Benefit Transfer of Non-Market Values – Understanding the concepts John Rolfe Central Queensland University

Outline of this talk 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 =  +  1 Z 1 +  2 Z  nZn +  aS 1 +  bS  zSn Vih = *cost *Vegetation *waterways * people leaving * reserve *education *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

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

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

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 ( – 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