标题： 野火与房价：阿特兰达纳的合成控制案例研究（2025年1月） 显示英文标题

标题： Wildfire and house prices: A synthetic control case study of Altadena (Jan 2025)

摘要： 本研究使用合成控制方法（SCM）来估计2025年1月的野火对加利福尼亚州Altadena地区房价的因果影响。 我们通过同行城市加权平均构建一个“合成”Altadena作为对照组；这种方法假设捐赠池中没有溢出效应。 结果揭示了一个显著的负面价格效应，且随时间推移而加剧。 事件发生后的六个月里，我们估计平均每月损失为32,125美元。 对此效应的统计证据较为复杂。 基于稳健的处理后与处理前RMSPE比率，结果在10%的水平上具有统计显著性（p = 0.0508）。 相比之下，当用处理后平均差距衡量时，该效应并不具有统计显著性（p = 0.3220）。 这项分析突显了处于火灾高发地区的社区所面临的重大财务风险，并展示了SCM在评估灾害相关经济损失方面的有效性。 显示英文摘要

摘要： This study uses the Synthetic Control Method (SCM) to estimate the causal impact of a January 2025 wildfire on housing prices in Altadena, California. We construct a 'synthetic' Altadena from a weighted average of peer cities to serve as a counterfactual; this approach assumes no spillover effects on the donor pool. The results reveal a substantial negative price effect that intensifies over time. Over the six months following the event, we estimate an average monthly loss of $32,125. The statistical evidence for this effect is nuanced. Based on the robust post-to-pre-treatment RMSPE ratio, the result is statistically significant at the 10% level (p = 0.0508). In contrast, the effect is not statistically significant when measured by the average post-treatment gap (p = 0.3220). This analysis highlights the significant financial risks faced by communities in fire-prone regions and demonstrates SCM's effectiveness in evaluating disaster-related economic damages.