Two-Stage Spatial Hedonic Model on Newly Built Condominiums in the Tokyo Housing Market

2014 ◽  
Author(s):  
Takahisa Yokoi ◽  
Haruhisa Ishizuka
Keyword(s):  
Housing Market ◽  
Hedonic Model ◽  
Two Stage ◽  
Spatial Hedonic Model

scholarly journals A Priori Spatial Segmentation of Commercial Property Market using Hedonic Price Modelling

2021 ◽  
Vol 29 (2) ◽  
pp. 16-28
Author(s):  
Hamza Usman ◽  
Mohd Lizam ◽  
Burhaida Burhan
Keyword(s):  
Housing Market ◽  
Market Segmentation ◽  
A Priori ◽  
Model Fit ◽  
Hedonic Model ◽  
Hedonic Price ◽  
Property Market ◽  
Commercial Property ◽  
Spatial Segmentation ◽  
Property Price

Abstract The improvement of property price modelling accuracy using property market segmentation approaches is well documented in the housing market. However, that cannot be said of the commercial property market which is adjudged to be volatile, heterogeneous and thinly traded. This study, therefore, determines if the commercial property market in Malaysia is spatially segmented into submarkets and whether accounting for the submarkets improves the accuracy of price modelling. Using a 11,460 shop-offices transaction dataset, the commercial property submarkets are delineated by using submarket binary dummies in the market-wide model and estimating a separate hedonic model for each submarket. The former method improves the model fit and reduces error by 5.6% and 6.5% respectively. The commercial property submarkets are better delineated by estimating a separate hedonic model for each submarket as it improves the model fit by about 7% and reduces models’ error by more than 10%. This study concludes that the Malaysian commercial property market is spatially segmented into submarkets. Modelling the submarkets improves the accuracy and correctness of price modelling.

Analysis of housing prices in Petaling district, Malaysia using functional relationship model

2019 ◽  
Vol 12 (5) ◽  
pp. 884-905
Author(s):  
Yun Fah Chang ◽  
Wei Cheng Choong ◽  
Sing Yan Looi ◽  
Wei Yeing Pan ◽  
Hong Lip Goh
Keyword(s):  
Housing Market ◽  
Functional Relationship ◽  
Housing Prices ◽  
Hedonic Model ◽  
Analysis Tool ◽  
Content Type ◽  
Proposed Model ◽  
Relationship Model ◽  
Housing Attributes ◽  
House Buyers

Purpose The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model. Design/methodology/approach A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes. Findings The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kembangan are more valuable. From the h-nearest houses indicator, it is concluded that the housing market in Sungai Buloh is the most volatile in Petaling District. Research limitations/implications As the data used are the actual housing transaction records in Petaling District, it represents only a segment of Malaysian urban population. The result will not be generalized to the entire Malaysian population. Practical implications This study is expected to provide insights to policymakers, property developers and investors to understand the volatility of the housing market and the influence of determinants in different sub-regions. The potential house buyers could also use the model to determine if a house is overpriced. Originality/value This study introduces measurement errors into the housing attributes to provide a more reliable analysis tool for the housing market. This study is the first housing research in Malaysia that used a large number of actual housing transaction records. Previous studies relied on small survey samples.

scholarly journals Measuring the value of air quality: application of the spatial hedonic model

2009 ◽  
Vol 3 (1) ◽  
pp. 41-51 ◽  
Author(s):  
Seung Gyu Kim ◽  
Seong-Hoon Cho ◽  
Dayton M. Lambert ◽  
Roland K. Roberts
Keyword(s):  
Air Quality ◽  
Hedonic Model ◽  
Spatial Hedonic Model

scholarly journals A hedonic model of the association between grocery brand provision and residential rental prices in England

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stephen Clark ◽  
Nick Hood ◽  
Mark Birkin
Keyword(s):  
Housing Market ◽  
Consumer Choice ◽  
Service Provision ◽  
Hedonic Model ◽  
Property Market ◽  
Content Type ◽  
Highly Sensitive ◽  
Data Source ◽  
Retail Grocery ◽  
Web Platform

Purpose This study aims to measure the association between local retail grocery provision and private residential rental prices in England. Renting is an important sector of the housing market in England and local grocery provision is an important aspect of service provision and consumers are known to be highly sensitive to the branding of this type of retailing. Design/methodology/approach This research uses a novel data source from a property rental Web platform to estimate a hedonic model for the rental market. These models incorporate information on the nature of the properties and their neighbourhoods, with an emphasis on how different retail brands are associated with rental prices. This retail brand is captured on two scales: the provision of local branded convenience stores and the provision of larger stores. Findings The study finds clear differentials in how the local grocery brand is associated with rental prices. When controlling for commonly explored confounding factors, “Luxury” retailers such as Waitrose and Marks and Spencer are associated with higher rental prices, while “Discounter” retailers are associated with lower rental prices. This finding has many implications, particularly in relation to potential price changes in an already challenging housing market for many people. Research limitations/implications This is an observational study and as such only associations (not causation) can be implied by these findings. Originality/value The focus of this research is on the private residential property market, an important market in England but one that has enjoyed less scrutiny than the sales or socially rented markets. Rather than using general accessibility to retail, this research has differentiated the association by the retail brand and store size, two very important aspects of consumer choice.

scholarly journals Realizing the Economic Value of a Forested Landscape in a Viewshed

2010 ◽  
Vol 34 (2) ◽  
pp. 72-78 ◽  
Author(s):  
Neelam C. Poudyal ◽  
Donald G. Hodges ◽  
John Fenderson ◽  
Ward Tarkington
Keyword(s):  
Economic Value ◽  
House Price ◽  
Housing Price ◽  
Nonmarket Valuation ◽  
Forest Area ◽  
Hedonic Model ◽  
Residential Housing ◽  
Davidson County ◽  
Spatial Hedonic Model ◽  
Forested Landscapes

Abstract Existing literature on nonmarket valuation indicates an ambiguous value of the view of a forest due largely to the fact that these studies relied on inappropriate proxies or poor measures of forest view. The current study attempts to fill this gap by using GIS to measure the actual forest area that is visible from a house and then using a hedonic regression model to examine how its value is reflected in residential housing price. A spatial hedonic model of residential housing price was applied to housing sales data in a forested landscape located in the southeastern portion of Cheatham County and the adjacent Scottsboro-Bells Bend area of Davidson County, near Nashville, Tennessee. Results indicate that increasing the size of forest area visible from a house by 1 ac increased the house price by $30. The findings imply that residents place a significant value on and likely pay a price premium to preserve the view of a forest. Findings from this study could be useful in evaluating viewshed protection policies as a hedge against development pressures that threaten the forested landscapes and in designing market protocols for scenic view as an ecosystem service.

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