A Causal Model of Residential Housing Prices in Hong Kong

Ge, J; Runeson, G; Lam, K

A Causal Model of Residential Housing Prices in Hong Kong

Ge, J

Runeson, G Lam, K

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Publisher:: China Architecture & Building Press
Publication Type:: Conference Proceeding
Citation:: Proceedings of 2003 International Conference on Construction & Real Estate Management, 2003, NA pp. 99 - 101
Issue Date:: 2003-01

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Field	Value	Language
dc.contributor.author	Ge, J https://orcid.org/0000-0002-2252-7829	en_US
dc.contributor.author	Runeson, G	en_US
dc.contributor.author	Lam, K	en_US
dc.contributor.editor	Wang, Y	en_US
dc.contributor.editor	Li, L	en_US
dc.date	2003-11-20	en_US
dc.date.issued	2003-01	en_US
dc.identifier.citation	Proceedings of 2003 International Conference on Construction & Real Estate Management, 2003, NA pp. 99 - 101	en_US
dc.identifier.isbn	7-112-02100-6	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11283
dc.description.abstract	The traditional multiple regression analysis is widely acknowledged as a reliable technique and acceptable forecasting performance. This study examines the role of population growth, household income, and transaction volume in determining residential housing prices. A causal model is developed for Hong Kong using quarterly aggregated economic variables for the period of 1980:1 to 2000:3. In order to assess the adequacy of the multiple regression analysis to housing prices forecasting, the model is evaluated on its predictive accuracy on out-of-sample forecasts for the period of 2000:4 to 2002:4. It is found that the housing prices behavior of the current period is affected by the events of previous periods. The results also show that the causal model has a good predictive power and can explain the causal relationships between variables.	en_US
dc.publisher	China Architecture & Building Press	en_US
dc.relation.ispartof	Proceedings of 2003 International Conference on Construction & Real Estate Management	en_US
dc.relation.ispartof	International Conference on Construction and Real Estate Management	en_US
dc.title	A Causal Model of Residential Housing Prices in Hong Kong	en_US
dc.type	Conference Proceeding
utslib.citation.volume	NA	en_US
utslib.location	Beijing, China	en_US
utslib.location.activity	Harbin, P.R. China	en_US
utslib.for	1202 Building	en_US
dc.location.activity	Harbin, P.R. China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/e-Press
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Built Environment
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.place-of-publication	Beijing, China	en_US
pubs.start-date	2003-11-20	en_US
pubs.volume	NA	en_US

Abstract:

The traditional multiple regression analysis is widely acknowledged as a reliable technique and acceptable forecasting performance. This study examines the role of population growth, household income, and transaction volume in determining residential housing prices. A causal model is developed for Hong Kong using quarterly aggregated economic variables for the period of 1980:1 to 2000:3. In order to assess the adequacy of the multiple regression analysis to housing prices forecasting, the model is evaluated on its predictive accuracy on out-of-sample forecasts for the period of 2000:4 to 2002:4. It is found that the housing prices behavior of the current period is affected by the events of previous periods. The results also show that the causal model has a good predictive power and can explain the causal relationships between variables.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/11283