Air pollution and the housing market: A neural network approach

Using the neural network method, this research explores the impact of total suspended particulate (TSP) and sulfur dioxide (SO₂), two major air pollutants, and of air pollution controls on the median real price of housing in Jacksonville, Florida. The results of this case study confirm the adverse effect of air pollution on the price of housing. The simulation of the model further suggests that pollution control measures improve property values. The findings imply that, in addition to other measures influencing the price of housing, property owners and buyers take air pollution and pollution controls into account.