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

Xinba Li and Chihwa Kao
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Xinba Li: Department of Economics, University of Connecticut, Storrs, CT 06269, USA

JRFM, 2022, vol. 15, issue 3, 1-25

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.

Keywords: COVID-19; housing value; spatial analysis; U.S.; geographically weighted regression (GWR) (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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