk reduction effect from burnt fuel that dominates over any disamenity impacts. On the other hand, the warning treatment effect is negative, suggesting an increase in risk perception due to vulnerability feelings. CHAPTER 2 studies the introduction of wildfire risk maps in 2015, known in Western Australia as ‘bushfire prone area’ maps. These maps were received with surprise by residents and areas mapped as ‘risky’ faced more stringent planning and building regulations. Taking advantage of the sharp boundaries that divide designated from non-designated areas, we use a regression discontinuity design to investigate the price differential for designated properties. We find that properties within bushfire prone areas are sold at a lower price, and results suggest that this discount is moreover driven by a pure information shock that increases risk perceptions, rather than by any predetermined risk perceptions or the more stringent planning and building regulations that apply to new builds. CHAPTER 3 studies preferences for prescribed fires by accounting for its exposure in terms of number of fires and area burnt. Prescribed fires are used by land managers to reduce the likelihood of uncontrollable wildfires, but generate disamenity impacts, such as smoke haze and road closures. These fires also face strong opposition from conservationists. Using property fixed effects and controlling for wildfire exposure, we find a positive preference for prescribed fires, and stronger results for more recent fires, which we attribute to the depreciating nature of risk reducing interventions over time and/or to availability heuristics due to recent fires being easier to retrieve. Our results are also stronger when we use the number of fires, than when we use area burnt, suggesting households pay more attention to the frequency component of risk, rather than consequence. Additionally, properties with no wildfire exposure are sold at a price significantly higher, suggesting perhaps that households’ demand for prescribed fires is higher in the absence of the risk reduction effect of wildfires. Our findings also suggest that the use of property fixed effects is important for an appropriate incorporation of time-constant attributes.

Overall, our findings suggest that risk perception updates are capitalised into the housing market, particularly in areas that are wildfire prone, as that of Western Australia; meaning that policy makers do have the potential to alter people’s beliefs about risk. Amid an increasing risk of wildfires across the globe, much more research is needed on identifying misperceptions on risk, tools for correction, and households’ preferences for forest management practices.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):