Determinants of House Price: A Decision Tree Approach

The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However, this approach is subject to criticisms arising from potential problems relating to fundamental model assumptions and estimation such as the i...

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Published inUrban studies (Edinburgh, Scotland) Vol. 43; no. 12; pp. 2301 - 2315
Main Authors Fan, Gang-Zhi, Ong, Seow Eng, Koh, Hian Chye
Format Journal Article
LanguageEnglish
Published London, England Routledge Journal, Taylor & Francis Ltd 01.11.2006
SAGE Publications
Sage Publications Ltd
Subjects
Online AccessGet full text
ISSN0042-0980
1360-063X
1360-063X
DOI10.1080/00420980600990928

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Abstract The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However, this approach is subject to criticisms arising from potential problems relating to fundamental model assumptions and estimation such as the identification of supply and demand, market disequilibrium, the selection of independent variables, the choice of functional form of hedonic equation and market segmentation. This study introduces and utilises an alternative approach—the decision tree approach, which is an important statistical pattern recognition tool. Using the Singapore resale public housing market as a case study, the article demonstrates the usefulness of this technique in examining the relationship between house prices and housing characteristics, identifying the significant determinants of housing prices and predicting housing prices. The built tree shows that homebuyers are more concerned about the basic housing characteristics of two-and threeroom flats or four-room flats such as floor area, model type and flat age. However, homebuyers of five-room flats pay more attention to floor level in addition to the basic housing characteristics. In addition, homebuyers of executive apartments are less concerned about basic quantitative characteristics and have higher housing consumption expectations and pay more attention to 'quality' and service characteristics such as recreational facilities and the living environment.
AbstractList The hedonic-based regression approach has been utilised extensively to investigate th relationship between house prices and housing characteristics. However, this approach is subject t criticisms arising from potential problems relating to fundamental model assumptions an estimation such as the identification of supply and demand, market disequilibrium, the selectio of independent variables, the choice of functional form of hedonic equation and marke segmentation. This study introduces and utilises an alternative approach-the decision tre approach, which is an important statistical pattern recognition tool. Using the Singapore resal public housing market as a case study, the article demonstrates the usefulness of this techniqu in examining the relationship between house prices and housing characteristics, identifying th significant determinants of housing prices and predicting housing prices. The built tree show that homebuyers are more concerned about the basic housing characteristics of two- and three room flats or four-room flats such as floor area, model type and flat age. However, homebuyer of five-room flats pay more attention to floor level in addition to the basic housin characteristics. In addition, homebuyers of executive apartments are less concerned about basi quantitative characteristics and have higher housing consumption expectations and pay mor attention to 'quality' and service characteristics such as recreational facilities and the livin environment.
The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However, this approach is subject to criticisms arising from potential problems relating to fundamental model assumptions and estimation such as the identification of supply and demand, market disequilibrium, the selection of independent variables, the choice of functional form of hedonic equation and market segmentation. This study introduces and utilises an alternative approach—the decision tree approach, which is an important statistical pattern recognition tool. Using the Singapore resale public housing market as a case study, the article demonstrates the usefulness of this technique in examining the relationship between house prices and housing characteristics, identifying the significant determinants of housing prices and predicting housing prices. The built tree shows that homebuyers are more concerned about the basic housing characteristics of two-and threeroom flats or four-room flats such as floor area, model type and flat age. However, homebuyers of five-room flats pay more attention to floor level in addition to the basic housing characteristics. In addition, homebuyers of executive apartments are less concerned about basic quantitative characteristics and have higher housing consumption expectations and pay more attention to 'quality' and service characteristics such as recreational facilities and the living environment.
The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However, this approach is subject to criticisms arising from potential problems relating to fundamental model assumptions and estimation such as the identification of supply and demand, market disequilibrium, the selection of independent variables, the choice of functional form of hedonic equation and market segmentation. This study introduces and utilises an alternative approach-the decision tree approach, which is an important statistical pattern recognition tool. Using the Singapore resale public housing market as a case study, the article demonstrates the usefulness of this technique in examining the relationship between house prices and housing characteristics, identifying the significant determinants of housing prices and predicting housing prices. The built tree shows that homebuyers are more concerned about the basic housing characteristics of two- and three-room flats or four-room flats such as floor area, model type and flat age. However, homebuyers of five-room flats pay more attention to floor level in addition to the basic housing characteristics. In addition, homebuyers of executive apartments are less concerned about basic quantitative characteristics and have higher housing consumption expectations and pay more attention to 'quality' and service characteristics such as recreational facilities and the living environment. Reprinted by permission of Sage Publications
The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However, this approach is subject to criticisms arising from potential problems relating to fundamental model assumptions and estimation such as the identification of supply and demand, market disequilibrium, the selection of independent variables, the choice of functional form of hedonic equation and market segmentation. This study introduces and utilises an alternative approach - the decision tree approach, which is an important statistical pattern recognition tool. Using the Singapore resale public housing market as a case study, the article demonstrates the usefulness of this technique in examining the relationship between house prices and housing characteristics, identifying the significant determinants of housing prices and predicting housing prices. The built tree shows that homebuyers are more concerned about the basic housing characteristics of two- and three-room flats or four-room flats such as floor area, model type and flat age. However, homebuyers of five-room flats pay more attention to floor level in addition to the basic housing characteristics. In addition, homebuyers of executive apartments are less concerned about basic quantitative characteristics and have higher housing consumption expectations and pay more attention to 'quality' and service characteristics such as recreational facilities and the living environment. [PUBLICATION ABSTRACT]
Author Ong, Seow Eng
Koh, Hian Chye
Fan, Gang-Zhi
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Snippet The hedonic-based regression approach has been utilised extensively to investigate the relationship between house prices and housing characteristics. However,...
The hedonic-based regression approach has been utilised extensively to investigate th relationship between house prices and housing characteristics. However,...
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SubjectTerms Alternative approaches
Apartments
Attention
Case studies
Datasets
Decision making
Decision models
Decision trees
Disequilibrium
Home buyers
Homebuyers
Housing
Housing authorities
Housing costs
Housing market
Housing prices
Market prices
Market segmentation
Modeling
Parks & recreation areas
Pattern recognition
Prices
Public housing
Quality standards
Real estate appraisal
Regression analysis
Resale
Resident satisfaction
Residential patterns
Social conditions
Statistical analysis
Supply & demand
Usefulness
Variables
Title Determinants of House Price: A Decision Tree Approach
URI https://www.jstor.org/stable/43198334
https://journals.sagepub.com/doi/full/10.1080/00420980600990928
https://www.proquest.com/docview/236312841
https://www.proquest.com/docview/36539578
http://scholarbank.nus.edu.sg/handle/10635/46117
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