Predicting House Prices with Spatial Dependence: A Comparison of Alternative Methods

2010 ◽  
Vol 32 (2) ◽  
pp. 139-160 ◽  
Author(s):  
Steven Bourassa ◽  
Eva Cantoni ◽  
Martin Hoesli
2012 ◽  
Vol 2 (2) ◽  
pp. 57-70
Author(s):  
Xin Janet ◽  
Ka-Chi Lam

This paper builds a house prices forecasting model for private residential houses in HongKong, based on general macroeconomic indicators, housing related data and demographicfactors for the period of 1980 to 2001. A reduce form economic model has been derivedfrom a multiple regression analysis where three sets and eight models were derived foranalysis and comparison. It is found that household income, land supply, population andmovements in the Hang Seng Index play an important role in explaining house pricemovements in Hong Kong. In addition, political events, as identified, cannot be ignored.However, the results of the models are unstable. It is suggested that the OLS may nota best method for house prices model in Hong Kong situation. Alternative methods aresuggested.


2019 ◽  
Vol 11 (2) ◽  
pp. 544 ◽  
Author(s):  
Ling Zhang ◽  
He Wang ◽  
Yan Song ◽  
Haizhen Wen

This study investigates the spatial dependence of house prices in the Yangtze Delta Urban Agglomeration since the year 2000. According to Moran’s I index and the LISA scatter plot derived from a cross-section data set, the spatial dependence of house prices can be traced across the 25 cities in the agglomeration and became more evident after 2005. This study develops a spatial panel model with geographical distance and economic distance weight matrices. Spatial effects significantly influenced house prices in both cases but the intensity of the former was weaker than for the latter. Income, proportion of the tertiary industry, and amenity exhibited significant indirect effects on house prices in other cities in the inner region of the agglomeration, while competition of population between cities with economic proximity exerted negative indirect effects. Furthermore, urban industrial structure, innovation capability, and urbanization degree revealed differences in terms of spatial dependence among various city groups.


2008 ◽  
Vol 17 (2) ◽  
pp. 191-200 ◽  
Author(s):  
Norman H. Sedgley ◽  
Nancy A. Williams ◽  
Frederick W. Derrick

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