Spatial–temporal neighbourhood-level house price index

Sipan, Ibrahim; Iman, Abdul Hamid Mar; Razali, Muhammad Najib

doi:10.1108/ijhma-03-2017-0027

Cited by 4 publications

(5 citation statements)

References 43 publications

(39 reference statements)

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“…Apart from that, the land size shows a positive coefficient because investors or buyers are willing to pay a higher price to occupy a larger space in accordance with the theory of economic utility. The geocoded variables (latitude and longitude) are significant, which agrees with the past studies (Clapp 2004;Nappi-Choulet and Maury 2009;Helbich et al 2013;Sipan et al 2018). Therefore, the existence of price variability of heritage properties at the local level is proved to be significant in this study.…”

Section: Resultssupporting

confidence: 91%

“…It gives the quality-adjusted price change between the base period 0 and each comparison period t. The HTDRM also integrates with the coordinates of the property (latitude and longitude) in order to capture the variability of the property price due to the location (Clapp 2004). There are a few studies that indicate the significant relationship between spatial heterogeneity and property price (Nappi-Choulet and Maury 2009;Helbich et al 2013;Sipan et al 2018). Therefore, the incorporation of geocoded locations in the price index model could resolve the issue of geographical differences in property price movement at the local level.…”

Section: Methodsmentioning

confidence: 99%

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Revisiting Investability of Heritage Properties through Indexation and Portfolio Frontier Analysis

Cheng

Ling

Gan

et al. 2021

Risks

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In recent years, the soaring prices of heritage properties in Georgetown, Penang have gained the attention of practitioners and investors. The practitioners claim that the prices of heritage properties within the core and buffer zones in Georgetown have increased more than 300% since the city was recognized as a UNESCO World Heritage site in 2008. Such heritage properties containing historical or art elements that lead to forming a diversified portfolio could exert a low correlation of returns with conventional assets. In addition, rehabilitation of heritage properties requires high restoration costs and conversion fees. Despite the above claims, there is an absence of empirical studies relating to heritage investability, particularly to prove whether the heritage properties are truly worth investing in. Thus, this study incorporates a self-developed heritage properties Index (PIHPI_HR) into the conventional investment portfolio for assessing diversification effects. This study has collected 853 units of transacted properties for constructing a 10-year price index (PIHPI_HR). Subsequently, its diversification effect was examined through the Efficient Frontier (EF), derived from the Modern Portfolio Theory (MPT). The findings have proven the optimization of the conventional portfolio by enabling investments in heritage properties where the return is higher than other investment assets at the same risk level. This study also unveiled the price movement of heritage properties together with their investment value, which is deemed to be useful for institutional investors and the public to formulate sustainable investment strategies in the future.

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Section: Resultssupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Revisiting Investability of Heritage Properties through Indexation and Portfolio Frontier Analysis

Cheng

Ling

Gan

et al. 2021

Risks

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“…This has facilitated the availability of crucial market information to stakeholders such as planners and property developers and other policy makers in the property industry (Hacievliyagil et al , 2022). Many of these studies have taken into account proximity and spatial effects (Song et al , 2022; Peng, 2020; Sipan et al , 2018). This is because house prices usually have a relationship to spatial issues (Ismail et al , 2021).…”

Section: Introductionmentioning

confidence: 99%

“…There is no developed house price index, although recent research has shown that the market is not random and that there is a possibility to have such an index in place (Nyanda and Muyingo, 2023). Because of the relative importance of proximity and spatial effects to house prices (Ismail et al , 2021; Sipan et al , 2018), it is best that such effects are tested to decide whether they should or should not be included in the hedonic pricing model, which in this case would be the basis for creating a house price index for Dar es Salaam (Nyanda and Muyingo, 2023).…”

Section: Introductionmentioning

confidence: 99%

“…The aim of this study is thus to examine the effect of proximity and spatial dependence on the hedonic house price model and, most importantly, the resulting house price index. This is important because the hedonic index is created after the hedonic model, and experience has shown that spatial effects may or may not be significant for the index (Sipan et al , 2018; Wilhelmsson, 2002; Ayse and Isaac, 1997). Should the spatial effects be significant and ignored, the resulting index could be under-presented and misleading.…”

Section: Introductionmentioning

confidence: 99%

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The effect of proximity and spatial dependence on the house price index for Dar es Salaam

Nyanda

2023

IJHMA

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Purpose This study aims to examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations. Design/methodology/approach Using the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence. Findings The inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market. Originality/value The paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

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