Spatial Econometric Analysis of Housing Price of Chinese Provinces

Author

Hu Zhaohui

Author_Institution

Res. Center of Fictitious Econ. & Data Sci. FEDS, Beijing, China

fYear

2012

fDate

12-14 Oct. 2012

Firstpage

187

Lastpage

190

Abstract

The high housing price is becoming more and more important to economical development and people´s living standard. This article introduces spatial economics to study Chinese provincial housing price and its determinant factors. The paper uses the Moran´s I statistic to test housing price´s spatial autocorrelation, and uses spatial panel data model to estimate the spatial error autocorrelation specification. The results show that there exists spatial autocorrelation in provincial housing price and spatial panel data model is a better model to explore the spatial autocorrelation and influencing factors of housing price.

Keywords

econometrics; real estate data processing; statistical testing; Chinese provincial housing price; Moran I statistic; determinant factors; economical development; housing price spatial autocorrelation; spatial econometric analysis; spatial economics; spatial error autocorrelation specification estimation; spatial panel data model; Cities and towns; Correlation; Data models; Economics; Robustness; Sociology; Spatial databases; Moran´s I; housing price; spatial autocorrelation; spatial economics; spatial panel data model;

fLanguage

English

Publisher

ieee

Conference_Titel

Business Computing and Global Informatization (BCGIN), 2012 Second International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4673-4469-2

Type

conf

DOI

10.1109/BCGIN.2012.55

Filename

6382496