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.
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.
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.
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.
Neighbourhood-level HPI is needed for a better understanding of the local housing market.
Sipan, I., Mar Iman, A. and Razali, M. (2018), "Spatial–temporal neighbourhood-level house price index", International Journal of Housing Markets and Analysis, Vol. 11 No. 2, pp. 386-411. https://doi.org/10.1108/IJHMA-03-2017-0027Download as .RIS
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