Housing Market in the Time of Pandemic: A Price Gradient Analysis from the COVID-19 Epicentre in China

K. Cheung, Chung Yim Edward Yiu, Chuyi Xiong
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引用次数: 39

Abstract

While the outbreak of the COVID-19 disease has caused asset markets to experience an unprecedented spike of risk and uncertainty worldwide, the real estate market in many global cities appears to be immune to the adverse effects. How does COVID-19 affect urban housing markets? This study is a first attempt to identify the pandemic’s impact on house prices by applying a price gradient analysis to the COVID-19 epicentre in China. Considering microlevel housing transaction data in 62 areas from nine districts in Wuhan City from January 2019 to July 2020, the hedonic pricing and the price gradient models suggest that there was, respectively, a 4.8% and a 5.0–7.0% year-on-year fall in house prices immediately after the pandemic outbreak. Although house prices rebounded after the lockdown period, the gradient models show that the price gradients were flattened from the epicentre to the urban peripherals. The price premiums in high-density areas were also substantially discounted after the city’s lockdown. Our findings are robust to different model specifications. The implication is that the risk associated with the pandemic is localised and transitory in nature. People may be able to internalise the risk by residing in low-density residential areas.
大流行时期的住房市场:基于中国新冠肺炎疫情中心的价格梯度分析
虽然新冠肺炎疫情的爆发使全球资产市场经历了前所未有的风险和不确定性,但全球许多城市的房地产市场似乎没有受到不利影响。COVID-19如何影响城市住房市场?本研究首次尝试通过对中国新冠肺炎疫情中心进行价格梯度分析,确定疫情对房价的影响。结合2019年1月至2020年7月武汉市9个区62个区域的微观住房交易数据,享乐定价模型和价格梯度模型显示,疫情爆发后,房价分别同比下跌4.8%和5.0% ~ 7.0%。虽然房价在封锁期后反弹,但梯度模型显示,从震中到城市外围的价格梯度趋于平缓。人口密集地区的房价溢价在封城后也大幅降低。我们的研究结果对不同的模型规格具有鲁棒性。这意味着,与大流行相关的风险是局部的和暂时的。居住在低密度居民区的人们可能会将这种风险内在化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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