IDEAS home Printed from https://ideas.repec.org/a/taf/specan/v17y2022i3p395-415.html
   My bibliography  Save this article

Covid-19 impact on US housing markets: evidence from spatial regression models

Author

Listed:
  • Jim Lee
  • Yuxia Huang

Abstract

This paper empirically investigates the conventional wisdom that urban residents have reacted to the Covid-19 pandemic by fleeing city centres for the suburbs. A conventional panel model of US ZIP code-level data provides mixed evidence in support of a shifting housing preference for more space or neighbourhoods farther from the urban core. Regressions accounting for spatial dependence and spatial heterogeneity show strong support of an urban flight within metro areas, but this local phenomenon is uneven across broad regions of the United States. The finding of geographical disparity underscores both the local as well as the regional nature of housing market conditions.

Suggested Citation

  • Jim Lee & Yuxia Huang, 2022. "Covid-19 impact on US housing markets: evidence from spatial regression models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 17(3), pages 395-415, July.
    • Handle: RePEc:taf:specan:v:17:y:2022:i:3:p:395-415
    DOI: 10.1080/17421772.2021.2018028
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/17421772.2021.2018028
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/17421772.2021.2018028?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Steven Bond-Smith & Philip McCann, 2022. "The work-from-home revolution and the performance of cities," Working Papers 2022-6, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    2. Baulkaran, Vishaal & Jain, Pawan, 2023. "COVID-19, home equity and retirement funding," Finance Research Letters, Elsevier, vol. 58(PB).
    3. Tsai, I-Chun & Chiang, Ying-Hui & Lin, Shih-Yuan, 2022. "Effect of COVID-19 lockdowns on city-center and suburban housing markets: Evidence from Hangzhou, China," Journal of Asian Economics, Elsevier, vol. 83(C).
    4. Sander van Cranenburgh & Francisco Garrido-Valenzuela, 2023. "Computer vision-enriched discrete choice models, with an application to residential location choice," Papers 2308.08276, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:specan:v:17:y:2022:i:3:p:395-415. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RSEA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.