Values of amenities in coastal zones

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Any policy of coastal zone protection and land use planning would benefit from a better idea of the benefits and costs associated with different patterns of land use. The pressure on the coasts is coming from individuals who derive benefits from living near the sea. Yet the same actions are causing external costs in the form of reduced visual benefits and reduced access to others who enjoyed these environmental services before. The aim of this article is to report on research that has valued such benefits and costs.

There are a few studies available of the value of coastal landscapes. Here we divide them into those that value a landscape for households that own and occupy or households or hotels that rent property with a sea view, and those that relate to the value of a landscape from individuals who are not occupiers of property on the coast. The latter are divided into people that visit the coast or live in coastal areas but not in close proximity to the sea, and people that want to see the coast preserved but do not visit the coast (the so-called non-use values). Often these two sets of values are in conflict: for owners to capture the value of a sea view means detracting from the value those visitors may get from access to a sea view or access to a beach or may wish to see it preserved for its own sake.

Values of Coastal Landscapes for Owners or Occupiers of Property

The value of visual amenity

The technique most used to value the benefits of visual amenities from property is referred to as the hedonic method, where house price data are used as the basis for calculating premiums placed on houses in locations with different landscape attributes. In this section studies that value coastal and lake views are reported.

Benson et al (1998)[1] conducted a hedonic study of the impact of views on property prices in Bellingham, Washington. They found a significant price premium associated with different types of views. They derived seven different categories of views finding a premium of 58.9 percent for an “unobstructed ocean view” down to 8.2 percent for a “poor partial ocean view”. A lake view adds less (18.1 percent) than an ocean view in most cases, but lake-frontage is found to add 126.7 percent to house prices – capturing aspects of the recreational amenities that are additional to the amenity value provided by the view itself. This study shows the potential for the use of hedonic analysis to further understanding of the valuation of unimpeded views relative to other types of views.

Fraser and Spencer (1998)[2] considered the residential land amenity of an ocean view by a scoring system based on three sub-characteristics of the view based on housing data from 114 sites in Western Australia. The three dimensions they used are degree of panorama, potential loss of view and elevation. The potential loss of view dimension introduces both time and uncertainty into people’s valuation. They find that the first two characteristics are dominant over the third, which was therefore not included. They also find diminishing marginal utilities to the purchaser as the level of each of these characteristics increases. A scoring matrix was used to determine the quality of the ocean view for each site. They estimate that for the best views with the lowest likelihood of the view being lost the view adds a premium of an extra 25 percent to the house price. The important point this study makes is that the impact of an ocean view on property will depend on how certain the purchaser is that the view will remain and not be blocked in the future. (See also Abelson and Markandya, 1985).

Bond et al (2002) [3] investigated the impact of views of Lake Erie on residential property using transaction based house prices. This was an analysis based on building codes, which reflected whether a house had a view or not. Having the desirable view of Lake Erie was shown to add an 89.9 percent premium to the house price.

Parsons and Wu (1991) [4] used a random draw of 1,435 houses sold in 1983 from one county on the Chesapeake Bay coast, Maryland, USA. They used their findings to estimate the impact of regulations requiring houses to be built further away from the waterfront by estimating housing development over time under various restriction scenarios. Using hedonic analysis, they distinguish impacts on three types of properties of different land use regulations: houses with frontage, views and distance from the water. They find that the value of lost frontage, views and distance leads to a loss of between $74,763 and $96,672 (depending on the econometric model). For loss of views and distance alone there is a loss of $6,553 to $7,883, and with distance by itself there is a loss of $233 to $524 per property. Hence the value of frontage alone would be in the range $68,880 to $90,119. As a percentage of the price of a house this amounts to a premium for sea frontage of between 75 and 98 percent.

In Europe Luttik (2000) [5]uses hedonic analysis to identify price premiums for different landscape types in the Netherlands. Using a sample of almost 3000 transactions, Luttik finds a premium for houses in attractive landscape types of 5-12 percent over houses in less attractive landscapes. Houses overlooking water attract a premium of 8-10 percent, whilst those overlooking open space attract a 6-12 percent premium.

Muriel et al (2006) [6] conducted a hedonic analysis for Finestère in France. Using a sample of 185 houses in 2005, they derive a property premium of 78 percent for a house with a good view of the sea compared to one without any view of the sea. They also assess the responsiveness of house prices to distance from the sea, finding an elasticity of -0.087 – i.e. a one percent increase in distance from the sea results in a 0.087 percent decline in property value (at an average distance of 6.5 kilometre). So a house that is 3 kilometres from the sea as opposed to 6 kilometres would have a value that is 4.3 percent higher. One that is two kilometres would have a value that is 6 percent higher. These numbers look rather low but are the only ones we could find that estimated a decay function.

A study in Israel (CAMP Israel, 2000) estimated increased room rates for hotels along the seashore of the country. It found accommodation within 2km of the coast charged rates that were about 39 percent higher than in similar classes of hotels further away from the sea.

Although the results do vary by site, there is some agreement across them. As a rough guide, a property with an uninterrupted ocean view will attract a price premium of between 25 and nearly 100 percent. The premium will be less for a partial view – perhaps a low as 8 percent for a ‘poor partial view’. The Israel study estimates hotel premium rates of 39 percent. The ‘decay’ function with respect to distance from the sea implies a decline in values of about 9 percent for households that are up to one kilometre from the sea as opposed to half a kilometre. There is no doubt, however, that more studies are needed to answer questions about the impact of density of housing and access to the beach on the value of such properties.

Values of Coastal Views and Access to Non-Property Owners

There are a number of different processes that can be used in order to value coastal views to non-property owners. These include:

  • The Value of Enjoyment (VOE) approach
  • Travel costs and CV approaches
  • Other non-valuation approaches

The VOE Approach

The most common in the literature is often used to value the recreational amenity of a beach, and is known as the Value of Enjoyment (VoE) method. This is included in the ‘Yellow Manual’, produced by the Middlesex University Flood Hazard Research Centre (Penning-Rowsell et al 1992) [7] and recommended by the UK government for valuing coastal protection (Whitmarsh et al. 1999)[8]. It elicits stated preferences by the use of a direct open question about the value placed on the enjoyment of a visit to the beach, and so does not require any payment vehicle to be expressed and avoids the possible biases that payments vehicles can bring to CVM studies (Marzetti 2003:17) [9]. In order to help frame this value, a VoE question should invite a comparison between the beach in question and alternative recreation sources. This also brings the respondent to consider the trade-off between using the beach and the alternative sites. As Whitmarsh et al. (1999: 455) [10] conclude, “By thus focussing on choice and sacrifice, it attempts to go to the heart of the problem of economic valuation.” However, they also note that VoE results are not limited by people’s income (ibid: 461).

The best Mediterranean European data for the value of enjoyment from beach use appear to be those from Marzetti (2003) [11] and Camp Israel (2000). The former uses Value of Enjoyment surveys for four beaches, of which only two have usable survey sizes. The beaches are Lido Di Dante on the North Adriatic Cost near Ravenna and the Barcola Seafront in Trieste. Their mean daily use values are reported in Table 1. The Israel study combines travel cost and other revealed expenditure data to estimate the value of beach visits. Its results are discussed further below.

The Marzetti study results in Table 1 show that the figures vary considerably between the two sites. The Lido Di Dante has three relatively distinct areas, varying by the levels of development – the least developed end is the most popular. Spring/ Summer values are between € 25 and € 32 and Autumn/ Winter values are between € 4 and € 20 . The standard deviations are large and do not exclude the possibility that the value may be zero for some individuals. Barcola is a crowded beach, and ‘New Beach’ is likely to be primarily used by locals. Values there are much lower – around € 5 to € 8 in Spring/ Summer and € 5 to € 6 in Autumn/Winter. Again the standard deviations are large.

Both sites have alternative beaches in the vicinity. We are not told the number of visitors to the Lido Di Dante, but we are told that there are 235,000 inhabitants of Trieste, and the survey found that 63.8 percent of residents visit the beach and that the beach is primarily used by residents, on average 20.9[12] days per resident. This gives an estimate of beach use of 3.1 million beach visits per year. A greater proportion of the town visits the beach in autumn/winter than spring/summer but spends a shorter time on the beach.

Table 1: Mean and Std. Deviation of Daily Use Values of Beach Use In Italy (Marzetti (2003)

Travel Cost and CV Approaches

The range of values given above is comparable to those found in a wider literature. Whitmarsh et al. (1999) [13] provide a summary of their own and other studies of coastal recreation. Their valuations range from € 12.42 to € 15.98 for the UK and € 4.27 to € 52.98 per person per day for the USA (all adjusted to 2001 €). The large figure in the USA was found using the Travel cost method for out-of-state visitors to Florida. The next highest US study found € 15.17 per person per day. The studies give no indications of the size of the beaches or the numbers of people visiting. Landry and McConnell’s 2004 [14] study used travel costs to estimate the value placed on recreation at two beaches in Georgia, USA. The survey was carried out over three seasons with over 2000 observations, and found valuations of € 7.72-€ 9.16 for one beach and € 17.01 - € 18.75 for a nearby alternative. Sohngen et al. (1999) [15] studied visitors to two beaches in State Parks on the coast of Lake Erie, USA. One of the beaches is 1 mile (1.61 km) long – the longest beach in Ohio – and both beaches have other recreational features nearby, such as hiking trails and fishing[16]. They find that the beach with more features has a higher valuation (€ 31.53) than a site that is more beach-focussed (€ 19.09). Polomé et al (2005) [17] summarised the literature on coastal defence, and in doing so, developed a benefit transfer function for beach recreation. They found shortcomings in the data arising from studies not presenting the total number of visitors to beaches and numbers of visits per visitor and on-site sample bias. They use 106 observations from 38 different sites in the UK, USA and the Netherlands. The studies were mainly from the 1990s but went as far back as 1975, and were predominantly VoE studies. They find that the average value is around € 16 for UK beaches and € 22 for US beaches (p.837, both figures have been converted to 2001 €). There were not enough studies to obtain a value for the Netherlands. However, there is still large uncertainty about these figures. They give the overall average value of informal recreation to be approximately € 20 (2001 €) per visit (p. 839). They also find that the date of the study makes little difference to the valuation, i.e. studies in the 1970s give similar valuations to later studies. On the other hand the concept of value used such as VoE, WTP etc, is highly significant in determining the result. This could mean that the benefit transfer is flawed, since different types of valuation give different results, or it could be that the differences in value are genuine – the USA studies typically used Consumer Surplus measures whilst the UK typically used VoE.

The CAMP study in Israel provides some useful additional material from another Mediterranean littoral state[18]. Surveys of vacationers were carried out in 1982 and 1994. Based on these the researchers estimated that the 13 million annual beachgoers spent NIS98 million on travel to the sites, 25 million on entry fees and 8 million on parking. In addition another 18 million persons visited areas close to the beaches, spending NIS 79 million. To this total of NIS 210 million they added a consumer surplus of 70 percent, making a total willingness to pay of NIS 357 million[19] in 1999 prices. Converting to 2001 prices, and euros we get a figure of € 3.5 per visitor. This is considerably lower than the EU/US values presented previously but then Israel has a lower per capita income than the countries from which the other values were obtained. The Israel study is also valuable as it is the only one that provides an estimate of the non-use value. A 1999 survey asked households what they would be willing to pay to prevent further construction on the coast. The value that emerged was NIS 31/year, or around € 9.4 in 2001 prices. This is significant as it applies in principle to the whole group from which the sample was drawn – i.e. the 1.6 million households in the country. Thus the gross annual WTP amounts to € 15 million. Some more conjectural is converting this to a value per kilometre of coast. Of the country’s 188 km coastline 50 kilometres are used for national infrastructures and defence uses and are closed to the public. The remaining coastline has been designated as follows: 59 kilometres as municipal shores (adjacent to urban settlements), 43 kilometres for preservation as nature reserves and national parks, and 36 for open space (free of all infrastructures and facilities). Thus at present about 79 kilometres are undeveloped. The WTP then amount to € 0.12 per household per kilometre per year.

Other Non-valuation Approaches

Some information on the value of landscapes affected by development can be gleaned from other landscape studies, not related to coastal landscapes. Arriaza et al (2004) [20] carried out a survey requiring participants to rank the best and worst pictures in a series. The first few pages summarise the theoretical/ philosophical literature on what landscape is and methods of describing and comparing different landscapes. 226 people were shown 10 panels, each with 16 randomly assigned photographs of the landscape in question (Andalusia, Spain). The photos were chosen to capture the relevant features of that landscape, with and without other features (e.g. olive trees with and without other herbaceous cover, with and without ‘pretty’ buildings, with and without industrial buildings). The best 4 and the worst 4 pictures in each panel were scored from + 4 to - 4. These scores were used as the dependent variable in a regression. A panel of researchers assigned each picture a score based on the pictures contents e.g. amount of water, presence of positive man-made elements, and degree of wilderness according to a strict scoring system. They found that the degree of wilderness and positive man-made features have the biggest impact upon a view’s desirability. The next most influential factors are the area of water and the colour contrast. This seems to suggest that positive building, for example houses in keeping with the area, can increase the attractiveness of a view. This study uses a methodology and is well grounded in the theoretical side of landscape evaluation. However, it is unlikely that the results will be very transferable to coastal areas, since people value different landscapes for different reasons, e.g. positive manmade elements may be valuable in some agricultural landscapes such as Andalucía or the Cotswolds, but on coastlines they would be less welcome.

Another approach to valuing landscapes is that of Dramstad et al. (2001) [21]. They used the Norwegian national monitoring programme for agricultural landscapes (the 3Q programme) as a case study, focusing on biodiversity, cultural heritage and human experience of the landscapes. A total of 1474 sample squares of 1 km x 1 km distributed over the country in proportion to the amount of agricultural land. These are taken on a 5 year rotation, so changes are recorded after 5 years. The first round was in 1998.

Dramstad et al. (2001) looked in particular at heterogeneity in landscapes as a common variable in analyzing biodiversity, cultural heritage and human experience. Heterogeneity of land types is found by dividing the 1km square into 100 sub squares and seeing how many sub squares are different in land type to their neighbours. This forms the heterogeneity index. Preferences for landscapes were found through asking people to rank photographs and text descriptions of the landscape within each square. Photographs were used to represent clearly defined levels of openness. Increasing heterogeneity was found to be a positive change for all aspects of the landscape-based values. This partially supports the Arriaza et al. 2004 [22] finding that landscapes with some human construction can be deemed attractive, but it does not provide data directly relevant to coastal zones. Nor does it indicate which kinds of development are desirable. Nevertheless the results are a useful warning that one should not regard all man-made development as ‘bad’ and that in some cases it can enhance the value of a landscape. More work is needed on the valuation of coastal landscapes using this promising framework.

As far as coastal landscapes are concerned a couple of studies have been conducted in the UK and one in Turkey using non-economic approaches. Morgan and Williams (1998) [23] asked coastal managers and students to rank 70 beaches in Wales. They found that the number of people on the beach did not significantly affect the scores given to different beaches, but undeveloped beaches scored better than those where anthropogenic structures were present. Beach commercialization had an impact only on the rankings of the students.

The other UK coastal study evaluated beach litter, to see which items were most offensive and which were less so (Tudrof and Williams, 2003) [24]. Not surprisingly people found items that were potentially harmful as the most offensive (syringes, gas canisters), followed by sewage related debris (sanitary towels, condoms). Least offensive were items of natural origin, such as seaweed and driftwood.

The Turkish study (Ergin et al., 2006 [25]) develops measures of coastal scenery based on scores derived from a fuzzy logic analysis. The methodology considers 26 coastal scenic assessment parameters which cover physical and human factors. They find top preferences for beach goers in Croatia and Turkey were absence of sewage, water colour and absence of noise and buildings. Access to the beach and landscape features appeared fifth and sixth respectively in Croatia.

These kind of rankings could be linked to values of these different features of a beach but that has not been done as far as we can see.

Conclusions on Valuation of Coastal Views and Access

The value of beach access vary according to the services provides and degree of crowdedness. There appears, however to be range of between € 5 and € 30 per visitor per year for European studies and € 5 to € 15 for US studies, if we exclude some outliers. In Israel, representing a lower income country values are also lower, at about € 3.5. The Israel study also provides the only non-use value of conservation of € 9.4 per household per year. While the numbers obtained above are useful, they leave a lot or questions unanswered. We do not know the value of an uninterrupted beach view when simply visiting a coastal area, and how this value is affected by coastal development or other factors relating to the beach. Some of the non-valuation studies provide useful information but it still remains to link it to monetary values. We also do not know the impact on beach visits when access to the nearest beach is impeded. Do individuals go to another beach further away (thus losing welfare) or do they go the same beach but incur a higher cost?

This article is part of the case study on urbanization in Mediterranean coastal zones.

Related articles

Travel cost method
Contingent Valuation Method
Hedonic Evaluation Approach
Value Transfer
Economic Value
Total Economic Value
Socio-economic evaluation
Non-use value: bequest value and existence value
Multifunctionality and Valuation in coastal zones: concepts, approaches, tools and case studies
Multifunctionality and Valuation in coastal zones: introduction


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  2. Fraser, R. and G. Spencer (1998) “The Value of an Ocean View: an Example of Hedonic Property Amenity Valuation.” Australian Geographical Studies 36(1) 94-86
  3. Bond, M.T, V.L Seiler and M.J Seiler (2002) “Residential Real Estate Prices: A Room with a View”. Journal of Real Estate Research 23(1/2) 129-137
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  12. The average number of days spent on the seafront in Spring and Summer is 23.5 and in Autumn and Winter is 18.3; assuming these are equal numbers visiting in both seasons the average days per resident spent on the beach is 20.9. The report does not give clear indications of how the number of residents visiting the beach per season changes, but it does tell us that 73.5 percent visit the seafront in autumn and winter, suggesting it is if anything higher in winter.
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  14. Landry, C. E. and K. E. McConnell, (2004) "Hedonic Onsite Model of Recreation Demand", Paper presented at the Southern Economics Association 74th Annual Conference, New Orleans, LA 2004.
  15. Sohngen, B., F.Lichtkoppler and M. Bielen, (1999)"The Value of Lake Erie Beaches", FS-078 Ohio State University
  16. The two beaches are Headlands and Maumee Bay. The Ohio State Parks websites outline the key recreational features for the Headlands and for the Maumeebay beach.
  17. Polomé, P., S. Marzetti and A. van der Veen (2005) “Economic and Social Demands For Coastal Protection” Coastal Engineering 52 819-840.
  18. Discussions with Israeli researchers revealed considerable doubts about the quality of this study. Nevertheless we include it as one of the very few that provides orders of magnitude estimates from a Mediterranean state.
  19. The study also adds local expenditures by the municipalities to provide cleaning services etc. of NIS 145 million a year. In our view, however, this is not appropriate. These outlays are a cost of providing the services that the visitors enjoy, in which case it should be subtracted from their expenditures to arrive at a net willingness to pay. Since other estimates are not net values we have not made such a correction but equally we have not added the municipal expenditures to the visitors WTP.
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  25. Ergin, A., A.T. Williams and A. Metcalf (2006) “Coastal Scenery : Appreciation and Evaluaton” Journal of Coastal Research, 22, 958-964.

The main authors of this article are AnilMarkandya and Mariaester Cassinelli
Please note that others may also have edited the contents of this article.

Citation: AnilMarkandya; Mariaester Cassinelli; (2020): Values of amenities in coastal zones. Available from [accessed on 20-06-2024]