Analysing the local geography of the relationship between residential property prices and its determinants
This paper analyses the local geography of the relationship between residential property prices and its determinants. A semiparametric geographically weighted regression (S-GWR) technique is employed to explore this relationship. Selling prices, structural and locational attributes data were collect...
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Online Access: | https://doi.org/10.1515/bog-2015-0013 |
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doaj-9fc09f884c8646b0a0d4078c80f87fa42021-09-05T20:42:37ZengSciendoBulletin of Geography: Socio-Economic Series2083-82982015-06-012828213510.1515/bog-2015-0013Analysing the local geography of the relationship between residential property prices and its determinantsDziauddin Mohd Faris0Ismail Kamarul1Othman Zainudin2Sultan Idris Education University, Department of Geography and Environment, Faculty of Human Sciences, 35900 Tanjong Malim, Perak, MalaysiaSultan Idris Education University, Department of Geography and Environment, Faculty of Human Sciences, 35900 Tanjong Malim, Perak, MalaysiaSultan Idris Education University, Department of Geography and Environment, Faculty of Human Sciences, 35900 Tanjong Malim, Perak, MalaysiaThis paper analyses the local geography of the relationship between residential property prices and its determinants. A semiparametric geographically weighted regression (S-GWR) technique is employed to explore this relationship. Selling prices, structural and locational attributes data were collected from the database of the Department of Valuation and Services of Malaysia, selected maps and reports. The outcome of this paper shows a strong geographically varying relationship between residential property prices and its determinants in which the residential property price determinants have a positive impact on prices in some areas but negative or no impact on the others. The magnitude of the effect is also found to be geographically varied; the capitalisation in residential property prices is found greater in some areas but less or with no effect in some other parts of the areas. The use of S-GWR technique makes it possible to reveal such geographically varying relationships, thus leading to a better understanding of the relationship between residential property prices and its determinants.https://doi.org/10.1515/bog-2015-0013house pricessemiparametric geographically weighted regression (s-gwr)structural attributeslocation attributestanjong malim |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dziauddin Mohd Faris Ismail Kamarul Othman Zainudin |
spellingShingle |
Dziauddin Mohd Faris Ismail Kamarul Othman Zainudin Analysing the local geography of the relationship between residential property prices and its determinants Bulletin of Geography: Socio-Economic Series house prices semiparametric geographically weighted regression (s-gwr) structural attributes location attributes tanjong malim |
author_facet |
Dziauddin Mohd Faris Ismail Kamarul Othman Zainudin |
author_sort |
Dziauddin Mohd Faris |
title |
Analysing the local geography of the relationship between residential property prices and its determinants |
title_short |
Analysing the local geography of the relationship between residential property prices and its determinants |
title_full |
Analysing the local geography of the relationship between residential property prices and its determinants |
title_fullStr |
Analysing the local geography of the relationship between residential property prices and its determinants |
title_full_unstemmed |
Analysing the local geography of the relationship between residential property prices and its determinants |
title_sort |
analysing the local geography of the relationship between residential property prices and its determinants |
publisher |
Sciendo |
series |
Bulletin of Geography: Socio-Economic Series |
issn |
2083-8298 |
publishDate |
2015-06-01 |
description |
This paper analyses the local geography of the relationship between residential property prices and its determinants. A semiparametric geographically weighted regression (S-GWR) technique is employed to explore this relationship. Selling prices, structural and locational attributes data were collected from the database of the Department of Valuation and Services of Malaysia, selected maps and reports. The outcome of this paper shows a strong geographically varying relationship between residential property prices and its determinants in which the residential property price determinants have a positive impact on prices in some areas but negative or no impact on the others. The magnitude of the effect is also found to be geographically varied; the capitalisation in residential property prices is found greater in some areas but less or with no effect in some other parts of the areas. The use of S-GWR technique makes it possible to reveal such geographically varying relationships, thus leading to a better understanding of the relationship between residential property prices and its determinants. |
topic |
house prices semiparametric geographically weighted regression (s-gwr) structural attributes location attributes tanjong malim |
url |
https://doi.org/10.1515/bog-2015-0013 |
work_keys_str_mv |
AT dziauddinmohdfaris analysingthelocalgeographyoftherelationshipbetweenresidentialpropertypricesanditsdeterminants AT ismailkamarul analysingthelocalgeographyoftherelationshipbetweenresidentialpropertypricesanditsdeterminants AT othmanzainudin analysingthelocalgeographyoftherelationshipbetweenresidentialpropertypricesanditsdeterminants |
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