scoping study into the use of recreational surveys for economic
TRANSCRIPT
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
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.
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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
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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
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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
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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
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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
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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
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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.
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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
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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
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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/
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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
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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:
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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
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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.
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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?
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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
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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.
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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
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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.
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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.
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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.
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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.
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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.
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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)
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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?
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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.
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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.
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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
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“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.
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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
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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).
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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.
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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.
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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.
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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.
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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
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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
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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.
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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
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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.
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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
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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
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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
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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
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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.
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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
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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
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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
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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
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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.
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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.
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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.
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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).
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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
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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.
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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.
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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.
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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).
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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
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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.
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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-
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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.
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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.
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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
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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
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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.
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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
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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
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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
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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
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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.
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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
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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.
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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
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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.
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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.
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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
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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)
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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
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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.
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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
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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
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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
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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?
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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.
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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.
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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
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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
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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.).
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(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.
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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.
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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
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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.
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REFERENCES
Adamowicz, W. L., G.D. Garrod, and K.G. Willis (1995) Estimating the Passive Use
Benefits of Britain's Inland Waterways, Centre for Rural Economy Research Report,
University of Newcastle upon Tyne, Newcastle.
Amelung B. and Viner D. (2006) The sustainability of tourism in the Mediterranean:
Exploring the future with the Tourism Comfort Index Journal of Sustainable Tourism
Vol 14 Nos. 4
AMION Consulting (2008) The economic benefits of green infrastructure – an
assessment framework for the NWDA
Austen, M.C., C. Hattam, S. Lowe, S.C. Mangi, K. Richardson (2009) Quantifying
and Valuing the impacts of marine aggregate axtraction on ecosystem goods and
services. Published September 2009. MEPF project number 08/P77
Bateman, I. J., A. A. Lovett and J. S. Brainard (1999) Developing a Methodology for
Benefit Transfers Using Geographical Information Systems: Modelling Demand for
Woodland Recreation, Regional Studies 33, 191-205.
Bateman, I. J., Brouwer, R., Davies, H., Day, B. H., Deflandre, A., Di Falco, S.,
Georgiou, S., Hadley, D., Hutchins, M., Jones, A. P., Kay, D., Leeks, G., Lewis, M.,
Lovett, A. A., Neal, C., Posen, P., Rigby, D. and Turner, R. K. (2006) Analysing the
agricultural costs and non-market benefits of implementing the Water Framework
Directive, Journal of Agricultural Economics 57, 221-237.
Bateman, IJ, Day, BH, Georgiou, S and Lake, I (2006b) The aggregation of
environmental benefit values: Welfare measures, distance decay and total WTP
Ecological Economics 60 (2006) 450 – 460
Bateman, I.J., Brouwer, R., Ferrini, S., Schaafsma, M., Barton, D.N., Dubgaard, A.,
Hasler, B., Hime, S., Liekens, I., Navrud, S., De Nocker, L., Ščeponavičiūtė, R., and
Semėnienė, D (2009) Making Benefit Transfers Work: Deriving and testing
principles for value transfers for similar and dissimilar sites using a case study of
the non-market benefits of water quality improvements across Europe CSERGE
Working Paper EDM 09-10
Bateman, I.J., E. Diamand, H. Langford, and A. Jones (1996) Household Willingness
to Pay and Farmers` Willingness to Accept Compensation for Establishing a
Recreational Woodland, Journal of Environmental Planning and Management 39,
no. 1, 21-43.
Bateman, I.J., G.D. Garrod, J.S. Brainard and A.A. Lovett (1996) Measurement
Issues in the Travel Cost Method: A Geographical Information Systems Approach,
Journal of Agricultural Economics, Vol 47(2): 191-205.
Bateman, I.J., Willis, K.G. & Garrod, G.D. (1994). Consistency between contingent
valuation estimates: A comparison of two studies of UK National Parks. Regional
Studies 28, 457-474.
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 112
Bateman, IJ and Jones, AP (2003) Contrasting conventional with multi-level
modelling approaches to meta-analysis: Expectation consistency in U.K. woodland
recreation values. Land Economics 79(2) 235-258
Bennett, R., Tranter, R., Beard, N. & Jones, P. (1995). The value of footpath
provision in the countryside: A case-study of public access to urban-fringe
woodland. Journal of Environmental Planning and Management 38, 409- 417.
Bennett, R.M., Tranter, R.B. and Blaney, J.P. (2003) The Value of Countryside
Access : A Contingent Valuation Survey of Visitors to the Ridgeway National Trail
in the United Kingdom, Journal of Environmental Planning and Management, 46(5):
659-671.
Benson, J.F. & Willis, K.G. (1991). Valuing informal recreation on the Forestry
Commission estate. Forestry Bulletin 104. London: HMSO.
Benson, J.F. and K.G. Willis (1990) The Aggregate Value of the non-priced
recreation benefits of the Forestry Commission estate, Benson, J.F. and K.G.
Willis, Department of Town and Country Planning, The University, Newcastle upon
Tyne. Report to the Forestry Commission.
Bestard, AB and Font, AR (2009) Environmental diversity in recreational choice
modelling Ecological Economics 68 2743–2750
Bishop, K. (1992) Assessing the Benefits of Community Forests: An Evaluation of
the Recreational Use Benefits of Two Urban Fringe Woodlands, Journal of
Environmental Planning and Management 35, no.1, 63-76.
Bockstael NE, Hanemann WM, Kling CL (1987) Estimating the value of water quality
improvements in a recreational demand framework. Water Resour Res 23:951–960
Bockstael, N.E. and McConnell, K.E. (2006) Environmental and Resource Valuation
with Revealed Preferences: A Theoretical Guide to Empirical Models, Springer.
Bockstael, N.E., McConnell, K.E. and Strand, I.E. (1991) “Recreation”, in Braden,
J.B. and Kolstad, C.D. (eds.) (1991) Measuring Demand for Environmental Quality,
North-Holland, Elsevier Science Publishers, Amsterdam.
Boxall, P.C., Hauer, G., Adamowicz, W.L. (2001) “Modeling Congestion as a Form of
Interdependence in Random Utility Models”, Staff Paper 05-01, Department of
Rural Economy, University of Alberta.
Brainard, J., I Bateman and A. Lovett (2001) Modelling Demand for Recreation in
English Woodlands, Forestry 74(5), 423-438.
Brainard, J.S. Lovett, A.A. and Bateman, I.J. (1999) “Integrating geographical
information systems into travel cost analysis and benefits transfer”, International
Journal of Geographical Information Systems, 13(3): 227-246.
Brouwer, R. (1999) Public Right of Access, Overcrowding and the Value of Peace
and Quiet: The Validity of Contingent Valuation as an Information Tool, Centre for
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 113
Social and Economic Research on the Global Environment (CSERGE) Working Paper
GEC 99-05. University of East Anglia and University College London.
Christie, M., B. Crabtree, and B. Slee (2001) An Economic Assessment of Informal
Recreation Policy in Scottish Countryside, Scottish Geography Journal 116, no. 2
125-142.
Christie, M., Hanley, N., Garrod, B., Hyde, T., Lyons, N., Bergmann, A., & Hynes,
S. 2006, Valuing Forest Recreation Activities: Final Phase 2 Report. Forestry
Commission: Edinburgh
Church, A., Gilchrist, P., Ravenscroft, N. & Taylor, B. (2008)
Valuation of recreational benefits of improvements in water quality – potential
benefits and data requirements. Collaborative Research Programme (CRP) on River
Basin Management Planning Economics
Clawson, M. & Knetsch, J.L. (1966). Economics of Outdoor Recreation. London: The
John Hopkins Press.
Coalter, E, Long, J. & Duffield, B. (1988). Recreation Welfare - The Rationale for
Public Leisure Policy. Aldershot: Gower Publishing Company Ltd.
Cobbing, P. & Slee, W. (1993). A contingent valuation of the Mar Lodge Estate,
Cairngorm Mountains, Scotland. Journal of Environmental Management and
Planning 36, 65-72
COUNTRY LAND AND BUSINESS ASSOCIATION Response to Consultation on Coastal
Access Scheme
Countryside Agency: The economic impact of recreation and tourism in the English
countryside (could be economic impact / not relevant)
Curry, N. (1994). Countryside Recreation, Access and Land Use Planning. London:
Chapman & Hall.
Dalrymple G. and Hanley N. (2005) Using economic valuation to guide the
management of outdoor recreation resources. Tourism. Vol. 53 (2005), No. 2.
Davidson, S, Martin, C and Treanor, S (2009) SCOTTISH ENVIRONMENTAL ATTITUDES
AND BEHAVIOURS SURVEY 2008, Ipsos MORI report to Scottish Government Social
Research
Davis, J. and C. O'Neil (1992), Discrete Choice Valuation of Recreational Angling in
Northern Ireland, Journal of Agricultural Economics, Vol. (43), 3, pp. 452-457.
Defra (2007) An introductory guide to valuing ecosystem services
http://www.defra.gov.uk/environment/policy/natural-environ/using/
Defra (2009) Consultation on the English National Parks and the Broads: Draft
Circular – revised version combining Circular 12/96 and Circular 125/77 Vision for
National Parks: Government priorities
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 114
Defra (2009b) Marine and Coastal Access Act Newsletter Issue 12 – Final Edition,
November 2009.
Defra/DCMS (2002) Economic costs of Foot and Mouth Disease in the UK: A joint
working paper.
http://archive.cabinetoffice.gov.uk/fmd/fmd_report/documents/D-
GovtPublications/DEFRA_DCMS.pdf
Dolman, P., Lake, I. R. & Bertoncelj, I. (2008) Visitor flow rate and recreational
modelling in Breckland. UEA, Norwich.
Eckton, G.D.C (2003) Road-user Charging and the Lake District National Park,
Journal of Transport Geography 11, 307-317.
ECOTEC (2003) Craven Access Enhancement and Promotion: A Report to the
Yorkshire Dales National Park Authority
ECOTEC (2008) The economic benefits of Green Infrastructure: the public and
business case for investing in green infrastructure and a review of the underpinning
evidence. Report to Natural Economy NorthWest
ECOTEC (2008b) The economic benefits of Green Infrastructure: Developing key
tests for evaluating the benefits of Green Infrastructure. Report to Natural
Economy NorthWest
Edwards, V and Knight, S (2006) Understanding the Psychology of Walkers with
Dogs: new approaches to better management
eftec (2010) Valuing Environmental Impacts: Practical Guidelines for the Use of
Value Transfer Policy and Project Appraisal
http://www.defra.gov.uk/environment/policy/natural-
environ/using/valuation/index.htm
eftec (2010b) The Economic Contribution of the Public Forest Estate in England.
Final report to the Forestry Commission.
eftec and Environmental Futures (2006) Valuing our Natural Environment, Final
report to Defra. http://www.eftec.co.uk/eftec_reports/eftec-
Valuing_Our_Natural_Environment-136.pdf
Elson, M.J. (1977). A review and evaluation of countryside recreation site surveys.
Cheltenham, Countryside Commission.
ELVS Consortium (2006) England Leisure Visits Technical Report for the 2005
survey. ELVS Consortium.
Entec Ltd. (2002a) Methods of predicting the levels and patterns of recreational
use of open countryside. Report for the Countryside Agency.
Entec Ltd. (2002b) Methods of predicting the levels and patterns of recreational
use of open countryside. National Model Update. Report for the Countryside
Agency.
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 115
Forester, B.A. (1989). Valuing outdoor recreation activity: A methodological survey.
Journal of Leisure Research 21, 181-201.
Forestry Commission (2009) Results from the UK 2009 survey of Public Opinion of
Forestry
Fuller, R.M., Smith, G.M., Sanderson, J.M., Hill, R.A. and Thompson, A.G. (2002)
The UK Land Cover Map 2000: Construction of a parcel-based vector map from
satellite images, The Cartographic Journal, 39, 15-25.
Garrod, G. and K. Willis (1992) The Amenity Value of Woodland in Great Britain: A
Comparison of Economic Estimates, Environmental and Resource Economics, 2,
415-434.
Garrod, G. and K. Willis (1992) The Environmental Economic Impact of Woodland: A
Two-Stage Hedonic Price Model of Amenity Value of Forestry in Britain, Applied
Economics 24, 715-728.
Garrod, G., K. Willis, M. Raley and M. Rudden (1998) Economic Evaluation of Access
Provisions in the MAFF Agri-environment Schemes, Report to the Ministry of
Agriculture, Fisheries and Food (now Department of Environment, Food and Rural
Affairs - DEFRA).
Garrod, G.D. and Willis, K.G. (1991) “Some empirical estimates of forest amenity
value”, Working Paper 13, Countryside Change Unit, University of Newcastle upon
Tyne.
Grijalva, T, Berrens, RP, Bohara, AK and Shaw, WD (2002) Testing the Validity of
Contingent Behavior Trip Responses. American Journal of Agricultural Economics
84(2): 401-414.
Haab, T. C. and K. E. McConnell (1996). Count data models and the problem of
zeros in Recreation demand analysis. American Journal of Agricultural Economics,
78, 89-102.
Hanley, N and Barbier, EB (2009) Pricing Nature: Cost-benefit analysis and
environmental policy Edward Elgar, Cheltenham.
Hanley, N., B. Alvarez-Farizo, and D.W. Shaw (2003) Rationing an Open-Access
Resource: Mountaineering in Scotland, Land Use Policy 19, 167-176.
Heberling, MT and Templeton, JJ (2009) Estimating the Economic Value of National
Parks with Count Data Models Using On-Site, Secondary Data: The Case of the Great
Sand Dunes National Park and Preserve, Environmental Management 43:619–627
Henley Centre (2005, paper 2) Demand for outdoor recreation: A report for Natural
England‟s outdoor recreation strategy
Henley Centre (2005, paper 4) Supply of places for outdoor recreation: A report for
Natural England‟s outdoor recreation strategy
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 116
Henley Centre (2005, paper 6) Impact of outdoor recreation: A report for Natural
England‟s outdoor recreation strategy
Hill, GW and Courtney, PR (2006) “Demand analysis projections for recreational
visits to countryside woodlands in Great Britain” Forestry, Vol. 79, No. 2, 2006.
doi:10.1093/forestry/cpl005
HM Treasury, (2007) Review of Sub National Economic Development and
Regeneration
Hotelling, H. 1949 A reply letter to a U.S. Park service request. In The Economics of
Public Recreation, Mimeograph. R.A. Prewitt (ed.). National Park Service,
Washington DC.
Huang, J.-C., Haab, T.C., Whitehead, J.C., 1997. Willingness to pay for quality
improvements: should revealed and stated preference data be combined? Journal
of Environmental Economics and Management 34, 240–255.
Hynes, S, Hanley, N and O‟Donoghue, C (2009) Alternative treatments of the cost
of time in recreational demand models: an application to whitewater kayaking in
Ireland, Journal of Environmental Management 90 (2009) 1014–1021
Institute of Transport & Tourism (2006) Demonstrating The Economic Case For
Cycle Tourism In The North Yorkshire And York Sub-Region: Final Report
Jacobs (2009) Benefits Transfer Valuation Framework for Inland Waterways
Jeon, Y and Herrigesm, JA (2010) Convergent Validity of Contingent Behavior
Responses in Models of Recreation Demand, Environmental & Resource Economics,
vol. 45(2), pages 223-250
Johnstone, C and Markandya, A (2006) Valuing river characteristics using combined
site choice and participation travel cost models Journal of Environmental
Management 80 (2006) 237–247
Jones, A., Bateman, I. and Wright, J. 2002 Estimating arrival numbers and values
for informal recreational use of British woodlands. Final Report to the Forestry
Commission, CSERGE School of Environmental Sciences, University of East Anglia.
Kingston, R, Cahill, D, Handley, J, Tzoulas, K and James P (2009?) Toward a Green
Infrastructure valuation model: Assessing the potential for the CITYgreen GIS
software for use as a tool for qualifying the economic benefits of Green
Infrastructure in the UK
Klein, R.J.T and I.J. Bateman (1998) The Recreational Value of Cley Marshes
Nature Reserve: An Argument Against Managed Retreat?, Water and Environmental
management, 12(4), 280-85.
Land Use Consultants (2010) EVALUATION OF THE SUSTAINABLE DEVELOPMENT
FUND IN ENGLISH NATIONAL PARKS 2002-2009 Final evaluation report produced for
the English National Park Authorities Association
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 117
Landry CE and McConnell KE (2007) Hedonic Onsight Cost Model of Recreation
Demand Land Economics 83 (2): 253-267
Liley, D., Sharp, J., Clarke, R. T. & Lake, S. (2009). Natural England‟s approach to
monitoring access on sites, a review. Footprint Ecology / Natural England 2009.
Loomis, J.B., Sorg, C.F. & Donnelly, D.M. (1986). Evaluating regional demands for
estimating recreation use and economic benefits. Water Resources Research 22,
431-438.
Lovett, A., Brainard, J. and Bateman, I. 1997 Improving benefit transfer demand
functions: a GIS approach. Journal of Environmental Management 51, 373 – 389.
Martin-Lopez, B, Gomez-Baggethun, E, Lomas, PL and Montes, C (2009) Effects of
spatial and temporal scales on cultural services valuation Journal of Environmental
Management 90 (2009) 1050–1059
Maxwell, S. (1994) Valuation of Rural Environmental Improvements Using
Contingent Valuation Methodology: a Case Study of the Marston Vale Community
Forest Project, Journal of Environmental Management 41, 381-399.
McConnell, K. E. 1992. "Onsite Time in the Demand for Recreation." American
Journal of Agricultural Economics 74 (4): 918-25.
McConnell, K.E. (1985). The economics of outdoor recreation. In A.V. Knesse & J.L.
Sweeny (eds), Handbook of Natural Resources and Energy Economics. New York:
Elservier Science Publishers, pp. 677-722.
Meisner, C, Wang, H, and Laplante, B (2008) Welfare Measurement Convergence
Through Bias Adjustments in General Population and On-Site Surveys: An
Application to Water-based Recreation at Lake Sevan, Journal of Leisure Research
40:3 457-478
Morgan, O.A., Huth, W.L., (2010) Using revealed and stated preference data to
estimate the scope and access benefits associated with cave diving. Resource
Energy Econ. doi:10.1016/j.reseneeco.2010.01.005
National Trust (2001) Valuing our environment: Wales, Cumbria and Northumbria.
Natural Economy Northwest (2009?) The Economic Value of Green Infrastructure
Natural England (2008) Natural England Open Access Annual Monitoring Report 2007
O‟Neill, D. (2001) Revealed Preference, Stated Preference and Combined Models of
Choice of Nature Reserve for Birdwatchers in the South East of England, MSc
dissertation as part of the course in Environmental and Resource Economics,
University College London.
OECD (1995). The Economic Appraisal of Environmental Projects and Policies: A
practical guide. Paris: OECD.
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 118
Pearson, M.J., I.J. Bateman and G.A. Codd (2001) Measuring the Recreational and
Amenity Values Affected by Toxic Cyanobacteria: a Contingent Valuation Study of
Rutland Water, Leicestershire, Economics of Coastal and Water Resources: Valuing
Environmental Functions, Kluwer Publishing, Dordrecht.
Peirson, G., D. Tingley, J. Spurgeon and A. Radford (2001) Economic Evaluation of
Inland Fisheries in England and Wales, Fisheries Management and Ecology,
2001,8,415-424.
Phanuef, D.J. and Siderelis, C. (2003)”An application of the Kuhn-Tucker model to
the demand for water trail trips in North Carolina”, Marine Resource Economics,
Vol. 18, 1-14
PWC (2004), Valuing our environment: the economic impact of the National Trust in
Northern Ireland, Report for the National Trust
Radford, A.F., G. Riddington and D. Tingley (2001) Economic Evaluation of Inland
Fisheries: Economic Evaluation of Fishing Rights, R&D Technical Report/Project
Record W2-039/TR/1 (Module A), Division of Economics and Enterprise, Glasgow
Caledonian University and MacAllister Elliot Partners.
Randall. A. 1994. "A Difficulty with the Travel Cost Method." Land Economics 70
(Feb.): 88-96
Roberts, G. (1997). How many more can we take? In Countryside Recreation
Network News 4(1). Cardiff: CRN.
Royal Society of Edinburgh (2002) Inquiry into Foot and Mouth Disease in Scotland.
RSPB (1998) Geese and local economies in Scotland, report to the National Goose
Forum by RSPB and BASC.
RSPB (2002) RSPB reserves and local economies, report prepared by Anna Shiel,
Matthew Rayment and Graham Burton, Sandy, Beds: RSPB.
Scarpa, R., S. Chilton., G. Hutchinson., and J. Buongiorno (2000) Valuing the
Recreational Benefits from the Creation of Nature Reserves in Irish Forests,
Ecological Economics 33 pp. 237-250.
SNH (2006) Scottish Recreation Survey: technical report 2004/05. ROAME No.
F02AA614/3
Spurgeon, J., G. Colarullo, A.F. Radford and D. Tingley (2001) Economic Evaluation
of Inland Fisheries Module B: Indirect Economic Values Associated with Fisheries -
General Public Survey, Environment Agency R&D Project Record W2-039/PR/2.
SQW Consulting (2008) Contribution of the Peak District National Park to the
Economy of the East Midlands. Final report.
TA/SWT (2003), The Economic Value of the South West Coast Path, Report by
Tourism Associates and South West Tourism
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 119
TEP, Ibis Environmental & Design Consultants and ECOTEC (2009) How to Deliver,
Measure and Demonstrate the Economic Contribution of the Natural Environment at
a Project Level: A Guide for Project Managers
The Ramblers Association (2003) The Economic and Social Value of Walking in
England, report prepared by Dr Mike Christie University of Wales Aberystwyth and
John Matthews, Independent Research Consultant. Available at
http://www.ramblers.org.uk/.
Thiene, M and Scarpa, R (2009) Deriving and Testing Efficient Estimates of WTP
Distributions in Destination Choice Models Environmental and Resource Economics
44:379–395
Thornton, A (2009). Public attitudes and behaviours towards the environment -
tracker survey: A report to the Department for Environment, Food and Rural
Affairs. TNS. Defra, London.
Viner D., Sayer M., Uyarra M., and Hodgson N., (2006) Climate Change and the
European Countryside: Impacts on Land Management and Response Strategies.
Report Prepared for the Country Land and Business Association., UK. Publ., CLA, UK
180 pages.
Viner, D. (2006). Impacts of Climate Change on Tourism in Marine Climate Change
Impacts Annual Report Card 2006 (Eds. Buckley, P.J, Dye, S.R. and Baxter, J.M),
Online Summary Reports, MCCIP, Lowestoft, www.mccip.org.uk#
von Haefen, R.H. and Phaneuf, D.J. (2008) “Identifying demand parameters in the
presence of unobservables: a combined revealed and stated preference approach,
Journal of Environmental Economics and Management, 56, 19-32.
von Haefen, R.H., Phaneuf, D.J. and Parsons, G. (2004) “Estimation and welfare
analysis with large demand systems”, Journal of Business and Economic Statistics,
Vol. 22, No. 2.
Whitehead, JC, Phaneuf, D, Dumas, CF, Herstine, J, Hill, J and Buerger, B (2010)
Convergent Validity of Revealed and Stated Recreation Behavior with Quality
Change: A Comparison of Multiple and Single Site Demands Environmental &
Resource Economics, vol. 45(1), pages 91-112.
Whiteman, A. and J. Sinclair (1994) The Costs and Benefits of Planting Three
Community Forests: Forest of Mercia, Thames Chase and Great North Forest,
Report to Policy Studies Division, Forestry Commission.
Whitmarsh D. Nothen J., and Jaffrey S (1995) Contingent valuation of Coastal
Resources: A Case Study of Beach Recreation in the UK. Centre for the Economics
of the Marine Environment, for Gosport Borough Council.
Willis K. and Garrod, G.D. (1990) The Individual Travel Cost Method and the Value
of Recreation: The Case of the Montgomery and Lancaster Canals, Environment
and Planning C: Government and Policy, 8, 315-326.
Scoping study of recreational surveys for economic valuation – Final Report
eftec July 2010 120
Willis, K.G. and Garrod, G.D. (1991) “An individual travel cost method of
evaluating forest recreation”, Journal of Agricultural Economics, 42 (1): 33-42.
Zandersen, M, Termansen, M and Jensen, FS (2007) Testing Benefits Transfer of
Forest Recreation Values over a Twenty-Year Time Horizon Land Economics 83 (3):
412-440
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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
45 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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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
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
Data collection relating to leisure trips
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
Data collection relating to leisure trips
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
47 Information obtained from http://www.naturalengland.org.uk
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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
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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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
Taking Part51 Dept. Of culture, media, and sport,
Arts Council England, English Heritage, the Museums, Libraries and Archives Council (MLA) and Sport England
2005-onwards, annual
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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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
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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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
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
1993-onwards, annual
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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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
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
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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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Table 5: Stated preference studies of recreation values
Study (name/date) Method Area/Service Value Other services?/Value transfer?
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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Table 5: Stated preference studies of recreation values
Study (name/date) Method Area/Service Value Other services?/Value transfer?
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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Table 6: Revealed preference estimates of recreation values
Authors Date Method Area/Service Value Other services?/Value transfer?
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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Table 6: Revealed preference estimates of recreation values
Authors Date Method Area/Service Value Other services?/Value transfer?
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
Authors Date Method Area/Service Value Other services?/Value transfer?
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
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Table 7: Meta-analyses of recreation values
Authors Date Method Area/Service Value Other services?/Value transfer?
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