scoping study into the use of recreational surveys for economic

Scoping study into the use of recreational

surveys for economic valuation

NEE0906

Final Report

for the Department for Environment, Food and Rural Affairs

July 2010

eftec 73-75 Mortimer Street London W1W 7SQ tel: 44(0)2075805383 fax: 44(0)2075805385 [email protected] www.eftec.co.uk

mailto:[email protected]

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Scoping study of recreational surveys for economic valuation – Final Report

eftec July 2010 i

This document has been prepared by:

Economics for the Environment Consultancy Ltd (eftec)

73-75 Mortimer Street

London

W1W 7SQ

Authors:

Dr Rob Tinch

Dr Dugald Tinch, University of Stirling

Dr Stephanie Hime

With input from:

Allan Provins

Professor Ian Bateman, University of East Anglia

Professor Nick Hanley, University of Stirling

Dr Paulette Posen, University of East Anglia

Reviewed by:

Ian Dickie

Allan Provins

Acknowledgements

The study team would like to thank the project steering group, consultees, and

others who have helped with data or queries, and with comments on an earlier

draft:

Kevin Andrews, Sarah Andrews, Eszter Ballo, Ralph Barnett, Ian Barrett, Amanda

Brace, Rob Bradburne, Janice Clark, Rebecca Clark, Sam Cunnington, Rob Curry,

Alison Darlow, Brett Day, Helen Dunn, Murray Ferguson, Magali Fleurot, Pippa

Gibson, Simon Gillham, Martin Gorringe, Chris Greenwood, Rebecca Hand, Julian

Harlow, Carol Hrynkiewicz, Kirsty Inglis, Laura Irvine, Bridget Jones, Kevin

Lafferty, John Manning, David Markham, Berta Martin-Lopez, Guy Mawle, Paul

Morling, Rebecca Nash, Terry Robinson, Claudia Rowse, Justine Saunders,

Rosemary Sayer, Joy Smart, Pat Snowdon, Lyndsey Swift, Kerry Turner, Nathan

Warren, Bill Watts, Will Williams.

With apologies to any inadvertent omissions from this list. As ever, any errors are

the responsibility of the authors alone.

eftec offsets its carbon emissions through a biodiversity-friendly voluntary offset

purchased from the World Land Trust (http://www.carbonbalanced.org) and only

prints on 100% recycled paper.

http://www.carbonbalanced.org/


eftec July 2010 ii

TABLE OF CONTENTS

EXECUTIVE SUMMARY ..................................................................................... V

1. INTRODUCTION ...................................................................................... 1

1.1 BRIEF ............................................................................................. 1

1.2 METHODS ......................................................................................... 1

1.3 OUTDOOR RECREATION IN ENGLAND / THE UK .................................................... 2

1.4 RECREATION AS AN ECOSYSTEM SERVICE ........................................................... 3

1.5 STRUCTURE OF REPORT............................................................................ 5

2. POLICY NEEDS........................................................................................ 6

2.1 CONSULTATION .................................................................................... 6

2.2 POSSIBLE USES OF VALUE INFORMATION ............................................................ 8

2.3 CONSULTATION RESPONSES ....................................................................... 10

2.4 CONSULTATION CONCLUSIONS .................................................................... 38

3. SURVEY DATA ....................................................................................... 41

3.1 GENERAL OFF-SITE RECREATION SURVEYS ......................................................... 42

3.2 SPECIFIC OFF-SITE RECREATION SURVEYS ......................................................... 48

3.3 OFF-SITE SURVEYS WITH SOME OUTDOOR RECREATION CONTENT .................................. 51

3.4 ON-SITE RECREATION SURVEYS ................................................................... 54

4. VALUATION METHODS ............................................................................. 59

4.1 GENERAL ......................................................................................... 59

4.2 MEASURES OF EXPENDITURE AND ECONOMIC IMPACT .............................................. 60

4.3 METHODS FOR VALUING RECREATION ............................................................. 61

4.4 ISSUES IN RECREATION VALUATION WITH REVEALED PREFERENCE METHODS ........................ 78

4.5 USE OF GIS ...................................................................................... 88

5. DATA ASSESSMENT ................................................................................. 90

5.1 DATA NEEDS ...................................................................................... 90

5.2 DATA AVAILABLE ................................................................................. 91

5.3 GAPS ............................................................................................. 96

5.4 SOLUTIONS ....................................................................................... 98


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6. RECOMMENDATIONS ............................................................................. 102

6.1 SCOPE FOR DRAWING ON MENE AND OTHER SURVEYS .......................................... 102

6.2 POSSIBLE ADJUSTMENTS TO MENE ............................................................. 103

6.3 PROPOSALS FOR BESPOKE SURVEYS ............................................................. 104

6.4 CONCLUSIONS .................................................................................. 108

REFERENCES ............................................................................................. 111

ANNEX 1:SUMMARY OF RECREATION SURVEYS IN THE UK ..................................... 121

ANNEX 2:EXISTING EVIDENCE ON RECREATION VALUES ........................................ 128


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BOXES, FIGURES AND TABLES

Box 1: The Marine and Coastal Access Act 2009 ......................................... 15

Box 2: "The value of water": Water UK ................................................... 19

Box 3: Marine recreation in the UK: PSEG findings. ..................................... 22

Box 4: Criteria for “State of the Park” indicators ....................................... 29

Box 5: STEAM (Scarborough Tourism Economic Activity Monitor) ..................... 31

Box 6: Value Transfer case study of Peak District National Park ...................... 33

Box 7: Drivers for the MENE survey ........................................................ 44

Box 8: Monitoring the environmental impact of CROW ................................. 56

Box 9: Adjustments to expenditure measures ........................................... 60

Box 10: A note on understanding of the travel cost method .......................... 68

Box 11: Climate change and tourism ...................................................... 86

Box 12: Detailed list of visit area types from single random visit section of MENE 95

Box 13: Summary of recommendations from Liley et al (2009) ...................... 100

Figure 1: “Knowledge pyramid” for ecosystem goods and services..................... 4

Figure 2: Implementing the individual travel cost method ............................ 64

Figure 3: Implementing a RUM based on travel cost .................................... 66

Figure 4: Basic Value transfer steps ....................................................... 72

Table 1: Question types and frequencies in MENE ...................................... 46

Table 2 Summary of Economic Valuation Techniques for Outdoor Recreation ...... 77

Table 3: Basic type of visit location as determined in MENE survey .................. 94

Table 4: Summary of recreational surveys .............................................. 121

Table 5: Stated preference studies of recreation values .............................. 128

Table 6: Revealed preference estimates of recreation values ....................... 131

Table 7: Meta-analyses of recreation values ............................................ 134


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EXECUTIVE SUMMARY

Background

Outdoor recreation values are often substantial, and can be among the most

valuable ecosystem services provided by certain resources. This is particularly true

when there is some investment in recreation facilities and where human

populations live nearby.

Various forms of outdoor recreation value evidence are used by different actors

across Defra policy areas. In some contexts, notably for making cases to Regional

Development Agencies and other local and regional development purposes, a focus

on local expenditures, Gross Value Added, and jobs supported is common. These

impacts are important, but fall outside the main scope of this research, which is

focused on the economic (rather than financial) value of outdoor recreation, as

reflected in the willingness to pay of participants.

Role of economic valuation

Economic value evidence is useful at a range of levels, depending on the policy

context, and this is not so much a function of the broad policy area or type of

recreation activity, as of the specific policy or decision context. The recreation-

specific organisations have considerable interest in this area, but most say values

would be useful rather than essential, and there is little interest in unilateral

funding of valuation studies. Some of the Defra policy areas have strong demand

for values, notably water in the context of the Water Framework Directive, and

more generally the „value for money‟ agenda makes availability of recreation

values a high priority in some areas.

Thus arguably the main demand for values is from the policy appraisal and

evaluation side, but if this demand were met, there would also be use in

management and priority setting. It is notable that developing robust estimates of

trip numbers, and information on the determinants of visits, are in many cases

more important than refining unit values for recreation.

Measuring the value of changes in outdoor recreation can be challenging, in

particular due to the impacts of alternative substitute sites, and of changes in

recreation quality at specific sites. Values per trip can often be estimated, and

use can be made of value transfer based on existing studies. Good methods exist

for assessing the effects of marginal changes in provision (quality, size or number

of sites) but applying this to the wide range of outdoor recreation activities in

England / the UK will require primary valuation studies, and improved time-series

data on recreation.

Recreation surveys

Many organisations do invest in primary data collection through on-site surveys on

land they manage or own, but there is no overall coordinated approach at the

national level. There could be important economies of scale in meeting the


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demand for recreation value provision at national level, through a standardised

programme of data collection and centralisation, and a strategic approach to

primary valuation research and the development of value transfer functions.

MENE survey

The Monitor of Engagement with the Natural Environment (MENE) survey will

produce very useful information for understanding recreation at national and

regional levels. MENE has deliberately focused upon capturing all visits to the

natural environment including those that are shorter, more informal, and closer to

home, such as dog-walking trips. The evidence suggests that these types of visits

were under-estimated by previous surveys, but are important features of people‟s

lives. MENE will be useful in providing good estimates of overall recreation

activity levels, and this will be important for certain purposes, including

aggregating value estimates to regional and national levels, and focusing attention

on all aspects of outdoor recreation.

The main use for MENE data in terms of valuation and trip number estimation is

likely to be in providing a clear national level assessment of total visit numbers.

This will provide a useful top-down check for estimates derived from bottom-up

visit prediction models and will enable grossing up to total values per region based

on estimated values per trip from travel cost work. A secondary use for the MENE

data in this context will be for improving / informing value transfer functions.

In order to enhance the usefulness of MENE data in this context, we suggest that

consideration be given to extending the first half of MENE (the seven day trip diary)

to cover more detail about the type of site/environmental resource visited on each

visit occasion. Exactly what additional detail should be covered depends on the

resource and time constraints for the survey, and the number of trips per week

(that would need to be examined in more detail). Some increase in detail should

be considered, and would improve the level of resolution of the data, enabling

more reliable grossing up or value transfer adjustments.

Recommendations

Recognising that MENE data alone will not provide value evidence (which was never

the intention behind MENE) we suggest that the best approach to taking outdoor

valuation research forwards in England (or the UK) would be either one single study

or several separate major studies, covering recreation at specific types of

resource: coastal resources; national parks; open access land; inland water sites;

and woodlands and forests.

The best methodology to use would be based on the random utility approach to

travel cost modelling, seeking to detect within-site and across-site resource quality

effects. Face-to-face interviews would enable direct use of GIS software for

automatic geo-coding of outset and destination points. The level of information

obtained from each respondent should be enhanced by surveying both actual

behaviour and stated behavioural intentions under future scenarios.


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A national database of recreation sites should also be developed. This would be

required initially in the study areas, and then nationally to enable value transfer.

It would however be useful to develop the national database early, since ideally

the study areas should be selected to be roughly representative of the national

situation.


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1. INTRODUCTION

1.1 Brief

The overall aim of this work is to establish how recreational survey data in England

(including data from the new “Monitor of Engagement with the Natural

Environment”, MENE) could be used for generating economic values for policy

appraisal purposes, both in the short (1 year), medium (2-3 years) and long term (5

+) and what capacity (software, hardware and expertise) will be required to enable

its effective use within Defra‟s current spatial analysis and data systems.

Key policy questions for this project to answer include:

1. What are the perceived needs and potential future uses for recreational

value evidence in all Defra policy areas?

2. How can economic valuation methods best be applied to recreational

survey data, to support policy appraisal and evaluation by valuing (a) the

total benefits of recreation at specific sites, and (b) changes in the quality

of sites and facilities?

3. What is the potential for developing a tool for transferring values

estimated at one site for application at another?

4. How could the MENE data and locally more detailed data be combined for

aggregation, calibration or checking purposes?

5. What are the theoretical and practical strengths and weaknesses of the

economic valuation methods available, and how should these considerations

structure their use?

6. How might any identified gaps or weaknesses be overcome by alterations to

MENE or through other work such as additional surveys or analysis?

1.2 Methods

The project has been approached through a combination of desk-based research,

including a strong element of stakeholder consultation, evidence and literature

review, analysis of gaps and reflection on possible steps for moving the agenda

forward.

The consultation has taken the form of a series of semi-structured telephone

interviews and other email contact with a number of key organisations and

individuals, aiming in particular to ensure policy relevance for the research. The

main topic for the consultation was a review of valuation evidence needs: a

comprehensive review of the conditions under which recreational value evidence is

currently used, or potentially could be used, in Defra policy areas. A key element

was assessing the demand for new or improved estimates of recreation values by

different organisations and policy sectors.

The second activity was a review of practical and theoretical aspects of valuation

methods: in particular travel cost / random utility methods, and also value

transfer. The review covered the data and research requirements, and theoretical


eftec July 2010 2

strengths and weaknesses, of different valuation methods for different objectives

(such as quality changes at existing sites, completely new or removed sites,

marginal or total values at large scales) and for development of value transfer tools

(for unit or function transfer, and for scaling up and value aggregation purposes).

At the same time, existing evidence on values deriving from use of these valuation

methods was collected and summarised.

This was complemented by a review of the content of the MENE survey and other

data sources, including geographically-referenced data relating locations and

characteristics of recreation resources, travel routes, and human populations,

within the context of using the data for all the different recreation valuation

purposes noted above: the primary objective here was to consider the extent to

which the MENE survey could be useful for aiding the estimation of recreation

values and/or their subsequent use for value transfer.

Drawing on the needs and possible uses of value evidence, the methodological

assessment, and the data review, we then made an overall assessment of how

value evidence based on MENE survey and other data might be used by Defra and

other key stakeholders in the short, medium and longer terms, and what the

research and resource requirements of such uses would be, and identification of

any evidence gaps and proposed solutions.

Finally the findings were summarised, with suggestions for future research, and for

possible extensions to MENE and other data collection methods.

1.3 Outdoor recreation in England / the UK

Outdoor recreation, as considered in this report and in the national off-site

recreation surveys, covers a very wide range of human use and enjoyment of the

natural world, including general outdoor activities such as walking, bike rides,

observing nature, picnicking, using viewpoints and otherwise simply spending time

outdoors in the natural environment, and also more specific and focused activities

such as rock-climbing, angling, canoeing, mountain-biking and so on. Outdoor

recreation need not involve long journeys or lengthy periods of activity, and can

occur near the home on a regular basis, as well as less frequent day trips or holiday

time spent outdoors. Time spent in the garden, routine shopping trips and the like

are not considered to be “outdoor recreation”, but activities such as dog walking in

a local park are.

With this broad definition, clearly outdoor recreation is a very common activity.

The England Leisure Visit Survey (2005) estimated that there were 0.77 billion visits

made to the countryside in 2005; Goode (2006) reports that approximately 33

million people make over 2.5 billion visits to urban greenspaces each year in

England. The 2009 “Survey of public attitudes and behaviours towards the

environment” (Thornton, 2009) finds that 48 per cent of respondents used public

gardens, parks, commons and other green spaces at least once a week.

This report is concerned with the ways in which outdoor recreation could be

measured and valued in economic terms, drawing on existing data, ongoing surveys


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and new research, to meet policy needs for valuing the ways that policies and

decisions impact on recreation values.

1.4 Recreation as an ecosystem service

In recent years, and in particular since the publication of the Millennium Ecosystem

Assessment (MA 2005), there has been a strong emphasis on the theoretical and

practical development of approaches based on identifying, measuring and in some

cases valuing the goods and services provided by ecosystems (Costanza et al. 1997;

Daily 1997; Boyd and Banzhaf 2007; Fisher and Turner 2008; Luck et al. 2009; Mace

et al. 2009; Haines-Young et al. 2009). The concept of ecosystem services

captures the dependence of human well-being on natural capital and on the flow of

services it provides (Daily 1997; MA 2003; MA 2005; Turner and Daily 2008).

The framework of ecosystem goods and services is an anthropocentric approach,

based on the ways in which ecosystems contribute to human wellbeing. This blends

well with the common, also anthropocentric, framing of environmental economics.

Section 4 discusses in more detail how the ecosystem service “outdoor recreation”

can be represented and valued within the “Total Economic Value” (TEV) framework

(Pearce and Turner 1990; Defra 2007). This framework is useful as a way of

structuring information about values to humans, and in particular in recognising

multiple sources of value, including non-material and non-selfish values.

TEV distinguishes among several different types of value:

direct use, either consumptive or non-consumptive

indirect use (e.g. watching documentaries about outdoors)

option value (i.e. what it is worth paying now to maintain the option to carry out some currently unplanned activity in the uncertain future)

non-use values, including altruistic, bequest and pure existence values.

Recreation is generally considered as a non-consumptive direct use, though there

are some forms of recreation that are consumptive either by their nature (e.g.

hunting, fishing) or because of overcrowding effects (a site becomes “saturated”

with visitors) or damage associated with use (e.g. path erosion, off-road driving,

disturbance of wildlife, or disruption of peace and quiet in rural areas), resulting in

declining value, in effect “consuming” part of the resource.

In addition to the direct value to individuals from recreation, there may be mental

and physical health and educational benefits arising through outdoor activities.

These may or may not be recognised directly within individuals‟ values for outdoor

recreation: generally we assume they will be, but if for example there are health

benefits (or for that matter risks) of which participants are not aware, but would

value if they knew of them, this may result in additional values.

Many recreation values are dependent on both the biodiversity, geodiversity and

cultural heritage of the landscape. In addition, the same ecosystems / areas that

support recreation will in most cases support a wide range of other ecosystem


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goods and services. In general, we have reasonably good qualitative understanding

of many ecosystem services, but often rather less quantitative measurement, and

much less understanding of the economic value of the services. This is illustrated

in Figure 1, highlighting the narrowing of the set of services for which we have

good information as we move from simple description through qualitative

understanding, through quantitative measurement, availability of data suitable for

estimating monetary values, and finally actual, reliable valuation.

Qualitative review of goods and services

Quantitative assessment

Valuation review

Monetary

valuation

Full range of habitat and ecosystems goods and services

Non-specified

Figure 1: “Knowledge pyramid” for ecosystem goods and services

(Source: Armstrong et al 2010, adapted from ten Brink / TEEB 2008).

In terms of this “knowledge pyramid”, most forms of outdoor recreation in the UK

are currently located somewhere between qualitative and quantitative

understanding, though for several recreation types there are some monetary

valuation studies available, and in some cases, notably forest recreation, there is a

long history of valuation efforts and actual use of values (see section 2.3 and Annex

2). Overall, however, we are missing key data that would allow a proper

quantitative and monetary assessment of outdoor recreation: most fundamentally,

we do not really know where and how often people engage in specific recreation

activities, nor how they select from among possible recreation options and sites,

beyond quite broad national estimates of general participation from national off-

site surveys and more detailed but piecemeal information from on-site surveys (see

section 3).

There is a desire from many quarters, including Defra and Natural England, to

improve the data available. The new national off-site survey, MENE, is one part of

the work programme, and there are other suggestions and actions, discussed

further below, that will contribute to a better measurement of visits and visitor

behaviour. But there is relatively little attention, to date, on the questions of how


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to derive better monetary estimates for the economic value of recreation, within

the TEV framework. The main purpose of this report is to explore various aspects

of this question.

1.5 Structure of report

The next section of the report reviews the actual and possible uses of recreation

values in various Defra policy sectors and partner organisations. The discussion is

based largely but not exclusively on the consultation responses. There are some

places in the consultation responses where technical aspects of valuation methods

are noted: we do not give details in this section, but defer detailed discussion of

methods to section 4 of the report.

Section 3 reviews the availability of survey data for outdoor recreation in the UK,

covering the full range from national off-site surveys such as MENE to various on-

site surveying and monitoring programmes.

Section 4 presents the main methods available for economic valuation of outdoor

recreation, with a strong focus on revealed preference methods (although stated

preference is widely used, it falls outside the main focus of this research).

Sections 5 and 6 seek to draw together the information from the research,

contrasting the data needs for valuing recreation with the data available, and

making suggestions for possible research and monitoring that could help to bridge

the gap, resulting in robust, transferable values for outdoor recreation in England

and other parts of the UK.

Annex 1 presents a tabular summary of the survey data sources covered in Section

3.

Annex 2 presents a summary of some existing recreation valuation studies,

primarily though not exclusively from the UK.


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2. POLICY NEEDS

To achieve the objectives of this research, and to ensure that the results are of

greatest possible use, we need to develop a clear understanding of policy areas and

circumstances for which estimates of the economic value of outdoor recreation

currently are, or could in the future be, of use. We have therefore consulted

widely to establish the demand for evidence on recreational values across a wide

range of policy areas and organisations.

2.1 Consultation

The consultation with Defra officers and other key stakeholders aimed to provide a

comprehensive review of the conditions under which recreational value evidence is

or potentially could be used in Defra policy areas. There have been 30 phone

interviews or written contributions (consultees were given the choice, most

preferred phone) from 15 organisations. Interviews varied in length, but generally

lasted 20 to 30 minutes, and sought to explore in some detail the ways in which

recreation value evidence is or could be used in the consultee‟s organisation or

policy area.

The interviews were informally structured to explore a general set of themes in a

way appropriate to the respondent and her/his role in recreation assessment or

management. The overall objective was to reveal information relating to:

current use of value evidence;

potential for making greater use of value evidence in future; and

barriers to increasing use of recreation value evidence.

Discussions were not exclusively restricted to recreation: in some cases useful

information associated with views on, or use of, monetary valuation or the

ecosystem services framework more generally, or comments on how policy drivers

or rules restrict or condition the analyses that may be relevant, were explored.

The list of possible areas to cover in interviews included:

Details of the respondent’s role and professional involvement with

outdoor recreation: target respondents had direct management or policy

roles, but also indirect where their policy area impacts on, or is affected

by, recreation (wind-farm development, flood defence...). Do decisions

mostly influence quality, quantity/availability, or both? What is the scale of

impacts/decisions – national, regional, site-based?

When taking a decision involving recreation impact, how is that impact

assessed? This is a key issue – is the assessment qualitative or quantitative?

Does it focus on trip numbers? Is it monetary? How is it measured, is there

monitoring or modelling, how is that information used? What is the time-

horizon, is discounting used? Do they have targets? When estimating


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impacts on recreation, to what extent are substitute sites / additionality

taken into account? How is the affected population defined?

Does the respondent make use of national or regional recreation surveys

such as the England Leisure Visits Survey / Scottish Recreation Survey / UK

Tourism Survey / Public Opinion of Forestry / Inland Waterways Visitor

Survey (etc.) – and if so, what information is used, and how?

Is the respondent ever involved in designing, commissioning, or using the

results of bespoke surveys, for example via automatic or manual visitor or

vehicle counts, on-site surveys? If so, under what conditions, and how is the

information used?

Does the respondent ever make use of monetary estimates of the value

of recreation? If so, where do the estimates come from? Are they fixed at

a national level or varied for individual applications? How are they used –

e.g. formal CBA? What is the underlying methodology? How reliable are

they considered to be?

And if not, why not? – possible reasons include lack of monetary estimates,

lack of trust/belief in monetary estimates, policy frameworks or objectives

that explicitly exclude monetary valuation, lack of basic data (e.g. trip

numbers), focus primarily on key target social groups, and so on.

Does the respondent use other measures of economic impact of

recreation – for example tourist expenditure, multipliers, estimates of

employment impacts?

Does the respondent consider the health impacts of outdoor recreation –

and if so, how?

How useful would the respondent find improved estimates of the

monetary value of outdoor recreation? Is this a pressing need, or

something that would be nice but not really essential, or something they

don‟t believe is possible or wouldn‟t use anyway?

Recreation activities include a wide range of outdoor pursuits, such as walking and

dog-walking, cycling, riding, angling, boating and so on, using the full range of

outdoor environments in the UK. So most Defra policy areas have the potential to

impact on recreation, and could therefore use recreation value evidence in policy

appraisal. However there are of course some areas where the recreation impact is

clearer and more important, and also some areas in which ongoing policy

developments and expenditures make the recreation issue particularly salient at

present. The current and potential future demand for recreation values in

different policy areas and related organisations was assessed during the

consultation exercise. Below, we set out first the generic possible ways in which

value information could be used (section 2.2) and then the views expressed within

different policy areas and organisations regarding the current and future use of


eftec July 2010 8

monetary values for recreation (section 2.3). Overall conclusions follow in section

2.4.

2.2 Possible uses of value information

Although at present there is rather limited use of monetary value estimates for

recreation, because for most policy areas values are not available, there is wide

potential for greater future application of new values.

2.2.1 Value for Money, monitoring and review

A recurring theme in the consultation was the need to demonstrate value for

money, and in particular this was a concern within Defra in view of likely fiscal

constraint and the difficulty in demonstrating value for more intangible

environmental benefits in competition with other departments. Recreation and

access are seen as areas in which it ought to be possible to derive reasonably

robust measures of economic value and there is considerable interest in using

revealed preference valuation methods to this end. For example, Defra is

currently investigating the added value of National Park Authorities – major

recipients of grant-in-aid – and recreation is one of several important features to

consider. Other key current areas for monitoring and review include the decadal

review of the Countryside and Rights of Way (CROW) Act 2000 legislation and a

review of agricultural payments under environmental stewardship under which

funding is given to land owners for access.

2.2.2 Appraisal and impact assessment

Where a policy will impact on recreation values, this needs to be taken into

account in policy appraisal and impact assessment. Monetary values for recreation

impacts would clearly be very useful for this. Topical and recent examples include

the next round of River Basin Management Planning, the Marine Conservation Zone

(MCZ) designation process, Impact Assessment (IA) for Phytophthora spp1, the

Marine and Coastal Access Act (2009) and so on. Values are also needed for

ongoing regular appraisals, such as appraisals for flood risk management options.

2.2.3 Seeking funding

Organisations often have to demonstrate value for money, or present appraisals, in

order to secure funding for projects and investments. Monetary values for

recreation and other ecosystem service changes may play a role in this, although at

present they are not widely used. Often the funding body has a specific set of

criteria or targets, and the bids are pitched directly at these – in the case of

Regional Development Agencies (RDAs), for example, this primarily means

1 “A genus of plant-damaging Oomycetes (water moulds), whose member species are capable of

causing enormous economic losses on crops worldwide, as well as environmental damage in natural

ecosystems.” http://en.wikipedia.org/wiki/Phytophthora


eftec July 2010 9

demonstrating contributions to Gross Value Added (GVA) via expenditure and

employment impacts.

2.2.4 Prioritisation

Christie et al (2010) demonstrate the use of benefit-cost ratios (BCR) to assess

priorities for future investment in countryside recreation. By ranking the

improvement programmes according to the level of the BCR (see OECD, 1995) they

conclude for Grampian region that prioritisation should be given to path upgrade,

the creation of short paths and path maintenance programmes in areas next to

rivers and lochs as this was where the greatest BCRs were obtained (14.62, 11.47

and 11.32 respectively). Path maintenance and path upgrade in mountain areas

also showed high BCRs. BCR values of less than one were obtained for investments

in visitor facilities at specific locations. As Christie et al. suggest, comparison of

the relative values of the BCR can provide clear indications of public preferences

and economic benefits, and this is useful information to aid the development of

strategic, cost-effective policies for recreation provision. However there may be

other objectives (such as provision for specific target groups in the population) that

need to be taken into account. It would be possible to adjust BCRs using weights

for specific target groups.

2.2.5 Understanding, communication and advocacy

Recreation values can play an important role in improving our general

understanding of basic questions about recreation – who does it, when and where,

why and why not, and how these answers relate to environmental quality, access

and information provision, costs of access and activities, demographic factors and

so on.

Monetary value estimates are not really essential to addressing these questions,

but the techniques of travel cost and Random Utility Models (RUM) can be useful in

teasing out functional relationships, and give monetary values into the bargain; the

monetary values also give a useful tool for comparing different provision options

and the relative merits of different sites.

Monetary values can also be important tools for communication and advocacy

purposes. They can put recreational experiences on a level footing with other

marketed goods and activities, providing a concise and easily understood indicator

of value.

General advocacy of different activities and policies can also be aided by reference

to economic values of impacts. For example, Natural England is promoting the

adoption by local authorities of “Accessible Natural Green Space Standards”2, and

reference to the economic value of recreation would be a useful prop for this

activity as it could help local authorities to justify the expenditures in economic

2 A set of benchmarks for ensuring access to places near to where people live: for details, see

http://www.naturalengland.org.uk/ourwork/enjoying/places/greenspace/greenspacestandards.aspx


eftec July 2010 10

terms (as well as help Natural England to justify its expenditure on promoting the

standards).

2.2.6 Planning and location decisions

Recreation impacts also feature in spatial planning decisions. The value of

recreation lost or gained could be an important consideration, both in determining

planning decisions, and in determining any compensatory measures required.

Marine spatial planning will also need to take account of interactions between

recreation and other activities. Even where the focus of a planning decision is

primarily on avoiding and mitigating resource conflicts and externalities, there may

nonetheless be scope for considering the relative values of different recreation

activities and taking value into account in determining trade-offs and

compensations.

Jones et al (2002) present results suggesting that “while visitor arrivals at UK

woodlands are highly responsive to a variety of locational factors, they are

somewhat less responsive to the facilities on offer at these sites” (Brainard et al.,

1999; 2001)” – which suggests that scarce resources may be better invested in

optimising site location rather than to extend the diversity of facilities within

existing woodlands.

2.2.7 Pricing decisions: fees, payments

Recreation values have the potential to be used for justifying or setting the level of

entrance fees, car park charges, and similar prices. And travel cost methods can

also help to predict the impacts of pricing changes, i.e. by how much will visitor

numbers fall if an entrance fee is introduced, and what is the loss of benefit to

society associated with that fall in use?

Note that potential for charging for recreation access can also limit the

applicability of stated preference methods, if there is concern about giving an

incorrect impression that such charges are planned. This can make revealed

preferences more appropriate if such concerns exist.

Recreation values can also be useful in justifying and determining levels of

payments for ecosystem services. This is particularly relevant for areas such as

provision of access, for example on Higher Level Stewardship land, where the value

of the service provided could be an important factor justifying the payment of

subsidy.

2.3 Consultation responses

The consultation responses below are mainly structured by policy area (such as

access, health, water…), with Defra, Natural England and Environment Agency

responses being split across these. Responses for other bodies with more specific

remits (e.g. Forestry Commission, National Parks Authorities, RSPB, National Trust)

have been presented in separate sections. Similar ideas arise in several areas, and


eftec July 2010 11

this can make the discussion a little repetitive, however, recognising that some

readers may want to focus just on specific areas of interest, this is unavoidable.

The general view within Defra, and a key driver for this research, is the objective

of getting a better view of recreation value needs over all areas. Recreation values

are needed for policy appraisal and for demonstrating value for money; indeed in

many areas this is seen as a pressing need, within the current context of increasing

pressure to show value for what departments do in the face of fiscal constraint.

But valuation effort must itself be appropriate and proportionate in order to

provide value for money in terms of the better results it can facilitate. By looking

across all areas, can we find opportunities for better Value for Money (VfM),

perhaps by making wider use of recreation value estimates, using the same

underlying data for different purposes, making valuations more flexible for

application to different policy contexts, or making better use of spatial data for

taking account of substitute sites. In the past studies have been piecemeal, and

there is a view that a more strategic approach should be adopted.

Key issues include how to value not only a recreation site, but also quality changes

at sites. Key policy areas include water quality (in particular in the context of the

Water Framework Directive (WFD) and monitoring how water quality changes link

to recreation value changes), landscape and biodiversity, and access under Higher

Level Stewardship (HLS).

In recent years, there has been a lot of work using stated preference techniques

(contingent valuation and choice experiments), generally involving environmental

goods with substantial non-use values. This has been useful work in terms of

appraisal of the environment, but recreation is seen as a bit more tangible, and

there is a perception that effort is needed to redress the balance and make greater

use of revealed preference evidence, and also production function approaches.

Such evidence can be seen as more robust, because it is based on actual behaviour

and measurements, and there is scope to make more of existing and new

evidence/data on recreation activities and numbers in primary valuation studies.

Given the objectives set out above, and the aim of ensuring value for money in

valuation research, value transfer is of interest as well. Defra has produced value

transfer guidelines (eftec 2010) and there are useful case studies in this area (for

example ex-post forestry valuation, Peak District National Park).

Generally, monetary valuation is seen as ideal, but information on trip numbers or

reasons for visiting is also of use. There is a desire to make use of all available

evidence, especially quantitative evidence, even if monetary values are not

available. Research and development is also ongoing on other (non-monetary)

metrics and deliberative processes, though assessment of these developments is

beyond the scope of this study.

Within Natural England, there is similar interest in calculating the value of specific

actions and programmes. Both qualitative and quantitative approaches are

adopted, with different approaches being appropriate for different questions and


eftec July 2010 12

user groups. For example in work on “healthy walking” (see section 2.3.2) to

improve health, the primary data requirement is to demonstrate net savings for

health provision using cost data and quantitative estimates of the reductions in

treatment needs.

The use of recreation information changes with the “sales pitch” used for each

different case. Work with Visit England, for example, focuses more on using the

leisure visit survey to provide evidence of people‟s connection with the

environment, and demonstrating how green tourism is income generating, relating

it to the numbers of people visiting the countryside and environmental interest,

but the quantitative evidence here is much weaker than on the health side.

The Environment Agency (EA) is also interested in monetary valuation, and thinking

is increasingly turned to markets for ecosystem services, with this policy area

expected to increase in importance. Key areas of EA activity for which recreation

impacts are important include flood and coastal risk management, navigation,

fisheries and water quality. Although monetary values could be useful in these

areas, and in principle can be used (for example in flood risk evaluations), in

practice this tends not to be done at present. Recreation is considered both

directly in the policy areas, and also via economics analysis provided to support

these areas.

Generally, monetary estimates are seen as much more compelling than other

measurements in the current political/social climate. The usefulness of monetary

measures depends on the audience, however, and other “levels” can be used if

appropriate and available. In some cases “sound bites based on sound evidence”

are sufficient. Better general values for recreation would be useful, but values

“tailored and focused” on target sectors could be of critical importance, and in

general, targeting and segmentation are important.

For many organisations, consideration of the economics of recreation is very much

focused on visitor spend and local or national economic impacts. The impacts on

visitors themselves are considered but generally not within an economic valuation,

willingness to pay framework – the focus is more on measures of visitor numbers,

satisfaction, activities, reasons for visits. Here of course the research methods and

interests overlap considerably with economic valuation methods, in particular

random utility methods that help to tease out the impact of different facilities and

features on visitor / visiting behaviour. In most cases there is potential interest in

making greater use of monetary values, and a recognition that this could be useful

particularly in demonstrating the benefits of expenditures, seen as increasingly

important in a tighter funding climate. There is relatively little sign of willingness

to fund or undertake large-scale valuation research unilaterally, but there would

be quite widespread willingness to cooperate with such research, and interest in

exploring the possible uses of the results.

2.3.1 Access

Recent and ongoing developments in access provision are a clear area in which

recreation values are central, especially in the context of value for money.


eftec July 2010 13

Maintaining and extending green infrastructure, and providing and improving

access, all require expenditure. Local authorities and countryside managers need

evidence for this expenditure to show that it represents value for money, as well as

support in seeking funds for proposals.

Natural England has a key role in providing this evidence, and is encouraging local

authorities to adopt “Accessible Natural Green Space Standards”, partly because of

evidence that green space creates health benefits and enhances people‟s sense of

community. Additional evidence on the monetary value of recreation benefits

from access to green space would provide an additional argument for adopting the

standards, and for NE investing in advocacy to promote their adoption.

In Defra the Sponsorship, Landscape and Recreation team has responsibility for

policy associated with enhancing access and encouraging outdoor recreation. On

the sponsorship side they manage grant-in-aid (to Natural England, National Parks,

Forestry Commission…). Grant recipients use funds to achieve their objectives, and

also use it to lever other funds, but there is an increasing need for “line of sight”

between the grant and its application/impacts, and for measures of benefits

associated with the expenditure, driven by the value for money agenda.

On the programme side, the team works on policy for public rights of way, access,

and coastal access. The landscape side covers designations and the European

landscape convention, but the objectives are in a sense more vague: “sustainable

landscapes conserved”, but people have very diverse views on what a “good”

landscape is; often just what they‟re used to. There is a need at this programme

level to quantify the benefits of Defra‟s work on recreation, much of which is done

via delivery bodies/recipients of grant-in-aid. This is driven by the value for money

agenda, in particular demonstrating benefits and presenting evidence on

investments to senior Defra decision-makers and Ministers. There is a struggle to

demonstrate Value for Money for a lot of the less tangible Defra activities, and

recreation is seen in some respects as an “easier target” for valuation. But there is

a real lack of recreation value data, except for forestry, and there are important

data issues hindering work to address this gap:

1. How many visitors are there – actually and potentially - for different sites

and activities?

2. How can numbers and benefits be linked back to policy and management

interventions, such as National Park Authorities‟ actions?

3. What is the valuation evidence for valuing trips?

On the recreation and access side, Defra is considering the best approach to

assessing the full impacts of outdoor recreation in economic terms. There is also a

focus on indicators of numbers of visits to the outdoors, with figures collected from

a range of agencies, looking at the number of people involved and changes in visit

behaviour under changing conditions. There is interest in quantifying health

impacts (see section 2.3.2). Segmentation work is ongoing, including in the

context of the MENE survey, in part due to the Natural England Diversity Review


eftec July 2010 14

which identified underrepresented sections of society, and there is a desire to

identify target groups such as those with inadequate supply for their recreation

demand. There is also a distinction to make between general “value to public” and

specific segment issues. Equity is considered, in the context of looking for equal

access and opportunities.

Both Defra and the EA are working on inland waterways recreation issues, and

monetary values are potentially important here. Defra and the Inland Waterways

Advisory Council (IWAC) recently commissioned Jacobs “to assess the diverse range

of benefits provided by inland waterways in England and Wales”; results of the

study (Jacobs 2009)3 include a value transfer/valuation tool and guidance on its

application. The study is the first part in Defra‟s two-year Research and

Development Programme, managed by IWAC, aimed at enhancing the evidence

base for investment in inland waterways. The research covers a full range of

ecosystem goods and services deriving from inland waterways, including recreation,

and presents economic value estimates for most of them, also including recreation,

based on literature review and value transfer. For recreation, estimates are

provided for both consumer surplus and expenditure for a range of recreational

activities undertaken in or along waterways. However it is noted that the data are

old (early 1990s), and that public preferences have probably changed significantly

since the original studies were published. It is also stressed that the physical data

required to aggregate these benefits – notably visit numbers - are available from a

number of sources, but with no centralised means of accessing the data, and a lack

of consistency across navigation authorities.

Generally the overall position is: given objectives, how do we achieve them, how

do we measure them, how do we value them? At present recreation values are not

much used, whether because they are not available, or because those estimates

that are available are not considered reliable. But there is interest in using

economic values in future. They would be useful for demonstrating value for

money and which expenditures are “making a difference”, and this is important for

budgeting, particularly in view of likely fiscal constraint, making it extremely

beneficial to be able to demonstrate cost effectiveness. Breakdown of estimates

to the Government Office Region level would be useful.

More generally, evidence on the value of recreation is important for monitoring and

evaluating a broad range of activities. For example, Natural England estimates

that provision of coastal access (see Box 1) is likely to cost around £50 million over

10 years: evidence is needed on whether this is value for money.

3 www.iwac.org.uk/reportsIWAC


eftec July 2010 15

Box 1: The Marine and Coastal Access Act 2009

The Marine and Coastal Access Act 2009 aims to improve public access to, and

enjoyment of, the English coastline, providing secure and consistent rights for

people to enjoy the coast with confidence and certainty. A series of long-distance

routes around the coast of England will be proposed under the powers contained in

the 1949 Act, as amended by the 2009 Act. An Order under the 2000 CROW Act

will give the public a right of access (with a few exceptions) to the route, all land

to the seaward of the route and any of the classic coastal land types (including

cliffs and dunes) and land to the landward of the route up to a suitable boundary

(such as a fence) or other physical feature. The right of access will then come into

force for a section of the long-distance route following an Order by the Secretary

of State. It is currently planned that the establishment of the coastal route

throughout England will be completed after 10 years. (Defra 2009b)

The Countryside and Rights of Way (CROW) Act 2000 is subject to a decadal review:

evidence is needed on the value for money of staff time and resources invested in

implementing CROW, and of the grant aid for works to enhance and manage

access. If the use of monetary values for recreation can help to establish benefits

and VfM, this could help improve the case for including access in master planning.

Recreation policy and management decisions may also be influenced by evidence

on economic values: for example, should visitors be charged for guided walks in

National Nature Reserves (NNRs)? Of course monetary value is only part of the

equation here – there are other targets, and possible equity issues, to consider.

Similarly, monetary values could inform the appraisal of investments in visitor

centres planned for „Champion‟ NNRs. Recreation values could also be useful for

policies such as car-parking charges in National Parks: in justifying the policy and

perhaps in setting the charges.

Access can be contentious, with the Country Land and Business Association (CLA) in

particular resisting extensions of rights of way, being “fundamentally opposed to

the coastal access provisions of the Marine and Coastal Access Act”4, campaigning

against the British Canoe Union and the Welsh Canoeing Association campaign for a

„Right to Row‟, and so on. Concern is expressed on the one hand over “the lack of

basic natural justice”, but also “the ability to extend the right of access over large

areas of land and the impact on the environment and wildlife.”5 Although

recreation values could potentially inform this debate – for example enabling

comparison of the benefits to recreationalists with the costs to landowners – this

would be unlikely to resolve the more fundamental source of the conflict, which is

grounded in views of property rights.

4 http://www.cla.org.uk/Policy_Work/Consultation_responses/access/Coastal_Access/1001538.htm/

5http://www.cla.org.uk/News_and_Press/News_Archive/Access_to_the_Countryside/Access/105748.h

tm/


eftec July 2010 16

2.3.2 Health

Health policy falls outside of Defra‟s remit, but as an additional benefit of

recreation in the natural environment, can be a relevant consideration, and there

is interest from various quarters in the health impacts of outdoor recreation.

These may be seen as more or less important to the recreation agenda: on the one

hand there is no strong evidence that outdoor exercise has any more health

benefits than indoor and would be viewed generally as more a Department of

Health issue. On the other hand, Defra‟s People and Landscapes programme is

considering the use of QALYs (Quality Adjusted Life Years) to attempt to place a

monetary value on the relationship between health and engagement with the

natural environment and outdoor environmental quality.

Natural England‟s Healthy Walking programme has been running for ten years,

providing a framework of training and accreditation to develop “Healthy Walking

Schemes” to encourage sedentary individuals to seek exercise. The aim is to

embed the scheme in health care, with results related to the NHS obesity survey

and demonstration of cost reductions, through reduced medication and an

increased probability of longer healthier life. It has also been found that GP‟s have

begun to refer some people to the schemes instead of prescribing pharmaceutical

solutions.

The DoH has recently provided additional funds to expand the scheme, with the

aim to provide “downstream benefits”. It is currently used by approximately

35,000 people per week, with a target for 130,000 users by 2012. The outcome

target is for 200,000 people who participate in the programme (noting that not all

participants attend every week) seeing an improvement in health. Approximate

calculations suggest that if the average “walking for health” walker participates for

three times per week over ten months, for every pound spent on the scheme over

seven pounds are saved (Joy Smart, pers. comm.). Given figures that 70% of the

population are not active enough, savings of £1.1 to £1.8 billion per annum could

be possible. The programme is set in the context of the obesity strategy and

survey, which are cross-government initiatives, with the main partners being the

DCSF and DoH. Natural England has stressed the importance of green space in

yielding these savings. It is worth noting that the savings here relate to costs of

providing health care, and there will be significant additional value to the

individuals involved, associated with their improved health status, and in all

probability with direct enjoyment of the walking activity.

The Forestry Commission is also interested in health issues, citing research

underway at Glasgow looking at the correlation between outdoors access and life

expectancy and obesity, for example. This could be useful in project evaluation of

programmes for delivery associated to healthy physical activities, and for

establishing the importance of outdoors in this context.

Health bodies and stakeholders require demonstration of monetary values to a

greater extent than has traditionally been the case for those considering

environmental issues, therefore to some extent the methodologies for valuation

are better developed, and there is a greater requirement to make the “sales


eftec July 2010 17

pitch”. On the other hand, these observations relate largely to estimates of cost

savings and to QALY calculations, and not to values based in the willingness to pay

framework of economics. Cost savings are only part of the value of health

improvements, taking no account of the benefits to the individuals involved.

QALYs provide a partial index of benefits, estimating for any intervention the

number of years of life saved, with each year weighted by a quality of life index,

but this is not directly related to a measure of willingness to pay for health

improvements.

The scale at which values are required varies depending on the context. Generally

values need to be sector specific rather than regionally specific, but in some cases

(e.g. Healthy Walks) specific regions and Primary Care Trusts are being targeted for

delivery and policy, drawing on the obesity survey. In these case values can be

required down to a smaller spatial scale or at a local programme level. “Value

transfers” giving general values are considered most useful for national impacts.

Again, however, this relates to cost saving measures more than to willingness to

pay estimates.

2.3.3 Water

One of the key areas of demand for recreation values is in water management, in

particular in the context of the Water Framework Directive, and also new

legislation for floods and water management.

The target under the WFD is to move progressively to “good status” for all waters,

via a 6 yearly cycle of river basin planning. River Basin Management Plans (RBMPs)

for each river basin district must be produced in 2009, 2015, 2021 and so on.

Amongst other things, the plans must list the environmental objectives, justify how

and where alternative objectives have been used, and summarise the programme

of measures which will be taken to achieve the objectives.

The first round of plans (2009) will see only about a quarter of waters achieve good

status. These plans drew on a national study (conducted by NERA) involving large

scale stated-preference (SP) valuation; water companies have also applied area-

based SP. Within these studies non-use values are very important. There have

been situations in which large investments have been recommended based on

benefit estimates within which around 90% of benefits are non-use values (based on

stated preferences for conservation aggregated over a large non-user public).

Amongst policy-makers there is an element of scepticism about using these

methods to justify further investments, given the protection already afforded to

the environment and the policy of no deterioration. There is a view that greater

emphasis is needed on the non-market use element of water resources, particularly

in the context of a greater focus on the detailed local situation for specific water

bodies, where the user population and associated values are important. Future

decisions for second and subsequent rounds of RBMPs are expected to be taken

based on a much more detailed view of local costs and benefits.

Issues arising here include:


eftec July 2010 18

The distinction between use and non-use values – where non-use may be

estimated reasonably via national level surveys, but where use values

require local data, either for primary study or for benefit transfer purposes.

In some cases there can be problems distinguishing between use and non-

use values, though generally this can be dealt with through careful survey

design.

The definition of what constitutes a site, especially in the case of linear

features such as rivers, that may be accessed from many points along a

length.

What constitutes a substitute site (both within and outside the UK, or the

specific country/region of interest) and to what extent improvements in

values in one area are net, rather than displaced from substitute sites. For

this, panel surveys could be especially useful, tracking the evolution of

behaviour within a specific user group.

Hence there is a view that the second round of RBMPs will make much more use of

revealed preference measures. One of the key questions is therefore to determine

the extent to which existing surveys of origins and destinations could enable

valuation, and to what extent new surveys may be required. But values are needed

by 2012/2013 at the latest, so there is limited scope to wait for MENE to build up a

critical mass of data.

In many cases, knowing visit numbers, and how they relate to change in

environmental quality, would be just about enough: policy makers could make

informed judgements based on this quantitative information. Monetary values

would be the icing on the cake, enabling assessment of whether conclusions are

justified in monetary terms, and feeding in to tests of disproportionate costs under

the WFD. But other forms of quantitative information about how households are

affected would sometimes be sufficient: how many walkers, anglers, bathers,

canoeists are using a particular resource? On the other hand this would not fully

cover the benefits of changes in quality for existing users.

The real problem is that at present the range of estimates is too wide to be

practically useful. Even where values are hard to estimate, for example in the

education and health impacts of outdoor recreation, there is a need for objective

frames of reference, and limited room for qualitative descriptions of benefits that

lack context or a baseline. At least some attempt must be made to scale and make

values quantitative. This is itself another factor behind the wish to focus on

revealed preference: in travel cost, we need to look at participation and numbers,

and use these for valuation; in contrast to stated preference, where the valuation

method can be applied without estimates of participation, and there can remain

substantial uncertainty and debate regarding the user and non-user populations

over which aggregation should be carried out.

The issue of valuing recreation is important to the RBMP process and Defra would

consider establishing additional surveys/research specifically for water, if the


eftec July 2010 19

ongoing work in MENE and elsewhere is not sufficient to establish values with

confidence.

Box 2: "The value of water": Water UK

Water UK‟s publication “The Value of Water” (www.water.org.uk) notes a wide

range of benefits from water resources, including that “enhanced water quality

helps create and sustain economic activity based on leisure, recreation and

tourism”, that “rural tourism is important because it encourages diversification of

economic activity and can help maintain livelihoods” and that “some of the most

popular pastimes in the UK are water-based.” It notes that angling has 4 million

participants, more than any other sport, and an economic value of over £3 billion

per year; and that of 91 million domestic holiday trips taken in 2003, a quarter

involved a water-based activity. There is no attempt to place a value on the

recreation experience, but it is likely that were such data to be available,

organisations such as Water UK could be interested in making use of the evidence

as part of their general advocacy and publicity work.

2.3.4 Flood risk management

The recreation impacts of flood risk management activities can be important, in

particular where defence lines are abandoned or undergo managed realignment,

where there is footpath access over the top of defence structures, or where

navigation or angling interests are impacted. However, monetary values of these

recreation activities rarely figure in appraisals. There are historical reasons for

this: traditionally the policy area was about agriculture/drainage. More recently

built property values were incorporated in assessments, but the values of all the

assets involved were all still tangible. Although some non-market values are

included (notably the „value of statistical life‟ which is a monetary value of

changes in risks of death6) recreation is generally omitted. This can influence

decisions: for example at Cuckmere in East Sussex, a decision was taken to

abandon a headland that received 700,000 visits each year from walkers. However,

the appraisal of the site did not value the recreational activities involved; had

these values been considered, a different appraisal outcome might have been

reached.

One of the key problems is that the Environment Agency has permissive powers to

provide protection from flooding, and it is therefore often easier and cheaper to

abandon defences (stop maintaining them, let natural erosion take its course) than

to engage in managed retreat (deliberately breaching defences at strategic points,

retreating to high ground or a new line of defence, often creating new intertidal

habitat in the process). These can have quite different impacts on recreation,

including notably that managed retreats may better allow maintenance of existing

pathways (e.g. with a footbridge over a breach) or construction of new ones,

6 For example, a risk reduction of 1 in a million for a population of 60 million people would equate to

60 „statistical‟ lives saved – we can‟t say specifically who was/will be „saved‟, just that overall we

expect 60 fewer deaths from that risk source over the time period in question.

http://www.water.org.uk/


eftec July 2010 20

compared with the abandonment scenario. Though recreation values have been

used in academic/consultancy studies (e.g. eftec‟s Wareham study, see Defra 2007)

and in principle are included in guidance, in practice they are not accounted for in

monetary terms. But recreation is often considered as part of what is / is not

acceptable to local communities.

There is certainly scope to make greater use of monetary recreation values in flood

risk management, though this would require good estimates of the different

impacts of scheme options, and site substitution issues would potentially be

important.

2.3.5 Recreational Fisheries

The Environment Agency has responsibility for managing certain aspects of

recreational fisheries, in particular through the sale of rod licenses that are

required for any fresh water fishing. At present there are two main ways of

deriving participation estimates for fisheries:

1. Through rod license sales, which gives an estimate of numbers participating

in freshwater fishing, but not the level of activity.

2. Broadly similar omnibus surveys at 5-yearly intervals into “Public Attitudes

to Angling”. Includes “have you been fishing” over past 1/2/5/10 years,

split by freshwater and sea.

Marrying up (1) and (2) is tricky: there is higher reported participation than license

sales. In control surveys of river banks, about 5% of people fishing don‟t have a

license, and the figures can match up roughly if we assume that those without

licenses fish only once in a while, whereas rod license holders fish quite regularly.

More detailed surveys were carried out in 2001 and 2007 (surveys of rod license

holders). 2001 was particularly detailed, breaking results down by area and type of

fishing, and giving estimates of consumer surplus, based on willingness to pay for

the activity and participation rates, split by game and coarse fishing.

There are no current plans to get better data. New values would be useful, but

would need to be determined with considerable care. Travel cost models for single

sites are seen as problematic for fisheries: there would be more interest in Random

Utility Models (see section 4.3.4) taking into account site substitution and

frequency, but there are several features to consider. One is that the existence of

a site/opportunity doesn‟t necessarily mean that people know about it (and this

also means that better publicity of existing opportunities may be more effective

than trying to create new ones). Issues include:

is the site accessible?

if it is, how easy is it to get hold of the landowners and get permission?

what is individual knowledge of these factors?


eftec July 2010 21

what are the alternative locations and activities?

But the recreational value is seen as an important gap, in particular for evaluating

different activities to increase levels of angling. It is possible to work out the

regional economic impact, but not (with any accuracy) the value to the anglers

themselves of the recreational experience. The EA would be interested to see how

recreational fisheries values fit within the much broader value context of the WFD

and RBMPs. It would be interested in further work if Defra was planning to take

forward a general valuation of outdoor recreation and would want to explore how

fisheries were taken on board in such work.

2.3.6 Marine Policy and Marine Protected Areas

Up to now, there has been no direct use of recreation values in Defra marine

policy. However the MCZ regional projects are conducting impact assessments and

this involves a number of small-scale surveys, including recreation surveys, though

the sampling frames are not intricate. Different regions are using different

methods. The overall aim is to understand the values that users attach to different

areas (asking which areas are used and how often), but this is not being interpreted

in a monetary valuation sense, and data structures are constraining (e.g. “how

often do you visit?” being recorded in categories - once/week, once/month … -

that do not allow accurate evaluations). One region is augmenting the basic

questions about how respondents would divide 100 pennies across these areas,

which gives some indication of relative valuations, but does not allow actual WTP

estimates.

Overall the evidence on recreation, and in particular on economic benefits,

available for use in the MPA designation process has been rather weak. There are

important recreational uses of the marine environment, some of which are likely to

be heavily dependent on aspects of environmental quality (notably angling, diving,

birdwatching) and recreation values should play a role in marine spatial planning

more generally. However, evidence on the monetary value of these activities, and

the relationship to environmental variables, is largely lacking. For example Austen

et al. (2009) presented an analysis of the impacts of aggregates extraction in which

leisure and recreation was accounted for through expenditure measures: no data

were available for monetary valuation, and the relationship between recreation

and the impacts of aggregates extraction was also uncertain.

For the Productive Seas Evidence Group (PSEG), ABPmer and the Crown Estate

looked at recreation values, but found this a challenging issue. The main focus was

on tourist expenditure and the impact on local economies. Participation in a

number of different activities was reported, sourced from regular British Marine

Federation reporting. A range of different economic measures were considered,

based on those that were available: turnover (boat sales etc), investment

(infrastructure), expenditure (on recreation). The findings are summarised in Box

3. Consumer surplus/ willingness to pay measures of recreation were not

considered, because it was considered that suitably robust measures were not

available, and primary research was beyond the scope of the PSEG project. But


eftec July 2010 22

there was a view that better understanding the recreation value is extremely

important, as it could represent the third most important economic value from the

sea7. The overall picture is that recreational data is important for marine

management, and it would be useful to establish consistent data both for the

impacts on local economies, and for consumer surplus measures.

Box 3: Marine recreation in the UK: PSEG findings.

PSEG split value evidence into three main categories:

Principal: the direct impacts of leisure and recreation activities. These are

difficult to assess (since recreation values are not available and many activities do

not involve market expenditures) but some indication of significant value is given

by numbers of participants: in 2007, 5.4 million people participated in watersports

and 0.8 million in sea angling.

Ancillary: associated construction, manufacture, repair and facilities. Useful

indicators include regular reports by the British Marine Federation of the small

commercial marine industry (turnover £1.84 billion in 2006/07); surf retail report

(turnover £200 million in 2007); and total expenditure from recreational fishing

(£538 million for England and Wales in 2003 and £141 million for Scotland in 2008).

These sources provide a total estimated market turnover due to leisure and

recreation of £2.74 billion.

Secondary: accommodation and other tourism services. The estimated income for

coastal towns from tourism in the UK is calculated at £4.8 billion, resulting in a

GVA of £2.26 billion.

Other benefits identified as potentially substantial include employment and

cultural values. It is noted that activities and values are dependent on the general

economic situation and on the environment, in ways that are very difficult to

quantify: removal of marine fauna and flora, physical or visual disturbance of

wildlife, pollution and alteration of coastlines, and measures to facilitate access

can all influence values.

It should also be noted that these categories are not strictly additional in an

economics framework. In particular, the expenditures on accommodation and

tourism services are costs of participation in leisure and recreation activities, and

can not be considered as additional benefits to the users of recreation resources

(though they do represent benefits to the local economies).

Defra is planning a five-year programme of valuation work in the marine

environment. At present this seems likely to go ahead, though details of scale and

timing are not finalised, and priorities are to be defined. The focus will be at the

habitat level, using an ecosystem services framework, and recreation will be

7 Behind oil and gas and telecommunications; fisheries values are relatively small.


eftec July 2010 23

considered within this. The key driver for the research is for policy appraisal and

value for money purposes.

2.3.7 Agriculture and Environmental Stewardship payments

Outdoor recreation in agricultural landscapes is important, and valuing this

recreation could add to the evidence base used for targeting and evaluating policy,

for example in justifying agri-environmental schemes. There is a lack of research

in this area, and at present agriculture is an area where recreation values could be

useful but are not actually used.

The value of recreational benefits from environmental stewardship could be

important, and not currently quantified. There is particular relevance for National

Parks, with Defra (2009) stating that the government “expects further close

cooperation with Natural England to ensure that agri-environment scheme delivery

is properly integrated with National Park objectives and activities within the

farmed environment.” National Park objectives include promoting recreation (see

section 2.3.11).

Defra has no plans at present to commission research to look at this specifically.

There is an ongoing project on stewardship aiming to calculate willingness to pay

for schemes carried out: this may cover recreational value implicitly, but not

explicitly or in separable form. Results will be used for assessing the value for

money of stewardship, determining what works best, and prioritisation for the next

round of the Rural Development Programme for England.

Values in this area will also be useful for Natural England work on access on

Environmental Stewardship land, and more generally within the Rural Development

Programme for England, which has multiple objectives (including biodiversity,

landscape and access). Evaluations within the Programme aim to provide a best

estimate of value overall. For environmental stewardship schemes and rural

development regulations the marginal impact is the focus: in other words it is not

the recreational value of agricultural land per se, but the difference between land

which is and isn‟t in the schemes.

Recreational values are not as yet included within appraisals, and the costs and

benefits of deriving and using such values within the Rural Development

Programme remain to be considered. Valuation of recreation is a secondary

objective compared to the valuation of biodiversity and landscape changes, and

the interest is more in the joint value of biodiversity, recreation, landscape and

water quality, and it may not be necessary to separate them out. The MENE survey

data will not be specific enough to farmland management to allow a focus on the

marginal difference of land managed in a specific way, and so on the face of it

seems unlikely to be directly useful for this work.

Recreational values would also be useful for Defra‟s environmental accounts, but

are currently not included in them. In general, most uses of recreation values will

focus on the marginal values of a specified change in provision or quality.

However, the baseline/counterfactual for the environmental accounts is one of „no


eftec July 2010 24

agriculture‟, characterised by land abandonment and return to scrub land or

woodland (and not by alternative uses of land such as a land development). This

was chosen to keep in line with the conventional accounts which assume a

counterfactual of „no production‟. Generally this means that total values for

agriculture need to be included, and the total values of recreation might be

included in the accounts. This is a debatable point, however, since the „no

agriculture‟ baseline would not stop recreation on the scrubby/wooded land.

Recreation can also be heavily impacted by agricultural diseases and associated

policy. The foot and mouth epidemic in 2001, for example, had a major impact on

tourism and outdoor activities across the UK. For the UK, losses to agriculture and

the food chain were estimated at £3.1bn, and losses to tourism were about the

same (£2.7bn-£3.2bn) (Defra/DCMS, 2002). Similarly, the costs to Scottish

agriculture were estimated to be £231m and the loss of gross revenue to tourism to

be between £200–250m (Royal Society of Edinburgh, 2002). But these figures take

no account of the loss of consumer surplus for users of the outdoors; though nor do

they take account of displaced expenditure on other tourism or other goods and

services. In any event, it is clear that there is a potentially large cost that, in the

absence of robust estimates of recreation values, has not been accounted for.

Recreation impacts also occur in less extreme circumstances: for example,

recently, in the less serious and rapidly controlled 2007 outbreak, Windsor Great

Park, which normally has two million visitors per year8, was closed for three

months9; this will have resulted in loss of consumer surplus for potential visitors

who will have visited elsewhere or engaged in other activities, but without good

estimates of recreation values, taking into account substitute sites and activities,

these losses are hard to assess.

At present, Defra is commissioning work for assessing the damages associated with

Phytophthora10 infestations, asking contractors to suggest and implement

methodologies for valuing the loss of visitors to heritage gardens from having to

close an entire garden or parts of it. It is not clear to what extent „lost‟ visitors

will switch to other heritage gardens not affected, so that overall there will be no

loss at a national level, or will instead engage in other activities, and contractors

will be asked to investigate these possible effects.

Monetary values for recreation would be useful in this context, for Impact

Assessments or updates of Impact Assessments. For Phytophthora, for example,

there were no valuations available for heritage gardens. Tourist expenditure was

used, but Defra is seeking to improve/update this measure.

8 http://www.thecrownestate.co.uk/windsor_great_park

9 http://en.wikipedia.org/wiki/Foot-and-mouth_disease#United_Kingdom.2C_2007

10 A genus of fungus-like water-moulds, and in particular P. ramorum causing “sudden oak death” and

P. kernoviae affecting particularly beech; both also affect other species and notably rhododendrons.


eftec July 2010 25

Overall, in the agriculture area it is considered that recreation values would be

useful for a range of purposes, at present especially for the Phytophthora work.

However this is not seen as an urgent priority for primary research – there are more

pressing gaps such as valuing changes in agricultural landscapes. Therefore the

potential for using value transfer techniques to transfer outdoor recreation values

for use in agricultural assessments is of particular interest.

2.3.8 Rural policy

Recreation is important in rural policy especially in the context of identifying what

tourism contributes to rural communities. Defra is in the process of commissioning

a literature review of evidence for these impacts, to fill the current evidence gap

on its impact specifically on rural communities; on details of tourist spend and

businesses supported; and on the distinction between purely rural and part

rural/part urban visits. The additionality11 of visits, and multiplier effects,

including associated employment, are also of interest.

There is interest in clarifying the characteristics that determine beneficial impacts

to tourists and local communities – is a golf course better than a car park, for

example? Facilities may also be used by locals, providing rural benefits as well as

employment opportunities, and these factors also need to be taken into account.

The main interest in this policy area, therefore, is not really on the values to

tourists, but rather on the local economic impact. However, some of the research

issues will be the same, in particular because of the need to determine what

factors attract tourists to rural areas.

2.3.9 Forestry Commission

Forest recreation has long been recognised as important and valuable, and the

Forestry Commission was at the forefront of using recreation values in the UK. The

initial focus was on revealed preference, with a suite of studies by Ken Willis and

others dating back to the early 1990s (see e.g. Willis and Garrod 1991, Garrod and

Willis 1992) and resulting in a standard value per visit being adopted in FC

economic appraisals, established in 1992 at £1 per visit (since indexed). The Willis

et al. work focused on key benefits of forestry, but predated the ecosystem

services framework.

Willis et al (2003) estimated values of £1.84 to £3.06 (at 2008 prices) for each

recreational visit. Bateman and Jones (2003) provide a meta-analysis of forest

recreation values for the FC. They include 13 different studies published before

1997, covering 21 different woods and forests that provide a total of 77 different

estimates of the per-person per-visit recreational benefits from both travel cost

and contingent valuation methods. The majority of these estimates relate to use

value, although 16 are classified as relating to use plus option values. Of the 61

11 „Additionality‟ here refers to the extent to which visits are extra visits induced by policy

interventions, compared to visits that would have taken place anyway.


eftec July 2010 26

value observations related to current use values, estimates range from £0.11 to

£4.78 (2008 prices).

Values are seen as very useful for management, being used for impact assessment

and economic appraisal, and also aggregated for strategic appraisal and advocacy

(figures for Ministers and so on). Both value and trip numbers are needed, and

value is very important: a recent submission to Defra required estimates of values,

not just numbers of visits.

More recently, the FC has commissioned studies using stated preference methods

(Christie et al 2006), though this research used travel cost and contingent

behaviour (see section 4.3.5) as well as choice experiments. The aim was to

explore how attributes of sites affect total value, and values for different types of

users/ segments of the market. Christie et al estimate the value of recreational

improvements to forest sites for different user types (walkers, cyclists, horse

riders, nature watchers) ranging between £8.53 - £16.18 per visit (2008 prices) via

travel cost studies. Contingent behaviour and choice experiment analyses are used

to estimate changes in visitor welfare associated with improvements12 to specific

recreational facilities (e.g. value of paved cycle track to cyclists).

Spend and employment data are also considered, but these are relatively trivial in

comparison to the very large benefits of some non-market categories, including

recreation.

There has been no primary valuation work since the studies cited above, and there

are no current plans to invest in more primary research in stated or revealed

preference, but economic values are used in appraisal and assessment, for example

in eftec (2010b). Currently the FC is more interested in the „next level‟ beyond

recognition of non-market values: policy instruments for achieving better

outcomes. Further valuation studies would be useful, but not as useful as policy

mechanisms, such as biodiversity offsets or changes to the tax regime, that could

make a practical impact on the ground. However there are gaps in the ecosystem

service valuation base generally, and filling these would be useful. New numbers

on basic recreation values are not a priority, but work that would show how to take

substitute sites and activities into account is important. The FC does make

assumptions regarding displacement – e.g. a study of Galloway forest park reduced

values by a fixed % to allow for this – and substitute sites are being included in

some predictive modelling work, but there is a need for more research in this area.

There is also a desire to start “drilling down” from basic value estimates to explore

details, for example associated with values for people living near high quality

12 Note however that what one user considers an improvement may be viewed as excessive

development by another: in principle, valuation studies should detect averages across all, including

those who have negative values for a change. In practice, those who prefer low-facility areas are

likely to focus activities on such areas. For detailed specific assessments these factors may be

important considerations, but for the current broad assessment, with scenarios involving limited

changes in facility provision, such nuances can be ignored.


eftec July 2010 27

forests, assessment of how spaces change behaviour, and roles the outdoors can

play in improving life.

Various primary surveys (see sections 3.2.1, 3.4.3, 3.4.4) and data are used by the

FC, and its Forestry Research division carries out valuation of the economic and

social contribution of forestry. It is also investigating employment, recreation,

learning and community capacity, health and well-being impacts.

In terms of data held and possible use in travel cost, the 1990s data used for

developing values included home postcode data, and so enables the (approximate)

estimation of start-points for trips. However more recent studies often do not

record postcodes, and often use location-specific questions (rather than the older

standard set), limiting the potential for combining data across surveys and

estimating travel cost functions.

2.3.10 British Waterways

British Waterways carries out an annual telephone survey (Inland Waterways Visitor

Survey – see section 3.2.2) as well as automated on-site monitoring and a

programme of annual on-site visitor surveys (see section 3.4.5). Data are used in

particular to examine trends in visitor numbers, with a target of doubling the

number of pedestrians using waterways by 2012. Data are also used to assess the

impact of projects, and for fundraising, marketing and general awareness

activities.

2.3.11 National Parks Authorities

The National Parks and Access to Countryside Act 1949 defines the purposes of the

Parks as being:

to conserve and enhance the natural beauty, wildlife and cultural heritage

of the National Parks; and

to promote opportunities for the understanding and enjoyment of the

special qualities of the National Parks by the public.

The Norfolk and Suffolk Broads Act 1988 gives the Broads Authority these

two purposes plus a third of protecting the interests of navigation.

The Sandford Committee (1974) gave rise to the Sandford Principle, leading to

guidance and then legislation13 that requires any “relevant authority”, when

performing functions which relate to or affect land in a Park, to attach greater

weight to the purpose of „conserving and enhancing‟ if it appears that there is a

conflict between the two National Park purposes. The Sandford Committee and

Principle are also at the root of the “honeypot” approach to visitor management,

with the conclusion that “By developing the capacity of suitable areas to absorb

13 Section 62 of the Environment Act 1995, which inserted section 11A(2) in the National Parks and

Access to Countryside Act 1949.


eftec July 2010 28

greater numbers of the more gregarious visitors, pressures may be diverted from

the wilder and more sensitive areas”.

Defra (2009) stresses that “It is vital that all opportunities to deliver greater value

for money are seized.” and explains that for the NPAs this means:

demonstrating the value for money of the activities that they carry out in

pursuit of their purpose;

seeking and achieving better for value for money in the procurement of

goods and services through, for example, collaborative procurement and

embracing the principles of „sustainable procurement‟;

delivering operational efficiency savings through, for example, sharing

back-office functions, accommodation;

improving property and asset management; and

developing further funding streams, for example taking on additional

funded work from local authorities.

The Government expects Authorities to develop and publish their plans for

achieving greater value for money and to engage fully in any future review of the

delivery landscape.

National Park Authorities use both qualitative and quantitative approaches to

evaluating recreation impacts. All National Parks release annual management

reports that set out qualitative and quantitative targets and indicators. Visitor

surveys are taken, covering visitor satisfaction, head counts, ethnicity and so on.

Work is ongoing on developing “State of the Park” indicators (see Box 4): there are

about 300 different types of data collected across the Parks, and performance

indicators link to local authority / Audit Commission performance indicators.


eftec July 2010 29

Box 4: Criteria for “State of the Park” indicators

Suitable indicators should meet the following criteria:

measure „outcomes‟, not outputs;

cumulatively, provide „balanced coverage‟ of the range of issues directly relevant to national park purposes;

measure the „State of the Park‟, not the national park authority (i.e. include data from a range of organisations);

be relatively easy to „understand‟ by the public;

use „robust‟ and unambiguous definitions;

be capable of being collected at least every five years so data is „up-to-date‟ and it is possible to see trends over time;

be „useful‟ (to national park authorities, Defra, ENPAA and NE);

be „affordable‟ (i.e. not cripplingly expensive) to collect. Possible indicators for access include:

Percentage length of Public Rights of Way which are 'easy to use'

Total length of routes accessible to those with limited mobility

Length/percentage of rights of way that are fully accessible by

wheelchair users

Number of passengers using NP bus services annually

Total area of land open to public access

Percentage of land open to public access which can be closed for live

firing

Number and percentage of days each year that range danger areas

may be closed to the public (published closure)

Number and percentage of days each year that range danger areas

were actually closed to the public (actual closure)

Important issues vary from park to park: some fairly common issues can be

identified, such as the impact of wild camping and the use of off-road vehicles.

Each National Park makes use of STEAM (see Box 5) in conjunction with local tourist

boards to derive estimates of tourism expenditure. Parks often enhance national

data with their own surveys or analysis for bespoke purposes, but there is no

coordinated approach. For example Yorkshire Dales National Park Authority

commissioned research into cycle tourism (Institute of Transport and Tourism 2006)

while developing a Cycle Tourism Strategy. This focused on estimates of current

and projected demand and expenditure, and also cited evidence for health savings,

but did not consider consumer surplus values for cyclists.

Beyond the identification of tourist numbers, tourist expenditure and local

economic impacts, monetary values for recreation have not been used, but would

be considered useful. Other issues have higher priority (for example assessment of

an area‟s capacity, the role of substitute sites and impacts of displaced pressure)


eftec July 2010 30

and the key management aims are to improve experience and mitigate against

negative impacts; but valuation could contribute to this.

There are certain provisos. While it is important to recognise that outdoor

recreation is valuable, even though direct payments for it are low, attempts to

measure this value must not obscure the other „intangible‟ and social benefits such

as psychological benefits, children going out, learning about risk and challenging

themselves, which might not be represented in recreation values. Monetary values

would be particularly useful for demonstrating value for funding purposes, but

would need to be cut, or cuttable, to the National Park boundaries. In some cases

the need for monetary values was considered “pressing”, in order to show that the

aims of a park are achieved and can be demonstrated.

Defra is interested in evaluating the value for money of grant-in-aid to National

Park Authorities, and is carrying out work on “what is the added value of NPAs?”,

looking at impacts on biodiversity, cultural heritage, recreation, education, and so

on. One of the key issues is determining additionality – i.e. what is the added

benefit of the NPA management actions, over and above values that would exist in

the absence of this activity?


eftec July 2010 31

Box 5: STEAM (Scarborough Tourism Economic Activity Monitor)

The Scarborough Tourism Economic Activity Monitor (STEAM) was initially

developed in the 1980s in Canada. It has been adopted for use in the UK and is

widely applied, for example by National Parks authorities and local authorities.

STEAM defines a tourist day visit as one which crosses a boundary from one area

into another area, for a period of at least three hours for non-routine leisure

purposes. This includes outdoor activities, but also indoor attractions, visiting

friends and so on. STEAM uses visitor expenditure data from visitor surveys and

estimates of the number of visits to estimate local economic impacts of tourism.

STEAM is not a formal statistical model but rather a spreadsheet model, with the

values of the relationships in the spreadsheet being specified at each stage by the

user. Within the overall framework of the model, the precise data input can vary

depending on what survey data are available, supplemented with expert opinion

regarding the structure of tourism in relation to the local economy.

In contrast to more traditional approaches focusing on demand for tourism

activities, STEAM focuses on the supply side, and also focuses on the local

economic impact. STEAM is not designed to provide precise estimates of tourism

activity, but rather to assist in monitoring trends. The focus is on all tourism, not

solely on outdoor activities.

The focus on local economic impacts means that STEAM does not take any account

of the value of recreation in the sense of this report, i.e. the value to the people

undertaking the activity.

Peak District NPA

The Peak District NPA has developed a Recreation Strategy & Action Plan for 2010-

2020. The plan develops aims, outcomes and actions to provide the basis for

working with partners to ensure a “more joined-up approach” to delivery of

recreation. Priorities include raising awareness of recreation opportunities

(particularly to target groups), including how to access the NP more sustainably;

improving health messages; increasing opportunities for all; and increasing

community participation and volunteering. There is only a small budget to help

deliver this (£5k p.a.) so it will be done mainly by influencing others and seeking

funding.

Recreation impact is considered mainly in a qualitative way, though individual

initiatives may have their own quantitative measures. The statutory purposes,

refined within the National Park Management Plan and its daughter document, the

Recreation Strategy, mean that customer satisfaction is considered above monetary

aspects, although the impact on the local economy of increased tourism spend is

considered. The success of projects is assessed against targets within those

documents: for example relating to increasing participation by target audiences in

guided walks, cycle hire, and volunteering.


eftec July 2010 32

The PDNPA uses the England Leisure Visits Survey and UK Tourism Survey for

background information (e.g. trends in behaviour) and the Active People Survey to

measure recreation activity locally (although the data cannot be cut to the NP

boundary, so can only be indicative). Surveys of their own services are also used,

generally to gauge customer satisfaction and monitor against targets for reaching

certain audiences. In 2008 an on-line Recreation Survey was used to better

understand use of the NP (what people do there, patterns of behaviour, future use,

spend, …) to provide background for the Recreation Strategy. A Residents survey

has been carried out to understand local views about the Authority, including

questions on recreation (frequency, satisfaction). The Authority no longer carries

out automatic people counts, but other organisations provide counters on national

trails within the NP (the Pennine Way and Trans-Pennine Trail). The Highways

Authorities provide data on vehicle counts which may be used for transport

planning.

Economic impacts of PDNP tourism have been considered in “Contribution of the

PDNP to the economy of the East Midlands, Nov 2008” and “Peak District Tourism

Employment Study, 2001”. The PDNPA is currently considering the acquisition of

STEAM data on volume and value for the NP (currently they use STEAM data for

Peak District & Derbyshire Destination Management Partnership, a tourism body of

which the NPA is a partner). These are used as background information and to

understand trends in behaviour. A basic problem in making more use of economic

or monetary values is limitations in the recreation and tourism data available, and

the cost of further research work. There is also an issue of obtaining data that fits

the NP boundary. The idea of monetary values for recreation is considered “nice

rather than essential”, and in practice difficult to achieve, though it is recognised

that in financial terms it might be in the National Parks‟ interest to assess the

value of recreation visits.


eftec July 2010 33

Box 6: Value Transfer case study of Peak District National Park

eftec (2010, case study 6)14 presents a case study of value transfer for assessing

the benefits of visitor services provided by the Peak District National Park

Authority. Based on transfer of values from the economic literature on recreation,

and estimates of the impacts of withdrawing visitor services provided by the

PDNPA, aggregate estimates of loss of annual benefits to visitors from withdrawal

of services amounts to approximately £3 – 5 million in total.

This is only a partial assessment of the value of visitor services: it covers visitor

centres, ranger guided walks, volunteer activities and educational activities, but

there is no value estimate for benefits derived from the provision of basic visitor

facilities, activities such as maintenance of footpaths and trails and the ranger

service. The numbers of visitors per year that are likely to benefit from these

excluded aspects from the aggregate calculation could be substantial, implying

that even relatively small unit values could result in substantial aggregate

benefits, making the £3 – 5 million a conservative estimate. Estimates within the

sensitivity analysis could support values up to £36m per year.

The case study draws on a variety of data and inevitably highlights gaps and

uncertainties in applying valuation to the complex set of visitor services provided

by PDNPA. A fuller and more detailed assessment of the NPA expenditure would

require further data, notably robust visitor counts and profiles. There is also

scope for primary valuation study with a specific focus on the outcomes arising

through the NPA‟s activities, in contrast to the evidence available for value

transfer which relates to general recreation values. This would represent a

substantial step forward in assessing the value for money of the NPA‟s expenditure

and would assist also in prioritisation and strategic planning, identifying service

areas that generate the greatest value to visitors.

2.3.12 Natural Economy Northwest

Natural Economy Northwest (NENW) is a partnership between the Northwest

Regional Development Agency and Natural England. NENW has been working on the

evaluation of green infrastructure, in particular in the context of making the case

for investment in Green Infrastructure (GI). GI is seen in a broad context as “the

Region‟s life support system”; there is particular emphasis on the economic

benefits of GI, but multiple other benefits are recognised including improved

biodiversity, access, health and well being.

It is stressed (AMION 2009) that because the Review of Sub-National Economic

Development and Regeneration (HM Treasury 2007) identified RDAs as the principal

delivery agents for increasing regional Gross Value Added (GVA) per head, this

14 http://www.defra.gov.uk/environment/policy/natural-environ/using/valuation/documents/case-

study6.pdf


eftec July 2010 34

“needs to be the „ultimate‟ quantified outcome for assessment of RDA

interventions.” This means that a key challenge for the work was to relate GI

interventions, where possible, to the overall RDA outcome measures – “while

recognising the „legitimacy‟ of other impacts and outcomes”.

Hence the headline “key message” is “The Northwest‟s environment generates an

estimated £2.6bn in Gross Value Added (GVA), and supports 109,000 jobs”.

However, another key message is “Economic value is complemented by the non-

market social and environmental benefits that green infrastructure can offer.”

NENW presents a list of values taken from the background reports under the

heading “The tourism value of forests”:

“It is estimated that woodland recreation in England has a value of between

£1.66 and £2.78 per visit” (an estimate based on value transfer of consumer

surplus estimates )

“An additional 330,000 visitors to the National Forest since 1995 have

contributed an additional £128m annually, creating and supporting more

than 500 full time equivalent jobs” (an expenditure measure)

“The annual value of forests in the UK in terms of recreation and landscape

value equates to some £400m. In the Northwest the annual value has been

estimated at £35m” (most likely based on consumer surplus measures)

“Research indicates that residents in suburban settings are willing to pay

£7,680 per household for views of broadleaved forests, which would equate

to £4.2bn across the UK” (a measure from hedonic pricing, and a capital

value – i.e. this is a stock value, not a flow of benefits, and so can not be

added to annual flow values)

Individually these estimates are all useful, however it is important to recognise the

different contexts (added in parentheses) and in particular to note that we can not

directly add or compare consumer surplus estimates and GVA estimates, or flow

and capital values.

NENW (2009) notes that “Other policy and information requirements are still in

progress. An important role will be played by Defra‟s work on valuing ecosystem

services, which will allow major gaps to be filled in Treasury advice on valuing non-

market goods, and play a strong role in persuading public and private investors that

green infrastructure can provide more valuable outputs than can be attributed

using current measures.”

The overall conclusion to be drawn from this is that there is a very clear willingness

to use monetary valuations for recreation (and other ecosystem goods and services)

if sound estimates can be made available. At the same time, there appears to be a

need for better communication and guidance regarding what the different

measures are, and how they can be used and combined.


eftec July 2010 35

2.3.13 RSPB

RSPB visitor surveys tend to focus on what attracted visits, how important wildlife

is in a visiting decision, and estimation of spend. Distinctions are made between

locals, day trippers and longer stay visitors, and an estimation is made of the role

of reserves in motivating visits to an area. Multipliers are then used to estimate

full time job equivalents supported by the expenditure. Surveys are not systematic

or regular: there are a few reserves with annual surveys – the main visitor sites –

and some others with 5-year intervals. The big reserves draw 80-100,000 visitors

per year, but there are not many sites getting over 50,000. For charismatic

species, there can be bespoke/one-off surveys, and these are easier to undertake

at specific watchpoints (e.g. viewing nests of iconic species such as ospreys, sea-

eagles). The general RSPB approach to recreation surveys/monitoring is to focus

on 10 reserves in detail and then scale up the results. The 2002 publication

“Conservation Works” reported evidence from the last detailed survey, with

piecemeal annual updates undertaken since then; another detailed survey is

planned for this year. Relevant visitor data also exist for sites with entrance fees

and/or metered parking.

The information is used for a range of communication purposes. The target

audience is often RDAs, making an economic case for funding, hence the impacts

on local or regional jobs and expenditure are key. Information is also used for

tourism promotion (e.g. regarding charismatic species) and more general advocacy

work, presenting the RSPB as a landowner understanding its contribution to local

economies and GDP.

The RSPB has never attempted to use stated preference methods in its surveys, due

to concern about giving the impression that is considering charging for access to

reserves (free access being a key selling point of membership). Travel cost has not

been attempted either, with the exception of the Harley and Hanley (1989) study

at Loch Garten, although many surveys do cover visitor start point and spend, and

so it might be possible to use the data for this purpose, by estimating the cost of

travel from start point to site. But data on socio-economic characteristics are not

collected in any detail, so the range of variables available for inclusion in the

model would be limited.

Discussions are ongoing about research into the impacts of reserves on well-being.

This does not necessarily imply monetary valuation, and education benefits and

health benefits are of key interest. In general, there is not enough understanding

of the motivations for visits (birds, site attractions, facilities) and this is one focus

of research. Substitute sites and activities are not really taken into account, and

there is a problem of connecting changes in visit numbers to changes in site

quality.

Historically the monetary value of recreation has not been a key issue, rather being

considered as a by-product of primary conservation objectives. Now, however, the

RSPB is moving with the trend of considering ecosystem service provision in the

round, with a focus on multiple functions, and a matrix of different users and the

services/functions from which they benefit. Mapping visitor numbers and


eftec July 2010 36

movements, reasons for visits, and values will be important for strategic and

advocacy purposes.

2.3.14 National Trust

Traditionally the National Trust has only surveyed and monitored visits and levels

of satisfaction for buildings in the NT portfolio, but more recently there has been

some specific concentration on outdoor activities. Generally the Trust has used

surveys that visitors take away from properties to be completed and then returned

by post, and it is recognised that there is a particular problem of selection bias

with this method (different completion rates for different user groups). There has

also been a history of ad hoc on-site research, originally only in buildings, but in

the last year or so extended to outdoor resources, where staff invite people to

discuss what they enjoy about the site; but this is not considered ideal, either,

since it interrupts people‟s enjoyment of their visit.

A major component of this research outdoors has been to identify if the Trust‟s

segmentation model, with seven classifications of user characteristics, holds up for

outdoor resources as strongly as for built property. There is also a desire to assess

how characteristics of sites impact on enjoyment. The main focus is to identify

how to improve experience at the Trust‟s properties.

The approach to assessing decisions with impacts on recreation has been mainly

qualitative, based upon surveys, but with some quantitative analysis such as

considering how far people have travelled (locals and tourists). The NT

segmentation model features strongly; other national surveys such as ELVS have

been used to provide visit patterns and background.

Monetary values have not been used: the focus is more on awareness. Statistics

from perception surveys suggest that 80% of visitors recognise the National Trust

for its houses and gardens, but only 30% for its coast and countryside landholdings.

The Trust wants to raise this profile; against this context, monetary value is

relatively unimportant.

There is also concern as to how values would be calculated, and a view that travel

cost approaches may overlook the importance of local green spaces. The values

could also be misused, and in particular do not cover cultural non-use and spiritual

values that could, potentially, be enormous.

The overall view is that the figures for monetary value of recreation are not

needed by the Trust, but would be considered interesting and would potentially be

used. Value transfer techniques – whether monetary or more general – are also of

interest, if it is possible to learn how analysis from one site can inform assessment

at others (and thereby avoid the need for disruptive on-site surveying, or imperfect

take-home surveys).


eftec July 2010 37

2.3.15 Scottish Natural Heritage

SNH uses a range of data, notably from the Scottish Recreation Survey. The

recreation team is investigating the use of data collected, summarising economic

information and identifying whether it is useful. Data on average expenditure are

considered useful, but at present there is no use made of monetary estimates at

all. Research is underway to approach the use of monetary estimates in a

consistent and coherent way; results are starting to be used, but on the whole

remain inaccessible due to the sheer volume of data.

SNH is working with “Paths for All” developing an economic and social tool kit to

quantify the economic and social benefit of footpaths. Monetary valuation of

recreation is not yet seen as a “pressing” need, but is an “increasing” need.

Quantifying impacts and measuring value for money is going up the agenda, with

fiscal constraint in the public sector imminent, and expressing impacts in monetary

values is useful.

2.3.16 Visit Scotland

Particular interests include identifying the gross value added of tourism, measuring

the number of visitors and how much they spend, identifying the main drivers and

attractions, marketing and evaluating the outcome of marketing. Forecasting is

also an important aspect. A wide range of surveys and data are used, and

additional surveys are designed and commissioned. The main objectives are to

enhance visit numbers and expenditure, with knowledge being developed in order

to formulate positive policy and strategy to encourage growth in the tourism

economy, but there is also a need to demonstrate returns on these investments.

Monetary values for recreation benefits could be of use, as could estimates for

other non-marketed goods and services. For example, evidence from studies

reporting the value of ancient Scottish woodland and the value of cultural heritage

could be useful. In the specific case of Scotland, monetary estimates are becoming

increasingly important with the introduction of single outcome agreements15 and

the need to show return on investment (this is somewhat analogous to Value for

Money in the UK context).

Overall, different measures are needed for different contexts. The focus tends to

be more on showing the impact on GDP, or on identifying direct expenditure and

employment impacts, but non-market measures can also be of interest, within the

overall picture of the tourism economy, and provides reassurance that a range of

baselines are available.

15 SOAs are agreements between the Scottish Government and Community Planning Partners which set

out how each will work in the future towards improving outcomes for the local people in a way that

reflects local circumstances and priorities, within the context of the Government's National Outcomes

and Purpose http://www.scotland.gov.uk/Topics/Government/local-government/SOA.


eftec July 2010 38

2.3.17 Countryside Access and Activities Network (Northern Ireland)

Monitoring by CAAN is partly quantitative and partly qualitative. One of the main

measures has been visitor numbers, collected via people counters, but this is not

seen as highly reliable. There has been increasing use of the website to get an

idea of numbers alongside more qualitative data, as well as working with the NI

Tourist Board on tourist numbers. But overall there are problems in achieving

reliable statistically relevant numbers. Some UK surveys are useful, e.g. the UK

tourism survey, but data are lacking for Northern Ireland. In some cases more in-

depth research is used, for example research is planned into walking, involving

online surveys, face to face interviews and focus groups.

Some previous scoping studies for research have aimed to estimate the value of

outdoor activity, but it was concluded that funding large-scale primary research in

this area was not within the means of the organisation. Better outdoor recreation

values would be very useful, primarily for demonstrating value to government

funders. Of greatest use would be NI specific values, and there is concern that

benefit transfer methods using UK-wide research might not be valid, failing to take

into account the specific character of Northern Ireland.

2.4 Consultation conclusions

Recreation value evidence can be used in a wide range of settings. We know from

existing work (see Annex 1) that values can be substantial. However they are also

often difficult to assess, in particular due to variations in value associated with

characteristics of recreation resources, substitute resources, and user populations.

In addition, often we do not have time-series data, and this makes it difficult to

assess the effects of changes in provision (quality, size or number of sites). This

means that in some cases where recreation impacts are assessed, simple

approximate unit values are used, and in other cases, recreation values are not

taken into account in monetary terms at all.

In the consultation, we have sought to consider the characteristics of the outdoor

recreation value evidence required: the scope of the change (marginal values,

discrete change in quality, new resources, total values); the level of aggregation

(for all uses and users, or disaggregated for different groups); the spatial and

temporal scales of interest; the required degree of accuracy; and the main uses to

which the values are or could be put. The general picture in response to these

questions is summarised below:

Scope of change: depending on purpose. Often marginal changes are of

interest, because the main use for values is in project appraisal and policy

assessment, but in some cases (e.g. managed realignment, large new nature

reserves, new urban community woodland) changes can be very large scale

from a local perspective. There is also demand for values for more general

communication and advocacy purposes, and here total values – for a given

resource or area – are of interest. Total values could also be used in

agricultural accounts and other forms of accounting for ecosystem services.


eftec July 2010 39

Level of aggregation: while for many applications the value aggregated over

all users, or an average value per user, is sufficient, some organisations do

make considerable use of segmentation models for resources users.

Spatial scale: is very context dependent. For general advocacy work and

broad-scale policy planning, the pitch may be the whole country level,

while for detailed assessment of, for example, damages associated with

heritage garden closures due to Phytophthora, values are needed at the

individual garden level. There can be boundary issues, for example ENPAA

stressed the need to be able to cut data to National Park boundaries. There

are also issues with the definition of scale and the “what is a site?”

question, in particular for linear features such as rivers, waterways and

footpaths.

Temporal scale: again this is context dependent. Generally project and

policy appraisal should take account of all impacts and in many cases this

can mean quite long time horizons, while for communication, advocacy and

funding-search the time horizons can be short, or even just current year. In

terms of timing of value evidence, in some cases the need is very pressing –

this is notably the case for use of values in River Basin Management

Planning, where values are required by 2012/2013 at the latest.

Degree of accuracy: the general view is “the best we can get” but with

different thresholds for reliability. In some settings, for example forestry,

values for recreation are already in use, and any improvement in reliability

will be welcome. In other cases there are concerns about methodologies

and the risks of losing sight of other important factors such as cultural and

spiritual non-use values; or there is more of a focus on promoting use levels,

and monetary value is seen as a potentially useful, but non-essential, side

issue. In some areas there is a view that revealed preference estimates are

on a sounder footing than stated preference estimates, since they are based

on actual behaviour, and this is driving the valuation agenda. One problem

cited (in the context of value transfer, but this applies more generally) is

that value estimates can be taken as too certain - i.e. the uncertainties are

not adequately reported or considered – which can be seen as a risk

associated with using monetary values for policy purposes. More generally,

there are perceived problems with data availability and reliability, for

valuation purposes and more generally.

Value transfer: there is often scepticism regarding the applicability of value

transfer, in particular regarding the importance of specific local features

and characteristics. There was also a suggestion that part of the problem is

that local scale data are not robust enough, making case studies more

appropriate than value transfer. But we would suggest that this needs to be

considered within the context of the level of accuracy required, and noting

that a value transfer based on a set of good quality, statistically sound

studies may be more accurate, and also cheaper, than a small-scale primary

study.


eftec July 2010 40

It is clear that there are many potential uses, and potential users, of monetary

values for outdoor recreation. The recreation-specific organisations have

considerable interest in this area, but most say values would be useful rather than

essential. Some of the policy areas have strong demand for values, notably water

in the context of the WFD, and more generally the value for money agenda makes

availability of recreation values a high priority in some areas. Thus arguably the

main demand is from the policy appraisal and evaluation side, but if this demand

were met, there would also be use in management and priority setting.

Many respondents noted that, while monetary values would be most useful, reliable

estimates of trip numbers, and information on the determinants of visits, would be

good enough. This relates to the concern identified by Bateman et al. (2002) that

economics research has tended to focus on estimation of robust unit values for

recreation, whereas the most important determinant of changes in values of

recreation is changes in the number of visitors, and this has been relatively

overlooked. More generally, value transfer studies have demonstrated that the

sensitivity of results to beneficiary populations is very high, and therefore requires

increased attention which had previously been focussed on unit values.

There are many different niches, and many organisations that would use values if

they were available, but that are not likely to invest significantly in primary

valuation research. Many organisations do invest in primary data collection through

on-site surveys on land they manage or own, but there is no overall coordinated

approach at the national level. There could be important economies of scale in

meeting the demand for recreation value provision at national level, through a

standardised programme of data collection and centralisation, and a strategic

approach to primary valuation research and the development of value transfer

functions. It is, therefore, good to have a consistent approach, and economy of

scale in collective data provision/coordination.


eftec July 2010 41

3. SURVEY DATA

Across the UK many recent or ongoing surveys have examined aspects of outdoor

recreation, at national, regional, organisational, policy and/or site levels. Some

target specific user groups (such as anglers or hunters) or specific areas (such as

the Peak District), while others have a broader scope and examine where people

visit in general, the leisure activities they participate in, how much they spend,

and so on. In addition to these surveys and monitoring there are research projects

that look at specific recreational activities. Here we provide a summary of the

main recreational surveys that have been conducted in the last few years.

Table 4 in Annex 1 provides a list of the key points relating to each survey

(including details of who sponsored or sponsors the work) while the following

sections provide further details.

Liley et al (2009) make a distinction between “survey” (data collection at a

particular point in time) and “monitoring” (periodic collection allowing trend

estimation). In this study we are interested in both, and also in various different

scales and approaches to measuring recreation activities. The following broad

categories can be identified (see Liley et al, 2009):

Off-site surveys: generally large-scale, aiming to identify general use patterns and

drivers. They can be conducted by post, by phone, in street or in home. Very

large sample sizes are required for robust results, but even so may not be able to

provide reliable data for specific sites. One advantage over on-site surveying is

that they can reach non-users and explore barriers to participation. For outdoor

recreation, MENE is the main current example, following the England Leisure Visits

Survey (ELVS) and predecessors. There are a number of other relevant surveys

focusing on more specific aspects of recreation (e.g. Public Opinion of Forestry,

Inland Waterways Visitor Survey), and some more general ones that touch on

aspects of recreation (e.g. UK Tourism Survey, International Passenger Survey).

On-site surveys: on-site questionnaires often involve face-to-face interviews, but

can also be in the form of questionnaires to complete and post back (used e.g. by

the National Trust, and seen as less disruptive to visit enjoyment). Information

collected can cover data for segmentation/profiling of visitors, travel modes and

distances, site satisfaction, expenditure and so on. This kind of survey lies behind

most applications of travel cost models to single sites, though it is also possible to

carry out travel cost in the respondent‟s home, generally for multiple-site models,

as in the ChREAM study (see Section 6.3) Surveys tend to be quite local, for single

sites or groups/types of sites, and there is no coordinated approach at national

level or across different organisations. There are also examples of application

across large areas, notably the All Forest Visitor Surveys in Scotland and Wales, and

the National Parks Visitor Survey in 1994.

On-site access monitoring: can be carried out in various ways, including automated

car or footfall counts, parking or entrance fee records, or manual counts at access

points. This can produce accurate estimates of visit numbers, though generally


eftec July 2010 42

there are uncertainties, whether in grossing up from a short surveying period to an

annual estimate (for manual counts) or inherent in the counting technology (for

automated counts). In itself, such monitoring is not sufficient for travel cost,

because no information is generated about visitor departure points, but the

monitoring is sometimes combined with a survey questionnaire for some proportion

of users. And such monitoring can be sufficient for developing functions to

estimate visit numbers, or for grossing up estimates of the value of individual visits

to total values for sites.

3.1 General off-site recreation surveys

The Monitor of Engagement with the Natural Environment (MENE) is the most

recent national off-site recreation survey, headed by Natural England with support

from Defra and the Forestry Commission. MENE is the latest in a series of national

outdoor recreation surveys, including the England Leisure Visits Survey (ELVS) 2005,

and its forerunners the Great Britain Leisure Visits Survey (2002) and UK Leisure

Day Visits Surveys (1994, 1996, 1998). In addition a number of other national

surveys focus on specific aspects of outdoor recreation, while others have some

relevance to outdoor recreation as part of their focus.

There has been a general issue of lack of comparability across all surveys (MENE,

Scottish recreation survey, Welsh, ELVS, GBDVS...), resulting in a lack of useful

data for trends. Reliability and consistency have also been variable: for example

ELVS had good coverage, but the Forestry Commission estimates that about half of

visits to woodland were not picked up in GBDVS or ELVS. The Scotland recreation

survey (2003) came up with much higher visit numbers. But the Scotland and Wales

All Forest Surveys for visits to FC forests give much lower numbers than from the

Scotland recreation survey, quite possibly because people were stating trips to FC

Forests that were in fact trips to other forests.

One of the objectives of MENE, therefore, has been to develop a stable set of

questions that will allow trend data to be generated over several years of the

survey.

3.1.1 MENE

MENE followed a scoping study (TNS 2007) commissioned by Natural England that

involved a review of existing data on recreation trips and development of options

for future data collection. Key drivers for the development of MENE are presented

in Box 7 below. MENE fits within Natural England‟s “Social evidence roadmap16”

that identifies five key questions about public engagement with the natural

environment:

Who uses and doesn't use the natural environment, and why?

16 http://www.naturalengland.org.uk/ourwork/enjoying/research/socialroadmap/default.aspx


eftec July 2010 43

What are the qualities of natural places and living things that people value,

enjoy and benefit from?

What is the evidence for social benefits arising from engagement with

nature?

What role does the natural environment play in influencing behavioural

changes?

When we talk about 'engagement' with the natural environment, how should

'engagement' be measured?

The survey is continuous and ongoing, and fieldwork started in March 2009; results

for the first full year will be available in summer 2010. Full information on the

survey can be seen on the Natural England website.

Previous surveys (see below) were led by a consortium of agencies, including the

Countryside Agency (now part of Natural England), Defra, Environment Agency,

Forestry Commission and various National Park authorities. MENE is managed by

Natural England, with Defra and Forestry Commission consulted at all stages and on

the project board that guides the development of the survey. There is a particular

desire to maintain a stable set of questions over a longer period, in order to

extract trend data.

MENE also has a different sample size and methodology from ELVS and previous

surveys. In particular, MENE is part of a omnibus survey conducted in respondents‟

own homes. This has various advantages, including increasing the response rate,

but also means that the survey is not geographically randomised but rather occurs

in clusters spread round the country. This does imply that the representation of

specific recreation areas will not be random/representative, although the

representation of resource types should be. This point applies rather less to major

recreation sites which have wide catchments, but these sites are not likely to be

picked up very frequently in the survey anyway.

MENE seeks to meet not only national but also regional data needs: this means that

a relatively large sample is required (MENE will involve about 40,000 interviews per

year) and this in turn limits the number of questions that can be included for a

given level of expenditure.

Notably, in the context of this research, though the development of the MENE

survey involved extensive consultation with stakeholders, including previous

partners from ELVS, the potential for using the survey for economic valuation

purposes was not identified as a key driver for the survey. The MENE survey,

therefore, has not been designed with economic valuation in mind, and any

suggestion in this report of „problems‟ with using the MENE survey for valuation

purposes is not intended in any way as a criticism of MENE or the process by which

it has been developed.


eftec July 2010 44

Box 7: Drivers for the MENE survey

Natural England has an objective to increase levels of engagement between members of the population and the natural environment. Engagement goes beyond visits to the outdoors – encompassing other outcomes of the experience such as enjoyment, understanding and learning. The scoping study behind MENE reported Natural England‟s views that:

comparability with the results of previous surveys undertaken in England is useful but not vital;

survey methods must be “robust in light of current trends in data collection methods and the public‟s willingness to respond to survey questionnaires”;

focus is now less on the number of visits taken, and more on the proportion of the population taking part; and

levels of engagement overall and within different sub-groups of the population are of more interest: ideally gaining an understanding of relationships between enjoyment, understanding and frequency of participation in outdoor recreation and what motivates people to engage.

It is noteworthy, however, that this stops short of a focus on the value of the trips to different individuals. Other drivers include:

Changing drivers of demand: understanding the increasing range of leisure activities available, and interactions between participation in outdoor recreation and „competing‟ activities.

Health benefits: fulfilling an increasing need to understand and measure the health benefits of outdoor recreation.

Carbon impact: this is increasingly important, and requiring specific data on travel modes and distances.

Segmentation: more sophisticated methods would help in the assessment of different engagements for different groups, and thence to targeting interventions and information provision.

Minority groups: connected to the above, care is required to ensure that particular groups (e.g. ethnic minorities, people with long term illnesses or disabilities and carers) are covered.

Geo-coding: proved very useful for 2005 ELVS, and is essential for future surveys.

Target areas: surveys must assess visits to open access land, National Parks and other designated land (though most members of the public are unaware of an area‟s designation). Sub-national coverage may also be important. Surveys may need “booster” samples in some cases.

Latent demand: surveys should seek to assess latent demand and scope for encouraging visits to „new‟ places. This is important for example in assessing how changes to provision or quality may influence demand.

MENE defines out of doors as “open spaces in and around towns and cities,

including parks, canals and nature areas; the coast and beaches; and the

countryside including farmland, woodland, hills and rivers”, and defines spending


eftec July 2010 45

time out of doors as “anything from a few minutes to all day”, potentially including

time spent near “home or workplace, further afield or while on holiday in

England”, but not time spent in the garden or on shopping trips.

The survey is split into sections:

“7 trip day diary”, asking basic information about all the outdoor trips over

the past week, including the main activities undertaken, and the general

location; and

“More detail on single randomly selected visit section”, which looks at one

trip on one of the last 7 days, including information sufficient to geo-code

start and end points, and therefore in principle providing the basic data

necessary for travel cost modelling.

It is also split into question “sets”, which are not all asked during every

interview. Questions and timings are summarised in Table 1.

The focus on the past week means that recall of visit behaviour should be

reasonably accurate, whereas questions relating to a whole year would likely

involve much more error.

MENE will therefore provide information on the volume of visits from home to the

natural environment by the adult population of England, and the main

characteristics of visits to the natural environment, including the duration, main

activity, and type of destination for all visits. Because MENE is a random survey, it

will be possible to gross up the figures to provide overall estimates for the whole

population.

However, this is only true at a broad level (frequencies and types of site) not for

specific sites, because the specific sites will be recorded only for a single random

visit per respondent, because the sample size for any given site will not be large

enough to allow valid statistical inference, and because the sampling method

(omnibus survey) is random for the population overall, but is not strictly

geographically random, being rather clustered. The survey was not designed to

provide robust visitor numbers to small sites, and so clustering was not felt to be a

significant concern. If data are aggregated over several years to provide estimates

for smaller sites, the extent of clustering should be minimised over time. The

extent of clustering is currently under review (based on the first year of data

collection). This is discussed in more detail in Section 5.2.1.

For a single random visit per respondent, the origin and destination, distance

travelled and mode of travel will be recorded; more detailed information on the

single random visit will be collected on a monthly basis. This more detailed

information includes expenditure during the trip, potentially important for travel

cost modelling in which on-site expenditures are taken into account.


eftec July 2010 46

Table 1: Question types and frequencies in MENE

Frequency Question numbers/subject

Weekly Q1 – Volume of visits per day

Q2 – Type of place for each visit taken

Q3 – Duration for each visit taken

Q4 – Activity for each visit taken

Q5 – Specific place – single random visit

Q6 – Village/town/city – single random visit

Q7 – Place name – single random visit

Q8 – Distance travelled – single random visit

Q9/10 – Where journey started from – single random visit

Q11 – Transport type used

Q19 – Access to car

Q20 – Dog ownership

Q21 - Health

Monthly

Q12 – Reasons for visit – single random visit

Q13 – Party composition – single random visit

Q14 – Whether with dog – single random visit

Q15/16 – Expenditure during visit – single random visit

Q17 – Frequency of visits – last 12 months

Q18 – Barriers to visits – last 12 months

Quarterly

E1 (between Q16 and Q17) – Outcomes of visit

E2 to E5 – between Q18 and Q19

E2 – attitudes to environment

E3 – activities in the natural environment

E4 – pro-environmental activities

E5 – changes in lifestyle

3.1.2 English Leisure Visits Survey

The 2005 English Leisure Visits Survey (ELVS) was the fifth in a series (1994, 1996,

1998 and 2002), but with a new focus exclusively on trips made in England by adult

residents of England. In addition ELVS was novel in providing geo-referenced

information for visit start and destination.

The survey was led and co-ordinated by the Countryside Agency (now Natural

England) and sponsored by a consortium of agencies with an interest in recreation

and tourism in England. The objective of measuring the participation, scale and

expenditure of leisure day trips was similar to previous studies. A new objective

was to produce more information about visits to National Parks and open access

land.

The survey took place from February 2005 to February 2006, with approximately

50,000 interviews taking place: around 23,500 in the core sample and 26,700 in a

“booster” sample. The booster was needed in order to increase the coverage of

visits to National Parks and large areas of open access land, but in practice little

over 900 additional “hits” were recorded. The basic issue is that major “days out”,

for example to National Parks, do not occur frequently enough to be picked up in


eftec July 2010 47

large numbers in a survey focusing only on the last 7 days, and it should be noted

that the same issue will arise with MENE.

Liley et al (2009) note that ELVS data were (and still are) widely used and quoted

as the key data on outdoor recreation in England. But there has been criticism,

notably that ELVS estimates of visitor numbers to National Parks and Open Access

Land were inaccurate and underestimated visitor numbers. The technical report on

ELVS (Research International, 2006) notes that “the data on visits to National Parks

and visits that included a trip to open access land must be handled with due

caution and used, reported and quoted with a caveat”.

The format included a 7-day trip diary and detailed questions on a single visit,

much as in the MENE survey. Additional questions were included if any trip

involved a National Park or open access land. Questions on frequency of outdoor

trips over the past year were also included.

The main results from ELVS were published in 2007, in the form of a main report,

technical report, headline facts leaflet and full supporting data, available from the

Natural England website.17

Day Visits Surveys (fore-runners to MENE and ELVS) were carried out in 1994, 1996,

1998 and 2002-03, for a consortium of government departments and agencies

interested in tourism and recreation. The surveys provided estimates of the total

number of leisure day visits from home to towns, countryside and seaside in Great

Britain (England, Scotland, and Wales). They also gave the demographic profile of

visitors and attributes of the visits such as duration and distance.

These surveys and ELVS allow some consideration of trends, however changes in

questions and survey methodologies mean that clear and statistically valid trend

information is not available. For example, ELVS (and now MENE) classes visits by

four main types of destination (Inland towns/cities, Seaside towns/cities,

Countryside and Seaside coast) whereas the Great Britain Day Visits Survey used

three main types of destination. This is one of the driving factors behind Natural

England wishing to retain control over MENE and keep the same question set over a

number of years.

3.1.3 Wales Outdoor Recreation Survey (WORS)

Following a 2006 pilot, Countryside Council for Wales (CCW) and Forestry

Commission Wales (FCW) commissioned the Wales Outdoor Recreation Survey

(WORS). The main survey ran for 12 months, with fieldwork undertaken between

January 2008 and January 2009, and results published later in 2009. The

partnership plans to repeat the survey in 2011.

17 http://www.naturalengland.org.uk/ourwork/enjoying/research/monitor/leisurevisits/default.aspx


eftec July 2010 48

The survey covers the outdoor recreation of Welsh residents, including activities,

places visited, motivations for using the outdoors, barriers to visiting the outdoors

and the „latent demand‟ for outdoor recreation.

3.1.4 Scottish Recreation Survey

Scottish Natural Heritage (SNH) and the Forestry Commission commissioned the

Scottish Recreation Survey to run on a continuous basis from July 2003 to the end

of 2013. The overall aim of the survey is to provide continuous monitoring of

participation in informal outdoor recreation in Scotland. Results are available on

the SNH website.18

The survey is divided in to 4 sets of questions that are asked with differing

frequency throughout the year. There is a „core‟ set, asked every month, while

the other sets are rotated and asked at least quarterly.

The main questions focus on overall levels and frequency of participation in

outdoor recreation during the last 12 months, and total number of visits over the

previous 4 weeks. The frequency question goes on categories (8 levels, from

„never‟ to „more than once per day‟) and so does not give an exact measure.

3.2 Specific off-site recreation surveys

3.2.1 Public Opinion of Forestry, Forestry Commission

The Forestry Commission has conducted biennial surveys of public attitudes to

forestry and forestry-related issues since 1995. Initially the survey was GB-wide,

but more recently (2001 onwards) there have been separate surveys for the UK,

Scotland, Wales, and sometimes Northern Ireland. In 2009 there were surveys for

UK (2000 adults), Scotland (1000) and Wales (1000). Some questions were asked in

all three of the surveys, but an increasing number of questions have become survey

specific, allowing questions of particular relevance to management in that country.

The surveys include “have you visited?” and “frequency?” questions, that can lead

to approximate estimates of visitor numbers. Questions also include general

attitudes towards the different services provided by forestry, and towards climate

change.

Results of the surveys are available online19. Results from 2009 (FC 2009) show that

77% of respondents had visited a woodland or forest in the last few years. Of

these, 61% had been to a woodland or forest at least once a month in the summer

of 2008 and 34% visited at least once a month in the winter of 2008/09.

18 http://www.snh.org.uk/publications/on-line/comm-reports/srs_10.asp

19 http://www.forestry.gov.uk/forestry/infd-5zyl9w


eftec July 2010 49

3.2.2 Inland Waterways Visitor Survey, British Waterways

The Inland Waterway Visits Survey (IWVS) was piloted in August 2003 and has run

continuously since January 2004. The survey is undertaken by MEW on behalf of

British Waterways. The survey is undertaken by telephone with a target of 480

interviews per fortnight, providing an annual sample of around 12,000. The sample

is randomly selected to be a representative sample of British households.

Respondents are asked to indicate on how many days during the preceding two

weeks they had participated in a range of specified activities “on inland waterways

used by boats”. Both leisure and activities such as walking to work are covered.

Respondents are asked to name the specific destinations of their visit(s) so that

analysis can be undertaken regarding the numbers of visits to sites managed by

British Waterways. The data are scaled up to provide an estimate of the total

number of visits to inland waterways per year.

3.2.3 Northwest Day Visit Survey

The survey collects detailed information on tourist day visits taken for leisure

purposes by residents of the North West area and within a 90 minute drive time

catchment of this area (a radius which includes Birmingham, Leeds and Newcastle).

To be defined as a tourist day visit, the visit must have been taken outside of the

respondent‟s „usual environment‟, which is self-defined.

Respondents are asked to specify where they live, where they work and where they

usually go (if anywhere) for grocery shopping, shopping for everyday clothes, to

attend the cinema, theatre or concerts, or to go out for a meal. These places are

defined as the respondent‟s usual environment, and visits taken outside of this

area may be defined as a tourist day visit. Visits which include unusual activities

carried out within the respondent‟s usual environment are also defined as a tourist

day visit. Unusual activities are defined as those done only once in the previous

three months.

The survey approach followed involves two stages, both undertaken using an on-

line survey methodology. The core survey records the data regarding the volume

of visits taking at a regional and sub-regional level. Respondents are asked

questions about the nature and location of activities they have undertaken during

the previous 4 weeks. Details of frequency of participation in 11 types of broad

activity are recorded.

The second, follow up, stage of the survey aims to collect greater detail on

spending during visits which involved a particular activity, as well as marketing-

related information. Contact is made with respondents, selected on the basis of

activities undertaken, within 4 days of their completion of the core survey.

Detailed information is collected using a day trip diary approach which covers the

activities undertaken from leaving home to arriving back in more detail, when and

where money was spent and what was purchased. Data from this stage are

weighted to be representative of the 11 main trip purposes recorded in the first


eftec July 2010 50

stage, and by the age, gender and ArkLeisure segments20 of people making the

trips.

3.2.4 Survey of Rod License Holders 2001, 2007

Data for this survey were collected during 2001 in a series of telephone interviews.

The survey was repeated in 2007, though in a slightly less detailed format. The

main information collected related to the number of days spent angling by rod

license holders during the previous year. Trip details included a variable relating

to the distance of a respondent's 'nearest' angling site, and the amount of time

spent at the site, however, data relating to angler expenditure was not collected.

In addition, general socio-economic variables and respondent address were

recorded.

3.2.5 Watersports and Leisure Participation Survey

This survey has been conducted annually since 2001 by Arkenford marketing for a

consortium of maritime organisations including the British Marine Federation (BMF),

Maritime and Coastguard Agency (MCA), Royal National Lifeboat Institution (RNLI),

Royal Yacht Association (RYA) and Sunsail. The main objective of the survey is to

estimate the levels of participation in 20 water based leisure activities both in the

UK and abroad. The annual sample is approximately 12,000. Data collected

include the level of participation in each of the 20 activities, information relating

to the club membership of individuals and where within the UK (in terms of region)

they have participated in water based recreation during the previous 12 months.

The survey does not collect data relating to recreational expenditure, nor the

postcode of respondents, although details relating to a respondent's 'home' region

are available.

3.2.6 The Economic and Environmental Impact of Sporting Shooting 2004

This study was conducted for a consortium of organisations including the British

Association for Shooting and Conservation (BSAC), Countryside Alliance (CA), and

Country Land and Business Association (CLA), in association with Game and Wildlife

Conservation Trust (GCT). The primary aims (PACEC, 2004) were to:

define the key components of shooting and their associated interests;

assess the economic contribution of the sector to the UK economy;

identify the conservation and habitat management activities arising from

live quarry shooting; and

evaluate the environmental benefits and costs associated with shooting

20 See http://www.arkenford.co.uk/arkenford_tourism_arkleisure.php : eight value-based consumer

segments that identify the motivations and purchase drivers that influence people‟s leisure choices in

tourism as well as in what activities they undertake.

http://www.arkenford.co.uk/arkenford_tourism_arkleisure.php


eftec July 2010 51

Different questionnaires were developed for individuals involved in providing sports

shooting and those taking part. Data were collected on where respondents

participated in shooting (at a regional level), their home region, frequency of

participation and shooting related expenditure.

3.2.7 The Economic Impact of Game and Coarse Fishing in Scotland 2006

Fishery owners were surveyed in order to construct a database from which angling

effort over 2,830 brown trout, rainbow trout and coarse fisheries, and salmon and

sea trout fisheries on a river-by-river basis could be aggregated. In addition, a

survey of anglers collected information relating to angling location, home, target

species, and expenditure was conducted. The study included questions to assess

how anglers would respond if and when a particular area or type of angling was not

available.

3.3 Off-site surveys with some outdoor recreation content

3.3.1 United Kingdom Tourism Survey

The United Kingdom Tourism Survey (UKTS) is a national consumer survey

measuring the volume and value of tourism trips taken by residents of the United

Kingdom. It is jointly sponsored by VisitBritain, VisitScotland, Visit Wales and the

Northern Ireland Tourist Board. The survey is the main measure of UK domestic

tourism volume, value and characteristics and has been running for 15 years.

The survey covers trips, involving at least one night away from home, made by UK

residents for any purpose (including for example holidays, visits to friends and

family, business) in the UK and Ireland over four weeks preceding the interview.

Only respondents who have taken any visits (about one in seven) are asked any of

the questions which follow.

Tourism volume (number of trips, number of nights) and value (expenditure) are

measured, for all overnight trips. Further details are collected on up to three

trips, including the main purpose, places visited, types of accommodation used,

part size and composition, and transport types used.

Originally conducted by telephone, since May 2005 the survey has switched to a

face-to-face format, due to concerns about the reliability of the telephone survey

data.21

Data from the UK Tourism Survey are used by various organisations, for example

the Forestry Commission, to help identify return to the local economy from tourist

expenditure associated with overnight trips involving an outdoor recreation

component.

21 http://www.enjoyengland.com/corporate/corporate-information/research-and-

insights/statistics/UKTS.aspx


eftec July 2010 52

3.3.2 General Household Survey

Data collection for this survey has taken place annually since 1971. The main

objective of the survey is not related to leisure but broader topics covering

household, family and individual information. However a section relating to leisure

was included in the 2002 survey. Information relating to the participation of

respondents in a number of activities was collected, including a mix of indoor and

outdoor recreation22 (e.g. swimming; diving indoors/outdoors; cycling;

indoor/outdoor bowls - ten-pin bowling; keep fit/aerobics; martial arts; weight

training and so on). Details were collected relating to the facilities used by

respondents, whether they had taken part in competition during the previous 12

months, and relating to other hobbies, and general socio-economic variables. The

primary sampling units relate to respondent postcode sectors and responses are

clustered by this factor.

If it were possible to include recreation questions in a future GHS, this could be

useful for segmentation/profiling purposes, and for determining the main

substitute activities for different categories of outdoor recreation users.

3.3.3 International Passenger Survey

This survey is used to gather information relating to international tourism with up

to 250,000 face-to-face interviews conducted annually. The sample population is

drawn from all individuals entering into the UK through ports, airports or the

Channel Tunnel. Data collected include main reasons for visiting the country as

well as details of fares and expenditure.

3.3.4 Active People Survey

The Active People Survey has been carried out by Ipsos MORI on behalf of Sport

England, annually since 2005. Its main objective is to measure levels of sport and

active recreation including walking and cycling for recreation and more formal

sports, at both a national and local level. The survey measures frequency, intensity

and duration of participation: the underlying theme is providing information on

how many people undertake levels of activity which are beneficial to their health.

Other information collected by the survey includes membership of clubs,

involvement in competitions and contribution to sport through volunteering.

3.3.5 Taking Part

Taking Part is a continuous national survey of adults (aged 16 and over) living in a

representative cross section of households in England. The annual sample size is

around 29,000 people, carried out by BMRB Social Research23. The main areas

22 See nesstar.esds.ac.uk for full list.

23 http://www.culture.gov.uk/reference_library/research_and_statistics/4828.aspx


eftec July 2010 53

covered by the survey are levels of participation in the arts, heritage and sports

across the adult population, as a whole and within certain priority groups.

Included in the questions regarding sports, respondents are asked about their

participation in a number of outdoor recreation activities (including swimming,

cycling, angling, canoeing, windsurfing, skiing, climbing, mountaineering, hill

trekking, rowing and recreational walking) and about reasons why they do or do not

participate.

3.3.6 Attitude surveys

These surveys generally do not cover recreation specifically, but cover a wide

range of information of tangential relevance to outdoor recreation and general

views of the natural environment. Such information could potentially be useful in

deriving value transfer functions, for correcting for attitudinal differences.

In England the Survey of Public Attitudes and Behaviours toward the Environment

has taken place in 1986, 1989, 1993, 1996-7, 2001 and 2007. The 2009 survey24 was

commissioned jointly by Defra and the Energy Saving Trust and consisted of 2,009

in-home interviews plus additional questions in an omnibus survey of 1,772. The

2009 survey gives a representative picture of what people in England think, and

how they behave, across a range of issues relevant to the environment including:

Knowledge of and attitudes towards the environment

Energy and water use in the home

Purchasing behaviours

Recycling, composting and reusing waste

Food and food waste

Travel behaviours and attitudes

Carbon offsetting

Biodiversity and green space

Volunteering behaviours

Wellbeing

In Scotland the Scottish Environmental Attitudes and Behaviours Survey (SEABS)

200825, commissioned by the Rural and Environment Analytical Services division of

Scottish Government and carried out by Ipsos MORI, plays a similar role.

24 www.defra.gov.uk/evidence/statistics/environment/pubatt/

25 http://www.scotland.gov.uk/Topics/Research/by-topic/environment/social-

research/SESEN/workprogramme/Themes


eftec July 2010 54

3.4 On-site recreation surveys

Liley et al (2009) note that there is “wide variation in the on-site monitoring

conducted on different types of sites across England”, both in terms of design of

monitoring and subsequent use of data, in part arising due to historic differences in

the form and objectives of organisations involved, and due to differences in the

nature of sites and designated areas. There have been attempts to introduce

consistent guidelines or standard protocols, notably Natural England‟s Visitor

Monitoring Toolkit for Open Access Land, but in general there is no coordinated

approach, and data from different surveys cannot easily be compared or combined

for analysis.

3.4.1 National On-Site Visitor Monitoring Survey

The implementation of Part 1 of the Countryside and Rights of Way Act 2000

(CROW) created, with effect from 2004/5, new public rights of open access over

mapped areas of registered common land and open country (mountain, moor,

heath and down) throughout England.

In total, there are now over a million hectares of open access land in England

where people are not confined to public rights of way. Of this one million hectares:

193,450 hectares are 'section 15 land', where the public already had a right

of access prior to CROW, often including 'higher rights' such as horse-riding.

Well over half of the area falls within Sites of Special Scientific Interest

(SSSIs).

Almost 150,000 hectares has been voluntarily dedicated by the Forestry

Commission and other landowners for permanent open access.

Natural England (and previously The Countryside Agency) set up a National Open

Access Monitoring Programme to help identify the level of take up, use and impacts

of these new rights. This includes a National On-Site Visitor Survey, originally

developed and piloted in 2005, then run from 2006. The results feed in to the

CROW monitoring reports, available on-line.26 The main objectives of the survey

are to gain a better understanding of:

who is visiting access land;

the use, and changes in levels and patterns of use, of access land;

visitor awareness of their new CROW rights and responsibilities;

visitor behaviour;

visitor satisfaction and experience;

26 http://www.naturalengland.org.uk/ourwork/enjoying/research/openaccess/default.aspx


eftec July 2010 55

the potential impacts on sites with nature conservation value;

the effectiveness of different forms of statutory restriction;

the effectiveness of the Access Management Grant Scheme (AMGS); and

(more recently added) questions also investigate links between health,

exercise, and the reasons for visiting access land, and questions on

understanding of the term “right to roam” in comparison with “open

access”.

In 2007 the survey covered 66 open access sites via three sampling approaches:

26 randomly selected national monitoring sites

6 monitoring sites selected for specific nature conservation or land

management reasons

34 local monitoring sites chosen by the local authority (against criteria

drawn up by Natural England) for their nature conservation and land

management qualities

sites within National Parks are not included.

This National Programme:

allows changes over time in use of the new rights, and in patterns and levels

of recreational activity, to be monitored;

allows strategies to be developed for tracking the use of the new rights over

the longer term;

encourages local monitoring, by demonstrating best practice;

provides early warning of any potential adverse impacts, so that suitable

access management measures can be put in place; and

helps inform future guidance.

3.4.2 Local On-Site Visitor Monitoring

To complement the National On-Site Visitor Survey, Natural England has developed

a Monitoring Toolkit for local partner organisations to use for monitoring visitors to

access land at local site level, in a way compatible with the National Survey.

Natural England is working closely with National Parks and local access authorities

to promote this monitoring toolkit. Eight access authorities used the toolkit in

2007. Natural England collates the results and combines them with data from the

National On-Site Visitor Monitoring Survey, boosting the sample size and further

improving understanding of public use of open access land.


eftec July 2010 56

Box 8: Monitoring the environmental impact of CROW

In addition to generating value for participants and local economies, recreation

can have negative environmental impacts. These may also be addressed via

monitoring. The Upland Breeding Bird Survey (UBBS) is an example: an extension

to the national volunteer-based Breeding Bird Survey (BBS) coordinated by the

British Trust for Ornithology (BTO) since 1994, the UBBS aims to monitor whether

the introduction of the CROW rights has any influence on upland breeding bird

populations. This also provides a good indicator of the general environmental

condition of the landscape and its constituent habitats. Initial results show that

most key upland species numbers have remained stable or increased, suggesting

that implementation of CROW access has not had a significant negative effect on

upland species, however monitoring needs to continue for many more years before

firm conclusions can be drawn. (Natural England 2008)

3.4.3 Forestry Commission: All Forest Visitor Surveys

Between 2004 and 2007 the Forestry Commission undertook All Forest Visitor

Surveys in Scotland and Wales, aiming to measure the volume of visits to their

estates and the profile of visitors. Data collected in the All Forest Surveys include

headcounts and interview data (of course the numbers interviewed are much less

than numbers counted) at all access points to a sample of forests. The forests

included in the survey were selected by the Forestry Commission as representative

of their whole estate in terms of their perceived levels of usage and proximity to

areas of population.

The surveys provided estimates of the total numbers of visits taken to the FC

estate, demographic information on forest users, details of where they live and

types of transport used to reach the forest, information on activities undertaken,

possible areas of improvement and levels of expenditure.

3.4.4 Forestry Commission surveys in England

The same approach has not been attempted in England: there has been no attempt

to survey numbers across the whole estate, and no plans to do this. There are

instead quality of experience surveys at key sites. Quantitative information is

collected using car park and footfall monitors at some sites across the UK, and

work is ongoing into improving the accuracy of these methods. England has been

running surveys at 3 to 4 selected sites a year since 2003 to assess the quality of

visitor experience, and there have been many locally-initiated surveys each year.

Current plans for England involve more of the same: there is interest in better

estimates of total visit numbers, but not yet a method for doing this. One issue

identified with use of MENE data for estimating forest recreation trips is that

children represent 1/4-1/3 of forest visitors, but are not covered in MENE. There

are no plans for All Forest Surveys in England, nor for repeats in Scotland/Wales.


eftec July 2010 57

3.4.5 British Waterways monitoring

British Waterways runs a network of about 200 automated pedestrian counters on

popular sites and routes throughout Britain, plus other automated counters run

jointly with Sustrans. Data from these counters supplement the Inland Waterways

Visits Survey (see section 3.2.2). In addition, British Waterways conducts a

programme of annual visitor surveys on over 36 sites, in summer and autumn, each

with a wave of 100 interviews. The questionnaires include segmentation/profiling

questions, opinion on facilities, and enjoyment of the site.

3.4.6 National Parks Visitor Surveys

The National Parks Visitor Survey 1994 was commissioned by the Countryside

Commission and Countryside Council for Wales and undertaken by the Centre for

Leisure Research. The survey involved fieldwork at 12 National Parks across

England and Wales and aimed to collect information on the characteristics of

visitors, reasons for visiting, frequency of visiting, activities undertaken, attitudes

and spending patterns. The survey also aimed to provide estimates of numbers of

visitor days spent in each park.

Various National Parks have also run their own surveys. The Peak District National

Park (NP) visitor survey was designed to collect data to provide information

relating to effective visitor management of the Peak District NP, with past surveys

taking place in 1986/87, 1994 and 1998. Data were collected from one of two

visitor surveys administered on site at one of 24 different locations within the park.

Information on visitor and trip profiles was collected on site, i.e., socio-economic

variables, trip start/end times, the postcode of where the visitor had travelled

from etc. A follow-up questionnaire was then given to respondents to be posted

back which included more detailed questions relating to the respondent's trip.

Yorkshire Dales NP Authority (NPA), Northumberland NPA, Dartmoor NPA and the

North York Moors NPA are all cited in Natural England‟s CROW monitoring report

(Natural England 2007) as carrying out monitoring of open access land, in some

cases using volunteers.

3.4.7 National Trail and Strategic Recreational Route monitoring

In England there are thirteen National Trails, long distance routes for walking and,

in some parts, cycling and horse riding. National Trail monitoring uses a variety of

methods including on-site face to face surveys, automated counters, and on-line

surveys.

Strategic Recreational Routes are off-road routes used for walking, cycling or horse

riding that pass through attractive natural or built heritage, can provide for a

journey of more than one day and attract both local and tourist use (Liley et al

2009). A 2008 omnibus survey assessed the current use and potential demand for

Strategic Recreational Routes in England.


eftec July 2010 58

3.4.8 Other on-site monitoring

Liley et al (2009) note several other categories of site for which there may

sometimes be visitor monitoring, but where this is piecemeal and not coordinated

or collected at national level. Such sites include:

Country parks: there are about 267 country parks in England, mostly near

built-up areas. Visitor surveys are carried out by some sites, but there is no

strategic approach to monitoring use or visitor levels.

National Nature Reserves (NNRs): there are 222 NNRs in England. On some

sites there is visitor monitoring for specific local needs, but there is no

national co-ordination of visitor data on NNRs. Similar remarks apply to

Areas of Oustanding Natural Beauty.

Sites of Special Scientific Interest (SSSIs): there are over 4,000 SSSIs within

England, covering over 1 million hectares There has been limited visitor

monitoring on individual SSSIs. Some surveys have been commissioned where

there are concerns relating to visitor levels and biodiversity impacts. In

both the Brecks and Dorset, visitor survey data have been used to develop

predictive models to explore how visitor rates may change in the future

with new housing (Dolman et al., 2008, Liley et al., 2006b).


eftec July 2010 59

4. VALUATION METHODS

Economic valuation methods are discussed widely in the environmental economics

literature and we do not attempt to give a comprehensive review here. Good,

recent references include:

eftec (2006) for a review of economic (monetary) and non-economic

(deliberative, qualitative) approaches to taking environmental impacts into

account

Defra (2007) for a general overview and case studies of valuation in an

ecosystem service framework, targeted at government use

Hanley and Barbier (2009) for an up-to-date review and case studies of the

tools available for valuation and cost-benefit analysis in environmental

policy

eftec (2010) for guidelines on value transfer, adapting existing valuation

data to new applications

The discussion below covers the different methods available, specifically within the

context of valuing outdoor recreation.

4.1 General

Outdoor recreation is often free at the point of delivery, but is nevertheless of

great value to those who engage in it. Economic valuation of recreation seeks to

derive a demand curve for recreation activity, aiming to estimate the economic

value of changes in quantity and/or quality. „Economic‟ in this context does not

mean „financial‟ but rather signals that impacts on human welfare are being

measured and expressed in monetary terms.

The objects of valuation can be changes in quality of resources, or changes in

quantity (new/lost sites), or the total value of recreation in a given geographical

area for a particular type of resource or activity. The application can be to

different levels of change, from marginal to total. The level of change is partly a

function of scale – the loss of a single recreation site might be considered “total” in

a very local context but “marginal” when assessing national recreation

opportunities and values – and there are issues here associated with scaling up and

aggregation of values. There are also different time profiles for valuation –

sometimes we are interested in potential future changes, as when assessing

scenarios or appraising possible policy interventions, and sometimes in evaluation

of the impacts of past interventions or environmental incidents (for example, the

impact on coastal recreation values of an oil spill). In each case the methods and

data requirements may be slightly different.

There are many different techniques for estimating economic values of

environmental goods and services; recreation values are commonly addressed using

the travel cost method or stated preference methods. Travel cost is one of the


eftec July 2010 60

revealed preference techniques, based on detailed analysis of actual behaviour

that has both environmental and market elements. Stated preference methods

involve interviews eliciting behavioural or payment intentions under structured

hypothetical situations.

The main potential use for recreation survey data such as that to be derived under

MENE is for travel cost modelling. A further possible use is for value transfer

techniques. These involve taking one or more existing valuation studies and

transferring the value estimates to a new site; this requires careful adjustments to

take into account differences between the original study site(s) and the policy

application site. Recreational survey data may be of use in understanding the

patterns of use of the study site and/or the policy application site.

4.2 Measures of expenditure and economic impact

Many assessments of the “economic value” of tourism focus on contributions to

local or national economies, and disregard the additional value (surplus) to the

participants in recreation. Estimating this surplus is the key topic of interest in

this report. The other measures are also important, of course, but serve different

purposes, in particular in assessing impacts on particular communities or in

securing funding from organisations with a focus on economic development.

Therefore we do not focus on these measures in this report. However it is worth

noting that there are problems inherent in a focus on financial impact, and

especially local financial impact, rather than a full measure of economic value.

These go beyond merely overlooking the value to the individuals engaging in

recreation, to policy assessments that can seem counterproductive from a broader

perspective. For example ECOTEC (2003) focused on such measures, in a study of

“access enhancement and promotion” for part of the Yorkshire Dales, and

concluded (amongst many other things) that it should be a priority to increase

length of visitors‟ stays whilst avoiding adding significantly to day visitor numbers.

Favouring overnight visitors over day visitors may well be a good way of increasing

total expenditure, but is not necessarily a good way of increasing benefits.

Box 9: Adjustments to expenditure measures

When estimating expenditure measures, there are several additional factors that

are often taken into account. These depend on defining some boundary for the

impact, often on a regional level (which may not reflect national interests).

Multiplier effects: direct expenditure within an area will lead to additional

indirect and induced spending, leading to further economic and employment

benefits. These are typically accounted for using multipliers on the basic spend.

Displacement: where some benefit arises at the expense of a reduction in

spending/employment elsewhere in the target area.

Leakage: where part of the benefits accrue outside the target area, this may be

netted out of the calculations.


eftec July 2010 61

4.3 Methods for valuing recreation

There are many different approaches to estimating the value of outdoor

recreation. The main options are discussed below, and summarised in Table 2 at

the end of the Section.

4.3.1 Stated preference

Stated preference methods have the advantage of being applicable, in principle, to

any change in goods or services that can be represented in a hypothetical question

or choice. There have been many applications to recreation (see Table 5 in the

annex).

The contingent valuation (CV) method is a survey based approach to valuing non-

market goods and services. The approach entails the construction of a

hypothetical, or „simulated‟, market via a questionnaire methodology where

respondents answer questions concerning what they are willing to pay (or willing to

accept) for a specified environmental change. This is most closely analogous to a

single-site travel cost application, in that valuation is for a particular location and

specific change: CV has limited capacity to deal with site-substitution issues. CV

studies are also likely to pick up non-use values (for conservation or protection of a

particular site) whereas revealed preferences only relate to use of the site.

Choice modelling refers to a set of stated preference techniques which ask

respondents to choose between alternative scenarios that are presented in terms

of the characteristics (or „attributes‟) of the good or service of interest. For

example, the attributes of a recreation site may be presented as its accessibility,

facilities available, ecological quality, and so on. Different scenarios will also

include an associated cost attribute which can be represented in a number of ways,

commonly via an entrance fee. Choice modelling is closely related to random

utility methods (see section 4.3.4) and can be applied across sets of sites (for

example to examine people‟s preferences for a change in quality along 3 stretches

of river compared with 2 stretches of river).

However, there is a problem that people‟s preferences depend on where the

recreation sites are in relation to their place of residence, as well as on what the

changes in quality are, and this information is essential if people are to value

changes in quality or access (or if researchers are to understand the values they

give). How far is the site, where are the alternatives, and what are the relative

qualities, are all key factors in determining recreation value to an individual.

It is possible to take these factors into account, however, as demonstrated by

Bateman and others in the Aquamoney project (Bateman et al 2009). The strategy

was to specify precisely the location and nature of water quality change for a

specific stretch of river, while also showing other rivers in the same region, and use

a geographically dispersed sampling strategy to cover a range of people near to and

further from the changing sites. Distance from the respondent‟s to the improved

site and to unimproved alternatives were both significant variables in the

estimated model.


eftec July 2010 62

More generally, Jones et al (2002) note that stated preference methods are

relatively poor at generating data for predicting visit numbers, because survey

respondents “find it difficult to quantify essentially subjective and even

subconscious factors which impinge upon their decision to visit a given site.” They

give the example of substitute availability, which may be significant in determining

a visit, but which is very difficult to express in a way that is both suitable for use in

visit number models and easy for respondents to take into account.

Bateman (pers. comm.) notes that this is somewhat reflected in the observation

that stated preferences appear more sensitive to changes in water quality than

revealed preferences. In other words, when asked about a given change in water

quality respondents may provide a willingness to pay even though there is no

evidence that this change has any influence upon observed behaviour. Arguably

this may reflect non-use values for such changes. However, the alternative

interpretation is that survey respondents are overly sensitive to such information

and/or presume that it will have a greater impact upon quality than overtly stated.

Christie et al (2010), on the other hand, argue that studies comparing the merits of

different approaches to valuing recreation “have predominantly concluded that the

CV method is the most appropriate technique to use for the evaluation of

countryside recreation due to its flexibility and its capacity to assess passive-use

values as well as use values (Young & Allen, 1985; McConnell, 1985; Loomis et al.,

1986; Forester, 1989).”

But it is not necessarily relevant that passive-use / non-use values have to be

estimated via stated preference: within an ecosystem services framework, we do

not expect a single estimate to cover all sources of value. In fact, it may be more

useful to separate out recreation use values from existence and bequest values.

Admittedly, there is then a potential problem of double counting when the non-use

values are separately estimated via stated preference, because it is difficult to

know what portion of value from the stated preference survey might in fact be use

value for recreation – though careful survey design can minimise this risk. In any

event, there is substantial merit and interest in deriving estimates that are

grounded in actual rather than hypothetical behaviour, where this is feasible.

4.3.2 Zonal Travel Cost

The travel cost method (TCM) uses the costs incurred by individuals travelling to

reach a site, in addition to costs incurred at the site, as a proxy for the price of the

recreational activity, and combines this information with information about visit

rates for different people or areas to derive an estimate of the value of recreation

at the site.

Originally the method was applied to visit frequencies from different „zones‟

around a site. The approach is to divide the entire area from which visitors to a

site originate into a number of visitor zones. The dependent variable for analysis is

the visit rate, the number of visits made from a particular zone in a period divided

by the population of the zone, often expressed as visitors per 1,000 population.


eftec July 2010 63

Visitor zones may be defined according to pre-determined distances from the site,

and early models used concentric circular zones, but later approaches made use of

more complex calculations, including GIS, to work out zones based on travel

time/cost rather than simple distance, and/or to define zones based on geo-

political units, allowing more accurate data via official census figures and

statistics.

The zonal model applies to the average behaviour of groups of people, and

therefore does not accord with theories based on individual welfare measures.

This means the zonal approach is now rarely used for value estimation, although

Martin-Lopez et al (2009) is a recent exception, looking at the impacts of applying

the model at different spatial scales. Most single-site travel cost valuation models

are now carried out using individual base models, discussed below.

However, when seeking to derive transferable functions, individual based models

are less useful, because by definition we do not have sufficient individual user data

to do primary analysis for unsurveyed sites. Jones et al (2002) stress that this

renders individual-based models incapable of estimating transferable arrivals

functions. The zonal method, on the other hand, relies on area statistics and allows

for estimation of arrivals functions based on information available at both surveyed

and unsurveyed sites. Hence zonal methods can be useful in cases where there are

data available (such as on-site surveys of a given set of sites, e.g. the Forestry

Commission survey database) that record only visits to the survey site and the

outset location. In such cases this data can usefully be used to estimate visitation

patterns to that type of site: this is essentially the approach of the Trip Generating

Functions discussed below. The lack of information on visits to alternative sites,

on the set of sites considered beforehand, and on total visits per year, means that

this approach is not suitable for estimating economic values.

4.3.3 Individual Travel Cost

Travel costs incurred by an individual include (i) travel expenditures and (ii) the

value of their time. Travel costs partly determine the number of visits an

individual may undertake and may be seen as the 'price' of a recreational visit to a

particular site. Surveying visitors to a site and asking them for information

concerning their travel costs, frequency of visits over a given period and other

determining factors allows estimation of a „trip-generating function‟ which explains

the number of visits as a function of travel costs and other relevant explanatory

variables. This can then be used to estimate a demand curve for recreation at the

site, allowing estimation of the total value of recreation at the site.

A survey is required to collect data on visitors‟ place of residence, demographic

and attitudinal information, frequency of visit to the site and other similar sites,

and trip information (e.g. purpose of the trip, length, associated costs etc).


eftec July 2010 64

Step 1 Administer

questionnaire to site

visitors

Data to be collected include:

Place of residence

Demographics

Attitudinal information

Frequency and length of visit to site and

substitute sites

Trip information (i.e. purpose, length,

costs, etc)

Step 2 Determine demand

function

Use econometric techniques to determine

demand relationship based on relevant factors

(e.g. distance to site, alternative sites, etc).

Step 3 Estimate total

recreation value

Integrate the demand function to estimate the

total recreation value of the site in terms of

consumer surplus. Considered in the context of

'price' paid (e.g. travel costs); this yields a WTP

estimate of a site‟s recreational value.

Step 4

(optional)

Estimate demand

equation of site

attributes

More advanced studies attempt to estimate

demand equations for differing attributes of

recreation sites and estimate values for these

individual attributes (see Random Utility

Models below)

Figure 2: Implementing the individual travel cost method

The TCM is a potentially useful tool for producing estimates of the use value

associated with well-defined recreation sites. A distinct advantage is that

estimated values are revealed from actual behaviour of individuals and the

formulation of demand curves. Analysis of demand curves can also yield significant

input to analysis of visitor rates and changes in these, which can aid the

management of these sites.

Practical applications of the approach, however, may be limited by data

availability. More methodological concerns may disadvantage the use of TCM

results, particularly with regards to different estimates of consumer surplus that

may arise as a result of adopting the Individual TCM or Zonal TCM approach, as well

as the treatment of substitute sites, the choice of appropriate functional form and

the calculation of the value of time. Finally, the TCM is not able to account for

non-market goods (or bads) that are imperceptible to short-term visitors. These

issues are further discussed in section 4.4.

4.3.4 Random Utility site choice models

Random Utility site choice models (RUM) (sometimes referred to as multi-site

recreation demand (MRD) models or discrete choice models) were introduced to


eftec July 2010 65

recreation studies by Bockstael et al (1987). The approach infers the value of

changes in the quality of recreation services by focusing on the decisions of

individuals to visit a specific site rather than alternative substitute sites. RUM have

become the predominant approach of the Travel Cost Method (TCM) (Greene et al.,

1997; Phaneuf and Smith, 2005). This model provides a convenient way to explain

the choice among mutually exclusive alternatives incorporating relevant

substitution and site quality effects, allowing more accurate representation of

recreation choice sets than previous TCM approaches

The key consideration here is that, when individuals use multiple sites, the value of

a change in quality of one site (or the value of the loss / gain of a site in the choice

set) will depend on the site‟s quality and proximity to where they live, but also on

the quality and proximity of the other sites: there is interaction between sites. In

effect people value a set of sites, all of which have different qualities and

characteristics.

The choice among available sites is modelled as depending on the comparison of

the characteristics of each site, via an individual‟s „indirect utility function‟, which

relates factors such as income, socio-economic characteristics, travel costs and site

quality characteristics to the utility (well-being or pleasure) derived from a

recreation visit. By specifying the functional form for the indirect utility function,

the RUM model considers the probability of an individual choosing to visit a given

site. This probability is determined by the arguments of the indirect utility

function, and parameters are estimated via maximum likelihood methods. The

monetary value of a change in site quality may then be estimated by relating the

coefficient for site quality to the implicit price of a visit, which, as in the TCM, is

inferred from the cost of travel to a site.

Application of a RUM requires a travel cost survey to collect data on visitors from a

selection of recreation sites, including data on the visitors‟ place of residence,

demographic and attitudinal information, frequency of visits to the site and other

similar sites and trip information (e.g. purposefulness, length, associated costs

etc). Survey data are also required on the specific characteristics of different

recreation sites and the level of the quality of these characteristics.


eftec July 2010 66

Step 1 Administer questionnaire

to site visitors

Data to be collected include:

Place of residence

Demographics

Attitudinal information

Frequency and length of visit to site and

substitute sites

Trip information (i.e. purpose, length, costs,

etc)

It‟s very important for RUM to also collect data

about the characteristics of each site to be

compared within a choice set.

Step 2 Determine RUM form The probability that an individual will visit a

given site is estimated on the basis of the costs

of visiting the site and characteristics of the site

relative to the characteristics of all of the sites

the individual may choose between. The

functional form of the utility function must be

specified by the researcher.

Step 3 Value changes in non-

market good/service

Relate the relevant function coefficient to the

coefficient of travel cost to yield an estimate of

willingness to pay for a marginal change in the

level of the non-market site characteristic.

Figure 3: Implementing a RUM based on travel cost

RUM is closely related to TCM. The key difference between the two approaches

arises from the way in which the decision to visit a recreation site is modelled

(Freeman, 1993).

In the TCM approach, individuals (or households) are modelled as choosing

whether or not to make a visit or several visits to a given site over a certain

period of time.

In the RUM approach, individuals (or households) choose, in a given time

period, whether or not to visit any site, and, if so, which site.

Hence, the TCM is suited to explain total visits to specific recreation sites over a

period of time (i.e. demand for recreation over a season or year), but within the

standard TCM it is difficult to capture the role of site specific characteristics or

qualities in influencing the choice of where to visit. In contrast, RUMs specifically

focus on the choice of which site to visit. In particular, the decision as to which

site to visit is determined by price (travel cost) and characteristics of different

sites. However, within the basic RUM framework, it is harder to explain total visits

to recreation sites.

Although RUM site choice models do not directly predict total recreational trips

taken in a season, there are various possible extensions and ways of linking site-


eftec July 2010 67

choice and participation in a single model (Johnstone and Markandya 2006)

including:

a repeated nested logit model, where the participation decision is the first

level, and site choice a second level;

using the inclusive value index from the site choice model as an explanatory

variable in a trip prediction model; and

variations on the above that split the inclusive value term into separate

price and quality terms.

One of the main advantages of RUM is the ability to estimate the recreational use

value associated with the changing environmental quality of a site, while taking

into account the location and quality of substitute sites. The two approaches are

complementary methods for estimating the value of non-market goods and services

from travel cost surveys, and the decision as to which one to apply will depend on

the required output. RUMs face some of the same disadvantages as the TCM, in

particular associated with the cost and difficulty of collecting sufficient data. As

with the TCM studies, the definition and calculation of travel cost and the cost of

time is important.


eftec July 2010 68

Box 10: A note on understanding of the travel cost method

The consultation (see section 2.3) showed that there is a need to communicate

better exactly what is implied by the travel cost method. For example there was

concern expressed over “use of a tool which places more value on people driving a

long way”, in light of the carbon cost implications. The idea that travel cost

places more value on trips that come from a long way is of course fallacious. The

fact that people are willing to travel further is indicative of higher values, but

those may accrue mostly to those travelling short distances who can access the

site more cheaply. The difference lies in the division of overall value between

measurable variables (e.g. personal time, driving distance) than can be equated to

some monetary value (e.g. cost of time, fuel prices), and intangible factors

(captured as consumer surplus). The travel cost method assumes (loosely speaking)

that the marginal consumer surplus is zero for the most distant visitors: the

highest consumer surplus measures accrue to those travelling short distances, as a

lower part of their overall value is taken up by tangible costs.

The concern over carbon costs is justified, and should be dealt with. To the

extent that people do not face the full costs of their driving, the real travel costs

(to society) will be underestimated, and this will result in higher surplus measures,

and also in higher visit levels (since there is in effect a carbon „subsidy‟ to

driving), than would be socially optimal. This could be adjusted for by calculating

the external carbon cost of travel emissions and adding that separately in the

assessment. However, in the UK petrol and diesel are quite heavily taxed and it is

not obvious that the actual cost of driving is below the full social cost. It is

possible that tax on road fuel could result in the opposite bias, resulting in lower

levels of outdoor recreation than would be socially optimal, and lower total

surplus measures. But in any event, these issues apply to the total values

estimated for particular sites, and not to the demand curve itself. Since the

travel cost method relies on establishing a relationship between travel cost and

use levels, and it does not really matter what the source of the cost is (fuel,

entrance fee, travel time), the relationship between demand level and cost can be

established.

4.3.5 Combined stated and revealed preference

One weakness of revealed preference methods is the limitation of assessment to

actual situations: analysing possible future changes in provision, access, or site

quality is not possible directly for a single site. It may be possible, drawing on a

wider RUM analysis, but ideally the range of options actually available would need

to cover the new features of interest (but see discussion of Whitehead et al, 2010,

below). One way round this is to use combined SP and RP methods, keeping

responses “anchored” in actual behaviour, while extending the scope to cover

possible changes to provision or quality. This also has the advantage of increasing

the information gained per survey respondent. The main methods of combining SP

and RP data are (pooled) Random Utility Models and Contingent Behaviour models.


eftec July 2010 69

If the focus is on different characteristics of recreation sites, their values and their

impacts on site choice, then a pooled Random Utility Model can be estimated,

combining revealed preference data from actual site choices with stated

preference data relating to options not currently in the choice set.

Contingent behaviour models look at stated intentions regarding behaviour changes

as either price changes (e.g. Englin and Cameron 1996) or environmental quality

changes (e.g. Hanley et al 2003). This allows combination in pooled or panel data

models of observed {travel cost, quality, frequency} data sets with hypothetical

ones.

With pooled data from RP and SP methods, a key issue is “whether the two types of

discrete choices can be pooled together under a single preference structure”

(Huang et al. 1997). Use of a single preference structure to describe revealed and

stated preference behaviour can cause biased coefficient estimates. Morgan and

Huth (2010) use a single-site travel cost model to estimate use-value estimates for

recreational cave diving, and extend this with stated preference data relating to

scope effects (an additional cave system) and improved access. Estimating

separate models, they find that divers use different travel cost preferences when

assessing their revealed and stated preference trip counts, but a single preference

structure to evaluate site quality changes.

There is some evidence (Grijalva et al, 2002) that stated recreation behaviour

intentions under changed quality conditions can be less subject to bias associated

with hypothetical markets than other stated preference methods, presumably

because of strong familiarity with the activity and characteristics contributing to

its utility. However this may not hold for quality characteristics that can be

described clearly but are difficult to perceive in practice: for example changes in

water quality at the high quality (“good” to “excellent”) end of the scale.

There is also potential to use discursive methods to explore definitions of “sites”,

“facilities”, “improvement” and so on, helping to define the variables for inclusion

in stated preference, revealed preference, or value transfer analysis. Recently, for

example, Christie et al (2010) used focus groups involving word-association games

and semi-structured discussions to explore outdoor activities, problems

encountered and possible solutions. This led to a two-tiered categorisation of

recreation improvements:

Basic types of improvement: path improvements, path creation and the

provision of facilities were identified; and a “basic” and “intensive” level

was defined for each type of improvement;

Locations for improvement: six general locations: 'mountain and moorland',

'woodland and forest', 'coastal areas', 'fields and farmland', 'areas next to

rivers and lochs', and 'areas near towns and villages'.

Jeon and Herriges (2010) present evidence from the Iowa Lakes Survey where (a) a

wide range of environmental conditions exists and (b) the 2004 survey provides

information on anticipated trip patterns under both baseline and hypothetical


eftec July 2010 70

water quality conditions. They find different results from hypothetical and actual

water quality changes, and conclude that relying on the response to hypothetical

changes to environment conditions to infer actual responses is therefore a

potentially misleading approach. Whitehead et al (2010) make an application to

beach recreation and find that models converge in predictions of behaviour but not

in willingness to pay estimates.

Whitehead et al, considering also Jeon and Herriges, conclude inter alia that

respondents do not appear to overstate trip-taking behaviour in stated preference

surveys, for quality change applications, provided the stated preference scenarios

include a status quo question. In addition, although joint estimation of RP and SP

data is “often touted as a solution to hypothetical bias”, they find that the

independently estimated SP model performs just as accurately as the jointly

estimated model. Furthermore, forecasts based on RP data outside the range of

site characteristics covered by those data align with SP results, suggesting that RP

estimates may not be strictly limited to the range covered by the data, though they

add that this may not hold for samples with more limited variation in the site

characteristics than theirs.

4.3.6 Value transfer methods

Value transfer (or benefits transfer) is a process whereby information regarding

economic value in one context is applied to a new context for which an economic

value is required: in the present context, the value of recreation at a particular

site may be estimated based on recreation values estimated in primary studies at

one or more other sites.

A distinct appeal of the value transfer approach to economic valuation is its

expediency and value for money properties in relation to commissioning original

valuation studies. The process of reviewing appropriate studies and undertaking

appropriate analysis can be achieved very quickly (a couple of days), though if

there is need to collate supporting data (such as number of visitors) for the policy

good context the timescale will be longer.

In the terminology of value transfer, monetary estimates of the value of a (non-

market) good or service are transferred from a „study‟ good or site to a „policy‟

good or site. The study good refers to the asset that is the subject of an existing

valuation study, whilst the policy good is that asset for which a valuation is

required. The simplest form of value transfer is to „borrow‟ the estimated average

WTP or WTA for some study good and apply it to the policy good context. This

approach implies that the preferences of the average individual for the study good

are an adequate description of the preferences of the average individual in the

policy site context. Essentially this amounts to the assumption that WTP for the

policy good is equal to WTP for the study good. This approach may be termed as

„average (or mean) value transfer‟ or „unadjusted unit value transfer‟. However,

the simplicity of this approach is subject to a number of caveats. Specifically,

there are a number of reasons why it would be expected that WTP will differ


eftec July 2010 71

between two sites, implying that the transferred value is an inaccurate measure of

WTP for the policy good. These include differences in the (Bateman et al., 2000):

Socio-economic characteristics of the relevant study site and policy site

populations;

Physical characteristics of the policy and study goods;

Valuation context, i.e. proposed changes in the quality and/or quantity of

policy and study goods that are valued; and

Availability of substitutes at each site.

Hence in general the policy good and the study good are unlikely to be identical.

An alternative approach, therefore, is to adjust the study good WTP estimate in

some way to account for the difference between it and the policy good. A common

adjustment involves modifying the policy good WTP amount to account for

differences in income (which is typically a fundamental determinant of WTP)

between the study good context and the policy good context. Alternatively, where

there is the requirement to make multiple adjustments to WTP amounts the

„function transfer‟ approach may be applied. Rather than transferring unit

estimates of WTP, the function transfer approach instead transfers information

from the study good context to the policy good context regarding the relationship

between WTP and a number of explanatory factors. Specifically, a WTP function

(or „bid‟ function) relates WTP for a change in a non-market good to changes in

parameters of interest including the factors relating to:

the good (e.g. price and characteristics of the good);

the affected population (e.g. socio-economic and demographic

characteristics and pattern of use of the good); and

the change (e.g. the quantity and quality of the good available with or

without the change of concern).

With a function transfer approach, WTP for the policy good is predicted on the

basis of the policy site value of these variables.


eftec July 2010 72

Step

1

Literature review Select studies to investigate

Compare population and location

characteristics

Compare site/good characteristics

Compare change in the good being valued

Step

2

Review study

methodologies

Ensure the studies contain WTP functions

Ensure the studies contain information on

property rights

Step

3

Adjust values Ensure values are adjusted

Explain how values are adjusted

Aggregate results

Produce final report

Figure 4: Basic Value transfer steps

Figure 4 shows the basic steps involved in value transfer – a fuller listing of eight

separate steps, ranging from defining the decision context to sensitivity analysis

and reporting, is provided in eftec (2010). Taking the policy good and decision

context as pre-determined, the initial step of a value transfer will be to conduct a

literature review. Here a search is made for relevant economic valuation studies

which consider scenarios similar to the policy good valuation context. From the

initial search, an appropriate study (or studies) is selected, which provides the

study good and the WTP results or function to be transferred to the policy good

context. An important consideration to be kept in mind when assessing the merits

of different study site studies is the expectation that, as noted above, WTP for a

particular good will differ between different locations. Therefore, in order to

minimize concerns relating to the „accuracy‟ of transferred values, it is important

to select the most appropriate WTP information from the most appropriate study.

Hence, what is needed is a set of criteria for assessing the appropriateness of WTP

surveys for transfer purposes. Such criteria include (Bateman et al., 2002a):

Site/good characteristics should be the same, or differences should be

accounted for;

The change in the provision of the good being valued at the two sites should

be similar;

Study and policy sites must be similar in terms of population and population

characteristics or differences in population must be accounted for;

Studies should contain WTP functions showing how WTP varies with

explanatory variables;

Studies included in the analysis must themselves be sound; and


eftec July 2010 73

Property rights should be the same across the sites.

In theory, adhering to these conditions would enable a suitable „match‟ to be made

between the policy site good to be valued and its associated appraisal context and

an existing valuation study from which to source WTP information. While not

explicitly mentioned in the above criteria (but implicit within them), geographical

or spatial location is a particularly important consideration in assessing the

appropriateness of a study for transfer purposes.

Depending on the similarity of the study good context and policy good context, it

may be appropriate to use the average value transfer approach. More likely,

however, differences in the policy and study site will require that some form of

adjustment is made. In order to adjust WTP values or apply the function transfer

approach it is necessary that supplementary data are collected for the policy site,

in particular, information on the affected population and their socio-economic and

demographic characteristics and also their pattern of use of the good in question.

In practice it is difficult to compare valuations derived by different TCM studies,

particularly due to potential differences in the specification of the trip generating

function and demand function. Use of different functional forms or underlying

methods will likely give rise to different estimates of value. Moreover, it is not

possible to compare summary statistics from the two different variants (see

below).

In a value transfer context, the transferability of estimates will depend on an

assessment of the similarity of the study good and the policy good. In particular, it

is necessary to assume that the preferences of individuals are identical in the two

contexts and that underlying travel costs are unchanged by the context. However

in some instances it may be possible to adjust for differences between the study

and policy sites.

Bateman et al (2009) stress the importance of including only variables that are

theoretically justified in the value transfer function. It can be possible to get a

better statistical fit by including all sorts of other variables, with site-specific

relevance for example, but the coefficients on such variables are unlikely to be

constant across sites, and the result is that even though the function fits the

original data more closely, it is mis-specified and results in greater errors when

transferring values to a new site.

As noted above, the principal advantages of value transfer are its expediency and

cost-effectiveness, enabling decision-making to be informed in a relatively short

period of time on the likely range of monetary value that may be attributed to non-

market environmental goods and services. Adjusted unit transfer and function

transfer approaches to value transfer also enable the analysis to modify WTP

according to likely determinants of WTP, giving the transferred values a certain

amount of sensitivity to key differences in the study good and policy good contexts.

The main disadvantages of value transfer focus on questions of accuracy in the

values derived in relation to original valuation studies. However, concerns


eftec July 2010 74

regarding accuracy are a necessary trade-off if otherwise, decision-making will not

be informed as to the likely monetary value of environmental goods and services.

The other principal disadvantage of value transfer is that the approach cannot be

used if there are no existing studies that have investigated the value of the

environmental good or service in question, which provide suitable WTP information

to transfer to the policy good scenario.

Once WTP amounts have been transferred to the policy site, or predicted via the

function transfer approach, the final stage of the process is the aggregation of WTP

over the appropriate population for the policy good context. Bateman et al

(2006b) stress the importance of the distinction between political jurisdiction (the

population of a particular geo-political region) and economic jurisdiction (the

group of people who share a particular value). In particular, two possible sources

of error/bias need to be taken into account:

Distance decay: values will fall with increasing distance from the site, but

this may be missed or under-represented by methods that do not sample

randomly across the whole economic jurisdiction; and

Self-selection bias: if the probability of responding to a valuation survey is

positively related to underlying values.

These problems take slightly different forms for stated and revealed preference

surveys, but both arise in both methods. Bateman et al (2009) use GIS to assess the

impact of the location of both improvement and substitute sites upon values in a

value transfer function based on repeated application of a stated preference

survey. The results show decay in values as the distance between improvement

site and the survey respondent‟s home increases, while values rise as the distance

to substitute sites increases. These are the expected results in theory, but

Bateman et al (2009) is the first time that these important effects have been

included within benefit transfer analyses.

4.3.7 Trip Generating Functions

It is possible to use methods similar to zonal travel cost to derive trip generating

functions that can be used for predicting visit rates and associated values for

unsurveyed sites. This is particularly relevant in view of the consultation finding

that, for many organisations, information on predicting and understanding visitor

numbers is a high priority.

As noted above, Bateman et al (2002) flag the anomaly that the primary focus of

environmental economics research in recreation has been the estimation of

transferable unit estimates of value and not visitor numbers. Jones et al (2002)

demonstrate for UK forests that the value of a day‟s recreation varies far less

across woodlands than do estimates of the numbers of visitors to different

woodlands. They suggest that the focus on transferring values rather than visitor

numbers “reflects both the allure of the former task and the spatial complexity of

the latter”, and go on to demonstrate how GIS tools can help to address these

complexities. Hill and Courtney (2006) suggest that another reason for the bias in


eftec July 2010 75

research effort is likely to be the limited availability of reliable visit count data at

a representative range of sites across the country.

Hill and Courtney (2006) present work similar to that of Willis and Benson (1989)

and Jones et al (2002), but based on a larger data set for UK forest visits. They

estimate a transferable trip generation function via a zonal technique, where visit

rates to given sites from a set of outset zones are predicted based on travel time(s)

from the outset zone to the site. The basic function explains (the natural

logarithm of) visit numbers as a function of population size, socio-economic

characteristics, facilities and other site characteristics, and the type, quality and

accessibility of substitute sites.

They include variables on the basis of explanatory power in univariate regressions

and stepwise regression methods. Model performance is evaluated on the basis of

the out-of-sample predictive power (as in Jones et al. 2002). Visit number data

were available for a total of 100 countryside (non-urban) woodland sites across GB

(42 in England, 41 in Scotland and 17 in Wales) but it is not possible to say if these

sites can be considered representative.

Site characteristics included forest age, size and species mix. Data on 27 site

facilities were recorded (including presence of a car park, picnic site, and visitor

centre and data on the number and length of trails). Since separate inclusion of

dummies for each facility type leads to problems with both multicollinearity (i.e.

facilities that are almost always found together) and loss of degrees of freedom

(reducing statistical power of the model), three facility index variables were

calculated to indicate the number of facilities present at each site: two

unweighted indices based on the number of facilities, and a weighted one with

weighting derived from rankings of facilities from a random sample survey of 1900

respondents at 44 of the 100 forest sites undertaken in the summer of 2002.

Proximity and nature of the local population were represented via demographic

data drawn from the 1991 Census, calculated for six travel-time zones around each

forest site. These were estimated using GIS cost-distance modelling techniques

based on Lovett et al. (1997) and Jones et al. (2002). Data for 11 key demographic

characteristics were assembled for each zone, including population size, indicators

of affluence, deprivation, age, ethnicity, access to transport and higher education.

The validity of the transfer functions in both Jones et al. (2002) and Hill and

Courtney (2006) is assessed by calculating the transfer errors from using the

function based on all but one of the sites to predict visitor numbers at the omitted

site, with each site omitted in turn. The observed-to-predicted ratio is then

calculated to assess validity of the model. Hill and Courtney find that 36% of

predictions are within ±50%, and 65% are within ±75% for the whole sample; these

figures rise to 44% and 80% for a sample based just on Forestry Commission sites.

Similar models have been applied on a more local scale to specific areas, as

reported in Liley et al (2009). They cite visitor models developed in Dorset and the

Thames Basin Heaths, in order to understand how visitor levels to these European

Protected Heathland Sites would change with new housing. Surveys were used to

produce models predicting visitor numbers based on the characteristics of the


eftec July 2010 76

access points and amount of housing surrounding each point, and then used to

predict changes in visitor numbers as a result of new housing (Liley et al., 2006a),

to inform access management proposals on sites, to determine the impacts of

access on Annex I bird species (Liley et al., 2006a) and to assist with SSSI condition

monitoring (Clarke et al., 2008a). Dolman et al. (2008) adopt a similar approach in

Breckland, but survey visitors within sites rather than at access points, because the

site was accessed via many small, informal access points.

Liley et al (2009) also report that basic GIS based models have been developed

(Entec Ltd., 2002a, Entec Ltd., 2002b) to predict the levels and patterns of

recreational use of open countryside in order to understand the likely changes in

visitor levels associated with the introduction of a new right of access within the

Countryside and Rights of Way Act (2000). A national model used data from the

England Day Visits survey to calculate the average number of visits made by

different socio-economic groups, which were then applied at a district level, with

day visits distributed on a per hectare / pro rata basis across all sites. Some simple

adjustments were made for distance and attractiveness (for example sites within

National Parks were scaled up by 20%). This is a simplistic approach that relies on

ad hoc adjustments rather than detailed modelling of actual visit data. Given geo-

referenced visit data, it should be possible to derive a more realistic model,

although MENE data are unlikely to be sufficient alone, since there will be very

sparse sampling for individual sites.


eftec July 2010 77

Table 2 Summary of Economic Valuation Techniques for Outdoor Recreation

Technique Applicability Pros Cons Overall Market price Entrance fees;

local expenditures

Easily observable and based on real payments

Relate to prices not values; free access does not mean zero value

Important data that must be processed carefully. Key input for travel cost.

Hedonic pricing In principle, for tourism, via housing and hotel/holiday let markets

Based on actual behaviour/ expenditures

Data may be hard to get. Problems defining market boundaries and participants.

Potentially useful if data are available but not recommended for primary study.

Travel cost: individual or zonal

Any site or activity which involves travel: works best for important sites.

Based on actual behaviour. Modest data requirements.

Hard to value prospective changes

Useful if available. Primary studies possible.

Travel cost: Random Utility /Multi-site recreation demand models

Any set of sites used for an activity: can work for general sites.

Based on actual behaviour. Takes substitution into account.

Requires more complex extensions if total trips are to be predicted.

Useful if available. Primary studies possible

Trip generating functions

Any set of sites used for an activity: can work for general sites.

Based on actual behaviour. Takes substitution into account.

Does not involve monetary valuation

Similar to travel cost, without the monetary step. Predicts visit numbers, and this may be enough for many purposes.

Stated Preference

Any activity or value about which questions can be framed: i.e. universal

Can be used to value all recreational activities. Additionality can be internalized.

Can be complicated to implement and analyse. Hypothetical – not grounded in actual behaviour

Difficult to separate use and non-use – bear in mind for avoiding double counting. Primary study expensive.

Combined revealed preference – stated preference methods

For sites that are used and possible changes to them

Extends scope of valuation while remaining anchored to real behaviour

May offer the best of both worlds


eftec July 2010 78

4.4 Issues in recreation valuation with revealed preference methods

There are a number of features, problems and options associated with travel cost

and related approaches to valuing recreation. The main ones are summarised

below.

4.4.1 Weak complementarity

Travel cost methods assume weak complementarity between expenditure on the

recreation activity and other goods and services (Hanley and Spash, 1993). This

means that when the number of trips, and hence travel expenditure, is zero, the

marginal utility and consumers‟ surplus of the site is also zero. The surplus of the

most distant/marginal visitors approaches zero as the cost of accessing the site

approaches the benefits enjoyed from the trip; and the total site value estimated

relates only to actual use values and not to any form of non-use or option values.

This is not a problem as such, but rather a reminder that any non-use values, which

could be significant, are not covered by these methods (and so may require

separate consideration).

4.4.2 Functional form

There is little theoretical guidance concerning the appropriate functional form for

the trip-generating function, and different studies often use different functional

forms. It is often observed that, for a single dataset, changing the functional form

can result in different estimates of consumer surplus without resulting in

significant differences in the statistical fit of different models (see for example

Hanley, 1989). Hence, appropriate specification of functional form is typically a

matter of expert judgment and consequently a potential weakness of the TCM.

Associated with this, there are various biases and data problems that often arise,

particularly in individual TCM. The dependent variable is a non-negative integer

and for on-site surveys the sample is truncated at one (no zeros can be observed).

On-site sampling also leads to endogenous stratification (oversampling of frequent

visitors). The data generally display overdispersion (Cameron and Trivedi, 1986;

Grogger and Carson, 1991), where the variance of each measurement is greater

than the mean. Various methods have been used to correct for these problems

individually, but it is extremely difficult to correct for them simultaneously

(Martin-Lopez et al 2009).

In RUMs, a common problem with the conditional logit model is the independence

of irrelevant alternatives (IIA) assumption, requiring that the relative probability of

choosing between any two sites is not affected by the presence of other sites in the

choice set. In fact it is often the case that presence of alternative site X can affect

the probability of choosing site Y over site Z. One way to deal with this is to use a

different modelling approach such as nested logit models that partition the choice

set into separate groups of sites.


eftec July 2010 79

4.4.3 Type of survey

The kind of survey instrument used can influence the results. If an off-site survey

is used (in-home, telephone, postal) there may be response biases including in

particular „zero-inflation‟ arising through the inclusion of many respondents who

would not visit the site at all, even at zero price. „Zero-inflation‟ is a problem

because if all people who do not report using a site are treated as potential users

(e.g. would use the site if costs were lower), this results in upward bias in demand

/ consumer surplus measures compared with a model that differentiates between

genuine potential users and those who are not interested and would not use the

site, even at zero cost.

Another problem with off-site surveys is “respondent recall bias”, if the site is

infrequently visited, or if data are being collected for RUM analysis involving

consideration of visits to a wide range of sites over a lengthy period. This can be a

particular problem with respect to geocoding the specific locations visited, though

use of face-to-face methods with paper or touch-screen maps can reduce this. One

of the main reasons MENE and similar surveys focus on the past 7 days is to avoid

this recall bias.

On-site surveys can result in truncation bias (not including anyone who does not

visit the site – which in particular means ignoring those who might if the costs or

quality were to change favourably) and more generally from endogenous

stratification (disproportionate sampling of people who visit more often).

Both truncation and zero-inflation bias are a reminder of the importance of

accurate data on the beneficiary population. These biases can be corrected for

through careful treatment (see in particular Haab and McConnell 2002). Separate

estimation of “participation” and “frequency” decisions can reduce or remove bias

associated with non-users. Adjustments to the distribution function can correct for

on-site sampling biases.

Meisner et al (2008) present results from a single-site model in which these

corrections are carried out, and find that after correction there is no significant

difference between the on-site and off-site surveys. This finding is important

because it has the potential to defuse the arguments that on-site surveys are not

representative of the entire population and that off-site surveys are not

representative of those actually using a site: if the results are the same, the

objections don‟t matter. They suggest further research to test these findings on

multi-site models.

4.4.4 Valuation of time

The monetary valuation of leisure time is an important problem for travel cost and

RUMs. Since time is scarce, there is an opportunity cost associated with time spent

travelling, and this needs to be included in estimates of travel cost. There are two

issues: estimating the travel time, and valuing the time.

For estimating the time, simple approaches assume constant speeds (e.g. Landry

and McConnell (2007) estimate travel time based on an average speed of 50 miles


eftec July 2010 80

per hour for all households); more sophisticated estimates can be made that allow

for different speeds on different road types using GIS, but this is more difficult and

data-intensive. Travel time can also be established directly through a question in

the survey.

For valuation of time, early applications of travel cost methods generally used a

proportion of the wage rate. But labour markets and laws are not so flexible that

there is a direct trade-off between working time and leisure time, for most people.

There are also complications that there may be some direct enjoyment of travel

time (for example a scenic drive to a recreation site) and that the values need not

be linear.

Hynes et al (2009) explore the use of various methods of incorporating the

opportunity costs of time in travel cost models: exclusion, the individual‟s reported

wage rate, and use of wage estimates from secondary data sources. They apply

the different methods in a conditional logit model for whitewater kayaking in

Ireland, noting that “statistically significant differences emerge”. Their results

demonstrate how decisions about how to measure the value of time have a strong

influence over consumer surplus estimates, which are significantly lower (higher)

when the opportunity cost of time is excluded (included at 100% of reported gross

wage) compared to valuing time at 100% of the estimated net wage derived from

the secondary dataset. But it is not clear which method is “correct”. Hynes et al

favour the use of an auxiliary data set to estimate wage regressions, which are

then used to estimate a net hourly wage for each individual in the recreation data

set.

Hanley and Barbier (2009) suggest that these problems mean it is preferable to

include travel time as a separate variable alongside travel cost.

4.4.5 On-site activities, heterogeneity of users and the definition of “site”

A further related issue is that of on-site activities. These may be considered as

attributes of the site, though they are not necessarily relevant to all users (see

Martin-Lopez et al 2009) and this might suggest separate functions for different

user types. This has led many authors to focus on a single activity type at a site, in

preference to considering all possible uses of a site.

A related issue is the definition of a “site” – although in some cases there are clear

boundaries, often there may be linear features, or a wide range of different

features or sub-sites, including different areas suited to specific activities, and so

on. For geo-coding purposes, linear features such as paths and rivers need to be

divided into suitable „sites‟, and this can be problematic, not least because what

constitutes a site may vary across different activities (for example, hiking and

climbing). Church et al. (2009) flag this problem for water bodies, noting that the

definition of site may vary substantially for different activities, even at the most

basic split into “amenity” (water bodies as backdrop for non-water-based

activities), angling, “immersion” and “on-water non-immersion” activities.


eftec July 2010 81

Martin-Lopez et al make a study of the Doñana National Park in Spain, described as

“complex and heterogeneous, providing cultural services that vary with location

and season”. It attracts about 4 million visitors per year, with three-quarters of

them focused in one area, El Rocio, famous for cultural reasons. This leads Martin-

Lopez et al. to identify five different geographical sectors within the park, and six

different types of user. The different user types visited different areas, for

different lengths of time, and at different times of year.

To apply the zonal model, Martin-Lopez et al. used distance quartiles to define

four zones for the whole sample and for each geographical area separately. The

resulting zones were rather different, with visitors to recreation areas travelling on

average much less than cultural/religious visits, for example. The global sample

gave average consumer surplus of 20.53€, but local values range from 2.90€

(recreational areas) to 70.63€ (El Rocío).

A similar approach with the individual TC method involved a general model and

separate models for different categories of individual (user segments). At one

extreme, the “one day visitors” for general relaxation and picnics generally came

from nearby, and were mostly regular or very regular visitors; the number of trips

in this group did not depend on travel cost since the trips and costs did not display

enough variability to constrain the models. For the other groups, consumer surplus

values per trip were:

€58.47 for environmental professionals

€31.47 for nature tourists

€30.53 for culture tourists

€12.11 for beach tourists

€73.76 for pilgrims

For the “global” model the averge value was €25.08.

Taking these differences into account leads to different aggregate results: a 200%

difference under the zonal model, and a 30% difference under the individual

model. Martin-Lopez et al argue therefore that global methods suffer from severe

limitations through ignoring spatial and temporal variations in consumer demand:

sub-dividing the survey into more homogenous sub-samples provided more accurate

and realistic results.

While taking account of preference heterogeneity could be important, it also

means that sample sizes need to be bigger and/or that confidence intervals for

individual groups are likely to be wider than they would be for a global sample.

Thus the right balance needs to be struck between splitting heterogeneous samples

into more homogeneous groups, and maintaining enough observations in each

group.


eftec July 2010 82

Cutter et al (2007) develop a different approach that models individuals as

choosing both on-site attributes and site activities. This model recognises that the

marginal value of site attributes are dependent on the choice of an activity (for

example, surfers and picnickers will not have the same marginal benefit for a

water quality improvement), and recognises that activities are not perfect

substitutes, allowing estimation of the marginal rates of substitution across

activities. This approach reduces biases in the welfare analysis of changes in site

attributes when preferences for attributes depend upon the choice of activities

undertaken at the site. The approach is essentially estimation of a model in which

individuals simultaneously choose an activity and a site, represented as a nested

model in which their choice of site is made in consequence of the choice of

activity.

Cutter et al (2007) make three suggestions for future research:

develop a more robust set of variables to predict individuals' choice of

specific activities;

rather than treating activities as "discrete choices," collect data on the

length of time each individual spends engaged in an activity, and model

individuals' choice of activities as a continuous and "quantity-based"

measure of consumption; and

explore other types of models (such as latent class models) to accommodate

individuals' choice of activities.

An additional feature of sites with multiple uses is the potential for inter-activity

externalities (negative effects of one activity on the enjoyment of other activities).

Where these exist, data collection may need to record the extent to which

individuals perceive level of other activities, and include interactivity externality

terms within the indirect utility function. Dalrymple and Hanley (2005) take this

into account in a travel cost model for Loch Lomond, looking at the clash between

water sports and “quiet” enjoyment of loch side. Cutter et al (2007) report that

interviews with hikers and bird watchers suggest that interactivity externalities

with other recreational users can be important. Picnic tables and barbeque grills

were negatively valued by these users because they are associated with activities

that generate noise, large groups, and congestion which interfere with the

enjoyment of hiking and bird watching.

4.4.6 Substitute sites and activities

A further issue to consider is the presence of substitute sites. This is a particular

problem for continuous models (zonal or individual TC) where demand for one site

is affected by the availability and quality of substitute sites. This is not easy to

reflect in the analysis as it requires a system of demand equations, including

estimates of how quality affects demand. If there are several similar sites within

a similar distance, then the demand for each site will be less than demand for the

recreation experience overall. Failure to account for this may lead to an over-

estimate of the recreational value of a given site: omitting the price of substitute


eftec July 2010 83

sites will bias upwards consumers surplus estimates for a given site. Jones et al

(2002) find only a weak (but statistically significant) difference in the value of

recreational forest visits based on facilities at a particular site, whereas the effects

of site location, proximity to populations and substitute sites provided a stronger

predictor of demand than facilities available.

Similarly, recreation users face not only alternative sites but also alternative

activities. This is perhaps best considered in a nested hierarchy of choices /

alternatives – the decision to go to forest B might be thought of as a nested set of

simultaneous choices:

to engage in outdoor recreation, go shopping, watch TV…

to walk, run, cycle, picnic...

to visit a forest, a beach, a river…

to visit forest A, forest B or forest C…

In addition to the effect of substitute sites, it is also difficult for the TCM to

capture fully the effects of variation in quality of sites and also individual

characteristics of sites and how these influence the demand for visits to a site. In

particular, an improvement in site quality should raise demand for the visits to the

site at every level of travel cost. Accordingly, the difference between the original

demand curve and the new demand curve represents the change in consumer

surplus. However, there is also the need to account for changes in other sites and

the substitution of visits from one site to another which arise from improved

quality as well as the impact on travel costs that this will create (Freeman, 1993).

While the TCM is suited to explaining recreation demand over a given time period

(e.g. the number of visits in a year), it is not suited to consider these effects.

That is why random utility site choice models came in. These models are suited to

consideration of the effects of the availability of substitute sites and changes in

quality levels of specific site characteristics (Bockstael et al., 1991; Freeman,

1993). For example, Johnstone and Markandya (2006) use the RUM site choice

model to allow for the effects of substitute sites in an application to fishing trips.

The models were able to evaluate the influence of the cost and quality attributes

of the substitute sites on site choice, and the significance and coefficients of these

variables reflect this. The model was successful in producing travel cost variables

always negative and significant, and some evidence of statistically significant river

quality variables with the expected sign.

Then the problem becomes (i) what is the set of substitute sites? (ii) what are the

best attributes to use to describe these substitute sites? (iii) how correlated are

these attributes across sites (i.e. can we estimate effects separately)?

Alternative sites can be incorporated into analysis (in the trip-generating function)

through specific questions to respondents in survey and GIS techniques can also be

applied to generate data (Brainard et al., 1999), such as distance between sites.

The ability to do this has increased greatly in recent years: Lovett et al. (1997)


eftec July 2010 84

suggest that the data available for these calculations, such as spatially explicit

information of average driving speeds, were not yet adequate to inform their

calculation, but Jones et al (2002) used measures of travel time to a wide range of

alternative site types, and Hill and Courtney (2006) defined several indicators of

proximity to substitute woodland sites, with size of woodland used as a proxy for

woodland quality. The availability of other woodlands in the proximity of the

visitor outset locations was quantified using data assigned to enumeration districts

or census output area centroids. However these indicators were highly correlated

with population size, and so only one of the variables could be included in any

regression. Generally, the main difficulty facing the definition of substitute sites is

no longer calculation of travel times, but obtaining data on the sites available and

their quality.

Jones et al (2002) note that the nature of the substitute relationship may be

complex. While at one level (most commonly considered) substitutes may act to

draw visitors away from a given site to alternative recreation opportunities, at a

broader level a high concentration of substitutes (a cluster) may draw people in to

an area, especially for holidaymaking. This leads them to consider both a wide

range of substitutes and a number of spatial scales in deriving substitution

accessibility indicators for each outset zone.

4.4.7 Conversion to annual estimates

For practical use, trip numbers or values must be expressed either as total

numbers/value over a given period of time (normally a whole year) or as changes in

numbers/value over that time. This is often difficult simply because of lack of

data to support aggregation over a whole year, especially where surveys have taken

place over a relatively short period in a particular season. Bateman et al (2002,

2006) note that errors in the aggregation process can result in greater variability in

estimates of total demand than errors in the statistical modelling. One of the ways

in which MENE data could help would be in underpinning scaling values, not for

specific sites (which will not be sufficiently represented in MENE for this to be

statistically reliable) but for general types of site.

4.4.8 Consideration of distributional impacts

Any method grounded in willingness to pay, including stated and revealed

preference methods, produces values that are constrained by ability to pay.

Households with lower disposable incomes, less ability to pay travel costs, and

even lower time values, will tend to have lower estimated values for recreation

whatever method is used.

By definition, the TCM only estimates the direct (recreational) use value of a

particular site; those who are unable to access the site, yet have a positive

preference for the site (in effect, a non-use value) will not be accounted for in the

analysis. Beyond that, appropriate survey sampling would permit analysis of the

characteristics of the user population and sub-groups within it: this could be

carried out in respect of particular target groups in the population (for example


eftec July 2010 85

low income groups) or could be based on segmentation/profiling work, with

different visit rates and values for different profiles.

4.4.9 Changing tastes and preferences

Economic values are contingent upon incomes, prices, tastes and preferences, and

though value functions can include information on incomes and prices, and can

therefore be updated with new values, changing tastes are much harder to account

for. Unlike prices and incomes, tastes are not directly observed, and though

proxies (age, class, education and so on, or more generally, customer

segmentation/profiling) are useful, and changes in proportions of these groups can

be used to update value estimates, if the fundamental underlying tastes change,

value estimates go out of date.

As an example, one possible scenario would see demand for recreation fall due to

increasing pressures on time, but it could be that despite the reduced total number

of hours of recreation, total value could rise, because a higher time-value would

tend to push values up. Which effect dominates will depend on the elasticities of

the two responses.

There are other possible changes that perhaps can be incorporated within existing

models, allowing for adjustments in value transfer. Loss of sites (for example to

coastal squeeze) is one such case, since the supply of sites will feature directly in

RUMs. Another example is climate change, where changed climatic conditions

affect recreation values in ways that may be predictable: this is discussed in Box

11.


eftec July 2010 86

Box 11: Climate change and tourism

The benefits of outdoor recreation and tourism can clearly depend on the

weather, and given the right data this can be taken into account in travel cost

models. Patterns in the weather make up the climate, and so the benefits also

depend on climate, and therefore on climate change, a feature that is particularly

important for tourism. Pinnegar et al. (2006) and Viner et al. (2006) summarise

the likely long-run implications for UK tourism:

Decline in the numbers of UK outbound tourists visiting the Mediterranean during the summer months;

Increase in domestic tourism within the UK;

Increase in overseas tourists visiting Britain during the summer months, in particular for coastal/beach tourism;

Increasing pressures on outdoor recreation environments, in particular the coastal zones and waters of the UK;

Possible coastal squeeze of beaches behind hard defences as sea level rises;

Loss of infrastructure for tourism due to sea level rise or a high replacement/maintenance cost if storminess increases;

Changing rainfall patterns (not very predictable as yet) that could lead to water supply issues (if it becomes very dry in summer).

Amelung and Viner (2006) describe a “Tourism Comfort Index (TCI)”. Like any

indicator the TCI simplifies a complex reality, but is a useful aid to the assessment

of climate change impacts on tourism at a regional scale. Viner (2006) notes a

high level of confidence that the TCI is changing and producing more favourable

conditions for tourism in North West Europe, predominantly driven by increasing

temperatures, while at the same time suitability of the Mediterranean, a key

competitor region has a declining TCI. There are also potentially important

changes in socio-economic conditions, for example increasing price of carbon

emissions and moral restraint in flying, but these are harder to predict with

confidence.

It would be interesting to consider the use of the TCI, or some similar variables, in

travel cost modelling and in value transfer work. This could potentially help in

accounting for the influence of climate on values and improve the validity of value

transfer functions.

Natural England commissioned a strategic futures consultancy firm, the Henley

Centre, to undertake an independent assessment of the main factors that will

influence the future of outdoor recreation.27 The Henley Centre consulted widely

among key organisations with an interest in the outdoors and looked at the trends

27 See http://www.naturalengland.org.uk/ourwork/enjoying/research/futuretrends/default.aspx


eftec July 2010 87

that they expected would have implications for outdoor recreation between 2005

and 2015.

Henley Centre's report on the main factors that will influence the future of outdoor

recreation includes a paper introducing the research and five discussion papers,

plus eleven appendices. Each of the discussion papers focuses on a different

aspect of outdoor recreation.

Demand for outdoor recreation

Health and outdoor recreation

Supply of places for outdoor recreation

Planning for outdoor recreation

The impact of outdoor recreation

Henley Centre (2005 paper 2) suggests a “best case outcome” for recreation in the

UK combining:

sustained focus on physical activity as a means of achieving health;

people seeking experience through connecting with nature;

youth-culture being environment-savvy as well as technology-savvy; and

overall more interaction with nature, resulting in increasing demand for

outdoor recreation.

They contrast this with a “worst case” in which:

purchased „health treatments‟ replace physical activity;

the experience economy narrows to an „adrenaline economy‟ in which

nature plays little part;

household IT entertainment and communications dominate children‟s

recreation; and

connecting with nature and outdoor recreation decline.

Economic valuation techniques may consider taste and preference variables as part

of the function explaining behaviour, but in estimating a value the individual‟s

preference is sovereign. If in fact people were to reduce outdoor recreation

because of “health freak” connotations, that reduction in demand would be picked

up in economics as a reduced value of recreation.

What the Henley Centre (2005, paper 2) findings do suggest, in the context of

economic valuation of recreation, is that it is likely to be necessary to update

valuation studies on a regular basis, to take account of changing tastes and values.

This is supported, for example, by Zandersen et al (2007) who note that


eftec July 2010 88

preferences for (forest) recreation have altered over time, stating that “Updating

the transfer model with present total demand for recreation improves the error

margins by an average of 282%. Average errors of the best transfer model remain

25%.”

4.5 Use of GIS

Bestard and Font (2009) note that “use of GIS has transformed many aspects of

valuation practice providing a means of relaxing some of the restrictive

assumptions implicit in TCM applications until the 1990s”. This includes much

greater accuracy in estimating travel distance, time and cost; more precise

characterisations of substitute sites, and greater ease and accuracy in using some

descriptive variables for site characteristics. Jones et al (2002) note how GIS

provides “a ready route for obtaining measures of the underlying determinants of

recreational visits including travel time and distance, travel cost, population

distribution and outset origins for potential visitors, the socio-economic

characteristics of those populations, and the spatial availability of substitutes and

complements.” In addition, when working with zonal models it is possible to derive

the same measures for unsurveyed sites, increasing the accuracy of transfer

functions for trip numbers or values.

The fundamental requirement is for geo-coding of the trip outset point and the

destination site. In the England Leisure Visit Survey, geo-coding of main trip

destination was undertaken using TARA, a system combining Quick Address, a

gazetteer containing a detailed list of potential visit destinations, and digitised

maps to help identify places not included in Quick Address or the gazetteer. Only

trips identified as „rural‟ were geo-coded. For „mobile‟ trips involving moving

through areas (walking, cycling, riding) respondents were asked to specify the main

trip destination; where a designated open access area had been visited, this was

assumed to be the main destination.

In MENE, the aim in principle is to geo-code all trips in the detailed randomly

selected visit section of the survey. However, as noted above, Liley et al (2009)

point out that geo-coding of sites only takes place after the interview: the trial of

MENE suggests that only 60-70% of sites will be geo-referenced at first, although

this is expected to increase as the data collection is improved and as the gazetteer

is further developed.

Hill and Courtney (2006) note that there remains work to be done, notably on the

estimation of reliable accessibility indices for substitute recreation sites. They also

note basic data problems, in particular in relation to the lack of spatially explicit

data on tourism populations, who cannot be characterised by census data.

Bestard and Font (2009) argue that “valuation studies have underutilized the

capacity of GIS to enhance the spatial representation of the environment” in that

they have not sufficiently examined the role of heterogeneity of landscape and

spatial configuration of land use in and around the recreational areas. They

propose further use of GIS “to improve the characterization of the physical context

in which recreational choices are made beyond the consideration of conventional


eftec July 2010 89

attributes”. Specifically, they suggest using a set of GIS-based geographical

indicators to characterise “environmental diversity”, including various landscape

ecology metrics (ranging from simple statistical indicators of patch number, mean

size, variation to more complex measures of edge density and shape complexity).

The possible indicators are grouped and reduced to a set of three covering land

fragmentation, visibility and landscape quality. Their inclusion improves the

goodness-of-fit of the model and its predictive power to estimate site-choice

probabilities. The authors also show that omitting environmental diversity

measures leads to systematically underestimated welfare measures.

One of the main barriers to successful application of GIS in solving socio-economic

and environmental problems is the availability of accurate data at appropriate

spatial resolutions for the task in hand. In this respect, it is imperative that the

quality of input data is known so that some measure of confidence in model

outputs can be expressed.

Data requirements of travel cost methods are outlined, along with the sources of

key datasets, in the following section. The formats and spatial resolutions of these

data are many and diverse; and this in itself introduces problems when attempting

to combine them. Therefore particular attention needs to be given to combining

data in meaningful and robust ways, in order to minimise model input error so that

this will not propagate to even greater error in the output.

Another important consideration is the processing power required for computation

involving large, detailed, datasets. For instance, travel cost analyses can be

performed relatively easily and quickly over small areal extents (e.g. at the district

level), but use of complex datasets over large areas will greatly increase

calculation times and processing requirements.


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5. DATA ASSESSMENT

The data requirements of travel cost methods can be substantial, and where data

have limited availability, or low reliability, this is likely to mean that only reduced

forms of the trip-generating function can be estimated, that value estimates are

unreliable or even that travel cost estimation is not feasible at all. This section

reviews briefly the data requirements of travel cost, and considers the extent to

which these can be met, through MENE and through additional work.

5.1 Data needs

Application of the RUM framework requires a travel cost survey to collect data of

visitors‟ place of residence, demographic and attitudinal information, frequency of

visit to the site and other similar sites and trip information (e.g. purpose of the

trip, length, associated costs etc). Additional information which may be useful and

lead to better estimates includes information on length of time spent on specific

activities, and information about other activities or sites that the respondent uses.

Practical application of the ZTCM requires data concerning the population of each

of the identified travel cost zones. Data on explanatory variables which are also

likely to influence visit rates include income, preference, availability of alternative

sites, and mode of travel (car, rail, etc) to the site.

Full application of a RUM approach would require an inventory of all recreational

sites. This is needed so the analysis can take into account the choices people make

concerning substitute sites and differences in the attributes (such as water quality)

of the sites. The inventory could potentially also fulfil demand from recreational

stakeholders for a readily available up-to-date database on locations of

recreational activities and the facilities provided. Such an inventory could be

developed as a stand-alone project, based on various existing sources plus original

research, and/or it could be based on the gazeteer from the MENE survey. Liley et

al (2009) report that a dataset of sites with access in England has already been

developed through the Integrated Access Project. However, further data collection

and processing is required to ensure completeness of coverage.

Use of GIS, along with geo-coded data, can help define travel cost zones (in zonal

methods), or calculate individual travel cost (in individual base methods). GIS is

also important for determining site characteristics, the availability, accessibility

and characteristics of substitute sites, and socio-economic characteristics

(Bateman et al., 2005).

Value transfer approaches reduce the need for primary data for policy application

sites. However, transfer can only be carried out if one or more suitable valuation

studies exist giving a good match to the policy good context. Ideally, it is useful to

have a number of suitable valuation studies which match the policy good context,

in order to provide a range of results and enable key sensitivities in the value

transfer process to be identified and considered. And although a new survey is not

needed, value transfer exercises do require a substantial amount of data


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concerning the policy site. A comprehensive comparison of the socio-economic

characteristics of the policy and study sites is required in order to determine

whether it is desirable to adjust WTP results, and data on the characteristics of the

policy site enable a function transfer approach to be applied.

5.2 Data available

Key data sources include:

The MENE survey and the other ongoing national and on-site surveys

discussed in section 3.

UK census (2001)28 giving measures of population, demographic structure,

social, economic, education, employment, health and housing data.

Neighbourhood Statistics (Office for National Statistics)29: detailed statistics

for specific geographic areas, including a “neighbourhood summary” of

socioeconomic characteristics by postcode area.

Area Profiles (National Audit Office)30: covering quality of life and public

services in a local area across 10 „quality of life‟ themes.

The Index of Multiple Deprivation 200731 combines a number of indicators

covering a range of economic, social and housing issues into a single

deprivation score for each small area in England. This allows each area to

be ranked according to their relative level of deprivation.

UK Borders32 digital boundary data (supplied by EDINA) onto which much of

the available census and socioeconomic data can be mapped, at the spatial

extent of the statistical Super Output Area.

Detailed road network information, in the form of the Ordnance Survey

MasterMap® Integrated Transport Network (ITN)33 dataset, which is fully

conversant with the Topography, Address and Imagery layers forming the

OS MasterMap® suite of products. The product suite includes a set of geo-

referenced addresses that can be easily cross-referenced to physical

features on the other layers. Road network attributes can be tailored to

requirements, supplemented by the Department for Transport Free Flow

28 http://www.statistics.gov.uk/census2001/census2001.asp

29 http://www.neighbourhood.statistics.gov.uk/dissemination/

30 http://www.areaprofiles.audit-commission.gov.uk/

31 http://www.communities.gov.uk/communities/neighbourhoodrenewal/deprivation/deprivation07/

32 http://edina.ac.uk/ukborders/description/

33 http://www.ordnancesurvey.co.uk/oswebsite/products/osmastermap/itn/


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Vehicle Speed Statistics 200734, and combined with information from other

layers to achieve high resolution analyses and estimations of travel times,

costs and accessibility. MasterMap® also includes large-scale digital detail

of a wide range of real world features (such as pubs, buildings of interest,

footpaths, antiquities, rivers, waterfalls, hedges, etc), as well as intangible

features such as county boundaries.

The Ordnance Survey MeridianTM2 dataset35, which provides a

comprehensive, but less detailed (hence less memory-intensive) alternative

to the MasterMap® product: this includes roads, rivers, urban boundaries,

administrative areas and place names. This dataset would be more

appropriate for approximate travel time calculations over a large area.

Public transport information, which is available from the Department for

Transport36.

The Centre for Ecology and Hydrology Land Cover Map 2000 (Fuller et al.,

2002), providing a classification system, derived from satellite imagery, of

26 land cover types at a 25 m grid cell resolution.

Various other data that characterise the environmental features of a

location, with national coverage of habitat types, designations and so on.

Examples include MAGIC datasets37 which provide, amongst other features,

digital boundaries for Areas of Outstanding Natural Beauty and National

Parks.

Data held by individual stakeholders: for example British Waterways holds a

digital representation of locations of all British Waterway features

(including recognised recreation access points).

There is a need to develop a database of recreation sites and characteristics, if

widespread application of RUM is to be possible. Most of the necessary data exist

but are not collected in a single dataset. One initiative here is the Woods for

People project, that has created a UK-wide provisional inventory of accessible

woodland.

Hill and Courtney (2006) note that one problem with Census data is that it only

provides information on the resident population. This is an issue because tourists

can account for a significant proportion of visits to many forest sites: around half in

their survey. The proportion tends to be higher in more rural areas and popular

holiday destinations: in fact there is a bimodal distribution, with visits to most sites

34 http://www.dft.gov.uk/excel/173025/221412/221546/227050/261688/vehiclespeeddata07.xls

35 http://edina.ac.uk/digimap/description/products/meridian.shtml

36 http://www.dft.gov.uk/pgr/regional/strategy/dasts/databook/

37 http://www.magic.gov.uk/


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dominated either by tourists or by local residents. The absence of tourist

population data will account for some of the unexplained variation in their forest

visit data. And if there are grounds for thinking that tourist visit decisions are

influenced by different factors than resident visit decisions – for example the

suggestion by Jones et al (2002) that availability of many substitute sites/activities

may draw more tourists to an area – then it may be necessary to distinguish

different trip functions for these groups.

Data availability and quality can be a major problem in empirical work, and often

the data that exist are subject to considerable error, as discussed by Hill and

Courtney (2006). They report results from modelling suggesting that the FC data

available to them were significantly more reliable than other sources used, leading

them to estimate some models for the FC dataset only.

It is therefore necessary to assess the quality of data available, in particular when

considering visitor counts with varying timing, grossing up and count methods.

Development and use of standard protocols would be helpful here.

Data availability is also a key factor limiting the transferability of existing models,

most being developed from datasets of questionable reliability and limited to

forests and woodlands located within a relatively small geographical area. Other

limitations include the restricted ability of earlier analyses to capture the spatial

complexity of demand functions (Bateman et al., 1999).

5.2.1 MENE data

Although most travel cost models make use of bespoke surveys, there have been

successful uses of secondary data for travel cost modelling. Heberling and

Templeton (2009) is a recent example of re-use of on-site data, originally collected

in a survey to help a US National Park “better understand the visitors”, for ITCM

purposes. Variables including travel cost and income were estimated based on

respondents‟ postcodes. After correction for truncation and endogenous

stratification, a successful fit to the data yielded recreational value estimates of

US$89/visitor/year or US$54/visitor/24-h recreational day (in 2002 US$). The

authors suggest that the same approach could be used for other data sets for

national parks, preserves, and battlefields. This does depend on postcode or other

geo-referencing information being available.

There are a number of questions in MENE that would potentially make useful

dummy variables in econometric estimation of travel cost functions and/or in

attributing individuals to segments prior to separate estimation of travel cost

values for different segments. But while in principle this may be possible with

MENE data, in practice there will not be enough observations from single sites to

enable the methods to be applied with any statistical accuracy. Even over several

years, sample sizes will remain too small for specific sites, though they could

become large enough for broad areas (for example National Parks).

MENE may be more useful for calibrating or aggregating value estimates, since

though it will not be representative at individual site level, it will give estimates


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for the total annual amount of outdoor recreation across England. However one of

the weaknesses of MENE for economic valuation purposes, is that, in the 7 day trip

diary section, it gathers only very general information about the type of resource.

Presenting the bullet-list from the questionnaire as a table (Table 3) highlights the

two basic dimensions revealed. This contrasts with quite detailed information on

activities (see the list in Section 1.3).

Table 3: Basic type of visit location as determined in MENE survey

Inland Coastal

Urban In a town or city In a seaside resort or

town

Rural In the countryside

(including areas around

towns and cities)

Other seaside coastline

(including beaches and

cliffs)

Only in the “single random visit” section does MENE go into greater detail, asking

“Which of the following list of types of place best describe where you spent your

time during this visit?”, and allowing multiple selections as appropriate (Box 12).

It will be worth considering whether (in the light of average number of trips per

week in the first year of data, when this figure becomes available) it would not be

possible to include this more detailed characterisation of visit types for all trips

reported. This would substantially enhance the sample size and accuracy of

estimates of total visits to different specific types of area, and could be valuable in

transferring and aggregating value estimates.


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Box 12: Detailed list of visit area types from single random visit section of MENE

The MENE survey detailed location question for the single random visit asks “Which of the following list of types of place best describe where you spent your time during this visit?” and presents the following options:

A woodland or forest (including community woodland)

Farmland

A mountain, hill or moorland

A river, lake or canal

A village

A path, cycleway or bridleway

Country park

Another open space in the countryside

----

KEEP TOGETHER IN THIS ORDER:

A park in a town or city

An allotment or community garden

A children‟s playground

A playing field or other recreation area

Another open space in a town or city

----

KEEP TOGETHER IN THIS ORDER:

A beach

Other coastline

---

ALWAYS AT END:

Other (specify)

5.2.2 Segmentation work

The Futures Company has recently conducted research38 into segmentation for

outdoor recreation for Defra, Natural England, Forestry Commission, British

Waterways, and the Environment Agency. This work aimed to identify the specific

needs, requirements and preferences of different groups in relation to the natural

environment, with the following specific research questions:

How can Defra and its partners more effectively get people into the natural

environment?

What are the different barriers and motivators for different groups?

Should any groups be considered higher priority?

38 To check: is report available?


eftec July 2010 96

What are the links between pro-environmental behaviours and engagement

with the natural environment?

Does increased contact with the environment lead to more pro-

environmental behaviours?

Do people in the different segments prefer different natural environments?

Segmentation work can be relevant to environmental valuation, because different

segments can have different tastes and preferences, and hence different value

functions. Separately estimating functions for different segments can be one

approach to dealing with this. This applies in particular to models in which the

assumption is required that preferences are homogeneous, but can also apply to

individual-based models if there is a need to allow different functional forms

(rather than simply individual parameters) for different segments. Segment-based

models could also be useful where the data required for individuals is not available

at the transfer/policy site.

An example of using segmentation in travel cost work is provided by Martin-Lopez

et al (2009). The segments used there were based on two-step cluster analysis,

resulting in six categories of users:

1. Environmental professionals and employees of the National Park

2. Nature tourists

3. One-day visitors

4. Culture tourists (cultural heritage sites and events)

5. Beach tourists

6. Pilgrims and other religious visitors

There was strong association between the user categories and the five geographical

sectors identified for the area.

This is an example of deriving segments specifically for the site(s) under

investigation. A more general approach, using standard segments to investigate

outdoor recreation generally, would not be so reflective of locally-specific

segments, but this would aid a value transfer approach.

5.3 Gaps

The MENE survey design has been carefully chosen as a cost effective approach to

deriving statistically valid estimates of overall levels of outdoor recreation in

England. There are practical issues regarding interview length and quality of

responses in the context of an omnibus survey, and it is not possible to achieve all

possible objectives with a single survey. This section discusses „gaps‟ in particular


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in the context of possibly using MENE data for valuation purposes, since this was a

key part of the study brief. However it is recognised that valuation was not a

driver for MENE: the gaps noted here are not criticisms of MENE but simply

comments on whether or not it may be possible to bend MENE data to an additional

purpose.

In MENE, even with rather large overall sample sizes, only a small proportion of

total visits are likely to be made to any specific site. Liley et al (2009) explain

that, if every MENE interview were to generate a named visit (and in fact some will

not, because some respondents will not have made any outdoor trips over the past

week) then there would be roughly 1 interview for every c.200,000 visits made to

the countryside (based on the 0.77 billion estimate from ELVS, divided by 40,000

interviews). This means that sites that attract fewer than 200,000 visits per year

(i.e. roughly 600 visits a day) are unlikely on average to be recorded at all within a

single year of MENE. In practice, the situation is even more complex because of

the geographical clustering of MENE data (see below).

This feature of national off-site surveys was illustrated in ELVS, for example, where

a total of 789 visits to National Parks and 407 visits to open access land were

recorded (TNS 2007). This means that the margins of error are large, and results

for individual National Parks are not reliable and cannot be compared. Very large

increases in survey responses would be required to give significant results for these

areas with such methodologies. The „solution‟ of using booster samples in

catchment areas around National Parks is not satisfactory, both because it does not

work efficiently (there is still a low proportion who have visited in the last week)

and because it could introduce bias towards shorter trips (i.e. ignoring people who

travel from much further away). There are two ways in which higher hits could be

achieved: one is on-site surveying, and the other is surveying that focuses on

annual „whole day out‟ trips rather than 7-day „every outdoor activity‟ trips.

This means that any use of MENE data to give estimates of visits to specific sites,

even very important ones, will be likely to have very wide confidence intervals.

This is not a criticism of MENE, which was not designed with a view to assessment

of specific sites, but rather an observation of the gap between the data that will

arise from MENE and the data that would be required for extensive travel cost

modelling. An additional gap relates to the fact that the MENE survey is not used

in its full form for every interview, with some questions asked only monthly or

quarterly (see Table 1). This limits the ability to use these variables, notably

expenditure, in data analysis, because fewer data points will be available that

cover all the variables.

There is a further issue associated with the use of an omnibus survey for collecting

location-specific data (such as for outdoor recreation). The geographical location

of respondents‟ homes, and therefore start-points for visits, is not random.

Although the data are not yet available for MENE, the Scottish Recreation Survey

uses a similar methodology and this gives some insights into possible problems.

Interviewing takes place at 42 sampling points across the country each month,

changing each time, making 504 points for a full year. The objective is to sample


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representatively as measured across local authority areas, however even at this

scale there can be substantial differences between the proportions of interviews

undertaken in some areas and the share of the Scottish population. SNH (2006)

reports that “greater efforts have been made to avoid such discrepancies through

more frequent reviews of the numbers of interviews achieved in each local

authority area and input into the monthly allocation of fieldwork sampling points”.

But even representativeness at local authority scale would not result in

representativeness in relation to location relative to recreation sites.

The extent to which MENE data may illustrate geographical clustering remains to

be seen: this was of course considered when the survey was tendered and it was

agreed that this would be reviewed after one year of data collection, which is in

hand.39 Although aggregating data over several years should reduce the level of

clustering, nevertheless it seems likely that this will pose a further barrier to using

the results of MENE for travel cost modelling purposes.

Liley et al (2009) note that, in addition to MENE data, there will be a need to

collect other basic data (transport used, routes with site, activities undertaken and

so on) if we are to understand and accurately assess the numbers of recreational

visitors to individual sites within England. They propose site-based monitoring

conducted using a standard approach, allowing data to be combined across sites,

across years and scaled up to a regional and national level, and also linked with

MENE data. They propose that car-park counts, manual counts, questionnaires and

automated counters should be used across a selection of mapped sites, with

standard methods determined and used by different organisations.

They also identify the need for accurate GIS data on sites with access, including a

standardised dataset of site boundaries, site IDs and site names (including the

ability to list more than one site name), and access points. This could be used for

determining sampling strategies for surveys and monitoring, and also for

georeferencing of data from different sources. However, they report that

currently GIS data on access are not available for the whole country, and though

most local authorities have information relating to green infrastructure, these are

not collated or digitised in a standard fashion, in particular for informal access

points and parking that can be hard to define clearly. Church et al (2009) also

stress the need for a GIS-based inventory of recreation sites and their quality

features (specifically, they discuss water-based recreation sites and water quality)

including a record of all recreational sites “so that it can be established where

people go for water-related recreation and where else they could have gone”.

5.4 Solutions

Fundamentally, site-based monitoring is essential alongside MENE: MENE alone will

not provide accurate information at the site level, or permit estimation of visit

numbers (or a fortiori values) in a disaggregated form. As discussed in section 3, a

39 Natural England, pers. comm.


eftec July 2010 99

wide range of data is being collected by various organisations, but with different

methodologies and frequencies, and not collated in standard or accessible formats.

In particular, Natural England is developing a more strategic and co-ordinated

approach to monitoring through its Integrated Monitoring Project. Liley et al (2009)

make a number of recommendations for Natural England to play a leading role in

developing “a more strategic approach to visitor monitoring, using a combination

of different methodologies to create a robust system of countrywide monitoring as

part of a wider, integrated monitoring programme”. In essence, their proposal is

to develop a programme of on-site monitoring for a sample of sites within the

gazetteer used for MENE, and modifications to the gazetteer, and to MENE, to

allow the different data to be integrated, leading to “a robust monitoring protocol

that can provide data across a range of spatial scales and provide a standard

measure of visitor numbers”. The specific proposals are listed below (Box 13).

Defra and many other stakeholder organisations clearly have important roles to

play if this single “visitor monitoring community” is to be realised.


eftec July 2010 100

Box 13: Summary of recommendations from Liley et al (2009)

Gazetteer/site inventory:

o Integrated Access Project data enhanced to include wider range of sites, with standardised dataset of site boundaries, site IDs and site names.

o Additional GIS data collated for sites in the gazetteer. This could include: habitat data, designated area boundaries, national trails, postcode data (number of residential properties surrounding each site).

o Access points digitised as point data and given unique ID. Standard definitions of access points developed, including formal and informal parking and foot access points.

MENE:

o The geo-referencing of MENE data is a focus in the early stages of MENE and initial results used to further develop the gazetteer.

o Scope for including additional named sites in MENE should be explored.

o Within the first year the extent of spatial clustering within the MENE data should be investigated and its potential biases explored.

For on-site counters:

o Standards set for the types of counter, locations and calibration, made widely available and promoted to other organisations.

o Network of new counters installed following a sampling protocol to ensure range of sites and use included. Local data fed into central database.

o Engage local and site-based support through periodic feedback on derived visit rates.

Direct counts:

o Standard questionnaire and count methodology designed and promoted to all relevant organisations and sites.

o Questionnaire and counts conducted on particular sample sites and wider if possible.

o Data provided to local staff and maintained centrally.

Car park counts:

o Standard method of car-park counts designed and promoted by Natural England.

o The method is adopted on sample sites and as widely as possible.

o Data are collated, analysed and reported centrally.

Liley et al (2009) state that if such an approach of strategic and consistent on-site

monitoring is adopted, “it should be possible to develop a predictive model of visit

rates that can be applied to all sites”, or more likely separate predictive models

for different types of site. The model(s) developed from on-site monitoring could

be tested with data from MENE, as noted above.


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The key points to note for present purposes are that:

these suggestions could also result in data of a form that would be suitable

for extensive travel cost modelling; but

for that to occur, due consideration must be given to the inclusion of

appropriate questions in the survey and monitoring.

Valuation work will be significantly easier and more reliable if the data needs of

the estimation methods are considered up front, rather than attempting to retrofit

economic valuation methods onto data designed for other purposes. Data designed

for estimating trip generation functions are likely to include almost all the

variables needed for full monetary valuation, so the additional cost and effort of

deriving any additional data will be modest, but it must be done at the same time.

Panel data (for the same sites over time, or for the same individuals over time)

could be extremely useful in determining how values change as various other

changes occur: for example, investments in visitor facilities and access, changes to

environmental quality, and changes in the set of alternative sites and activities

available. This potential should be considered when developing surveying and

sampling protocols to ensure that the necessary data are collected and that the

right sites are surveyed.

In addition to collecting appropriate data, the various analysis methods discussed

above also require econometric expertise. The timescale for analysis will typically

depend on the length of survey stage. For certain sites it may be necessary to

sample at different times of the year in order to provide an accurate account of

seasonal variations in visitor patterns and number. Given the potential need for

several sampling events, implementing travel cost methods may require a time

frame from 6 months to (potentially) one and half years, allowing for data analysis.


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6. RECOMMENDATIONS

6.1 Scope for drawing on MENE and other surveys

MENE was not designed for valuation purposes, nor to provide detailed information

for individual sites, and this section is not intended as a critique of MENE itself, but

simply an assessment of whether or not MENE data could be used for valuation

purposes. The short answer is “not really”, and this is for a number of reasons; but

MENE data will be useful for providing estimates of total outdoor recreation

activity, and this is likely to be useful in grossing up estimates to regional or

national totals, and perhaps for value transfer.

Firstly, the sample sizes for specific sites will not be large enough to enable robust

estimation of individual or zonal travel cost models – at least not in the short-run.

For some sites, it is possible that in the long-run a large sample will be built up,

but experience with the ELVS survey (including the need for top-up sampling for

national parks) suggests this will take considerable time: it is difficult to say

exactly how long, before the data from the first year are available, but several

years at least, even for significant sites. This is partly because the major sites are

visited relatively infrequently by any one visitor, and partly because the random

visit selection used in MENE makes it likely that many of the trips selected for

detailed analysis will be day-to-day, routine uses of the outdoor environment:

walking the dog or a stroll in the park. If a person has walked the dog morning and

evening for the past week, and has also spent a day at a major recreation site,

there is only a one in fifteen chance that the visit selected for detailed questions

will be the visit to the major site.

Secondly, national omnibus surveys, such as MENE, do not allow for identifying the

full range of similar recreation sites used by an individual over a longer period – or

even for that matter within the week, since the detailed focus is on a single visit –

and so the data will not be directly suitable for RUM investigation. The fact that

respondents might have visited a site but do not have this recorded (either because

it is outside the seven-day period, or because it is not randomly selected for

detailed analysis) is not an unusual problem – exactly the same occurs for on-site

surveys, where we only observe some fraction of actual visitors, and this is not a

problem for individual or zonal travel costs methods. It is however a problem for

RUM analysis, which requires knowledge of the set of sites from which individuals

choose, and the frequency of recreation at the different sites.

The first point above implies that it would be difficult to use MENE data for

individual or zonal travel cost, while the second implies that it would be difficult

to use the data for RUM analysis. A third issue, noted previously, is that the

sampling method is not geographically random, but rather clustered in the areas

where the omnibus is being carried out in a particular week. This means that

assessments for specific local sites (rather than general types of site) are likely to

be skewed – the park next to the streets in which interviews were carried out will

feature, the park serving the neighbouring community may not. This not


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necessarily a major concern in the long run, as it may tend to even out, and it is

probably not a problem for the major sites that draw from wide catchments.

MENE has deliberately focused upon capturing all visits to the natural environment

including those that are shorter more informal and closer to home, such as dog-

walking trips. The evidence suggests that these types of visits were underestimated

by previous surveys. These types of short, day-to-day engagement with the natural

environment are likely to be a large and significant part of many people‟s lives,

and it is important that they should be included in the survey, and also in valuation

studies.

So although MENE will probably not give large enough samples for individual sites to

facilitate travel cost analysis for those sites, and will probably not be suitable for

RUM analysis, MENE will be useful in providing good estimates of overall recreation

activity levels, and this will be important for certain purposes, including grossing

up value estimates to regional and national levels.

MENE data could also be useful in applying value transfer methods to recreation

data, through assessing any significant differences in recreation demand and

behaviour across different regions. It may be possible, for example, to relate

differences in recreation choice or frequency (estimated from MENE) to differences

in the set of recreation options open to individuals (estimated from other sources).

This could be estimated more effectively via research designed for that purpose,

but that would be costly, and it would be worth exploring whether MENE does

reveal useful information in this context. It will also be possible to explore with

MENE data how general outdoor recreation behaviour (e.g. trip frequency) varies

with socio-economic variables, and this again could be useful for value transfer

purposes.

Overall, the main use for MENE data in terms of valuation and trip number

estimation is likely to be in providing a clear national level assessment of total visit

numbers, which will provide a useful top-down check for estimates derived from

bottom-up visit prediction models, and will enable grossing up to total values per

region based on estimated values per trip from travel cost work. A secondary use

for the MENE data in this context will be for improving / informing value transfer

functions.

6.2 Possible adjustments to MENE

It would be possible to make some adjustments to the MENE survey in order to

enhance the usefulness for generating economic value estimates for recreation.

Changing the existing questions is not really an option since that would interfere

with the stated objective of keeping a stable question set for purposes of trend

measurement. But extensions could be arranged, and this might be a cost-

effective option since many of the background data are already being collected.

Given the key features and limitations of MENE, and the uses to which its data are

likely to be put, we do not suggest attempting to modify the survey sufficiently to

enable travel cost modelling with MENE data alone. The gap between data needs


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and data collected is too large, and will need to be filled in different ways, in

particular using on-site monitoring and surveying at strategic locations. Off-site

surveys typically cannot provide reliable estimates for recreation at specific small

to medium sites, and will struggle even for large sites. What off-site surveys such

as MENE are good at is providing reliable estimates of overall recreation levels in

total and at particular types of site, at the national scale. Attempting to get this

type of information for each individual site across the nation would be prohibitively

expensive. There is an inherent trade-off between survey design (sample size,

sampling approach, number of questions and method), cost, and the level of detail

in the information produced, and we need both off-site and on-site data, and

general and detailed surveys, in order to produce a comprehensive assessment of

recreation levels and values.

However, we do suggest that consideration be given to extending the first half of

MENE (the seven day trip diary) to provide greater detail about the type of

site/environmental resource visited on each visit occasion. This is subject to the

average number of trips taken in a week being low enough that it is feasible to

cover all trips in this slightly greater detail without making the survey too long. It

may not be possible to move all the way from the current short list (Table 3) to the

longer list used in the detailed section of the survey (Box 12) but some

improvement should be considered. A strategic approach might be adopted here in

order to target key recreation or site types in line with current policy priorities. It

is also worth considering that even where the total number of trips is high, the

total number of sites visited might not be: the majority in any given week might

well be to just one or two sites near the home, and it should be possible to design

the questions to extract this information without having to run through the full list

of site types for each trip (for example, by proposing the answers already given at

the top of the list). This would improve the level of resolution of the data,

enabling more reliable grossing up or value transfer adjustments (as discussed

above).

There may be a need for further specific minor adjustments to MENE, in

conjunction with other survey and monitoring work, to pick up potentially

important activities that are not adequately covered in the data. In this context,

Church et al (2009) note in particular angling, bird watching, outdoor swimming

(split by coastal and inland), triathlon, and walking by inland water, though in fact

MENE should provide information for most of these activities.

6.3 Proposals for bespoke surveys

We support the findings and recommendations of Liley et al (2009) regarding the

creation of standardised surveying and monitoring protocols, centralised data

collation, and development of a comprehensive database of sites and access

points. The data should be used both for predictive models of visit numbers and

for trip valuation purposes.

But deriving data from national surveys and standardised visitor monitoring

procedures that are sufficient to allow widespread prediction of visitor numbers


eftec July 2010 105

and economic values at individual site level will be a mid- to long-term project,

with substantial resource implications. In the shorter term, there is clearly scope

for further individual research projects to make strategic progress in valuing key

areas or forms of outdoor recreation, and for value transfer methods to be used to

enhance the value of the results. Some opportunities here are discussed below.

Applications of continuous travel cost models (individual TC, or possibly zonal) are

suitable for valuing major recreation sites with few very similar substitutes –

Stonehenge would be a good example. They are not really applicable for changes in

more day-to-day recreation facilities, especially if there are many alternative,

similar sites in the surrounding region. It is likely, therefore, that any application

of continuous travel cost models will be in response to a specific identified need at

a major site. This could well arise, and in such cases we would recommend an

individual TC approach, perhaps backed up with stated preference questions.

However the consultation carried out for this research did not throw up any such

current cases: rather, the policy demand is for valuation of much more general

forms of recreation, at a wide range of sites, generally in respect of changes in

environmental quality or access.

For valuing general outdoor recreation, RUM analysis is the best approach to adopt;

ideally this should include both revealed and stated preference elements, through

the use of behavioural intention questions (i.e. how would respondents‟ trip

behaviour change under different circumstances). RUM allows some key features

of site selection, quality and substitution to be considered in a way that models for

individual sites can not.

To illustrate the issues, note that Church et al. (2008) report that, because of

improvements in water quality that have already been achieved, water quality

does not significantly affect whether people undertake or enjoy recreational

activities on, in, or near water in England and Wales. However water quality does

still affect where people choose to enjoy water-based activities, as is illustrated by

the ChREAM study, which shows a clear and significant relationship between

improvements in water quality and increased recreational visits. However this

finding does not apply to all changes: people were found to be insensitive between

different grades of poor quality water, and similarly insensitive to graduations in

good quality water, but their behaviour did show a clear distinction between poor

and good quality water.

The implication is that there may be quite strongly non-linear variations in

recreation value as water quality changes, both for single sites, and for groups of

sites. On the one hand, for a specific site, use levels and values may be

irresponsive to small improvements at the “poor quality” end of the scale, then

increase quite rapidly as we move towards the low end of “good quality”, but then

stabilise and remain unresponsive to further improvements. For sites collectively,

there may be rapid increases in value as the first sites are cleaned up, but then

diminishing returns as more and more water recreation sites move to good quality,

to the extent that there may be little benefit in recreation terms from improving


eftec July 2010 106

more sites once demand for water-based recreation is met by existing good quality

sites.

To detect such within-site and across-site effects, a RUM approach, ideally

involving both observed behaviour and stated behavioural intentions, is required.

The most recent (ongoing) example from the UK forms part of the ChREAM project,

at the University of East Anglia (Bateman et al., 2006). The RUM in ChREAM

involves a face-to-face survey conducted in respondents‟ homes, relating to river

based recreational activity. A custom built computerised survey instrument was

written utilising touch screen response routines. Over 2,000 households were

interviewed using high quality, face-to-face interviewing techniques during 2008.

A large study area was defined as part of this project, which included multiple

diverse rivers, several hundred urban and rural recreation sites, and substantial

variation in accessibility and river water quality at different sites. Households

were selected from diverse locations across the full study area to embrace

variation in the quality and location of recreation and substitute sites.

The computerised software identified the location of each respondent‟s home

address40. Respondents were then asked to identify the location of any water

recreation sites they visited and to rate the water quality at the site; 531 possible

sites were identified on 3 rivers. A revealed preference analysis is used to relate

the number of visits made to each site to its associated travel costs and its water

quality (additional analyses are currently ongoing). The modelling approach is to

consider a full year as consisting of 365 possible choice occasions; on each day, the

following options are available: visit one of 531 sites on the 3 main rivers; visit

other rivers, canals, lakes; engage in other activity; or stay at home.

We would suggest either one single study or several separate major studies,

covering recreation at the following types of resource:

(i) coastal resources (beach use, marine wildlife and coastal footpaths);

(ii) national parks

(iii) open access land and impacts of agri-environment schemes on

recreation values (this could possibly be combined with (ii))

40A considerable amount of time was devoted to „cleaning-up‟ the postcode data before it

could be used in the GIS: the OS codepoint data to which postcodes had to be matched

required a specific format and all of the collected postcodes had to be put into the correct

format before the GIS would recognise them as identical to those in the codepoint dataset,

and match them to the appropriate points. A lot of time and effort could be saved by

paying attention to this type of detail when collecting data for GIS input (thorough training

of the survey team, specific rules for data entry) (Paulette Posen, pers. comm.).


eftec July 2010 107

(iv) inland water quality (although the ChREAM study goes some way

towards meeting this need)

(v) woodlands and forests

It would also be possible to include questions about substitution possibilities

between these resource types, and also with other activities; but the main focus

would be estimation by resource type. It is essential to include full, spatially

accurate recording of outset and destination locations for all trips over the survey

period. Adopting the visual mapping approach pioneered in the ChREAM survey

would be one way to do this.

The main problem with a single study is trying to cover such a wide range of

recreation activities within individual interviews: it will be time-consuming and

respondents may find it harder to cover the whole field than to focus on a specific

aspect of their recreation activity (e.g. “coastal”). However separate studies

would be likely to suffer from methodological differences, limiting the

comparability of estimates, unless explicit steps are taken to ensure that identical

methodologies are adopted.

The cost of such a programme of work need not be excessive. Bateman (pers.

comm.) suggests, on the basis of the ChREAM study, that revealed preference

surveys with in-house interviews is a representative and efficient method for

deriving recreation value data. The cost of surveying varies depending on various

factors including sample size requirements and interview length. A statistically

valid (main survey) sample for RUM modelling can be achieved for an outlay of

around £50,000 - £100,000. This would be for a single resource type (e.g. inland-

water-based recreation) and the costs for covering all resource types would be

correspondingly greater. Cost in terms of design stages (including fieldwork) and

staff time for design and analysis would also be incurred.

There will also be costs associated with developing a database of recreation sites.

This would be required initially in the study areas, and then (for value transfer

purposes) nationally. It would however be useful to develop the national database

early, since ideally the study areas should be selected to be roughly representative

of the national situation.

As noted previously, RUM methods give unit values for recreation but cannot

predict the total number of visits in a year for given sites. The best solution to this

is to combine the RUM data collection and analysis with a count model / trip

generating function estimated from the same sample. Alternatively, a completely

separate data collection and analysis can be carried out.

For some purposes, direct survey data from specific sites or off-site surveys

(depending on the application) can be used to derive estimates of visit numbers,

and the values from the RUM can be used in value transfer to the estimated

number of visits. However this is of limited use where the interest is in quality

changes, or changes in substitute site availability, since the surveys only give

estimates of actual use, not of how use would change under different conditions.


eftec July 2010 108

One further area of research interest is the overlap between recreation activities

and health benefits. Overall, there are some aspects of health benefits that will

be additional to the recreation values to individuals. In particular this is the case

for cost savings for the NHS, which individuals are unlikely to take into account.

More generally, the health benefits to individuals may well be incorporated within

their stated or revealed preferences relating to recreation activities. However this

depends on the extent to which individuals are aware of the connection between

recreation and health. Further research exploring the valuation links would be

useful here.

6.4 Conclusions

The overall aim for this research was to establish how recreational survey data in

England could be used for generating economic values for policy appraisal

purposes, in the short, medium and long terms.

Outdoor recreation values are often substantial, and can be among the most

valuable ecosystem services provided by certain resources. These values can be

challenging to assess, in particular for marginal changes in site quality, but careful

use of revealed preference (or stated preference) methods can give robust values

per trip. Use can be made of value transfers based on existing studies.

Through a consultation with policy- and decision-makers, we collected evidence on

the kinds of outdoor recreation value evidence required. In some contexts, notably

for making cases to Regional Development Agencies and other local and regional

development purposes, a focus on local expenditures, GVA and jobs supported is

common. These impacts are important, but fall outside the main scope of this

research, which is focused on the value of outdoor recreation to the participants.

Economic value evidence is seen as useful at a range of levels, depending on the

policy context, and this is not so much a function of the broad policy area or type

of recreation activity, as of the specific policy or decision context. This

determines, for example: the spatial and temporal scales of interest; whether the

focus is on valuing changes in recreation quality, the value of new sites, or total

values of recreation in an area or sector; whether the breakdown of value across

different groups in society is seen as important information; and the level of

accuracy required.

It is clear that there are many potential uses, and potential users, of monetary

values for outdoor recreation. The recreation-specific organisations have

considerable interest in this area, but most say values would be useful rather than

essential, and there is little interest in unilateral funding of valuation studies.

Some of the Defra policy areas have strong demand for values, notably water in the

context of the WFD, and more generally the „value for money‟ agenda makes

availability of recreation values a high priority in some areas. Thus arguably the

main demand is for policy appraisal and evaluation purposes, but if this demand

were met, there would also be use in management and priority setting.


eftec July 2010 109

Many organisations do invest in primary data collection through on-site surveys on

land they manage or own, but there is no overall coordinated approach at the

national level. There could be important economies of scale in meeting the

demand for recreation value provision at national level, through a standardised

programme of data collection and centralisation, and a strategic approach to

primary valuation research and the development of value transfer functions.

The MENE survey will produce very useful information for understanding recreation

at national and regional levels. MENE has deliberately focused upon capturing all

visits to the natural environment including those that are shorter more informal

and closer to home, such as dog-walking trips. The evidence suggests that these

types of visits were underestimated by previous surveys, but are important features

of people‟s lives. MENE will be useful in providing good estimates of overall

recreation activity levels, and this will be important for certain purposes, including

grossing up value estimates to regional and national levels, and focusing attention

on all aspects of outdoor recreation.

The main use for MENE data in terms of valuation and trip number estimation is

likely to be in providing a clear national level assessment of total visit numbers,

which will provide a useful top-down check for estimates derived from bottom-up

visit prediction models, and will enable grossing up to total values per region based

on estimated values per trip from travel cost work. A secondary use for the MENE

data in this context will be for improving / informing value transfer functions.

In order to enhance the usefulness of MENE data in this context, we suggest that

consideration be given to extending the first half of MENE (the seven day trip diary)

to cover more detail about the type of site/environmental resource visited on each

visit occasion.

Recognising that MENE data alone will not provide value evidence (which was never

the intention behind MENE) we suggest that the best approach to taking outdoor

valuation research forwards in England (or the UK) would be either one single study

or several separate major studies, covering recreation at the following types of

resource:

(i) coastal resources (beach use, marine wildlife and coastal footpaths);

(ii) national parks

(iii) open access land and impacts of agri-environment schemes on

recreation values

(iv) inland water quality

(v) woodlands and forests

Ideally, this would be enhanced by changes to the seven-day trip diary in MENE (as

discussed just above) such that we have better data on the total numbers of visits

to these types of resource, who is using them, and under what conditions. This

would improve the information available via the valuation results, for grossing up


eftec July 2010 110

across the country or regions, particularly in combination with a national database

of recreation sites (see below). But these changes to MENE would not be essential,

and would not help with local value transfer applications, where primary evidence

on site characteristics and populations would be required anyway.

The best methodology to use would be a RUM approach, seeking to detect within-

site and across-site effects. Face-to-face interviews would enable direct use of GIS

software for automatic geo-coding of outset and destination points. The level of

information obtained from each respondent should be enhanced by surveying both

actual behaviour and stated behavioural intentions under future scenarios.

A national database of recreation sites should also be developed. This would be

required initially in the study areas, and then nationally to enable value transfer.

It would however be useful to develop the national database early, since ideally

the study areas should be selected to be roughly representative of the national

situation.

Such research would be feasible within a 2-3 year time horizon, or potentially

faster where there is a pressing need (for example, in the development of the next

round of RBMPs under the WFD; and here the existing ChREAM study may help

meeting this need). The results of the research project or projects should be

enhanced with a set of guidelines or explanatory notes aiming to facilitate the use

of the results, and the national recreation site database, for value transfer

purposes.


eftec July 2010 111

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ANNEX 1:SUMMARY OF RECREATION SURVEYS IN THE UK

Table 4: Summary of recreational surveys41 Survey Sponsored by Year /

Frequency Objective Sample Size Population

Definition Geo-referenced?42

Visitor Spend?43

Definition of visit or participation

Monitor of Engagement with the Natural Environment44

Natural England, Defra, Forestry Commission

2009-onwards, ongoing, continuous

Data collection on outdoor recreation

40,000 per year

England Yes Y Basic information on all outdoor trips taken in the last seven days.

England Leisure Visits Survey45

Consortium led by the Countryside Agency (now part of Natural England), Defra, the Forestry Commission, the Environment Agency and eight of the nine National Parks in England46.

2006, one-off (part of series)

Data collection relating to leisure trips

23,500 England Yes Y Trips taken for leisure in the previous seven days before the survey.

41 U = unknown from references available; GOR = Government Office Region

42 Geo-referenced: with postcode or other information allowing reasonably accurate determination of outset and visit locations.

43 i.e. does the survey collect data on expenditure by visitors/tourists?

44 Information obtained from http://www.naturalengland.org.uk


46 The New Forest National Park was not in existence when the survey was commissioned.


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Visitor Spend?43


GB Leisure Day visits47

Countryside Commission British Waterways Countryside Agency Countryside Council for Wales Department for Culture, Media and Sport Forestry Commission Scottish Natural Heritage VisitBritain VisitScotland Wales Tourist Board Environment Agency

2002/3, part of series


6,600 England, Scotland and Wales

No – region of origin only

Y Round trips made from home for leisure purposes to locations anywhere in Great Britain excluding Northern Ireland

UK Leisure Day Visits Surveys

Countryside Commission Department of National Heritage Countryside Council for Wales Wales Tourist Board Scottish Natural Heritage Scottish Tourist Board Forestry Commission British Waterways Department of the Environment

1994, 1996, 1998


1994: E 3261; W 1991; S 1892. 1996: E 3467; W 2179; S 2009. 1998: E 2413; W 1995; S 1833.

England, Scotland and Wales

No Y Round trips made from home for leisure purposes to locations anywhere in Great Britain excluding Northern Ireland



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Visitor Spend?43


Wales Outdoor Recreation Survey

Countryside Council for Wales and Forestry Commission Wales

2008, 2011 planned

Data collection relating to recreational visits

Wales Yes Y Outdoor recreational visits in the last seven days and 12 months

Scottish Recreation Survey48

Scottish Natural Heritage

2003-2013 planned

Data collected to provide continuous monitoring of participation in informal recreation

~12,000 Scotland Destination map only

Y Level and frequency of participation in outdoor recreation in the last 12 months and total visits in the last four weeks.

United Kingdom Tourism Survey49

VisitBritain, VisitScotland, Visit Wales and the Northern Ireland Tourist Board.

1995-onwards, annual

Data collected on UK domestic tourism, 2,010 English visitor attractions, taking note of number of visitors.

50,000 UK U Y Overnight trips in the UK and Ireland in the last 4 weeks, further questions relating to 'short' trips during these 'overnight' trips. Details relating to main purpose of trip, trip details and expenditure are collected.

Active People Survey50

Sport for England 2005 onwards, annual

Measures how participation in sport varies between area and population groups

191,000 England Yes N Participation in sporting activities Details relating to club memberships and competitive events are also collected.

48 Information from http://www.snh.org.uk/publications/on-line/comm-reports/srs_10.asp

49 Information from http://www.enjoyengland.com/corporate/corporate-information/research-and-insights/statistics/UKTS.aspx

50 Information from http://www.sportengland.org/research/active_people_survey.aspx


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Visitor Spend?43


Taking Part51 Dept. Of culture, media, and sport,

Arts Council England, English Heritage, the Museums, Libraries and Archives Council (MLA) and Sport England


Measures overall, adult engagement with culture and sport

24,174 England Yes N Participation in activities ranging from sport, the arts and visits to heritage among others.

Public Opinion of Forestry52

Forestry Commission 1995-onwards, biennial

Measures the opinions of the public to forestry and forestry related issues.

4,000 UK, Scotland, Wales, sometimes NI

No N General information relating to visits to forests and woodland. Further information relating to respondent attitudes and forestry are collected.

Inland Waterways Visitor Survey

British Waterways 2003-onwards, annual

Measures participation of activities on inland waterways

12,000 British U U Participation of activities on inland waterways used by boats in the last two weeks.

Northwest Day Visit Survey53

Northwest Regional Development Agency

2007, one-off

Data collected on tourist day visits taken for leisure purposes

9,842 Residents of the North West

Yes Y Details relating to 'tourist days' (see section 1.4.5) Trips can be up to a 90 minute drive time away.

51 Information from http://www.culture.gov.uk/reference_library/publications/5396.aspx

52 Information from http://www.forestry.gov.uk/pdf/POFUK2009final.pdf/$FILE/POFUK2009final.pdf

53 Information from http://www.nwriu.co.uk/documents/NW_Day_Visitor_Survey07.pdf


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Visitor Spend?43


All Forests Visitor Surveys54

Forestry Commission 2004-2007, one-off

Measure the volume of visits to Forestry Commission sites

245 to 1300 per forest site

Visitors to the FC estate

Address is sometimes requested

Y Details relating to visits to FC estate sites.

National Parks Visitor Survey

National Parks Authorities

1994, one-off

Information relating to characteristics of visitors, reason, and frequency of visits to 12 National Parks

U Visitors to 12 National Parks in England and Wales

U U

Peak District visitor survey55

Peak District National Park Authority

2005, one-off

Main details in relation to Peak District visits

30,000 Visitors to the Peak District National Park

Yes Some Details relating to visits to the Peak District National Park Initial questionnaire with follow-up, the follow-up collected expenditure data

Survey of Rod Licence Holders

Environment Agency 2001, 2007 Data collection relating to angling

2,603 Rod licence holders, EA regions

Yes Y Fishing since 1st April last year (interview carried out in March).

General Household Survey

Information Centre for health and social care, the Department for Work and Pensions, the Scottish Government (2006 – 2008) and Her Majesty‟s Revenue and Customs (HMRC), Eurostat

Annual, but 2002 one off for including recreation

Data collection relating to participation in sport

13,250 UK population by GOR* using PC sectors

Yes N Taking part in activity (walking, swimming, cycling etc. within 4 weeks and 12 months prior to interview

54 Information from http://www.forestry.gov.uk/forestry/INFD-5PGAZZ

55 Information from http://www.peakdistrict.gov.uk/visitorsurvey.pdf


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Visitor Spend?43


Watersports and Leisure Participation Survey56

BMF, MCA, RNLI, RYA and sponsored by Ybw.com

2002 onwards, annual

Measures participation in water based sports in the UK

~12,000 UK population Yes N Participation in any of 12 water based recreational activities in the last 12 months.

International Passenger Survey57

National Statistics ONS


Measures of international tourism

~250,000 Passengers on all major routes in and out of the UK

No Y Participating in activities within their visit time. Unsure of how much expenditure data is collected

The Economic and Environmental Impact of Sporting Shooting58

British Association for Shooting and Conservation, the Countryside Alliance and the Country Land and Business Association, in consultation with the Game Conservancy Trust

2004, one-off

Determine environmental costs and benefits of shooting

Participants = 1,128 Providers= 968 Suppliers = 169 public = 623

Providers and participants of shooting opportunities, suppliers to both, and the public in the UK

Address Y "Guns who shoot any type of quarry across the UK" – A1.4, page 84 Expenditure data collected and a contingent valuation was carried out using a released game shooting estate

56 Information available from http://www.britishmarine.co.uk/upload_pub/WatersportsandLeisureOmnibus2009finalpublic.pdf

57 Information from http://www.statistics.gov.uk/ssd/surveys/international_passenger_survey.asp

58 Information from http://www.shootingfacts.co.uk/pdf/pacecmainreport.pdf


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Visitor Spend?43


The economic impact of game and coarse fishing in Scotland

Scottish Executive Environment and Rural Affairs Department

2006, one-off

Economic impact of game and coarse angling

2,364 (ref. Study within report)

Scotland No Y Expenditure information relating to angling

Survey of Public Attitudes and Behaviours towards the Environment

Defra and the Energy Saving Trust

Bi-annual, last 2009

The purpose of the research was to monitor and measure attitudes and behaviours towards the environment in England. The research comprised a face-to-face quantitative survey of adults aged 16 and over.

3781 England and Wales

Yes N N/A, to do with behaviour/attitudes rather than trips and visits

Scottish Environmental Attitudes and Behaviours Survey

Scottish Executive, Scottish Natural Heritage and the Forestry Commission

2002 one-off

Record public views on a wide range of environmental issues

4000 Scotland U U N/A, to do with behaviour/attitudes rather than trips and visits

Annual Monitoring Report on the effect of the public open access (CROW)59

Natural England 2006, 2007 should be annual

These are Annual Monitoring Reports on the effect of the public open access rights that came into effect in 2004 and 2005 under the Countryside and Rights of Way Act 2000 (CROW).

2007 – 66 open access sites; 2006 – 32 open access sites. Number of interviewees - U

Visitors to open Access sites in England

N N Those who visit an open access area that is part of the monitoring program.

59 Information from http://www.naturalengland.org.uk/ourwork/enjoying/research/openaccess/default.aspx

http://www.naturalengland.org.uk/ourwork/enjoying/research/openaccess/default.aspx


eftec July 2010 128

ANNEX 2:EXISTING EVIDENCE ON RECREATION VALUES

Table 5: Stated preference studies of recreation values

Study (name/date) Method Area/Service Value Other services?/Value transfer?

Christie et al (2010) CV Recreaton improvements in Grampian region

from £1.59 for creation of long paths to £4.24 for path maintenance

open ended WTP for basic and intensive levels of an improvement, followed by allocation of bid amounts across six types of area

Phillip and Macmillan (2006)

CV WTP for car parking in Cairngorms

Mean WTP £2.77; £4.04 if hypothecated

Indicative of difference between use and non-use, but not reliably Strong anchoring effect (to actual car park charge)

Christie et al. 2006 TC, CB, CE Rural forest and rural forest with specific recreational amenities. Cwm Carn, Dyfnant, Glentress, New Forest, Rothiemurchus, Thetford, Whinlatter

Average values by TC method over 7 sites: Cyclists – £14.97 Walkers - £14.51 Other Visitors - £14.99 Nature Watchers - £7.90 Horse Riders - £14.20 (CE, CB provided various values for specific site attributes)

Substitutes taken into account. n=1,568 For TC: Cyclists – 322 Walkers – 416 Other Visitors – 416 Nature Watchers – 104Horse Riders – 81

Euromontana (2005) CV Enjoyment of public benefits associated with the uplands

£52.74 per UK household Participants mostly users of uplands but may contain non-use values. Only 190 participants in two locations. Postal survey.

Fitzpatrick and Associates / Coillte (2005)

CV Recreation in Irish Forests

£4.44 average per visit


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Willis et al (2003) Public surveys. The specific valuation techniques are not described.

Average amenity value of UK woodlands

£172.77/ha/yr

Scarpa (2003) CV, BT. Compensating variation for recreational visit to woodland over 7 FC sites: Brenin (Wales), Dartmoor, Delamere, Epping, New Forest, Thetford

CV: £1.66 - £2.78 BT: £1.10 - £3.00

n=428 (for CV)

Grijalva et al (2002) Contingent Behaviour (combines elements of SP and TCM)

Restriction to access for rock climbing

£510 seasonal loss per climber for closure to two of four areas and £954.41 for closure of three areas.

Users surveyed for changes to visitation rate – value derived from travel costs incurred. US study.

Hanley et al (2002b) CE Valuing demand for recreation – using rock climbing as an example

Extra metre: £0.13 One hour reduction in approach time: £13.53 Crowded to not: £21.23. “Very scenic”: £29.21. “Three stars” climbs: £35.89

Sets out study design for valuation of recreational demand.

Brouwer and Bateman (2005)

CV Recreational Benefits Norfolk Broads

£363.36/hh/yr Flood protection and water quality included in value. Shows valuing the same resource with similar samples five years apart can give different values.


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Christie et al (2000) Improvements to recreational facilities in the Grampian region. Values per household per year:

£4.98 for path maintenance £2.80 for upgrading paths £3.34 for new short paths £1.87 for new long paths £4.60 basic facilities £2.00 user facilities

Scarpa et al (2000) CV Forests in Ireland £0.82-£2.35 WTP at the gate; avg. 35p higher if nature reserve

Bullock and Kay (1996) CV Southern uplands £89.34 visitors; £107.46 general public

Odd result that public WTP more than visitors. Likely reflection of part-whole bias.

Gourlay (1996) CV Loch Lomond Stewartry

£26.67 residents; £2.56 per visit. £16.83 residents, £3.28 per visit

Tax vehicle for residents; entrance fees for visitors.

Bateman et al (1993) CV Mean visitor WTP for the Yorkshire Dales

£34.70

Benson and Willis (1991)

CV New Forest visits Consumer Surplus: Over £607/ha/yr Values per visit from £1.91 - £3.81


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Table 6: Revealed preference estimates of recreation values

Authors Date Method Area/Service Value Other services?/Value transfer?

Morgan and Jutn (2010)

2010 TC, contingent behaviour

Cave diving in Florida $155 / person trip; $1075 /person year +$100 extra cave +$50 better access

Find different travel cost preferences for revealed and stated preference trip counts; but single preference structure for site quality changes. US study.

Hynes et al (2009) 2009 RUM White-water rafting in Ireland

Loss of one site: -0.92c to -2.91c; Loss of different site: -0.59 to -1.44c

Irish study.

Heberling and Templeton (2009)

2009 ITCM Great Sand Dunes National Park and Preserve, Colorado

$89/visitor/year or $54/visitor/24-h recreational day (in 2002 U.S. $).

Use of on-site, secondary data (i.e. not intended for TCM)US study

Meisner et al (2008) 2008 single site TC: comparison of on-site and hh surveys

Lake Sevan (Armenia) CS estimates not significantly different between on-site and household surveys, after correction for zero-inflation, truncation, endogenous stratification

Hill and Courtney (2008)

2008 Trip generating function (TCM method but no monetary value)

Countryside woodland areas in Britain

n/a - but implications for value transfer of TCMs.

Report that data issues, in particular the quality of available visit data, severely limit transferability.

Hynes et al (2007) 2007 TCM Farm commonage site in Connemara, Ireland

£25.60 /trip Substitution effects not considered: could overstate WTP. Beach access, machair grassland.


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Christie et al. 2006 2006 TC, CB, CE Rural forest and rural forest with specific recreational amenities. Cwm Carn, Dyfnant, Glentress, New Forest, Rothiemurchus, Thetford, Whinlatter

Average values by TC method over 7 sites: Cyclists – £14.97 Walkers - £14.51 Other Visitors - £14.99 Nature Watchers - £7.90 Horse Riders - £14.20 (CE, CB provided various values for specific site attributes)

Substitutes taken into account. n=1,568 For TC: Cyclists – 322 Walkers – 416 Other Visitors – 416 Nature Watchers – 104Horse Riders – 81

Johnstone and Markandya (2006)

2006 RUM Angling in upland, lowland and chalk rivers in England – various quality changes.

Depending on attribute, £0.04 to £3.93 per trip for 10% change

Cover 303 river stretches across England. Trip prediction model

Grijalva et al (2002) 2002 Contingent Behaviour (combines elements of SP and TCM)

Restriction to access for rock climbing. Users surveyed for changes to visitation rate – value derived from travel costs incurred.

£510 seasonal loss per climber for closure to two of four areas and £954.41 for closure of three areas.

US study.

Hanley et al (2002a) 2002 TC RUM Rationing of open access upland areas – costs of policies to restrict access

-£14.57 to -£16.90 seasonal change in compensating variation (variation between sites and policy)

Looks at implications of parking costs and increase walk on visitation rates for mountaineering. Identify over crowding of resources and implications for utility and environmental stress.


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Liston-Heyes and Heyes (1999)

1999 TC Consumer surplus of a trip to Dartmoor National Park

£13.06 and £16.72/day for day visitors and £4.17 and £30.43/ day for overnight visitors.

Range depends on time value: lower if excluded, upper if 43% of wage.

Scarpa (1999) 1999 TC Forests in Northern Ireland

£1.39-£8.47 Values for trips where main purpose is forest visit.

Garrod and Willis (1992)

1992 TC Open access forest resources

£5.04, £3.03, £1.09, £0.86, £3.32 and £2.79 for the New Forest, Brecon, Buchan, Cheshire, Lorne and Ruthin respectively.

High variation in values highlights the issues of using travel cost for value transfer

Willis (1991) from £1.42-3.31/visit Sample 4976, on-site at sites randomly selected from 15 different clusters.

Willlis and Benson (1988)

Derwent Ings, Upper Teesdale and Skipwith Commons

Estimated individual consumer surplus ranged from £0.59 ($0.90) for Skipwith Common to £2.29 ($3.51) for Upper Teesdale (1986 British pounds/U.S. dollars).

survey of 1,018 visitors


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Table 7: Meta-analyses of recreation values


Bateman et al (2009)

2009 BT function from multiple identical SP studies

River quality changes in several European countries

Show how inclusion of substitute sites influences values

Zandersen and Tol (2008)

2008 Meta-analysis of TCM: 26 studies in 9 countries (7 from UK)

Consumer surplus for forest trips

£0.57 /trip to £97.52/trip; Mean £15.06, median £3.94

Bateman, I. and Jones, A. (2003); Jones et al (2002)

2003 Meta-analysis of informal recreational value of woodlands (CV, BT)

Generally rural forest, with generic recreation benefit. Mix of commercial forest and nature reserve sites, FC and other

Estimates range from £0.07 to £3.14


eftec July 2010 135

Table 7: Meta-analyses of recreation values


Zandersen et al (2007)

2007 functional benefit transfer using RUM and GIS

52 forests, identical surveys 20 years apart, car trips to forests

Allow heterogeneous preferences across the population and for heterogeneity over space. Danish study.

Kaval (2006) Meta-analysis drawing on studies from several countries.

All activities (values per person day) Backpacking Birdwatching Camping Cross-country skiing Downhill skiing Fishing General recreation Hiking Horse Riding Hunting Mountain biking Picnicking Rock-climbing Sightseeing Viewing wildlife National parks

National forests

State parks and forests

£89.06 (sd £38.91) £81.36 (sd £86.15) £25.73 (sd £27.66) £21.71 (sd £8.16) £23.18 (sd £13.13) £35.81 (sd £66.72) £57.12 (sd £121.23) £21.34 (sd £24.72) £12.53 (sd 0) £32.50 (sd £25.48) £117.91 (sd £203.32) £48.43 (sd £73.97) £74.58 (sd £51.82) £36.33 (sd £52.89) £30.66 (sd £30.54) £86.77 £37.28 £35.93

1229 studies (global) 6 studies. 8 48 12 5 173 52 68 1 274 32 13 27 39 240

scoping study into the use of recreational surveys for economic

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