Methods and approaches for measuring the benefits of bathing waters
This part of the literature review brings together elements of the evidence relating to methods and approaches for measuring the benefits of bathing waters and the implications of variations of a change (improvement and deterioration) in BWQ in terms of the benefits identified on local and national economies. As we have seen above, these impacts can be wide-ranging and go beyond the purely economic impacts on tourism and employment, to include impacts on people's health and well-being, as well as, social and cultural benefits for visitors and local communities alike. Under this theme, this part presents findings on the following research sub-questions (see Table 2.1) in the order they are presented below:
- SRQ1.2_How are (or can) the range of benefits of bathing waters being (be) measured?
- SRQ3.1_How are (or can) the costs and benefits of an improvement or deterioration in bathing water quality classification being (be) assessed?
- SRQ3.2_How can effects on national and local economies and short and long-term effects be accounted for in assessments?
Within the literature reviewed (see Appendix 2) there is a mix of qualitative and quantitative approaches, which are presented and discussed in terms of their appropriateness and practicality of use in a bathing water context. We find that the combination of revealed and stated preference methods, incorporating questions that identify current and intended use but also capture the emotional responses to these environments, to be a commonly used approach. While there is some evidence in the literature on how BWQ (among other beach characteristics) influences benefits derived from bathing waters there is little to no evidence relating to how changes in bathing water classifications may impact on these benefits. A study undertaken for the Environment Agency (eftec, 2002) and ongoing (as yet unpublished) work by eftec for United Utilities and Southern Water have, however, considered these aspects by estimating whether there would be a change in visit behaviour given changes in BWQ.
Methods and approaches
Revealed preference: Travel Cost Method ( TCM)
Revealed preference methods estimate the preference for a non-market (non-traded) good by observing consumer choice for market goods and services that are affected by the non-market good. Amongst these methods, the travel cost method and hedonic pricing have commonly been used to capture the value of coastal environments. Hedonic pricing, can measure the impact of the presence of different environmental attributes ( e.g. green or blue space, view of the sea etc.) on the housing market ( i.e. house prices). An example would be the impact of beach proximity beach as one the atributes of the total price of a property, when that is disaggregated and expressed as a set of attributes (Ghermandi et al., 2010).
In the travel cost method, what people spend on travel (a market service) to a beach is used as a proxy for how much they value the recreational experience of being at that beach. The travel cost method is particularly appropriate for the valuation of bathing waters at sites where: (1) There is no entrance fee; (2) services from the natural resource are consumed in situ; (3) there is a recreational appeal (Gillespie et al., 2016; Ballance et al., 2000). This method assumes that the travel cost represents the 'fee' that visitors are willing to pay to access, what is otherwise, a 'public' and free access good. Travel cost would be applicable even if there was an entrance fee.
Travel cost method collects data on what visitors spend on items like travel, accommodation, food etc. on a beach visit day, where they travel from and how, how long they stay in / near the beach and other factors that will help researchers analyse the visitor demand for the visits. The data can be collected from routine visitor surveys or specifically designed questionnaires applied to randomly selected sample of visitors – as will be in this research. The result is a travel cost across different types of visitors for different activities, as much as data allow. If the overall visitor population is known, the survey results can be extrapolated to the bathing site to calculate the recreational value of the particular site.
Most studies reviewed use some primary data collected on beaches for their calculations (Ballance et al., 2000; Coombes and Jones, 2010; Morrissey and Moran, 2011). Data collected includes:
- Number of visitors;
- Frequency of visits (over the last 12 months);
- Activities undertaken on the beach;
- Duration of stay;
- Distance travelled / time required / starting location for the trip; and
- Spending (local and other).
These studies almost always include qualitative elements aiming to capture visitors' preferences on beach characteristics and factors that influence their decision about which beach to visit. These are presented to respondents in the form of Likert scale questions that asks visitors to rate various characteristics in terms of their influence or significance on their decision, on a scale of 'Strong' to 'Weak' or 'Significant' to 'Insignificant'. Sociodemographic characteristics of respondents are also recorded.
Some examples of the travel cost method from the sources reviewed include:
- Morrissey and Moran (2011) used the travel cost method to capture both the economic and welfare value  ) of commercial recreational activities in the West coast of Ireland. They found that the welfare impact on consumers, frequently referred to in economics as consumer surplus, emerges from the utility individuals derived from: (1) engaging in a niche recreational market; (2) the sense of identity; (3) the ability to engage in recreational activities in an environmentally sustainable manner; and (4) the ability to engage with companies with local knowledge. This study calculated the mean consumer surplus at €2,500 per trip, while the average travel cost was estimated at €1,283 per trip, meaning that individuals received almost double the benefit from engaging in these activities in excess of their travel cost; and
- Gillespie et al. (2016) employed this method to assess the use value a fishery provides to anglers (in-situ benefits) in Ireland. The study estimated consumer surplus ( i.e. the welfare derived by anglers over and above what was paid for the trip) (per trip) resulting from the services provided from recreational fishing and used that to construct estimates of users' WTP.
Stated preference methods are used to estimate the value of benefits and outcomes for which there are no prices in the marketplace and for which there are no revealed preference data that would enable their estimate. They "represent the only known approach to estimate values for changes in many public goods, including environmental services, human health effects […]"(Johnston et al., 2017 p.320-321).
Stated preference methods involve questionnaires for eliciting individuals' preferences for a given change in environmental quality. The two main approaches are:
- Discrete choice / contingent valuation: Respondents are asked their willingness to pay ( WTP) to ensure an improvement or avoid a loss, or their willingness to accept (monetary) compensation ( WTA) to forgo an improvement or tolerate a loss. The questions can be asked in a variety of formats including open ended, yes / no questions for a given amount and 'bidding games' ( e.g. if respondent says yes to £x, they are asked a second question with a higher amount); and
- Choice experiment: Respondents are asked to indicate their preference among two or more options, each of which consists of a combination of attributes. The status quo is commonly included as one of the options. One of the attribute is a cost element which enables respondents' WTP or WTA to be inferred from the choices they make.
Some examples of stated preference valuation of improvements in BWQ from the sources reviewed include:
- Hynes et al. (2013) used a combination of choice experiment and contingent valuation to estimate the economic benefits attached to an improvement in BWQ. Expressed in mean visitors' willingness to pay the value of these improvements was estimated as €6.78 per beach visit; and
- Hanley et al. (2003) used a combination of revealed behaviour ( e.g. current number of trips to the beach) and contingent behaviour ( e.g. stated number of intended trips under a scenario of increased environmental quality) to estimate an average individual value for the improvement in BWQ of £5.81 per person per year.
What is important to document and be aware of is the generalisability of value estimates from stated preference methods especially when these are used to support decision or policy-making (Johnston et al., 2017). Similar warnings exist in Ghermandi et al. (2010) with reference to the use of economic values from a particular study site to another geographical setting, at a national or sub-regional scale, as bathing water sites as well as the beneficiaries may vary across locations. While these considerations are crucial when looking for examples across Europe, this should not impact the aggregation of benefits across Scotland for this study, especially since the methodology incorporates bathing sites that account for the diversity of bathing sites in Scotland.
Qualitative assessment: exploring emotional responses
One of the scales used to measure the social and cultural benefits of bathing waters is the Perceived Restorativeness Scale ( PRS) developed by Hartig et al. (1997) using the four restorative qualities identified in the attention restoration theory ( ART) and referred to in Part 3. The PRS presents beach visitors with a series of 26 statements to which they answer using a Likert scale of 0 to 6 to record their responses. The final restorativeness score is the result of the mean aggregated scores across these statements. Hipp and Ogunseitan (2011) used this method, in a study with more than 1,000 visitors in Californian beaches, which calculated the mean score on the Perceived Restorativeness Scale to be 4.8 out of 6.0. A simplified version of the PRS was used more recently by Wyles et al. (2016), who presented beach visitors with a ten point Likert scale from not at all (1) to very much (10), to rate the original four factors associated with the attention restoration theory ( ART). The same study also used the Circumplex Model of Affect (Russell, 1980) to measure the impact of bathing waters on their mood and levels of excitement as a result of visiting the beach. Visitors were asked how the beach makes them feel on a scale of 1 to 10 from sad to very happy and from very calm to very excited (Wyles et al., 2016).
Measuring the benefits and costs of an improvement or deterioration in BWQ
There is limited literature on the impacts of a change in bathing water classification on the benefits of bathing waters (Cascade Consulting and eftec, 2009; eftec et al., 2014; Accent, 2010; Mourato et al., 2003; eftec, 2002). However, there have been studies exploring the benefits and costs of an improvement in BWQ (Coombes and Jones, 2010; Gillespie et al., 2016; Hanley et al., 2003; Hynes et al., 2013; McKenna et al., 2011; Nahman and Rigby, 2008; Czajkowski et al., 2015). This section looks across this literature to identify approaches in measuring the impacts of such a change. There is also a relatively large grey literature on the impacts of implementing the Bathing Water Directive in England and Wales for the Environment Agency and water companies. While this literature is confidential and cannot be reviewed here, as eftec and South West Research Company were involved in most of these their experience is reflected in the research design for the on-site and on-line surveys to be used in this current study.
Across the literature, there is a common set of indicators that have traditionally been used to measure the benefits and costs of a change in BWQ.
A change in the number of visitors attracted to a bathing site or a change in the frequency of trips undertaken by visitors to the beach has been used in a number of studies as a measure of the impact of an improvement or deterioration in BWQ (Hanley et al., 2003; McKenna et al., 2011; Gillespie et al., 2016). The assumption is that visitors treat travel costs as a kind of price so, similar to any goods traded in the marketplace, a deterioration in the BWQ will reduce the benefit  that visitors gain from the bathing site (good), leading to a reduced number of trips to the bathing site, representing a decrease in demand (Gillespie et al., 2016). Hanley et al. (2003) measured the change in the welfare per trip  visitors gained by recording respondents' stated intended changes in behaviour. The results of their survey revealed that 63% of respondents stated they would visit the beach more frequently if water quality improved. A similar method was used by Coombes and Jones (2010) in exploring the impact of beach litter on visitors' behaviour; 85% of both tourists and residents stated they would not visit the beach if it had more than 2 items of debris per square metre, while for more than 10 items per square metre that rose to 97%.
eftec et al. (2014) estimate a trip-generating function which predicts the frequency of visits to 'at risk' bathing waters in England as a function of visitor and beach characteristics. The study relies on a survey of 7,000 visitors at over 40 'at risk' bathing waters in England. The trip-generating function investigates the impacts of the following factors on the number of visits by an individual to a single bathing water: distance travelled, visitor type, bathing water quality (poor versus otherwise), visitor expenditure, group size, visitor age, visitor income, and the availability of substitutes (other beaches) within three different distance bands.
Nahman and Rigby (2008) attempted to establish the difference between the impact of a change in BWQ, as opposed to, a change in the Blue Flag status of beaches in South Africa. For that purpose, respondents were presented with two hypothetical scenarios: a 10% decline in BWQ; or the withdrawal of the Blue Flag status. In a deterioration of water quality, visitors responded with a reduction in their visits by 39%, whereas under the loss of Blue Flag scenario visitors suggested only a 6% reduction in visits. Despite these results not being transferable to the context of the bathing water classifications in Scotland, they do show: (1) the importance visitors attribute to BWQ; and (2) the importance / extent of the influence of beach awards on visitors' behaviour. Therefore, the potential reductions or increases in bathing water trips "depends not only on genuine water quality improvements but on the satisfaction and public perception of the quality of the bathing waters, influenced by the media and beach awards" (Cascade Consulting and eftec, 2009: p.6). This presents an interesting line of inquiry and highlights important aspects for similar studies to consider.
Using the stated preference and revealed methodologies (reviewed in the previous section) these intended changes in behaviour can be translated into losses for the tourism economy emerging from reductions in annual recreational value and the total expenditure of visitors for travelling to bathing sites (the methodology for aggregating across local and national impacts is discussed in the next section). Estimates of an increase or decrease in visitor spend to a particular beach has also been explored as a measure of impact (McKenna et al., 2011). Nahman and Rigby (2008) estimated that economic loss in the range of £1.5 to £2 million per annum under the loss of a Blue flag status, and between £6 to £7 million per annum in relation to a deterioration in BWQ  .
Another common option in measuring the impact of an improvement in BWQ is the use of a choice experiment to estimate visitors' willingness to pay for improvements in water quality (Hynes et al., 2013; Czajkowski et al., 2015). This approach allows the researchers to explore, at the same time, other attributes that can offer a better understanding of factors that influence visitors' behaviour. Czajkowski et al. (ibid) use this method to estimate the economic value to a specific category of beach users ("active recreationalist") of potential improvements to coastal water quality.
Finally, there is a link between improvements in BWQ and the "potential for healthcare savings and a reduction in the number of lost working days " Oliver et al. (2016: p.58). Health benefits associated with better BWQ link to the reduced risks to human health from bathing, and mainly refer to respiratory illness, urinary infections, ear infections and gastrointestinal illness (World Health Organisation, 2003). Out of these illnesses, previous bathing water valuation studies have focused mostly on gastrointestinal illness, and, to a lesser extent, on ear ache. Mourato et al. (2003) estimated the marginal WTP for a 1% reduction  in the risk of gastrointestinal illness across all bathing waters in England & Wales to be £1.10 per household per year. These value estimates have been used by Cascade and eftec (2009) to estimate the benefits of a reduction in gastrointestinal illness, as a result of achieving compliance with microbial standards in Scotland, at £5.8 million (over 25 years). Alternatively, instead of asking for WTP, studies can estimate the exposure to health risks and incidence of illness and value these at cost of illness including medical costs and work days lost. In assessing the merits of a potential improvement in BWQ, the cost of achieving this improvement would need to be considered and may indeed exceed any health benefit estimates. Cascade and eftec, estimated the costs of achieving compliance with microbial standards at £81.3 million (over 15 years) compared to the £5.8 million benefit seen above. Still, the health benefits from a reduction in the insidence of gastrointestinal illnesses are only part of a wider range of benefits that would emerge from an imporvement in BWQ.
Changes in BWQ can have an impact on the benefits provided by these environments and the enjoyment visitors derive.Studies have shown that changes in the environmental quality of bathing sites negatively impact on the perceived restorative qualities offered (Hipp and Ogunseitan, 2011; Wyles et al.,2016). These changes can be measured using the PRS scale (see Part 3) and by presenting respondents in beach surveys with hypothetical scenarios of reduced or improved bathing water quality. This method, used by Wyles et al. (2016) to understand the impact of litter on perceived restorative quality, revealed that this was much lower  for beaches with litter. This negative impact extended to affect, with participants stating that they were unhappy and less calm in littered environments.
Effects on national and local economies: Aggregating benefits and costs
There are many approaches to addressing economic valuation of the benefits and costs of bathing waters. In the literature, the main criterion in choosing the most appropriate approach is the availability of data. The approach to measuring the benefits of an improvement in bathing water classification in particular, has been explored in a combined revealed and stated preference survey study for the Environment Agency which collected and analysed data on the benefits and costs of improving at risk bathing waters in England (eftec et al., 2014). The study focused on the recreational benefits of bathing waters but could include non-use motivations of users too. The study did not attempt to estimate the health benefits (avoided health risks from low BWQ) and did not perform a qualitative assessment of social and cultural values. The approach is nevertheless interesting in the way the benefits are estimated and aggregated from a bathing site level to the national level. The initial assumption, similar to the one we have seen in studies exploring the impact of changes in BWQ, is that deterioration in bathing water quality classification implies a reduction in visits per year. The approach to moving from that initial impact to the impact on the national population is summarised in the steps below (eftec et al., 2014):
1. Estimate the change in the number of visits: Visitors' stated intentions when presented with a scenario of changed bathing water quality;
2. Estimate the value per visit: Visitors' willingness to pay per visit calculated using travel cost method;
3. Aggregate benefit (or cost): Multiplying the avoided reduction or increase (reduction) in visits by the value per visit;
4. Estimate the value of a potential improvement in bathing water quality: Calculated as increased willingness to pay per household per year;
5. Extrapolate to calculate the national level value of improvements; and
6. Compare benefits (avoided loss of value) and costs (measures taken to attain an improved status): Calculate Net Present Value and the Benefit Cost Ratio to inform decision making.
Having calculated the value per visit (step 2 above) using the methods reviewed in previous parts ( e.g. TCM or stated preference), the extrapolation and aggregation of impacts is dependent on the availability of local and national data on the total visitor population and frequency of visits to bathing sites.
Alternative methods for aggregating impacts exist in relevant literature in similar areas, such as the valuation of improvements in freshwater quality. Austin et al (2007) adopted two approaches in benefit aggregation by:
1. Identifying specific effects of the improvement ( e.g. more visitors swimming or lower water treatment costs for managing authorities) and adding up the individual estimates to calculate the total benefit; and
2. Estimating the effect of the improvement on property values in the adjacent areas and aggregating that to calculate the total benefit (see earlier references to hedonic pricing).
Revisiting the previous point regarding data availability, the latter approach is a useful axample of a single measure (property value) that is aggregate in that it "reflects how individuals value all of the various disaggregated benefits associated with restoration of any given area" (Austin et al., 2007 p.6)
Various surveys have tried to estimate the economic value of Scotland's bathing sites including:
- Hanley et al. (2003) combined information on the average number of trips to the beach per person across the local population to estimate the aggregate benefits of the total number of trips undertaken in a year. This figure added up to £1.25 million per annum, although calculations were caveated on assumptions on the population's trips to the beach due lack of actual data; and
- Fife Council (2000) estimated that from 250,000 visits to Fife's award beaches there is a £232,800 spend and that for every £1 spent around Fife's award beaches £20 goes back into the local economy  . In a later study in 2006 on the value of the Fife Coastal Path an annual net expenditure was estimated at between £24-29 million, with beaches mentioned as one of the key strengths for visiting the area by a quarter (26%) of the 480,000 to 580,000 estimated visitors (Fife Coast and Countryside Trust, 2007). Amongst visitors staying overnight, visiting the beach was mention by 46% of respondents  . Keep Scotland Beautiful (2004) estimated the average spend per person per visit to be £2.80 for non-award beaches, while it averaged at £3.00 for Seaside Award beaches and £7.80 for Blue Flag beaches.
An issue in the calculation of the impact of improvements at a wider level is the displacement effect (Cascade Consulting and eftec, 2009; McKenna et al., 2011; Oliver et al., 2016;). Provided with the choice of a bathing site with improved BWQ, visitors of a bathing site may decide to simply change their destination instead of increasing the overall number of visits to the beach. Thus, at the local level improved beach gains visitors, which is a benefit to the local economic; but at the national (or even regional) level, other beach(es) lose visitors and hence gain in one could be offset by the loss in others: "overall, these effects contribute to a transfer of Scotland's tourism wealth from one location to another" (Cascade Consulting and eftec, 2009: p.8).
Similarly, given a restricted budget for the management of a number of beaches across a region, the beach managing authority may decide to allocate resources on improving the quality of bathing waters on a particular bathing site, hence retracting resources that may be necessary for maintaining the BWQ in another site (McKenna et al., 2011) (these issues are explored further in Part 7 below).
Estimating local economic impact for Scotland's bathing waters
In Scotland, local economic impact analysis utilises the Scottish Input-Output (I-O) tables (Scottish Government, 2016). The tables use the 2007 UK Standard Industrial Classification ( SIC) of economic activities. Tourism, and coastal tourism are not neatly covered by the SIC codes used in the I-O tables. This explains why tourism has been assessed separately to other industries in Scotland in studies such as the Tourism Multiplier Study (Surrey Research Group, 1993) and the subsequent development of tourism satellite accounts ( TSAs) (Scottish Government, 2005). The Tourism Multiplier Study is now considered out of date and is no longer used in estimating local economic impacts related to tourism. Further, TSAs are no longer produced, even though elements of TSAs are used to estimate non-resident expenditure in the Scottish I-O tables.
As part of this research, the team contacted economists in the Scottish Government with experience of developing and or using the Scottish I-O tables as part of local economic impact analysis. This was based on helpful suggestions provided by the steering group. These contacts confirmed the findings above. They also suggested that the approach used in Scotland to assess the Commonwealth Games ( CWG) spending (Scottish Government, 2015) could be a possible approach to consider. However, further investigation showed that the method – which was developed over a number of years in the planning, delivery and legacy of the CWGs – would require complex modelling which is beyond the scope of this study. Further, the model relies on data regarding regional Local Authority employment by industry which is not publicly available and internally held by the Scottish Government due to disclosure issues.
The information above suggests that:
- Previous work to assess the local economic impact of tourism is now dated and no longer being used;
- The published Scottish I-O tables do not provide the level of specificity required to assess the local economic impact of tourism and in particular coastal tourism; and
- A possible method following the approach used for the CWG could be applied to estimate the local economic impact of beach visits. This method would require complex modelling which is beyond the scope of the current study.
Based on this, the suggestion is to use the Cambridge Model as outlined in the study's proposal and briefly described in Box 4.1 below.
Box 4.1: The Cambridge Model
The Cambridge Model is a computer-based model originally developed to calculate estimates of the volume, value and economic impact of tourism on a County or District basis. It draws on the combined experience of PA Cambridge Economic Consultants Ltd, Geoff Broom Associates and utilises a standard methodology capable of application throughout the UK. It therefore offers the potential for direct comparisons with similar destinations throughout the country. The approach was the subject of independent validation (R.Vaughan, Bournemouth University) in December 1994. The Model was judged robust and the margins of error acceptable and in line with other modelling techniques. Whilst the main part of the model was developed for tourism use the expenditure, employment and GVA approaches can be adapted to suit any situation with the use of updated specific data being applied to the model as it will be in this study.
The model was developed specifically to estimate the local economic impacts of tourism. It is applied by being populated with local data as much as possible. In this case, local data will be used to ensure that the model provides an accurate reflection of the economic and social parameters that are characteristic of Scotland ( e.g. wage costs, employment data, population data, other socio-economic data, etc.). The Cambridge Model has been successfully used in previous studies in England which have focused on bathing waters, notably by the Environment Agency in the Bathing Water Valuation Study (eftec et al., 2014). Using the same model, adapted to Scotland, would make the results from this study comparable to previous studies  .
In the longer term, there is the option for the Scottish Government to utilise the CWG approach using internally held data within the Scottish Government. This would require data about visitor spend at beaches which the on-site survey at the five survey locations will collect. Having this data (visitor spend per site) gives some flexibility regarding which approach(es) to use in the future  .
Healthcare savings / reduction in the number of lost working days
Benefits of improving BWQ in terms of avoided illnesses (and related medical costs and work days lost) can be estimated using two approaches: willingness to pay ( WTP) to avoid the risk (or certain case of illness) or cost of illness methods. The former is done via stated preference where respondents are presented with the symptoms of the illness, and the risk of them contracting it. However, as most UK studies, including the one by eftec et al. (2014) show, most beach visitors do not come into contact with the water during their visit. This would make it difficult to ask a meaningful WTP questions (to those who are not exposed to the risk), and difficult to find those who are exposed to the risk. This also shows that, while unit health costs (per person or per incidence of illness) could be high, the total cost could be low.
Therefore, cost of illness method is preferred as being more practical. On-site survey of visitors can collect data on the proportion of visitors immersing themselves (head in particular) in water – which is the main risk factor, and their past experience of (self-reported) illness due to BWQ (including how long they lasted for and how long ago they occurred). This provides the number of likely cases of relevant diseases which can then be valued using medical costs and lost work days using average wage rates in Scotland.
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