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Spatial Analysis and Modeling of the Housing Value Changes in the U.S. during the COVID-19 Pandemic

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  • Xinba Li

    (Department of Economics, University of Connecticut, Storrs, CT 06269, USA
    Department of Mathematics, University of Connecticut, Storrs, CT 06269, USA)

  • Chihwa Kao

    (Department of Economics, University of Connecticut, Storrs, CT 06269, USA)

Abstract

COVID-19 has affected almost all sectors of the economy, including the real estate markets across different countries in the world. A rich body of literature has emerged in analyzing real estate market trends and revealing important information. However, few studies have used a spatial perspective to investigate the impact of COVID-19 on property values. The main purposes of this study are as follows: (1) to explore the spatial distribution and spatial patterns of housing price changes during the COVID-19 pandemic crisis in the U.S. real estate market and (2) to model the spatially nonstationary relationships between the housing price change and COVID-19 characteristics. We find that housing price changes differ across space and appear associated with the spatial distribution of the COVID-19 case rates. The housing market volatility is amplified by the uneven distribution of some socioeconomic factors. The spatially uneven housing price changes may bring an uneven spillover effect to the rest of the economy and lead to divergence in economic growth across different areas.

Suggested Citation

  • Xinba Li & Chihwa Kao, 2022. "Spatial Analysis and Modeling of the Housing Value Changes in the U.S. during the COVID-19 Pandemic," JRFM, MDPI, vol. 15(3), pages 1-25, March.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:3:p:139-:d:771721
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    References listed on IDEAS

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    1. Zengzheng Wang & Fuhao Zhang & Yangyang Zhao, 2023. "Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education," Land, MDPI, vol. 12(1), pages 1-24, January.

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