疫情对城市房价的影响:来自2020年北京新冠肺炎疫情的证据

B. Qin, Yanyan Peng, lu feng
{"title":"疫情对城市房价的影响:来自2020年北京新冠肺炎疫情的证据","authors":"B. Qin, Yanyan Peng, lu feng","doi":"10.1108/ijhma-08-2022-0112","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.\n\n\nDesign/methodology/approach\nThe authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.\n\n\nFindings\nThis outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected.\n\n\nOriginality/value\nBy investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.\n","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020\",\"authors\":\"B. Qin, Yanyan Peng, lu feng\",\"doi\":\"10.1108/ijhma-08-2022-0112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.\\n\\n\\nDesign/methodology/approach\\nThe authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.\\n\\n\\nFindings\\nThis outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected.\\n\\n\\nOriginality/value\\nBy investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.\\n\",\"PeriodicalId\":14136,\"journal\":{\"name\":\"International Journal of Housing Markets and Analysis\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-03-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Housing Markets and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/ijhma-08-2022-0112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"URBAN STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Housing Markets and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijhma-08-2022-0112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"URBAN STUDIES","Score":null,"Total":0}
引用次数: 2

摘要

新冠肺炎大流行在全球范围内显著增加了经济风险和不确定性。COVID-19如何影响城市住房市场?不同地区遭遇新冠疫情有何不同?本研究旨在利用2020年北京住房市场数据,探讨疫情对房价的影响。设计/方法/方法作者使用2020年4月至9月的交易级数据对北京住房市场进行了享乐价格分析。这些数据包括从一家房地产中介网站上抓取的70,843笔交易。作者采用差异中的差异方法评估了2020年北京新发市场(北京最大、最重要的食品批发市场)新冠肺炎疫情的影响。新冠肺炎疫情导致2020年4月至9月北京房价下跌6.3%。然而,新冠肺炎疫情对城市不同街区房价的影响存在空间异质性。依赖面对面交流的行业所在社区的房价受疫情影响更大,而那些可以远程工作的社区的房价受影响较小。通过调查新冠肺炎疫情对北京房价的影响,本研究表明,至少在短期内,城市房价将受到疫情的影响。北京房价的涨跌在空间上存在异质性,表明不同社会经济特征和地理位置的城市街区在面对疫情时表现出不同的抵御能力。通过使用数据收集和严格的统计工具,该研究可能是首批研究COVID-19对城市内住房市场影响的研究之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020
Purpose The COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020. Design/methodology/approach The authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020. Findings This outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected. Originality/value By investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.80
自引率
29.40%
发文量
68
期刊最新文献
Comparative analysis of machine learning models in predicting housing prices: a case study of Prishtina's real estate market The exchange rates volatilities impact on the stock and real estate markets in South Africa Housing affordability and housing demand assessment for urban poor in India using the hedonic model Short-run dynamics and long-run effects of monetary policy on residential property prices in South Africa Relationship between housing, oil, gold and stock markets: evidence from UK and Norway
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1