Benefit Transfer of Non-Market
Values – Understanding the concepts
John Rolfe
Central Queensland University
Outline of this talk
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How does benefit transfer work?
Types of benefit transfer
Applications of benefit transfer
Improving the accuracy of transferred
values
1 - Benefit transfer
• The transfer of values from one case study to
another policy situation
• Attractive because of cost and time
advantages over the separate conduct of
non-market valuation experiments
• Can be complex because source and target
sites may not be identical
– Benefit transfer may involve some adjustment of
values
– BT may be associated with increased uncertainty
about values
How a benefit transfer function
works
• An indirect conditional utility function:
• Utility = Constant + attributes + individual factors
• Vih =  + 1Z1 + 2Z2 + .... nZn + aS1 + bS2 + .... zSn
• Vih = -0.828 - 0.023*cost + 0.031*Vegetation +
0.002*waterways - 0.015* people leaving + 0.149* reserve
+ 0.265*education + 0.0001*income
• In this example, it would be possible to adjust this benefit
transfer function to:
– Different site characteristics (e.g. vegetation, waterways)
– Different respondent characteristics (e.g. education, income)
Stages in BT process
#
1
2
3
Stage
Assess target situation
Identify source studies available and select
benefit transfer type
Assess site differences
4
Assess population differences
5
Assess scale of change in both cases
6
Assess framing issues (scope, scale, instrument,
payment vehicle, payment length, willingnessto-pay or willingness-to-accept format used, use
versus non-use)
7
Assess statistical modelling issues
8
Perform benefit transfer process
Notes
Transfer type largely dependent on source
studies available
(a) identify if BT possible
(b) identify basis for BT adjustment
(a) identify if BT possible
(b) identify basis for BT adjustment
(a) identify if BT possible
(b) identify basis for BT adjustment
(a) test if source study is appropriate
for BT
(b) Identify any basis for BT
adjustment
(a) identify appropriateness of model
in source study
(b) Identify any basis for BT
adjustment
2. Key mechanisms for benefit
transfer
• Point – total value
– Total value from a previous study
• Point – marginal value
– Value per unit transferred
• Benefit function transfer
– Function allows adjustments for site and
population differences
• Integrations across multiple studies
– Meta analysis
– Bayesian methods
Total point value transfer
• Takes the lump sum value from a source
study and applies it to the target
• Simple in theory but does not allow ….
– Variations in the quantity of the environmental
impact
– Variations in site differences
– Variations in population differences
– Variations in framing differences
Marginal point value transfer
• Takes the marginal value from a source study and
applies it to the target
• Allows some adjustment according to the variation
in the quantity of the environmental impact
• May also allow some variation in the size of the
population affected
• Still easy to do but does not allow ….
– Most variations in site differences
– Variations in population differences
– Variations in framing differences
Benefit function transfer
• The transfer of a benefit function from a
source study to a target application
• Allows for adjustments in site and population
differences
• May still not account for differences in the
way that tradeoffs are framed, or for temporal
differences
• Techniques such as Choice Modelling, which
produce value functions, are suitable for this
Meta analysis
• Meta-analysis for use in benefit transfer involves
the summarizing of results for several existing
source studies in a regression function,
• This function is then used to predict value
estimates for a target site
• Often difficult to do in practice because of
methodological and framing differences between
studies
Bayesian transfer
• Provides a mechanism for the results of several
studies to be combined together with attitudinal data
• Begins with a set of prior beliefs about the parameters
of interest, by drawing on existing data and/or
experience and beliefs from a range of stakeholders.
• This prior can then be modified as new data (e.g.
additional source studies) are incorporated.
• Modified priors are normally referred to as ‘posterior’
beliefs.
• Both priors and posteriors are usually presented in the
form of distribution functions
3 - Three main approaches to benefit
transfer
• ‘The Prospector’ – searches for suitable
previous studies and transfers results
across to target site
• ‘The Systematic’ – designs a database
of values suitable for benefit transfer
• ‘The Bayesian’ – combines both a
review of previous studies with potential
data gathering
The ‘Prospector’ in practice
• Once suitable source studies have been
identified, then decision is taken about
the best way of transferring values
– Point – total value
– Point – marginal value
– Benefit function transfer
– Meta analysis
• Reflects most examples of benefit
transfer
Examples of the Prospector
• A number of studies conducted in the
Fitzroy dealing with water allocation and
riparian development issues
• Results have been transferred to other
policy issues dealing with vegetation,
water development, protection of
cultural heritage
Question X: Options A, B and C.
Please choose the option you prefer
most by ticking ONE box.
Fifteen-year effects
How much I
pay each
year
Option A
$0
Option B
$20
Option C
$50
Healthy
vegetation left
in floodplains
Kilometres of
waterways in
good health
Protection of
Aboriginal
Cultural sites
Unallocated
water
20%
1500
25%
0%
30%
1800
35%
5%
40%
2100
45%
10%
I would
choose
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
0.12
0.1
0.08
0.06
0.04
0.02
0
2000 2001 2002 2003 2005
Brisbane
Vegetation
2000 2001 2005
Rockhampton
Waterways
$ per 1km improvement
$ per 1% improvement
Values for vegetation and waterways
over time
Examples of the Systematic
• Van Beuren and Bennett (2004) explored
values for NRM protection across Australia
• Morrison and Bennett (2004) explored values
for protecting river systems across NSW
• Windle and Rolfe (2007) developed a broad
data base of NRM values in Qld relating to
soils, vegetation and waterways
The Windle and Rolfe database
• Identified the values for improvements
in 3 key areas of the investment plans
for NRM regional groups
– Healthy vegetation
– Healthy waterways
– Healthy soils
• Identified sensitivity to regional issues
• Identified sensitivity to framing issues
Regional choice set example
Summary of values
Soil
Water
Vegetation
$ value of each 1% improvement
Brisbane – South East Queensland
Regional model
3.05
3.42
3.01
Statewide model1
5.34
4.99
7.69
Toowoomba – Murray Darling
Regional model
4.02
6.28
2.35
Mackay – Mackay Whitsunday
Regional model
4.60
7.82
2.42
Rockhampton – Fitzroy Basin
Regional model
3.70
6.69
4.48
Pooled models
Regional model
3.72
5.80
2.88
Statewide model
4.64
6.62
4.54
Issues with the systematic approach
• Usually designed to be very broadscale and
inclusive so as to cover large range of different
potential applications
• Not always easy to transfer values from a very
general application back to the specific
• Normally needs to be some adjustment involved
for the scope and scale changes
– But it is not clear what the theoretical basis for the
adjustment factor is and how they should be
calculated
The Bayesian approach
• Provides a mechanism to combine data
from a variety of sources and update it
with attitudinal data from target
population
• Complex and difficult to perform
• Not always clear how to weight the
contribution of different data sources
4 - How to make Benefit transfer
more accurate
• There are four main strategies
• Increase the pool of non-market
valuation studies
• Increase the accuracy and
understanding of the conducted studies
• Develop better systematic BT case
studies
• Improve the use of BT tools and
databases
Increasing the pool of studies
• Very limited pool of studies available to
source BT values
– Limits the potential use of BT
– Means many BT applications involve substantial
differences in site and populations, which may
lead to inaccuracies
– Makes it difficult to identify patterns of values, and
identify source studies that may be outliers
Increasing the accuracy
• Currently there are high levels of
uncertainty around many non-market
valuation estimates
– Unclear how differences in framing and
methodology affect outcomes
– Unclear how variations in scope and scale
can affect value estimates
– Unclear how values are set when elements
of risk and uncertainty are present
Dealing with the ‘specific to general’
tradeoffs
• A benefit transfer application will
rarely satisfy ‘ideal’ conditions
– Identical site characteristics
– Identical population characteristics
– Identical policy and tradeoff situations
• Better to think of a BT application as
a filtering mechanism
– Identify if there are major differences
between benefits and costs, or
– Identify if more detailed analysis needs
to be applied.
More systematic approaches
• It is cost-effective to develop data-bases
of values rather than a large number of
ad-hoc valuations
• Critical that future attempts to develop
systematic databases address the issue
of adjustment factors
– Required to transfer general values to
specific situations with scale and scope
differences
Develop better BT tools and
databases
• Better development of BT guides
• More examples and applications of
meta studies and bayesian approaches
• More use of BT databases
– Environmental Valuation Reference
Inventory in Canada (http://www.evri.ca/)
– Older ENVALUE site in NSW
5 - Conclusions
• Benefit transfer applications likely to rise
– Increased demand for valuations coupled
with time and cost constraints
– Increased supply of source studies,
whether on an ‘ad hoc’ or systematic basis
• Caution is needed to make BT accurate
• Work needed to improve the potential
for BT in a number of key areas