安静的代价：疫情如何影响城市居民对道路交通噪音的反应
The Price of Quietness: How a Pandemic Affects City Dwellers' Response to Road Traffic Noise
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中文总结 AI 辅助
以新加坡新冠疫情为实验，通过46980条交易记录研究租户对道路交通噪音反应，发现疫情后噪音使房租下降，用机器学习文本分析10425条广告发现租户对安静偏好增加，为量化居民安静支付意愿首篇论文，有政策启示。
中文摘要 AI 辅助
利用新加坡新冠疫情爆发作为准自然实验，我们使用2006年至2022年的46980条交易记录，研究租赁住房市场中租户对道路交通噪音反应的变化。我们的双重差分估计表明，疫情爆发后道路交通噪音使房租立即下降3.8%，次年进一步下降12.7%，相当于每月186.7美元。结果通过了平行趋势分析、排列安慰剂检验等。通过对10425条租赁住房广告的机器学习文本分析表明，租户对安静的偏好从2019年到2020年增加了约10%。新的居家办公商业模式和送货服务交通量增加可解释此模式。这是第一篇用大量交易记录量化新冠疫情背景下城市居民为安静支付意愿的论文，结果对城市规划、交通网络和人类住区相互作用有政策启示，为实现可持续发展目标提供了途径。
英文摘要
Using the outbreak of COVID-19 in Singapore as a quasi-natural experiment, we investigate tenants' changing responses to road traffic noise in the rental housing market, using 46,980 transaction records between 2006 and 2022. Our difference-in-differences estimates show that road traffic noise decreases housing rents by 3.8% immediately after the pandemic outbreak and further declines by 12.7% in the subsequent year-equivalent to 186.7 US dollars per month. The results are robust to parallel trend analysis, permutation placebo tests, and tests using alternative distance thresholds or distance to the nearest main road. Then, we adopt a machine learning text analysis of 10,425 rental housing advertisements, showing that tenants' preference for quietness increases by approximately 10% from 2019 into 2020. The new work-from-home business model and rising traffic from delivery services can explain for this pattern. To the best of our knowledge, this is the first paper using a large volume of transaction records to quantify city dwellers' willingness to pay for quietness in the COVID-19 context. Our results have policy implications for other nations and post-pandemic era on the interaction among urban planning, transport networks, and human settlements, and shed light on the pathway to achieve sustainable development goals.
