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dc.contributor.authorChowdhury, Tuhinur Rahman
dc.description.abstractEfficient housing markets are critical for economic stability in the United States. Over one million people died in the United States from COVID-19. One method employed to halt the spread of the virus were stay-at-home orders. The effects of stay-at-home orders on different distributions of housing prices in 101 housing markets were investigated in this study. To estimate the effects of executive orders on house prices, an unconditional quantile regression model was employed for analysis. Results suggest that lower-priced houses experienced a larger price increase while the executive order was in effect. Following the expiration of the executive order, larger price increases were observed in both lower and higher priced house markets. Using a binary logit model, we examined whether socioeconomic or demographic characteristics affect executive orders. Results suggest that more black individuals and democrats make home price increases more likely under an executive order at certain quantiles.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleImpacts of the Covid-19 Pandemic on Housing Marketsen_US
dc.typeThesisen_US
dc.date.accessioned2023-12-15T16:27:14Z
dc.date.available2023-12-15T16:27:14Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/10365/33311
dc.subjectCOVID-19 Pandemicen_US
dc.subjectHedonic Price Modelen_US
dc.subjectHousing Marketsen_US
dc.subjectUnconditional Quantile Regressionen_US
dc.subjectUnited States Real Estate Economyen_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeBusinessen_US
ndsu.departmentAgribusiness and Applied Economicsen_US
ndsu.programAgribusiness and Applied Economicsen_US
ndsu.advisorZhang, Lei


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