Modeling the Effects of Environmental Impacts and Accessibility on Real Estate Prices in Industrial Cities

This article presents hedonic Multiple Linear Regression models (MLR) to estimate real estate price variations in metropolitan areas as a result of changing environmental and accessibility conditions. The goodness of fit of the model has been compared along with a series of hypotheses about the performance of the specifications considering spatial relationships between observations. The case study for such analysis is the metropolitan area of Taranto (Southern Italy). The models which considered spatial dependence between observations offered a greater degree of fit in a scenario showing strong spatial correlation in MLR residuals.