The Effects of Neighborhood and Interior Characteristics on Residential Sale Prices

Abstract

This study analyses to what extent certain neighborhood and interior characteristics affect residential sale prices, after accounting for standard property variables. This is important to examine in order to understand the function of the housing market, the sources of price differences, and whether residential values can be controlled by prioritizing specific desirable property features. The study is based on a dataset of approximately 330,000 observations from the Multiple Listing Service (MLS), as well as walkability data obtained from Walk Score. The data is analyzed in Stata, using three regression models with different combinations of explanatory variables. The results show that the model containing neighborhood variables has a higher explanatory power than the model with the interior variables, though the magnitude of the interior attributes’ coefficients is stronger than those of the neighborhood features. The full model, containing all variables of interest, has the highest explanatory power, suggesting that this model explains more of the price variation than the other two models, and it provides the most comprehensive specification of the variation in residential sale prices, since it does not omit any potentially important variables included in the study. Overall, this suggests that, after controlling for standard property variables, both neighborhood and interior attributes are valuable determinants of the variation in sale prices in the housing market. Moreover, further research is intended, to gain more knowledge and skills in the area, and to expand the scope of the project to hopefully get more comprehensive and accurate results.