The Application of Box-Cox Transformation in Selecting Functional Form for Hedonic Price Models

Article Preview

Abstract:

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.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2869-2875

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] K.W. Chau: International Real Estate Review Vol. 1 (1998), pp.1-16.

Google Scholar

[2] S.X. Ma and A. Li: China Civil Engineering Journal Vol. 36 (2003), pp.59-64.

Google Scholar

[3] H.Z. Wen and S.H. Jia: Journal of Zhejiang University (Engineering Science) Vol. 38 (2004), pp.1338-1343.

Google Scholar

[4] G.E.P. Box and D.R. Cox: Journal of the Royal Statistical Society (Series B) Vol. 26 (1964), pp.211-252.

Google Scholar

[5] A.C. Goodman: Journal of Urban Economics Vol. 5 (1978), pp.471-484.

Google Scholar

[6] W.H. Greene: Econometric Analysis, 4nd ed., Beijing (2001).

Google Scholar

[7] A.C. Goodman and T.G. Thibodeau: Journal of Housing Economics Vol. 12 (2003), pp.181-201.

Google Scholar