{"title":"The Roof is on Fire: Wildfires' Effect on Housing Prices","authors":"Victor Sierra","doi":"10.2139/ssrn.3545603","DOIUrl":null,"url":null,"abstract":"Regression analyses have been commonly applied to studying the relationships between wildfires and housing prices in local markets. My study conducts a regression analysis on a panel of local markets using county-level data. It contributes to climate and housing literature by estimating the impact of wildfires on housing prices across the Western United States using a robust least squares regression. Most models estimate wildfire effects on housing prices using direct data from wildfire activities or acres burned due to wildfire as their variables of interest. Wildfire activity data is not easily accessible on the county-level; thus, this model utilizes average annual maximum temperatures to measure changes in climate over time which exacerbate and contribute to more frequent wildfire activities. (Westerling et al., 2007). My study finds that as the average maximum temperature increases within a county, the housing prices will generally decrease in value. The results of these effects are found to be statistically significant. Specifically, one percentage point increase in the growth rate of average maximum temperature reduces the growth rate of housing sales price by an average of 0.149 percentage point. These results can provide policymakers and researchers more information about land use in wildfire-prone areas and the impact wildfires have on housing markets.","PeriodicalId":10619,"journal":{"name":"Comparative Political Economy: Social Welfare Policy eJournal","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comparative Political Economy: Social Welfare Policy eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3545603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Regression analyses have been commonly applied to studying the relationships between wildfires and housing prices in local markets. My study conducts a regression analysis on a panel of local markets using county-level data. It contributes to climate and housing literature by estimating the impact of wildfires on housing prices across the Western United States using a robust least squares regression. Most models estimate wildfire effects on housing prices using direct data from wildfire activities or acres burned due to wildfire as their variables of interest. Wildfire activity data is not easily accessible on the county-level; thus, this model utilizes average annual maximum temperatures to measure changes in climate over time which exacerbate and contribute to more frequent wildfire activities. (Westerling et al., 2007). My study finds that as the average maximum temperature increases within a county, the housing prices will generally decrease in value. The results of these effects are found to be statistically significant. Specifically, one percentage point increase in the growth rate of average maximum temperature reduces the growth rate of housing sales price by an average of 0.149 percentage point. These results can provide policymakers and researchers more information about land use in wildfire-prone areas and the impact wildfires have on housing markets.
回归分析通常用于研究野火与当地市场房价之间的关系。我的研究使用县级数据对当地市场面板进行回归分析。它通过使用稳健的最小二乘回归估计野火对美国西部房价的影响,为气候和住房文献做出贡献。大多数模型使用野火活动的直接数据或野火烧毁的面积作为感兴趣的变量来估计野火对房价的影响。在县一级很难获得野火活动数据;因此,该模型利用年平均最高温度来测量气候随时间的变化,这些变化加剧并导致更频繁的野火活动。(Westerling et al., 2007)。我的研究发现,随着县内平均最高气温的升高,房价普遍会下降。这些影响的结果在统计上是显著的。其中,平均最高气温增速每提高1个百分点,住房销售价格增速平均降低0.149个百分点。这些结果可以为政策制定者和研究人员提供更多关于野火易发地区土地利用以及野火对住房市场影响的信息。