Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices

Wong, Siu Kei; Yiu, CY; Chau, Kwong Wing

doi:10.1007/s11146-012-9375-y

Cited by 23 publications

(9 citation statements)

References 31 publications

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“…Spatial autocorrelation (or spatial dependence) always exists in the real estate market [46]. Related explanations include but are not limited to spatial externality, external force, and spatial interaction [47,48]. Ignoring the presence of spatial autocorrelation would lead to biased and inconsistent parameter estimates.…”

Section: Methodsmentioning

confidence: 99%

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

2020

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Understanding the relationship between tourism demand and retail property prices is of great significance to tourist destinations, especially shopping destinations. The increase in tourism demand may alter the implicit prices of certain retail property characteristics (e.g., age and accessibility to transit). This study examines how tourism demand (measured by tourist volume) affects retail property prices in the tourist precinct of a shopping destination, namely Hong Kong. The implementation of the policy Individual Visit Scheme (IVS) in 2003 in Hong Kong has substantially increased tourist shoppers from Mainland China, and it is used as a quasi-natural experiment of the increased tourist volume. Spatial and non-spatial hedonic pricing models are developed based on the ground-floor retail property transaction data of Causeway Bay, Hong Kong before and after the IVS (1993–2011). The findings of this study are as follows. (1) Accessibility to transit has a larger positive price effect after the implementation of the IVS. (2) The implicit price of accessibility to accommodation facilities is not significantly altered by the implementation of the IVS. (3) Age has a larger negative price effect after the implementation of the IVS. The first two outcomes are related to the economic concerns of tourist shoppers, while the last can be explained by their hometown experience. Finally, practical implications are discussed.

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Section: Methodsmentioning

confidence: 99%

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

2020

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“…We follow the process ofWong et al (2013) which used spatial lag to determine spatial autocorrelation. For a full discussion see: Wong, S. K., C. Y.…”

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confidence: 99%

Examining the spatial relationship between environmental health factors and house prices

McCord

MacIntyre

Bidanset³

et al. 2018

JERER

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Purpose Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place. Design/methodology/approach A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM). Findings The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source. Originality/value Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

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“…Hence, there should be a functional inter-relationship between the sales price of the subject dwelling and the prior transaction prices of other dwellings within its neighbourhood. In practice, these price effects are acknowledged and injected by the traders and valuers in the property market through “the comparable-sales” valuation method to estimate real estate prices (Can, 1992) and Wong et al (2013)). Indeed, spatial lag hedonic modelling techniques have been extensively used in the literature to investigate real estate issues and problems.…”

Section: Methodology and Development Of Empirical Modelsmentioning

confidence: 99%

Information transparency and pricing strategy in the Scottish housing market

Lo¹,

Liu

McCord³

et al. 2021

IJHMA

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Purpose Information transparency is crucially important in price setting in real estate, particularly when information asymmetry is concerned. This paper aims to examine how a change in government policy in relation to information disclosure and transparency impacts residential real estate price discovery. Specially, this paper investigates how real estate traders determined asking prices in the context of the Scottish housing market before and after the implementation of the Home Report, which aimed to prevent artificially low asking prices. Design/methodology/approach This paper uses spatial lag hedonic pricing models to empirically observe how residential asking prices are determined by property sellers in response to a change in government policy that is designed to enhance market transparency. It uses over 79,000 transaction data of the Aberdeen residential market for the period of Q2 1998 to Q2 2013 to test the models. Findings The empirical findings provide some novel insights in relation to the price determination within the residential market in Scotland. The spatial lag models suggest that spatial autocorrelation in property prices has increased since the Home Report came into effect, indicating that property sellers have become more prone to infer asking prices based on prior sales of dwellings in close vicinity. The once-common practice of setting artificially low asking prices seems to have dwindled to a certain extent statistically. Originality/value The importance of understanding the relationship between information transparency and property price determination has gathered momentum over the past decade. Although spatial hedonic techniques have been extensively used to study the impact of various property- and neighbourhood-specific attributes on residential real estate market in general, surprisingly little is known about the empirical relationship between spatial autocorrelation in real estate prices and information transparency.

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Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices

Cited by 23 publications

References 31 publications

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

Examining the spatial relationship between environmental health factors and house prices

Information transparency and pricing strategy in the Scottish housing market

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