The value of trees, water and open space as reflected by house prices in the Netherlands
House price varies by landscape type. Attractive landscape types were shown to attract a premium of 5-12% over less attractive environmental settings. The most influential environmental attribute in the study is the presence of water features.
Luttik, J. (2000). The value of trees, water and open space as reflected by house prices in the Netherlands. Landscape and Urban Planning, 48(3-4), 161-167.
An attractive environment is likely to influence house prices. Houses in attractive settings will have an added value over similar, less favourably located houses. This effect is intuitively felt, but does it always occur? Which environmental factors make a location an attractive place to live in? The present study explored the effect of different environmental factors on house prices. The research method was the hedonic pricing method, which uses statistical analysis to estimate that part of a price due to a particular attribute. Nearly 3000 house transactions, in eight towns or regions in the Netherlands, were studied to estimate the effect of environmental attributes on transaction prices. METHODOLOGY Broadly speaking, there are two ways to establish the value-increasing effect of a specific housing attribute. The first way is to ask the people concerned, for example residents or estate agents, how they value a particular attribute. A second way is to derive the value from actual behaviour. The hedonic pricing method (HPM) is an example of the latter. Assuming that houses are valued for their several attributes, housing transactions are examined to estimate that part of a price due to a particular attribute. There are two categories of attributes: the structural characteristics of the house, like plot size, house type or number of rooms, and the locality, which may be valued positively or negatively. Although our analysis focuses on environmental attributes, which make tip a relatively small part of total house price, the HPM requires that all attributes that affect house price are included in the analysis. In 1995, a pilot study based on the HPM was carried out in Apeldoorn, a medium-sized town in the east of The Netherlands (Fennema et al., 1996). This study analysed 106 house transactions in a relatively new district, which is built round a park. The study demonstrated that location within 400 m of the park attracted a premium of 60% over houses located outside this zone. In addition, a house with a park view appeared to attract a premium of 800.
Some of the most salient results were as follows. We found the largest increases in house prices due to environmental factors (up to 28%) for houses with a garden facing water, which is connected to a sizeable lake. We were also able to demonstrate that a pleasant view can lead to a considerable increase in house price, particularly if the house overlooks water (8-10%) or open space (6-12%). In addition, the analysis revealed that house price varies by landscape type. Attractive landscape types were shown to attract a premium of 5-12% over less attractive environmental settings. The most influential environmental attribute in the study is the presence of water features. This corresponds with findings from landscape psychologists. As is stressed for example by Kaplan and Kaplan (1989): "Water is a highly prized element in the landscape''. Current town developments in the Netherlands indicate that town developers are well aware of the value of water features, given the large number of plans that include water bodies. As stated in Section 1, the Dutch government is searching for alternative sources of finance for creation and/or maintenance of nature and landscape features. Given the immediate effect of water features, as opposed to green areas which need time to mature, and the high premium water features seem to attract, they seem to be the major candidate for private finance or joined public-private finance.
EXSUM | C 2000 Elsevier Science B.V. All rights reserved. * E-mail address: firstname.lastname@example.org (J. Luttik)