The application of Box-Cox transformation in selecting functional form for hedonic price models

摘要

Box-Cox transformation allows functional forms more flexible. On the basis of the principle of model optimization, an empirical study is made for housing market of Hangzhou City. By collecting 2417 housing data in Hangzhou City, a housing hedonic price model with Box -Cox transformations is set up with 18 factors as housing characteristics. The model is estimated after the grid-search procedure by using MATLAB and SPSS software, and the statistical test shows that the logarithmic function is the optimal form. The model comparisons in the fitness and forecasting performance indicate that the logarithmic model is superior to other three models of the linear, semi-logarithmic and inverse semi-logarithmic. Empirical analysis suggests that the Box-Cox transformation is valid and feasible in choosing functional forms, can be used to optimize hedonic price models.