Development of price models for architectural and environmental quality for residential developments in Hong Kong

Abstract

a b s t r a c tFactors affecting a residential unit's price are always of interest to homebuyers and building developers, especially in a city like Hong Kong which is known for expensive housing. Literature review indicates that the governing factors can be categorized into architectural and environmental attributes. Among different methods commonly used for pricing, the hedonic price approach is viewed as the most suitable. However, the successful use of this method requires that homebuyers know and choose the attributes. Whilst choosing architectural attributes are not a problem for homebuyers, the same does not apply to environmental attributes. Previous studies by the authors have proposed some simple indicators for quantifying the environmental attributes. Based upon the developed performance indicators and the transaction records of two representative housing estates (Royal Ascot ¼ RA and City One Shatin ¼ COS), details of the properties, including transaction prices, architectural particulars and environmental characteristics were numerically transformed for the hedonic price analysis. The analysis results revealed that the willingness to pay (percentage of house price in parenthesis) for architectural and environmental attributes was HK$302.3/ft 2 (5.8%) and HK$886.8/ft 2 (28.2%), respectively, for RA and HK$1672.7/ ft 2 (31.9%) and HK$111.5/ft 2 (3.5%) for COS. It was found that elasticity of substitution (ES) of environmental attributes contributed 3.4e13.3% of the property price, compared to 0.6e5.5% for architectural attributes.

Estimating the Cost and Payment for Sanitation in the Informal Settlements of Kisumu, Kenya: A Cross Sectional Study

“…The relationship described in Equation (1), between the price and the attributes, is a linear model; although it can take other forms such as the semi-log, double log, quadratic, and box cox models [ 21 , 39 , 43 ]. The linear model, just like the normal linear regression model, assumes that the relationship between the dependent variable (house price or rent) and the other independent variables is linear.…”

“…Drawing from environmental economics, it is possible to estimate the cost of goods and services through information given by respondents about their preferences (stated preference), or through observation of behaviour (revealed preference). Stated preference methods have faced several critiques, including challenges of reliability and validity [ 14 , 15 , 16 , 17 , 18 , 19 , 20 ], since they are not based on what people actually do [ 21 ]. In addition, due to the hypothetical nature of most willingness to pay studies, it is argued that respondents may be ignorant, uncertain or unable to make a trade-off on the good or service [ 16 , 22 , 23 ].…”

Comparing the Impacts of Location Attributes on Residents’ Preferences and Residential Values in Compact Cities: A Case Study of Hong Kong

“…The hedonic price model is commonly used to show the relationship between residential property values and housing characteristics [19]. It assumes that people value the characteristics of a good or the services it provides rather than the good itself [38].…”

“…where P i is the recent sales or rental price of the ith observation, β is the regression coefficient, and X n includes the nth explanatory variables, such as plot size, household, income, age, living environment, proximity to public transport facilities, and other facilities. The semi-log form of the hedonic price model has been commonly used to relate the housing price and each constituent variable in recent literature [19,53,54]. The estimated semi-log hedonic price model allows an easy interpretation of coefficients [43].…”

“…Property economic conditions play significant roles in the increase in property prices [16,17]. Housing values are also significantly influenced by government town planning policies, land supply, and the tax system [18,19]. Extensive literature has focused on residential mobility and housing prices in low density and automobile commuting cities [12,20,21], but authors experienced limitations in capturing residents' demands in high-density and compact cities like Hong Kong. From a demand-side perspective, we developed the reliability interval method (RIM) to establish the residential attitude metrics (RAM), which indicate residents' needs in a neighborhood in compact cities.…”