D04

Research Abstracts on Spatial Information ScienceCSIS DAYS 2015

Hedonic Price Modeling of New Residential Property Values in Xi’an City, China
Kai Liu
Division of Spatial Information Science, Faculty of Life and Environmental Sciences, University of Tsukuba
Email: <liukai890208@gmail.com>(1) Introduction: Considering the increasing newresidential property values in China, this study estimatesthe implicit premium of several location factors affecting
on housing price in Xi’an City, using hedonic pricing
technique. It is verified that spatial local singularities
caused by unobserved variables or estimation bias can beassociated with multi- regression errors. This study
explores an unconven- tional viewpoint to residualproblem, which combines the regional differences andthe spatial distributions of singularities. The samples areclassified into 5 agglomerations, aiming to prove somehypotheses that following the residual analysis forrevealing the underlying reasons about the future trend
and variation of real estate market within each region. It
is effective to provide scientific basis of decision making
for the real estate investors and planners.
(2) Objectives: The main objectives of this study are to: 1)
attempt to apply hedonic pricing models in housing
market of Xi’an, 2) search for the most suitable
regression model by using SPSS and measure thepremium by presenting the monetary value of each key
characteristic to urban planner and decision-makers for
optimizing urban development projects, 3) reveal thecauses and mechanism about spatial singularities anddifferences.
(3) Data and Method: Figure 1 shows the 378-samples of
housing price and spatial data. Premiums on residential
properties from each factor can be quantized by using
hedonic pricing model. Considering the residual problem,
this study has read the spatial singularity and local
characteristics by using residual and cluster analysis.
(4) Results and Discusssions: 1) A within-zone housing
unit is sold 9.4% more than if it was outside theattendance zone of a Key Primary School. Herein, thepremium on residential properties from the influence of
educational resources has been quantized, i.e. the willingto pay for the high-quality educational resource. 2) A
corollary was got that advantages of rail transportation
had not yet adequately been brought into full play inXi’an (Table 1), and this detail is different like otherhedonic approach (Gu and Zheng 2010). 3) Residual
analysis is applied to understand the local differences on
housing pricing and the development situation of realestate market in Xi’an. Three special areas could befound regarded as high-technology area (A), luxury
residential area (B), and new town (C) in Xi’an. In
conclusion, this paper successfully assessed the housing
price trends and the real estate market prospects for newresidences. 4) 5 agglomerations can be classified forrevealing the future trend and variation of real estatemarket (Figure 2). 5) As this case study about hedonic
pricing modeling, the utilization of GIS and SPSS isdemonstrated to be effective and efficient.
(5) Reference:
Gu, Y. Z., and Zheng, S. Q. (2010) The impacts of railtransit on property values and land development
intensity: The case of No.13 line in Beijing. Acta
Geographica Sinica, 2, 213-223.
Table 1: Regression results* p<0.10; **p<0.05; ***p<0.01

Figure 1: Spatial data and housing price sample

Figure 2: Result of cluster analysis- 54 -