Measuring the impact of the urban microclimate on housing price using the spatial hedonic pricing method: The case study of Mueller, Austin, TX

Cities are becoming hotter as global climate change and urban heat islands intensify. However, heat is not uniformly distributed in a city as some areas have a much hotter thermal environment than others. To investigate whether house prices are affected by variation in the outdoor thermal environment, this study used statistical models to identify the importance of the microclimate around a house compared to other well-known structural, locational, and environmental characteristics. The effect of the outdoor environment on the thermal comfort of residents was modeled using the validated COMFA energy budget model. Micro-meteorological data that were directly measured in the study area were analyzed using the COMFA model. A semi-log hedonic pricing model was then utilized, and two models were developed: a spatial autoregressive (SAR) model, and a spatial error model (SEM) that considers spatial autocorrelation. The results $\left(p<0.0001\right)$ indicated that the outdoor thermal comfort level around a house is a crucial factor that affects housing market prices. In addition, the outdoor thermal comfort level showed high significance using both the SAR $\left(R^2=0.88\right)$ and the SEM $\left(R^2=0.89\right)$ models. These results have important implications by bringing to light a variable that affects housing prices and, until now, has been invisible.