Spatial-temporal neighbourhood-level house price index

Purpose – The purpose of this study is to develop a spatio-temporal neighbourhood-level house price index (STNL-HPI) incorporating a geographic information system (GIS) functionality that can be used to improve the house price indexation system. Design/methodology/approach – By using the Malaysian h...

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主要な著者: Sipan, Ibrahim, Mar Iman, Abdul Hamid, Razali, Muhammad Najib
フォーマット: Indexed Article
言語:English
出版事項: 2018
オンライン・アクセス:http://discol.umk.edu.my/id/eprint/7401/1/Spatial%E2%80%93temporal%20neighbourhoodlevel%20house%20price%20index.pdf
http://discol.umk.edu.my/id/eprint/7401/
https://www.emerald.com/insight/content/doi/10.1108/IJHMA-03-2017-0027/full/html
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spelling my.umk.eprints.74012022-05-23T10:16:52Z http://discol.umk.edu.my/id/eprint/7401/ Spatial-temporal neighbourhood-level house price index Sipan, Ibrahim Mar Iman, Abdul Hamid Razali, Muhammad Najib Purpose – The purpose of this study is to develop a spatio-temporal neighbourhood-level house price index (STNL-HPI) incorporating a geographic information system (GIS) functionality that can be used to improve the house price indexation system. Design/methodology/approach – By using the Malaysian house price index (MHPI) and application of geographically weighted regression (GWR), GIS-based analysis of STNL-HPI through an application called LHPI Viewer v.1.0.0, the stand-alone GIS-statistical application for STNL-HPI was successfully developed in this study. Findings – The overall results have shown that the modelling and GIS application were able to help users understand the visual variation of house prices across a particular neighbourhood. Research limitations/implications – This research was only able to acquire data from the federal government over the period 1999 to 2006 because of budget limitations. Data purchase was extremely costly. Because of financial constraints, data with lower levels of accuracy have been obtained from other sources. As a consequence, a major portion of data was mismatched because of the absence of a common parcel identifier, which also affected the comparison of this system to other comparable systems. Originality/value – Neighbourhood-level HPI is needed for a better understanding of the local housing market. 2018 Indexed Article NonPeerReviewed text en http://discol.umk.edu.my/id/eprint/7401/1/Spatial%E2%80%93temporal%20neighbourhoodlevel%20house%20price%20index.pdf Sipan, Ibrahim and Mar Iman, Abdul Hamid and Razali, Muhammad Najib (2018) Spatial-temporal neighbourhood-level house price index. International Journal of Housing Markets and Analysis, 11 (2). pp. 386-411. ISSN 1753-8270 https://www.emerald.com/insight/content/doi/10.1108/IJHMA-03-2017-0027/full/html
institution Universiti Malaysia Kelantan
building Perpustakaan Universiti Malaysia Kelantan
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Kelantan
content_source UMK Institutional Repository
url_provider http://umkeprints.umk.edu.my/
language English
description Purpose – The purpose of this study is to develop a spatio-temporal neighbourhood-level house price index (STNL-HPI) incorporating a geographic information system (GIS) functionality that can be used to improve the house price indexation system. Design/methodology/approach – By using the Malaysian house price index (MHPI) and application of geographically weighted regression (GWR), GIS-based analysis of STNL-HPI through an application called LHPI Viewer v.1.0.0, the stand-alone GIS-statistical application for STNL-HPI was successfully developed in this study. Findings – The overall results have shown that the modelling and GIS application were able to help users understand the visual variation of house prices across a particular neighbourhood. Research limitations/implications – This research was only able to acquire data from the federal government over the period 1999 to 2006 because of budget limitations. Data purchase was extremely costly. Because of financial constraints, data with lower levels of accuracy have been obtained from other sources. As a consequence, a major portion of data was mismatched because of the absence of a common parcel identifier, which also affected the comparison of this system to other comparable systems. Originality/value – Neighbourhood-level HPI is needed for a better understanding of the local housing market.
format Indexed Article
author Sipan, Ibrahim
Mar Iman, Abdul Hamid
Razali, Muhammad Najib
spellingShingle Sipan, Ibrahim
Mar Iman, Abdul Hamid
Razali, Muhammad Najib
Spatial-temporal neighbourhood-level house price index
author_facet Sipan, Ibrahim
Mar Iman, Abdul Hamid
Razali, Muhammad Najib
author_sort Sipan, Ibrahim
title Spatial-temporal neighbourhood-level house price index
title_short Spatial-temporal neighbourhood-level house price index
title_full Spatial-temporal neighbourhood-level house price index
title_fullStr Spatial-temporal neighbourhood-level house price index
title_full_unstemmed Spatial-temporal neighbourhood-level house price index
title_sort spatial-temporal neighbourhood-level house price index
publishDate 2018
url http://discol.umk.edu.my/id/eprint/7401/1/Spatial%E2%80%93temporal%20neighbourhoodlevel%20house%20price%20index.pdf
http://discol.umk.edu.my/id/eprint/7401/
https://www.emerald.com/insight/content/doi/10.1108/IJHMA-03-2017-0027/full/html
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