Abstract In this paper,we use the housing price of Boston as the sample and select 13 factors which may affect it to construct the measurable model about the housing price and the hedonic factors,and try to find the key factor affecting the housing price based on hedonic price by using the statistical tools such as regression analysis,cluster analysis,artificial neural networks model and regression trees model.Then,we compare the models according to the predictive effect and further discuss the key factor.This study finds that the number of rooms and LSAT (logarithm of the ratio of the lower class) are the two most important variables,which provides the message to policymakers that the state should greatly increase the transparency of real estate information,and pay attention to the impacts of different classes may have on the adjustment of real estate policy.
2015, Vol. 32 
