Efficient 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.