Abstract
The purpose of this study was to understand the varying effects of COVID-19 on the median house price in metropolitan areas in the USA. Recently, the demand for houses has increased due to the COVID-19 pandemic. The pandemic increased the desire to stay indoors and introduced working from home. Four different factors were tested for their impact on the housing market: number of COVID-19 deaths, number of available houses for sale, unemployment rate, and mortgage interest rates. The control in this study was 2018-2019 house price data. We hypothesized that the house supply would cause the greatest change in house prices. Ckmean clustering method was applied to separate 93 metropolitan areas of the USA into three groups with different median house price levels. We then conducted linear regression modeling for each group to determine the varying level of effect each of the variables had. The results suggested that unemployment rate had the largest correlation with house prices, especially for metropolitan areas with extremely high house prices. This result did not support the research hypothesis. Further research could clarify the findings of our study by using fine-turned modeling techniques and including more economic factors like immigration or tourism. Additionally, we can research the effect of COVID-19 on house prices globally.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
