Consumption preferences and environmental externalities: A hedonic analysis of the housing market in Guangzhou

Geoforum 38 (2007) 414–431 www.elsevier.com/locate/geoforum

Consumption preferences and environmental externalities: A hedonic analysis of the housing market in Guangzhou C.Y. Jim *, Wendy Y. Chen Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong Received 3 March 2006; received in revised form 25 September 2006

Abstract The urban housing market of China has been transformed since the 1980s from a centrally-planned to a free-market system. This study aimed to (1) investigate the position of outdoor environmental quality in house-buyers’ preferences; (2) assess monetary values attributed to environmental externalities by the hedonic pricing method (HPM); and (3) test the applicability of HPM in China. The study area was Guangzhou, the major city of south China with a booming real-estate market. A questionnaire survey was conducted with households in new residences sold in 2004. The main buying motives were improving living quarters and floor area. Security concerns and a preference for high-rise buildings were somewhat unexpected. Good outdoor environment, including green space provision, proximity to parks, and views of green space and water, carried significant hedonic values. Differences between the submarkets of old and new towns were found; new town households expected apartments in high-rise blocks, exclusive residential land use, and views of green space, while old town households preferred proximity to shopping areas and workplaces, green space within the development and proximity to nearby parks. The findings could help to fine tune the developing housing market to match supply with demand in quality terms. Values accorded to environmental attributes could justify funding for urban green spaces and nature conservation. The study verified the applicability of HPM to the housing context in China.  2006 Elsevier Ltd. All rights reserved. Keywords: Compact city; Consumption preference; Hedonic pricing method; Environmental externalities; Green space; Housing market; Housing value; Sustainable urban development; Guangzhou; China

1. Introduction The urban housing market of China has been transformed since the 1980s from a heavily subsidized centrally planned system to a free-market one. The old governmentsubsidized housing allocation system practised since the 1950s was abolished in 1998. Individual households have thus created a large pool of potential consumers and many housing units have been sold directly to sitting tenants and others (Fu et al., 2000; Zhao, 2003). China’s burgeoning real-estate market in a transitional economy has attracted academic, professional and investment interests from different quarters. A large body of literature has been gener*

Corresponding author. E-mail addresses: [email protected], [email protected] (C.Y. Jim).

0016-7185/$ - see front matter  2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.geoforum.2006.10.002

ated recently with a focus on housing reform and market privatization (e.g., Pudney and Wang, 1995; Chen, 1996; Wang and Murie, 1996, 1999; Zhou and Logan, 1996; Song et al., 1999; Zhang, 2000a,b; Wang, 2001; Huang and Clark, 2002; Zhao, 2003; Fang, 2004; Pan, 2004). However, little research has tackled household consumption preferences and buying decisions in China’s current transitional market context, although some studies have focused on specific issues such as housing acquisition in relation to location (Wang, 1996), house buying intention (Fu et al., 2000), tenure choice (Li, 2000a,b), and building design (So and Leung, 2004). Developers usually have limited knowledge of local housing preferences (Wang and Murie, 1999) and the price that consumers are willing to pay for preferred attributes, although they are increasingly aware of buyers’ fondness for high-quality environments,

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such as well-designed green spaces with water bodies (Zhao, 2003; Qin et al., 2004). This limited knowledge often results in an expectation gap between the housing supplied and what consumers demand. In urban areas, especially compact neighbourhoods, green spaces could provide valuable outdoor recreational opportunities and amenities. They play important roles in relieving congestion and the monotony of a built-up setting (McConnell and Walls, 2005). Their aggregate effects contribute significantly to improving environmental quality and the quality of urban life, and to the sustainability of urban ecosystems (Bolund and Hunhammar, 1999; Chiesura, 2004). These far-reaching benefits are particularly important to Chinese cities, which are undergoing rapid growth, which often creates or exacerbates poor living conditions. Nevertheless, the positive environmental externalities of green spaces have been inadequately addressed by developers and governments. The lack of relevant scientific-objective studies has imposed a bottleneck on their wider appreciation and application to urban planning and development. Providing a monetary value to their non-market benefits could furnish a universal and quantitative yardstick to gauge their services. The hedonic pricing method could effectively value environmental externalities (Garrod and Willis, 1999; Freeman, 2003). The fundamental assumption is that in purchasing a house, the homebuyer is paying not only for the dwelling unit but also its surrounding environmental and neighbourhood qualities. The market price is composed of a basket of individual value components, such as unit size, quality, location, and outdoor environmental attributes (Lancaster, 1966; Palmquist, 1991; Cheshire and Sheppard, 1998; Sheppard, 1999; Freeman, 2003; Paggourtzi et al., 2003; Sirmans et al., 2005). The hedonic pricing method has been applied in Europe and the USA to assess environmental externalities and the marginal value of associated factors (e.g., Anderson and Cordell, 1988; Garrod and Willis, 1999; Powe et al., 1995; Benson et al., 1998; Bolitzer and Netusil, 2000; Luttik, 2000; Tyrva¨inen and Miettinen, 2000; Geoghegan, 2002; Morancho, 2003; Price, 2003; Tajima, 2003; McConnell and Walls, 2005). Above basic requirement and affordability considerations, homebuyers might value individual characteristics differently and give more weight to the preferred attributes. This paper discusses the results of a study which aimed to (1) investigate home-buyers’ preferences in relation to outdoor environmental attributes; (2) assess actual monetary values attributed to environmental externalities by a hedonic pricing analysis; and (3) test the applicability of the hedonic pricing method in China by comparing consumers’ willingness-to-pay revealed by the hedonic analysis with their attitudes towards environmental elements within and surrounding residential developments. Guangzhou, the major city in south China, served as a case study platform. It has one of the most developed private housing markets in China (Wang and Murie, 1999; Li and Chen, 2005). Its annual investment in the real-estate sector ranked

415

fourth amongst large cities of China in 2004 (State Statistical Bureau, 2004a). The active housing market with increasing transactions (Zhao, 2003) indicated Guangzhou’s suitability as a case study. The study could foster an understanding of consumer behaviour and values in the Chinese urban housing market as the society and economy is transformed from a socialist to a capitalist market economic system. 2. The residential environment in Guangzhou before and after urban housing reform In general, residential areas in Guangzhou are divided into two groups, namely those built before and after the 1990s. The watershed marked the gradual transition from the central supply and allocation system to marketization. The changes aimed at alleviating the housing shortage problem, diversifying housing provision, nurturing the private real-estate market, and improving the quality of dwellings (OECD, 1995; Shaw, 1997; Li, 2000a; Fang, 2004). The old and new residential areas have different outdoor environmental conditions, reflecting underlying differences in land-use and lot-subdivision patterns and urban forms. Residential buildings constructed or redeveloped before the housing reform in the 1990s were mainly monotonous rectangular ferro-concrete blocks of six storeys or less. Large factory complexes had residential blocks to house workers, adhering to the local self-sufficiency principle that prevailed in the Mao era (Gaubatz, 1999). Adhering to the political and ideological tenets of state socialism, public ownership and state provision dictated the workings of the housing sector (Kirkby, 1990; Zhang, 2000b). Housing was perceived as a social service (Chiu and Lupton, 1992). Such a socio-political milieu and belief generated a housing scenario that contrasted sharply with the market-oriented housing system in western countries, where housing is usually conceived as a commodity and private property (Mathe´y, 1990). As a component of state welfare, dwellings were assigned to workers by work units mainly according to service duration without considering market mechanisms (Zhang, 2000b). Although a broad principle of equity was purportedly advocated in housing provision, it could not be satisfactorily realized in practice. Pragmatism and frugality dominated every aspect of urban life, and aesthetic pursuit and enjoyment were neglected. The location and quality of housing, which are key concerns of home ownership in the western world, were largely ignored under the old planning and allocation regime. The centrally determined rental level was detached from common housing quality indicators (Malpezzi, 1999). Residents had little choice regarding housing attributes such as location and size (Fu et al., 2000; Yu, 2006). Due to the common neglect of urban capital investments such as utilities and infrastructure, municipal authorities were reluctant to improve housing quality and associated facilities. Such unwillingness could be partly attributed to the lack of real-estate related revenues such as property

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taxes, rates and transaction duties. The rather indifferent if not lethargic housing policies resulted in widespread housing shortage and substandard provision, with merely 5.3 m2 per capita of national urban average floor space in 1978 (Kirkby, 1985). Environment-landscape enhancement and recreation–amenity facilities were generally shunned. Few environmental elements such as green spaces and water bodies were installed in residential locations, except for some remnant vegetation left by default or planted by residents after occupation. Such policies resulted in extensive grey, dull and non-descript living areas in cities. Back in 1981, public green spaces in Chinese cities, including those situated within recreational and residential lands, were merely 1.5 m2 per capita (Department of Integrated Finance of Ministry of Construction, 2004). The marketization of domestic housing after the 1980s, when direct government control was gradually relaxed, rapidly brought new developments. A housing market has been established and households have been encouraged to become homeowners. In 2004, housing investment in Guangzhou amounted to 39.1 billion RMB (US$4.88 billion), supplying a finished residential floor area of 7.9 million m2, while another 34.7 million m2 of residential housing was under construction (Guangzhou Municipal Statistics Bureau, 2005). For comparison, housing investment in 1990 at the incipient stage of the housing market was only 1.17 billion RMB (US$0.14 billion), and finished residential floor area was 1.6 million m2 which contributed 27.9% of the total residential provision in that year (Guangzhou Real Estate Yearbook Editorial Committee,

2001). Commercial housing (new properties supplied through the market mode) has emerged as the main channel for residents to satisfy their accommodation needs. The relative affluence of Guangzhou has permitted some residents to acquire their own homes. By the end of 2003, about 10% of households bought their units from the housing market (computed from data published in the Guangzhou Statistical Yearbook, 2004). For the commercial housing sector, two types of new housing estates have been built in Chinese cities: high-density mid-rise (7–20 storeys) and high-rise buildings (more than 20 storeys), and low-density villa-style houses (Yan et al., 2001; Zhao, 2003). Large-scale industries have moved away from core-city areas to give way to housing. In new residential precincts, various landscaping elements have been included to attract homebuyers, such as green spaces, water bodies and recreational facilities (Wang and Murie, 1999). The proportion of green areas in residential developments, including all vegetated patches, varies from nil to about 50% (based on information provided by Guangzhou Hefuhuihuang Real-Estate Consulting Company). The old towns (including Yuexiu, Dongshan and Liwan, see Fig. 1) occupy the site and environs where the ancient city was founded some 2000 years ago. Its building and road densities and land value are particularly high, and streets tend to be narrow. The recently built tall buildings with high plot ratio and site coverage have scant green space provision. New towns (including Haizhu, Tianhe, Fangcun and Liwan), mainly developed after the 1980s, are characterized by more spacious developments mainly

Fig. 1. Map of Guangzhou showing the old city core and the surrounding new town areas.

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of mid-rise buildings with generous green spaces. Due to pronounced differences in town plans, urban compactness, land value and environmental quality, the environmental externalities of the two submarkets deserve to be explored separately. Although it is acknowledged that local environmental quality has increasingly affected consumer home-buying decisions (Zhao, 2003), developers sometimes sacrificed green spaces and recreational facilities to increase profits (Tian, 2004). 3. Methodology 3.1. Study area and data collection The study was conducted in the main built-up areas of Guangzhou, where the real-estate market is one of the most developed in China (Wang and Murie, 1999). The land area and the sold floor area of buildings constructed by business concerns in Guangdong Province were the highest in 2004 amongst China’s 27 provinces and four municipalities (State Statistical Bureau, 2004b). After 1998, all government-subsidized housing distribution systems were abolished in the city. Most residential properties from then on became commodities that could be transacted in a free market. The exception was a small number of residential units built before 1998 with indeterminate property rights because of shared ownership between work unit and employee. To avoid potential bias due to market diversity and segmentation, this study focused on transactions of high-density developments of the mass residential sector recently constructed and sold in 2004. In Guangzhou, official statistical data of housing transactions are not available. The Guangzhou Real-Estate Transaction Centre, which is the authority that issues title deeds, holds some incomplete data on housing characteristics (such as floor area, building materials, and address) and purchase price. In any case, such data are not publicly available. Instead, we conducted a questionnaire survey in December 2005 to collect the required data directly from home-owners. The questionnaire was organized into three parts. The first part gleaned information about the apartment, including internal characteristics, location, outdoor environment and neighbourhood attributes. The data were used in the hedonic pricing analysis. The second part solicited views on the reasons for buying a new property, reasons for choosing this one, and the importance of environmental elements within and around residential developments. The last part gathered key demographic information about respondents, including age, family composition, educational level, occupation, and annual household income. The survey results of consumption preference of environmental attributes were compared with willingness-topay revealed by hedonic pricing analysis of actual transactions. The survey information served to explore the buying intention and motives of Guangzhou residents, identifying key and ancillary factors in determining housing consump-

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tion. A name list of residential developments sold in 2004 (a total of 112 sites) was obtained from the Guangzhou Hefuhuihuang Real-Estate Consulting Company. The chosen residential projects were all commercial, and different types of developers were involved, including state-owned companies, public–private joint-ventures, and private enterprises. Regardless of the nature of the developer, the pursuit of good profits following various market strategies is similar to developers in the western world, as are the sales promotion approaches such as brand-fostering and advertising (Wang and Huang, 1998). Other kinds of housing supply, such as low-rental residences provided by the government as social welfare to support the needy, were not included in the study. Using random sampling, seven to eight households in each site were chosen and face-to-face interviews were conducted with home-owners. Surveys were conducted at the respondents’ homes at weekends or after 6:00 p.m. during weekdays. Buying a property, which is a household’s most expensive purchase, usually involved a collective family decision. Thus the collected views were deemed to represent those of the household, regardless of whether the respondent was female or male. A recent study in Guangzhou indicated that a couple usually made the decision together, merging the opinions of both husband and wife (Zhao, 2003). Our study did not cover the differences between the two genders in terms of home-buying behaviour. No study has been found in the literature regarding the different perspectives and preferences of men and women in making home-buying decisions in the Chinese context. About 3% of the questionnaires with incomplete answers were eliminated. The overall response rate based on usable questionnaires was 67%, which is believed to be acceptable in social surveys especially in the Chinese context, where many people are not familiar with such probing of personal opinions and preferences by strangers. The face-to-face interview approach was adopted to reduce the refusal rate which is often significantly higher in telephone or postal surveys. The interviewees who declined might result in some biases. Due to the lack of data, it was difficult to probe the background of non-respondents to see if a particular group was excluded from the survey. Nevertheless, the response rate of this study was by no means atypical and the results are considered to be representative of home-owners and amenable to statistical tests. The environmental quality attribute (denoted by air quality) in residential areas was not included in the survey. This was because only a general air pollution index for the whole city was publicized, thus most homebuyers could not perceive its relationship with neighbourhood air quality. It could be assumed that air quality had limited influence on home buying decisions. However, traffic noise was included in this study as denoted by location near roads. Some data could not be given accurately by respondents, including plot ratio, green space rate, distance to the nearest shopping area, and distance to the nearest park. The first two

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were collected from relevant developers. The last two were measured on a Guangzhou digital map. The questionnaire data were checked by in situ investigation and average price information provided by corresponding developers. Overall, 521 sets of valid survey results were used in the data analysis conducted with SPSSPC 12 software. 3.2. Hedonic pricing method and regression model The basic premise of the hedonic pricing method is that the price of marketed goods is related to its constituent characteristics. The method has been commonly applied to assess variations in housing prices in relation to the value of inherent and external attributes (Freeman, 2003). In a competitive market, the systematic variation in the price of a heterogeneous property is comprised of a bundle of characteristics. The realized sale price could be attributed to the willingness-to-pay for the characteristics (Geoghegan, 2002; Habb and McConnell, 2002). In a regional housing market, enough housing provision with varied attributes could satisfy a wide range of consumer requirements. Thus the supply of housing characteristics is elastic, and the housing price is determined by the intrinsic and extrinsic characteristics: P ¼ a þ Sb þ Lc þ Gs þ e

ð1Þ

where P is an (n · 1) vector of housing prices, S is an (n · k) matrix of structure characteristics, L is an (n · l) matrix of neighbourhood characteristics, G is an (n · m) matrix of locational variables, a, b, c, s are the associated parameter vectors and e is an (n · 1) vector of random error terms. Neighbourhood factors include security, crime level, social status of the area, educational attainment and income level of residents. Locational factors consider distance to public services, work place, shopping areas, old towns and green or natural sites. Suppose the demand for housing characteristics is independent of the prices of other goods, maximizing a household’s utility subject to its budget constraint implies optimal conditions for each attribute. Thus the partial derivative with respect to any of its arguments gives the marginal implicit value of that characteristic (Geoghegan, 2002; Habb and McConnell, 2002). The hedonic price of each structural characteristic ðpSi Þ, that of each neighbourhood characteristic ðpLi Þ, and that of each environmental attribute ðpGi Þ, could be given by the following equations: pSi ¼ oP =oS i pLi ¼ oP =oLi

ði ¼ 1; 2; . . . ; kÞ ði ¼ 1; 2; . . . ; lÞ

ð2Þ ð3Þ

pGi ¼ oP =oGi

ði ¼ 1; 2; . . . ; mÞ

ð4Þ

The estimation and selection of hedonic pricing equations has been a major concern because there is not enough guidance from economic theory about the proper

relationship between housing price and its preferred attributes (Cropper et al., 1988). Differences between equations and related econometric issues have been widely explored (Habb and McConnell, 2002). They include linear form (parametric, semi-parametric, and non-parametric), semi-logarithmic form, double logarithmic form, Box–Cox transformation, and reciprocal form. The selection of the eliciting equation form might affect the accuracy of estimated results (Garrod and Willis, 1999; Malpezzi, 2003). Sometimes complicated transformation processes could bring more random errors (Davidson and MacKinnon, 1993). The semi-log equation, adopted in this study, was considered as the best fit without too many complicated computations (Bockstael, 1996; Geoghegan et al., 1997; Bolitzer and Netusil, 2000; Geoghegan, 2002). Another major issue that requires clarification is the definition and selection of independent variables in the hedonic equation. Some problems, such as collinearity, omitted variables and spatial autocorrelation might induce imprecise estimates. It is necessary to identify housing attributes with a bearing on homebuyer demands. In data analysis, inclusion of relevant factors and tackling econometric problems could improve accuracy. Besides housing price information, the 20 independent variables assessed in this study were divided into four groups, namely: (1) housing structure; (2) housing location and accessibility; (3) housing security which is a neighbourhood attribute; and (4) housing environment. The definitions of all variables included in this study and their expected effects on housing prices are given in Table 1. All the sampled residential precincts have attached parking lots, hence this factor may not incur notable differences in housing prices between sites. It was therefore not included in the study. Although the quality of property management influenced housing price in Beijing (Ma and Li, 2003), it was not included as a variable in the hedonic model because in Guangzhou property management forms an independent market controlled by its own factors. The cost and quality of property management vary according to the company and personnel selling the service. Contracts for property management in the city are contested by companies providing such services. The national Property Management Ordinance issued on June 2003 stipulates that residents not satisfied with management quality can switch to another company. Thus the influence of property management on housing price tends to be relatively remote and fluid. Knowing the management fees in advance of buying a new home, and that the management company could be changed thereafter, this factor would have similar effect on different buyers. Hence it was not included in the hedonic model although in the questionnaire survey property management was still considered in property choice. The following semi-log equation was applied to explore the relationship between housing price and housing attributes to deduce their individual marginal values:

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Table 1 Variables and their definitions enlisted in the hedonic pricing study of residential units in Guangzhou Variable

Definition

Unit or coding

Expected signa

Housing price variable P

Transaction price of the apartment

RMBb

n.a.

Housing structural attributes FLOORAREA Total floor area of the apartment NBEDROOM Number of bedroom NBATHROOM Number of bathroom STOREY Floor level on which the apartment is situated DIRECTION Main compass direction of the apartment QUALITY Quality of the building PLOTRATIO Plot ratio of the residential precinctc

m2 Count Count Count 1 with windows facing south and north, 0 otherwise 3 if good, 2 if average, and 1 if bad Ratio

+ + + + + + ?

Housing locational and accessibility attributes COMMERCIAL Located within commercial area RESIDENTIAL Located within residential area TRANSPORTATION Located close to main street CENTRALTOWN Located in old town aread WORKDISTANCE Distance to work place SHOPPING Distance to shopping centre

1 if 1 if 1 if 1 if km km

? + – + – –

Housing security attribute SECURITY Security condition around the residential precinct

3 if good, 2 if average, and 1 if bad

+

Housing environmental attributes GREENVIEW View of green space WATERVIEW View of water body STREETVIEW View of street BUILDINGVIEW View of building GREENRATE Green space provision rate in the residential precincte PARKDISTANCE Distance to the nearest park

1 with 1 with 1 with 1 with % km

+ + – – + –

yes, yes, yes, yes,

0 0 0 0

if if if if

view view view view

no no no no

of of of of

green spaces, 0 otherwise water bodies, 0 otherwise streets, 0 otherwise buildings, 0 otherwise

a

‘+’ sign denotes augmenting and ‘–’ suppressing effect on apartment price; ‘?’ indicates an inherently indeterminate effect. RMB denotes the Chinese currency Renminbi at about US$1.00 = RMB8.30. c Calculated by (Total floor area/Land area), an index of site development intensity. d The old town area denotes the old core of Guangzhou city, including the districts of Yuexiu, Liwan and Dongshan, which have high development and population densities and narrow streets. The new towns include the districts Haizhu, Tianhe, Baiyun, and Fangcun which were developed after the 1980s with a less congested urban form. e Calculated by (Green space area/Land area) · 100, an index of site greening intensity. b

ln P ¼ b0 þ b1 ln FLOORAREA þ b2 ln N BEDROOM

developed mainly because of the explicit differences in environmental externalities between old towns and new towns (explained in Section 2).

þ b3 ln N BATHROOM þ b4 ln STOREY þ b5 DIRECTION þ b6 ln QUALITY þ b7 GREENVIEW þ b8 WATERVIEW þ b9 STREETVIEW þ b10 BUILDINGVIEW

4. Results and discussion

þ b11 COMMERCIAL þ b12 RESIDENTIAL

4.1. Home buying intention and motives

þ b13 TRANSPORTATION þ b14 CENTRALTOWN þ b15 ln SECURITY þ b16 ln PLOTRATIO þ b17 GREENRATE þ b18 ln WORKDISTANCE þ b19 ln SHOPPING þ b20 ln PARKDISTANCE

ð5Þ

Based on field investigation of Guangzhou’s housing market, three analysis scenarios were developed. The first scenario included all study areas and data, and the other two tackled respectively two distinct submarkets. The second scenario included housing in old towns, and the third scenario in new towns. These two scenarios excluded the CENTRALTOWN variable. The last two scenarios were

Most homebuyers were rather young, in the 35–44 (36.7%) and 25–34 (35.3%) age groups. About 58% of the households consisted of three members and just over half of the respondents (52.7%) declared education to university or high-degree level. The most frequent annual household income bracket was RMB70,000–100,000 (23.2%), followed by the lower RMB50,000–70,000 (19.8%) and higher RMB100,000–150,0001 (19.6%). Thus, the main consumers of residential properties in 2004 were households composed of young to middle-aged parents with relatively high-level education, one child and reasonably good incomes. It is 1

The official exchange rate is US$1 = RMB8.048.

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Table 2 The principal motives stated by respondents for buying residential properties in Guangzhou Average scorea

SD

0.0 0.0 2.8

1.40 1.10 0.40

0.61 0.75 0.96

0.9

0.97

0.77

Motive

Valid responses (%) Very important

Important

Neutral

Unimportant

Very unimportant

Improving the living environment Improving the dwelling floor area Investment

46.6 32.7 13.6

48.2 44.9 33.4

4.6 21.4 38.6

0.6 1.0 11.6

Average

31.0

42.2

21.5

4.4

a

Average score is calculated from the ordinal weights assigned to: very important = 2, important = 1, neutral = 0, unimportant = 1, and very unimportant = 2.

possible that the sample might be biased due to the exclusion of potential home-buyers who were older, with lower education levels and lower household incomes, although currently it seems difficult for them to purchase housing in the free market. Improving the living space was the most important home-buying motive, with an average score of 1.4 (Table 2). Improvement in floor area of the dwelling unit was the next important motive, with an average score of 1.1. Investment was a lesser motive with a low-average score of 0.4, although 47% of the respondents still rated it as very important or important. The results indicate that new properties were mainly sold to owner–occupiers, and that the rental market was rather limited.

After two decades of housing reform and marketization, the shortage of accommodation in Guangzhou has been gradually ameliorated. The average per capita dwelling area increased significantly from 3.97 m2 in 1980 to 17.23 m2 in 2004 (Guangzhou Municipal Statistical Bureau, 2004). Improving indoor domestic space was no longer the primary motive for most households. Instead, improving the wider living environment has become the major concern, with a bearing on consumer preference. A housing consumption study in Shanghai (Wang, 1996) showed different results, where the main concerns were floor area and location (proximity to public facilities). Improving the living environment was ranked the least important factor. The Shanghai study was conducted in

Table 3 The factors stated by respondents that contribute to the decision to purchase residential properties in Guangzhou Factor

Valid responses (%) Very unimportant

SD

Very important

Important

Neutral

Key factors 1. Transaction price 2. Security concern 3. Quality of property management 4. Proximity to work place 5. Proximity to shopping area 6. Convenient public transport 7. Environment inside the residential precinct 8. Environment around the residential precinct

55.4 51.6 37.7 34.9 32.9 29.3 16.1 27.6

39.3 43.7 46.9 50.3 52.5 56.9 51.5 50.0

5.1 4.7 15.0 13.1 14.0 12.9 20.8 21.2

0.2 0.0 0.4 1.6 0.6 0.8 1.6 1.2

0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0

1.50 1.47 1.22 1.18 1.18 1.15 1.02 1.02

0.60 0.59 0.70 0.73 0.68 0.65 0.73 0.73

Average

35.7

48.9

13.4

0.8

0.0

1.22

0.68

Ancillary factors 9. Quality of building and decoration 10. Proximity to school 11. Provision of public facilities and utilities 12. Reputation of the developer 13. Design of partitions in the apartment 14. Design of building and development 15. Proximity to metro station 16. Location in central area of town 17. Popularity of the development 18. Location in new development zone

24.7 37.0 27.0 17.1 19.4 16.6 15.8 12.6 11.0 7.5

52.5 34.6 40.1 49.3 46.7 45.5 38.1 38.9 31.5 27.0

17.9 19.1 30.7 27.8 27.3 29.1 40.2 33.7 41.6 42.6

5.0 6.4 2.2 5.8 6.4 8.8 5.9 14.4 15.9 22.9

0.0 3.0 0.0 0.0 0.2 0.0 0.0 0.4 0.0 0.0

0.97 0.96 0.92 0.78 0.78 0.70 0.64 0.49 0.37 0.20

0.79 1.04 0.81 0.79 0.83 0.85 0.82 0.90 0.88 0.88

Average

18.9

40.4

31.0

9.4

0.4

0.68

0.86

a

Unimportant

Average scorea

Average score is calculated from the ordinal weights assigned to: very important = 2, important = 1, neutral = 0, unimportant = 1, and very unimportant = 2. The scores have been ranked in descending sequence.

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1996, during which the average per capita dwelling area (in the two study areas, namely 5.58 m2 in Jing’an and 5.87 m2 in Changning) were notably lower than the figure in Guangzhou in 2004. Some Shanghai households (40– 50%) then had only one unpartitioned room for all purposes and had no private wash room. Such an acute urban housing shortage resulted in a pressing quest for a larger dwelling space in Shanghai. In addition, most residents relied on bicycle and public transport (Wang, 1996), thus accessibility and commuting time to public facilities was a crucial consideration. The high-order demand for recreation and amenity had to be relegated behind the fulfilment of basic needs. The differences in motivation for buying houses between Shanghai and Guangzhou partially reflected the imbalance of supply and demand when the housing market was developed at different levels. In comparison with Beijing’s hedonic study (Yang, 2001), some housing attributes were weighted differently in Guangzhou. People in Beijing paid great attention to construction quality. The Beijing study was conducted in 1998 when the new Construction Law reacting to widespread concerns on construction quality had just been promulgated. Nevertheless, the issue remained a major worry of home buyers due to weak supervision and enforcement. In general, residents’ housing preference in Chinese cities is closely tied to the actual quantity and quality of the existing stock. Cities with different extant housing conditions will engender rather different housing demands. It also hints that housing preference will evolve in tandem with housing conditions, and that continual improvements would generate feedbacks to lift housing demands to highorder expectations related to environmental quality. It will be worthwhile to plan housing supply to cater to such changing attitudes and expectations. Other Chinese cities yet to be studied are expected to yield some unique relative weights in hedonic attributes. The varied permutations of physical and socio-economic realities of different Chinese cities would generate spatial variations in buyer behaviours in making pivotal home-buying decisions. Such regional disparities in human motives to acquire properties warrant differential if not tailor-made policies and administrative treatments. Macro-scale intervention of the property market by the central authority could be suitably modified to reflect the needs of different cities.

4.2. Key factors determining housing consumption Many factors affect home buying decisions. The questionnaire survey asked respondents to weight 18 factors (Table 3). Eight key factors with average scores exceeding 1.00 have strong bearings on home-buying decisions, with most respondents choosing them as very important or important. The standard deviations of the factors are relatively low and confined within a narrow range of 0.59–0.73, suggesting clustering of responses. It should be highlighted that the key factors are exclusively associated with factors

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external to the property, as they are not directly related to internalities (apartment size and quality). Price (average score 1.50) was accorded the top rank, with 94.7% of the respondents rating it as very important or important. Housing price was predominant for it is tied to the pragmatic if not clinching consideration of affordability (Lim and Lee, 1993; Zhou and Logan, 1996; Wang and Murie, 1999; Rosen and Ross, 2000). The big gap between income and sale price has remained an inhibitory straitjacket to buy and hence to short-term housing-market growth. Continued economic growth is expected to expand the middle class and generate demands for better housing (Shen, 2005). The recent withdrawal of old-style subsidized housing without a substitute, such as a public housing program, could trap low-income groups in poor housing with little hope of improvement (Yuan and Chen, 2005). Worries and vigilance about security were ranked second in housing choices. The average score of 1.47 reflected the fact that 95.3% of respondents rated it very important or important. That law and order is considered as a key issue is perhaps somewhat surprising. A certain measure of security was provided by gated residential communities that dominated new housing estates. The commonly installed features included perimeter walls and fences, secured gates, security personnel and professional property management (Wu, 2005). However, the emergence of inward-looking residential enclaves could reinforce physical and mental fragmentation of the urban structure to nurture feelings of insecurity (Wu, 2005). The fortress mentality could induce a positive feedback of intensifying the sense of fear of the world that lies outside the realm of exclusion. Recent rapid urbanization in China has sometimes dehumanized the traditional city milieu and community fabric. It could erode social cohesion and correspondingly sow the seeds of social instability (Pu et al., 2005). The large transient population in Guangzhou that emerged two decades ago has continued to expand without respite. This population has also been blamed for the rising crime rate and their presence has also brought social conflicts due to competition with local residents for jobs and other urban resources (Zhang, 2005). The transient population with very low income could only afford to live in places with low-housing quality. The urban villages, which are original rural settlements engulfed by the city in the course of urban sprawl, tend to have dilapidated houses, congested living conditions and poor sanitation where many transient people dwell. The existence of such incongruent enclaves has stressed social harmony (Liu, 2002). Many problems such as security, insufficient infrastructure, poor environmental condition, and congregation of jobless people have arisen due to the lack of planning and management of these occluded villages. Furthermore, polarization of income and inadequate social insurance have stretched social accord (Tang, 2005). Carrying such common negative connotations, residences situated in the vicinity of urban villages are considered as undesirable, resulting in depressed property values. The

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joint operation of these underlying and largely city-wide social problems with no foreseeable solutions could explain homebuyers’ attitudes towards security. The quality of property management was ranked third. Although property management was excluded in the hedonic pricing computations, residents were concerned about the quality of this service which is therefore included in the questionnaire analysis. In the pre-reform era, urban residential buildings were managed by work units or the municipal housing bureau, which provided limited services such as repair and maintenance (Xu and Fang, 1996). Many people still remember the minimalist building management of the old days. From the 1980s, property management companies have emerged to introduce professional care of properties (Lim and Han, 2000). However, the service quality has often failed to meet resident expectations. Consequently, frequent conflicts have occurred between home-owners and management companies. The Property Management Regulations promulgated in 2003 have ascertained the rights and responsibilities of the two parties, but home-owners’ rights sometimes can not be guaranteed (Zhou, 2005). Due to home-owners’ mistrust of property management, it was given much attention in the survey responses. In Guangzhou, many residents commute by public transport, with only 9.8% using private cars (Li, 2003). Proximity to work place, shopping area and access to convenient public transport would save home-owners travelling time. The day-to-day shopping habits of Guangzhou inhabitants remained typical of the compact city dominated by neighbourhood shops situated in the vicinity of dwellings. Most intra-city travel trips lie within an envelope of 8 km (Zhou and Yang, 2005). Extra-large shopping malls that could attract customers from an extensive catchment area, which could alter travelling patterns and behaviours, are yet to emerge. These three cognate factors, linked to location, accessibility and mobility, are understandably accorded due weight by residents, and given fourth to sixth ranks. Environmental elements within and around residential precincts were accorded seventh and eighth ranks. Residents are concerned about the poor and worsening environmental conditions in many Chinese cities. As a fast growing city, Guangzhou has been inflicted by rather serious pollution. The widespread dissatisfaction towards chronic pollution problems and concern about health impacts have raised environmental consciousness, although the sentiment might be influenced by materialism and could be rather superficial (Li, 1998; Hong, 2005). Their sphere of concern has extended from the development per se to surrounding areas, especially the immediate environs. Residents wanted to live in secure and exclusive residential developments in a pleasant environment. 4.3. Ancillary factors of housing consumption Ten ancillary factors have average scores below 1.00 (Table 3). Most respondents still rated them as very impor-

tant or important. Whereas the key factors have a group average score of 1.22, the ancillary factors have only 0.68. The standard deviations of ancillary factors, ranging from 0.79 to 1.04, are higher than that for key factors, suggesting that the second-echelon factors attracted more divergence in opinions. They have been divided into two groups. Group one has average scores of 0.70–0.99: quality of building and decoration, proximity to school, provision of public facilities, reputation of the developer, design of rooms in the apartment, and design of building and development. Group two has average scores less than 0.70: proximity to metro station, popularity of development, and location in old towns or new towns. The results showed that home buyers in Guangzhou were concerned with housing quality. A cluster of factors related to quality and design of buildings, associated with construction materials and workmanship, planning and aesthetics, were considered important in judging properties. The quality factor (quality of buildings and decoration) was rated notably more important (9th) than the two design factors (13th and 14th). Internal design (partitions in the apartment which refers to the configuration of its functional spaces) was rated slightly ahead of external design (design of building and developments). The city has witnessed significant improvements in building quality in recent years. The impetus initiated by the Ministry of Construction from the late 1990s has begun to take effect (Wang, 1994; Wang and Murie, 1999). Certification by a government department (Quality and Technology Supervision Bureau at various levels) to guarantee the quality of residential buildings (such as structure, materials and safety) is a pre-requisite to selling newly built units. The reputation of the developer (12th rank) is a factor that implies the delivery of good quality and design. Popularity of the development was ranked very low at 17th, hinting that the subjective interpretation offered by word-of-mouth views had limited influence in home-purchase decisions. Proximity to school was ranked 10th. China has a traditional and strong emphasis on the value of education. That proximity to school has been rated much below proximity to work place and shopping area begs explanations. Parents would usually target a small number of premier schools offering the best education to their children. Usually, the reputation of a school is gauged by the track records of its students gaining admission to prestigious institutions at the next level. The earnest desire to select premier schools is largely a footloose or aspatial type of decision that is independent of location. Proximity of schools to residences is therefore not a crucial consideration in home purchase. This factor has the highest standard deviation of 1.04, suggesting a notable spread of opinions amongst respondents. Providing public facilities and utilities within residential precincts was ranked 11th and is marked by a rather high (30.7%) neutral response. They involve mainly water, gas, telecommunications, television, roads and supermarkets.

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As stipulated in the National Criterion of Urban Residential Area Planning (GB50180-93), proposed by the Ministry of Construction and enacted in 1993, developers are required to provide adequate public facilities. A proposed development might not be authorized by the government if the facilities did not satisfy government guidelines. Thus newly built residential projects are equipped with public facilities, although the quantity and quality could vary amongst sites. Homebuyers would rely on the government to enforce the relevant regulations and hence would not be too concerned about this factor. In comparison with convenient public transport (ranked 6th), proximity to a metro station was rated very low (15th). The common synergy between the metro and housing desirability has limited applicability in Guangzhou. The present condition of the metro system in Guangzhou does not command a competitive edge over other public transport modes. Currently, there are only two lines serving a small part of the large metropolis. Taking the metro could incur more walking and transfer times, and it may not be as convenient as other public transport means. Moreover, metro fares are notably higher than those levied by other modes. Thus it is unsurprising that homebuyers attached less importance to living near a metro station. Location in old or new towns drew the least attention amongst the 18 factors. These two factors attracted respectively the largest and third largest proportion of unimportant responses. The proximity and transport factors are location-oriented and they deal with more specific location preferences than the general question about old or new

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towns. Such more focused and targeted factors have probably taken precedence over the actual siting of a residential development in the city. In China, the selection of housing location is heavily influenced by the strong desire to maintain an accustomed social relation network (Wang, 1996). Some benefits and negative impacts related to location were overlooked and compromised by other more preferred attributes. 4.4. Environmental attributes and home purchase Environmental elements ‘‘inside’’ (internal) and ‘‘around’’ (external) the residential grounds, five factors each, were rated by respondents according to degree of importance (Tables 4 and 5). Responses were markedly concentrated in the very important, important and neutral categories. In general, the inside responses had higher average scores than those for external ones. It implies that residents found the internal environment somewhat more important than external. The environment of the grounds where a resident actually lives was rated more important than the surroundings. The limited spread of standard deviations of the factors suggests similarity in the distribution of answer across the five response categories. Green space was ranked 1st inside residential grounds and 2nd around but only if it could be used by residents (Tables 4 and 5). However, green space around the residential area but not open to the public was accorded the lowest rank. The ecosystem services and visual benefits of such inaccessible spaces were valued but at a relatively low level.

Table 4 Respondents’ rating of the importance of environmental elements inside residential precincts Environmental element

Valid responses (%)

Average scorea

SD

Very important

Important

Neutral

Unimportant

Very unimportant

Green space Environmental quality Open space Water body Children’s playground

29.1 31.3 18.8 17.3 17.5

57.3 49.7 49.1 44.4 33.7

13.0 18.0 29.5 35.7 35.3

0.4 1.0 2.6 2.6 9.6

0.2 0.0 0.0 0.0 4.0

1.15 1.11 0.84 0.76 0.51

0.66 0.72 0.75 0.76 1.01

Average

22.8

46.8

26.3

3.2

0.8

0.87

0.78

a

Average score is calculated from the ordinal weights assigned to: very important = 2, important = 1, neutral = 0, unimportant = 1, and very unimportant = 2.

Table 5 Respondents’ rating of the importance of environmental elements around residential precincts Environmental element

Valid responses (%)

Average scorea

SD

Very important

Important

Neutral

Unimportant

Very unimportant

Environmental quality Green space (usable) Open space Water body Green space (unusable)

46.3 22.7 15.2 15.0 8.6

44.6 45.3 52.7 33.3 40.4

8.7 29.4 28.3 45.6 46.8

0.4 2.4 3.8 5.9 4.0

0.0 0.2 0.0 0.2 0.2

1.37 0.88 0.79 0.57 0.53

0.66 0.79 0.74 0.82 0.72

Average

21.6

43.3

31.8

3.3

0.1

0.83

0.75

a

Average score is calculated from the ordinal weights assigned to: very important = 2, important = 1, neutral = 0, unimportant = 1, and very unimportant = 2.

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Green space situated inside residential grounds secured a notably higher average score (1.15) than that outside (0.88). It implies that the more private, internal and readily accessible recreation space was deemed more important. Environmental quality was rated 1st inside the grounds and 2nd around. The average score for around (1.37) exceeded that for inside (1.11). The sequence is the opposite of green space preference. This finding implies that residents felt that environmental quality was a key factor in home-buying decisions, but they were more concerned about the surroundings than the interior areas. It could hint that the environmental quality inside residential grounds is in general better than other land uses except recreation (Guangzhou Environmental Protection Bureau, 2004). It could imply that environmental problems such as pollution were perceived to come from external sources. Beyond the boundaries of the residential grounds, there is a higher chance of encountering more problems due to air pollution and noise nuisance. Home-buyers harbouring such an impression would still rate as important the intra-grounds environmental quality. The concern about pollution and its harmful effects on health has notably affected preferences for homes. The average scores of other environmental attributes, including open spaces, water bodies, and playgrounds, either inside or around developments, were less than 1 (Tables 4 and 5). These factors played a lesser role in home choice. Differences in average scores indicated that water bodies and open space located inside residential grounds are valued more than in surrounding areas. The watercourses in Guangzhou, mainly the Pearl River, its tributaries and canals, traditionally served as part of the municipal sewage system. Recent increases in disposal have overtaxed the river’s natural cleansing capability, causing widespread and discernible deterioration of water quality (Guangzhou Environmental Protection Bureau, 2004). The poor state of water bodies in the city could have influenced questionnaire responses and depressed the importance of this environmental attribute. The provision of open space and playgrounds in the surveyed residential areas, as reported by respondents, was either inadequate or not as good as expected. This undesirable situation could be attributed to general land shortage in Guangzhou, thus pushing developers to maximize the development potential of residential lands. From 1990 to 1999, the continual movement of people into the city has raised the annual population growth to an exceptionally high level of 6.25%. For comparison, the annual increase in urban land supply was 4.75% (Ouyang et al., 2002). It showed clearly that urban land supply lagged behind population growth. New developments should be properly planned to reduce built-up density, insert green space and improve the quality of the compact urban environment. The myopic attempts to over-develop will negate the chance to bring much-needed relief, and perpetuate the plight and ills of overcrowding in the city. Such

real-estate supplies contradict the rising affluence of Guangzhou and the concomitant expectation for better housing. There was no significant association between homebuyers’ socio-economic factors (occupation, education, income and age) and their preferences of their environmental attribute preferences inside and around residential developments (Chi-square test was applied and the lowest p value was 0.067). An earlier empirical study of more diverse housing segments showed that occupation, and household income and party membership could affect house buying decisions (Li, 2000b). Our Guangzhou findings, focused on the commercial housing market, reflect the lack of socio-economic differentiation in appreciating the environmental benefits associated with residences. With reference to this particular facet of environmental awareness, the respondents apparently have a rather uniform if not homogenized outlook. The fact that most respondents fall into a rather limited socio-economic bracket (cf. Section 4.1) could explain this observation. The chronic plight of domestic overcrowding in China could generate property attribute preferences that differ from the prevailing western norm. The variations would also be tied to fundamental disparities in demography, with the western world’s stable or declining population, shrinking household size and overall expansion in the housing stock notably reducing overcrowding and favouring highquality single family housing (Clark et al., 1984). Although some factors of home selection have not been covered by this or other studies in China, a convergence towards a similar outlook and mentality is anticipated as the country’s emerging housing market, largely modelled after the west, gradually matures and takes on more global traits. The continued rise in disposable income would raise ancillary expectations of access to better schools, shopping, transport links, green spaces, nature and other communal facilities. Such human desires for higher order home qualities, both within and in the vicinity of living quarters, tend to traverse different cultures and economies, and spatial and temporal divides. Such commonality, reflecting a universal quest for better housing, could in time gradually permeate Chinese society with the expansion of the middleincome rank, resulting in obliteration of the differences between the west and the east. For instance, western socio-economic traits that affect home choice may gradually emerge or be more strongly expressed in China, such as (1) life cycle characteristics such as marital status, age of household head, and number of children in the household (Straszheim, 1973); (2) lifestyle influences in suburban clusters with a strong preference for outdoor parking space and plant watering services (Lee, 2005); (3) young and newly formed households (single-earner) are more inclined to live in more urbanized areas, whereas the least urbanised (suburban) areas are more attractive to dual-earner married couples (Kruythoff, 1994); and (4) convenience and amenity attributes such as better open space, shorter commuting time, lower transportation cost, lower development density and

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higher quality of school (Cooper et al., 2001; Earnhart, 2002; Margulis, 2002; Tajima, 2003). 4.5. The hedonic pricing analysis Results of the hedonic regression analysis for three scenarios, namely old towns, new towns and whole urban areas, are summarized in Table 6. The models have good explanatory power (adjusted R2 = 0.748 for scenario 1, adjusted R2 = 0.694 for scenario 2, and adjusted R2 = 0.725 for scenario 3). The three scenarios yielded rather similar results in terms of the magnitude and sign of regression results. In general, all housing structural attributes contributed positively to transaction price. Larger floor area, more bedrooms, more bathrooms, higher storey, higher building quality, facing both south and north directions, and higher plot ratio indicated a higher market price. Floor area commanded the principal control on price, as indicated by the tratios. Floor area is the only structural characteristic that influenced housing price. Unlike some western cities where houses are more common, the prevalent residences in Guangzhou are apartments in mid-rise and high-rise

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buildings. Usually, floor area is the major determinant of bedroom and bathroom numbers. Thus the choice of apartment size predicates the preference for bedrooms and bathrooms. The per-square metre price of apartments in new towns tended to be lower, hence it is more affordable for people to buy bigger units there. Living on higher floors also raised the willingness to pay, because it could improve views, air circulation and solar access in the densely built-up city. The positive effect of plot ratio on price is somewhat unexpected. The regression was significant for new towns and whole urban area scenarios. A high plot ratio engenders high-rise buildings and high-density environment, which are commonly regarded as undesirable features in other countries. In Guangzhou, however, people have preserved an ingrained mindset of linking low-rise tenement blocks to old poor-quality accommodation. Burdened by this historical baggage, they consider new high-rise buildings as a departure from the unpleasant legacy of dilapidation, overcrowding and backwardness. Living in tall multistoried apartment blocks connotes a high social status, which is consistent with current social value held by the young generation in China (Li, 2005; Wei, 2005). The

Table 6 Results of regression analysis of the semi-logarithmic hedonic pricing model for two housing submarkets and the whole study area in Guangzhou (dependent variable is lnP) Explanatory variable

Old town areaa Estimated coefficient

Housing structural attributes ln FLOORAREA lnNBEDROOM lnNBATHROOM ln STOREY DIRECTION ln QUALITY ln PLOTRATIO

New town areab t-Ratio

Estimated coefficient

Whole urban areac t-Ratio

Estimated coefficient

t-Ratio

11.358d 0.399 1.318 1.216 0.847 1.100 1.260

0.603 0.048 0.047 0.077 0.004 0.013 0.095

7.145d 0.609 0.822 1.818 0.109 0.267 2.075d

0.619 0.010 0.052 0.021 0.003 0.025 0.095

13.581d 0.230 1.600 0.721 0.131 0.916 2.718d

1.317 – 1.714 – 2.567d 5.547d

0.018 0.103 0.072 – 0.014 0.051

0.124 2.455d 0.242 – 0.335 1.181

0.072 0.043 0.026 0.039 0.045 0.152

0.403 1.464 0.103 1.212 1.792 4.248d

0.127

3.856d

0.068

0.109

4.008d

Housing environmental attributes GREENVIEW 0.016 WATERVIEW 0.071 STREETVIEW 0.028 BUILDINGVIEW 0.001 GREENRATE 0.147 ln PARKDISTANCE 0.099 Constant 8.265

0.267 2.280d 0.454 0.011 3.914d 2.515d 21.924

0.208 0.129 0.043 0.065 0.046 0.055 8.965

0.083 0.079 0.048 0.080 0.055 0.001 8.341

2.385d 2.976d 1.438 0.297 1.786 0.006 21.795

0.620 0.020 0.052 0.045 0.025 0.035 0.051

Housing locational and accessibility attributes COMMERCIAL 0.044 RESIDENTIAL – TRANSPORTATION 0.056 CENTRALTOWN – ln WORKDISTANCE 0.078 ln SHOPPING 0.270 Housing security attribute ln SECURITY

a b c d

1.414 3.951d 2.636d 0.924 0.219 1.009 1.185 16.303

Dependent variable: lnP, N = 213, R2 = 0.764, adjusted R2 = 0.748, the ‘RESIDENTIAL’ variable was excluded due to collinearity. Dependent variable: lnP, N = 308, R2 = 0.722, adjusted R2 = 0.694. Dependent variable: lnP, N = 521, R2 = 0.736, adjusted R2 = 0.725. Signifies statistical significance at the 5% level.

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attribute is not significant in old towns because the development density there is already very high. Any attempt to push it up further will be perceived as undesirable. Location and accessibility played a role in housing price. Location in residential areas and close to main streets could increase the selling price. Residential land use in new towns, as indicated by the significant regression and high t-ratio, had a notable influence on price. The better town planning and environmental quality in new towns are welcomed by home buyers (Fang, 2000). Proximity to main streets offered attraction to buyers because it provides convenient public transport (Zhang et al., 2005). The crowding and clutter typical of commercial areas in Guangzhou have depressed prices because they are construed as undesirable. Long distance to work and shopping, incurring higher travelling time and cost, would dampen price. Location in old towns, with a wide variety of shops and convenient public transport, could enhance the price (Wang et al., 2003). The hedonic model corroborated the finding of the questionnaire survey (Section 4.2) that better security could increase housing value. The regression results are significant for old towns and the whole urban area, but not for new towns. The clear demarcation of land lots and common occurrence of gated properties in new towns have reduced the security worry. Security is less of a concern in new towns, probably because of the lower crime rate and a general feeling of safety in the new neighbourhoods. The better security measures implemented in new towns could instil a sense of trust and peace of mind amongst the residents (Weng, 2001). Housing environmental attributes imposed both positive and negative effects on price. A view of green space could raise the price. The regressions are significant for new towns and the whole urban area, but not for old towns. The lack of green spaces in old towns and hence paucity of green view should have triggered a desire for more. Notwithstanding, home-buyers are unwilling to pay for limited views of tiny and scattered green pockets. The dim prospect of getting improvement in the densely built-up old towns has dampened expectation and willingness-to-pay to acquire this environmental benefit. They have literally abandoned the expectation of something that can hardly be achieved (Wang et al., 2003). The buyers have expressed a realistic judgment of the present and future situation. In new towns, the new planning and greening standards and lower land cost have permitted generous insertion of green spaces, thus whetting the appetite for green views. A water view had significant regressions in all three scenarios. The riverside city is criss-crossed by the Pearl River and its tributaries. Residents are accustomed to and value a water vista (Bao and Liu, 2005) thus a view of buildings and streets, could lower prices. Green space provision within the residential grounds and proximity to the nearest park could lift price. These two variables are significant for old towns but not for new towns and the whole urban area. The grave shortage of green space in old towns has nur-

tured an earnest desire for recompense within private spaces in residential grounds or in public spaces in nearby parks. People are seeking relief from the stresses of the urban environment, but the issue of convenient access is a concern. Most people are unwilling to walk more than 500 m or 10 min to reach a public green space (Burgess et al., 1988; United Nations Environment Programme, 2005). In old towns, people are willing to pay for green spaces that they can actually use for recreation and amenity, but are not willing to pay for green views. This apparent contradiction echoes a pragmatic bent in buyer behaviour. What can be used directly is worth more than visual glimpses. The overall consistency in regression results amongst the three scenarios indicates that the housing market in Guangzhou is apparently a uniform entity. Close inspection of the statistical significance of variables, however, hints at a dichotomy between old and new towns. In old towns, housing price is determined by seven significant (p < 0.05) explanatory variables arranged in descending order of contribution (Table 6): apartment floor area, distance to the nearest shopping area, green space provision within the residential development, security condition, distance to work place, distance to the nearest park, and view of water body. Other variables are statistically non-significant. In new towns, the five significant (p < 0.05) explanatory variables in order of contribution to price are: apartment floor area, view of green space, view of water body, location in residential land use, and plot ratio. For the whole urban area, the significant variables overlap with either new towns’ or old towns’ preferences, except the universal apartment floor area and view of water body. The results have embodied both old and new town preferences. Besides the clinching variable of apartment floor area, only view of water body is shared by old and new towns. People buying residential properties in the two contrasting parts of the city harbour different expectations and hence different willingness-to-pay attitude. The significant variables in general fall under two strands, namely the affirmative to get what is available, and the compensatory to get what is deficient. People choosing to buy homes in old towns expect to be close to workplaces and shopping areas. They anticipate compensatory relief with respect to the lack of security, and green space within and near their home grounds. For new towns, people expect to live in modern high-rise apartment blocks in exclusive residential land use with ample green views. Important environmental benefits such as high green space provision, at a high rate of about 30% in new towns (less than 10% in residential areas in old towns), are expected and literally taken for granted. The generous provision of parks in new towns is perceived in a similar manner. There is no need to pursue or compensate features that are widely available. Overall, the nature of the urban fabric and associated green spaces has notably moulded home-buying behaviour. The environmental externalities of Guangzhou’s housing market could be deduced by the partial derivatives whilst

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holding other variables constant (only significant variables are considered). In old towns, when the distance to the nearest park doubles, the housing price is expected to decrease by 6.6% (20.099  1). The price would increase by 7.3% (e0.071  1) for a view of a water body. In new towns, a view of a water body and green space could enhance the price by 13.7% (e0.129  1) and 23.1% (e0.208  1), respectively. The results showed that environmental attributes were valued differently in relation to local environment which affect home-buying preferences. The same environmental benefit, view of water body, could command greater value in new towns. Perception of water body quality might have influenced consumer behaviour. For the whole urban area, water view would increase price by 8.2% (e0.079  1) and green space view by 8.6% (e0.083  1). Our results are comparable to findings obtained in other cities and indicate similar buyer behaviour in the housing market with reference to environmental elements. For example, Tyrva¨inen and Miettinen (2000) found that in the housing market of Salo in Finland, buyers have to pay 4.9% more to obtain a dwelling with a forest view. In Boston, it was found that when the distance to the nearest park doubles, the property price was expected to decrease by 6% (Tajima, 2003). In Emmen in the Netherlands, the price of a house with a garden bordering on water is on average 28% (7% contributed by the vicinity of a lake, 10% by a water view, and 11% by a garden) higher than the price of house without such attributes (Luttik, 2000). The different accorded values in these studies might reflect the differential provision and perception of environmental elements. In addition, it is conceivable that environmental externalities are also relevant to other social and economic attributes such as state environmental institutions (Kiel, 2005). Overall, the hedonic pricing method could be applied to the housing market in China to quantify the contribution of environmental externalities.

acquisition. The money that is paid in home purchase, reflected as a share of the property transaction price, reflects realization of the preferences. The actualization of wishes was probed by the hedonic pricing method. The hedonic analysis in Guangzhou indicates that floor area is the main variable influencing selling price, which is similar to empirical findings in western countries (Morancho, 2003). Other statistically significant variables are distance to major shopping area and work place, security, view of water body, plot ratio, and view of green space. The findings demonstrate notable similarities between the survey and hedonic analysis. The implicit values revealed by hedonic regressions have quite faithfully echoed home buying preferences. Thus the hedonic pricing method has been applied successfully in the Chinese context even at the embryonic stage of housing market development. Several discrepancies could be assessed. For example, proximity to work place is ranked a key factor in the survey (Table 3), but in the hedonic analysis it was only statistically significant for old towns (Table 6). People willing to take advantage of better environmental conditions in new towns, which tended to be situated farther away from employment opportunities that are more concentrated in old towns, would dampen the urge to live near work places. An element of factor compensation could be detected, with one good attribute substituting another. The differences in planning standards, built-form, development density and green space provision between old and new towns have shaped purchase behaviour. Although the opinion survey identified a wide range of important preferred housing characteristics, in actual consumption the attention focused on a small number of pertinent issues. Such attributes reflected by homebuyers’ consumption behaviour have overshadowed others that could not trigger actual purchasing.

4.6. Comparing questionnaire results and the hedonic analysis

In China, the urban housing market has developed rapidly especially since 1998 with the abolition of the subsidized housing allocation system. From then on, residents have had to face the real-world and find housing in the open market. This drastic change has presented new challenges to both supply and demand sides of the most expensive commodity for most people. Understanding home preferences and underlying factors of buying decisions could inform the development of the housing market. Getting it right at the germinal stage will nurture a healthy expansion path to fulfil consumer expectations and to forestall mismatches. Despite their pertinent applicability, few relevant scientific studies have been conducted to provide hints and directions. In Guangzhou, our opinion survey indicates that improving the living conditions and floor area are key motives for most homebuyers. A small proportion of residents would acquire properties for investment purposes. Selling price is understandably the top consideration. External factors dominated over internal (housing structural)

A comparison of the results of the questionnaire survey and the hedonic analysis of housing price provides hints to the links between consumers’ wish lists and real-world consumption behaviour (Tables 3–6). The two sets of findings demonstrated interesting similarities. Home buyers are willing to pay for what they prefer, desire or value. For instance, both studies identified the importance of security, with buyers paying 11.9% (e0.109  1) more to improve security, if other attributes of the houses were the same. The locational preference was emphasized by both studies in choosing homes near major shopping areas and workplaces. Both studies identified internal and external (nearby) environmental conditions as key issues in home acquisition. Besides ready access to usable green spaces, availability of green and water views was stressed. The opinion survey extracted consumers’ preferences aspects, indicating background considerations in home

5. Conclusion

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ones in both housing preferences and hedonic demarcation of selling price. The importance attached to security is somewhat unexpected, reflecting a general feeling of dissatisfaction in law and order of the burgeoning city. The quality of property management was rated as important, again implying a general sentiment of inadequacy and yearning for improvement. This factor is to a certain extent associated with security. Proximity to shopping area, work place and convenient public transport, which are mainly found in core city areas, denotes a common wish to save time and effort on travelling. Such an inclination could contradict the preference for good environmental quality and good security which are less available in busy areas. General environmental condition, both inside and around residential grounds, also echoes heightened awareness and desire for improvement. Some commonly recognized factors, such as the quality and design aspects of properties, are considered less important. Similarly, proximity to school and metro station has unexpectedly been rated less important. Green spaces and water bodies in urban areas play an important role in enhancing local amenities, landscape and recreational opportunities. The positive and statistically significant coefficients of such views in the hedonic regressions demonstrate that homebuyers would pay for these environmental externalities. To the municipal government, the environmental, social and economic values of having nature in urban areas have always been difficult to assess. Without an objective and scientific valuation, it is difficult to get sufficient financial support for its provision and protection. This study approach could extract and value the environmental externalities embodied in the housing market. The disbursed sums could be used to justify investments on nature conservation and urban greening. In promoting housing development, governments could employ the research results to convince developers to provide more and better environmental elements. Some discrepancies exist between our findings and the housing studies of other Chinese cities. Regional housing markets show variations, even though they all operate under an apparently similar macro-scale political and social framework. Part of the differences might be linked to the inclusion of different variables in constructing the hedonic pricing model. In similar studies, it would be important to admit appropriate variables to reflect adequately the relationship between housing price and its contributory factors. For international comparison, the present disparities between the housing market in China and western countries, with reference to home buyer preference and behaviour, are expected to disappear gradually in the course of the country’s modernization. The recent housing reform in China aims at strengthening the real-estate sector to serve as a driving force for economic development. The realization of this objective requires efficiency gains, fine tuning and rationalization of the housing market. It needs more accurate prediction and determination of housing prices (Bin, 2004), and better

matching between housing supply and consumer demands. The premiums attached to environmental attributes, increasingly pursued to enhance quality of life, should be factored into housing price. Including green spaces and water bodies would raise the attractiveness and price of the residential properties. In conjunction with the nation-wide rapid expansion of urban areas, extensive agricultural lands have been engulfed by developments. Instead of the indiscriminate obliteration of nature and rurality, a precision planning approach could be combined with a limited impact development strategy to preserve areas with high-quality farmlands. Whereas some protected green fields could continue to practise agriculture, others could be converted to woodlands or naturalistic green spaces to be incorporated in the future town plan as valuable nature-in-city enclaves. In addition to providing the wide range of ecosystem services, such green spaces could provide venues for passive recreation in a welcome countryside ambience, and pleasant scenic amenities if they fall within the viewshed of nearby residences. Rapidly expanding cities in China and other developing countries have a golden opportunity to plan for the inter-penetration of city and nature. Governments with the vision to grasp such fleeting chances are desperately needed to create truly liveable and sustainable new city areas. Such value-added elements will lift the total sale value of developments, and developers could obtain a better return on investments. More valuable properties could in turn permit the government to raise more property and business taxes, part of which could be ploughed back to the community to enhance infrastructure and amenities. Residents living in a green and pleasant neighbourhood tend to be happier, healthier and more productive. However, housing should be more than just a blinkered concern for economic efficiency and growth (Green and Malpezzi, 2003). Like western countries, housing constitutes the largest asset of most Chinese families. The housing market and related policies would profoundly affect not only economic life but also social goals in any society (Kleinman, 1996). Overall, taking environmental issues seriously in housing developments offers an important path to the broad sense of sustainable urban growth that encompasses economic, environmental and social dividends. Acknowledgements The authors would like to express gratitude to the research grant support kindly provided by the Hui Oi Chow Trust Fund and the Committee on Research and Conference Grants of the University of Hong Kong. References Anderson, L.M., Cordell, H.K., 1988. Influence of trees on residential property values in Athens, Georgia (USA): a survey based on actual sales price. Landscape and Urban Planning 15, 153–164.

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