Paper Info
Title
A Geographically Temporal Weighted Regression Approach with Travel Distance for House Price Estimation.
Abstract
Previous studies have demonstrated that non-Euclidean distance metrics can improve model fit in the geographically weighted regression (GWR) model. However, the GWR model often considers spatial nonstationarity and does not address variations in local temporal issues. Therefore, this paper explores a geographically temporal weighted regression (GTWR) approach that accounts for both spatial and temporal nonstationarity simultaneously to estimate house prices based on travel time distance metrics. Using house price data collected between 1980 and 2016, the house price response and explanatory variables are then modeled using both the GWR and the GTWR approaches. Comparing the GWR model with Euclidean and travel distance metrics, the GTWR model with travel distance obtains the highest value for the coefficient of determination (R-2) and the lowest values for the Akaike information criterion (AIC). The results show that the GTWR model provides a relatively high goodness of fit and sufficient space-time explanatory power with non-Euclidean distance metrics. The results of this study can be used to formulate more effective policies for real estate management.
Year
DOI
Venue
2016
10.3390/e18080303
ENTROPY
Keywords
Field
DocType
geographically and temporally weighted regression,travel time,housing prices
Econometrics,Geographically Weighted Regression,Akaike information criterion,Unit-weighted regression,Explanatory power,Coefficient of determination,Travel time,Statistics,Property management,Goodness of fit,Mathematics
Journal
Volume
Issue
Citations 
18
8
1
PageRank 
References 
Authors
0.37
8
6
Name
Order
Citations
PageRank
Jiping Liu1116.00
Yi Yang227761.06
Shenghua Xu3115.02
Yangyang Zhao4529.46
Yong Wang521.08
Fuhao Zhang6142.69