HOW THE RESURGENCE OF SCHOOL QUALITY SHAPES HOME PRICING DECISIONS POST-COVID-19: EVIDENCE FROM NORTH GEORGIA

Abstract

This paper attempts to study how the resurgence of school quality shapes home pricing decisions post-COVID 19 in using data from 187 single-family homes in Gainesville, Georgia, a city with relatively low high school quality. The correlation analysis results show positive linear associations between the price of a house and numerous variables, namely the number of bedrooms, number of bathrooms, square footage, lot size, and parking spaces. There is also a negative linear association between the price of a house and its age. The results from regression analysis show that the number of bedrooms, bathrooms, square footage, and parking spaces are significant predictors of home prices. The results also suggest that in areas like Gainesville, where school quality does not impact home prices, delayed recovery or other local factors might explain the divergence from this trend.

Keywords

• pandemic
• home prices
• school quality
• regression
• correlation