Valuation 11: Benefit Transfer and Meta-Analysis Why benefit transfer? Different types of benefit transfer Value transfer Function transfer Validity and sources of error Examples

Last weeks we looked at Various methods to estimate the value of environmental goods and services not traded on markets Also, some empirical examples were shown It turned out that it is actually very hard to reliably estimate prices – one needs many assumptions, good data, and smart statistics, and even then all sorts of things may go wrong

What is benefit transfer? Benefit transfer uses economic information captured at one place and time to make inferences about the economic value of environmental goods and services at another place and time Benefit transfer involves economic values that may be either positive (benefits) or negative (costs) Study Site Policy Site $

Why benefit transfer? Valuation is hard As a result, applied valuation studies are expensive A small hedonic pricing study, for instance, costs about a year of a PhD student – that is, after the data have been collected and digitised Ditto for travel costs A contingent valuation study is more expensive Monetary values are also hard needed Wouldn't it, therefore, be nice if we could take the estimated values of case 1 and apply them to case 2?

History Environmental benefit transfer came into being only once the non-market literature itself grew large enough to allow comprehensive synthesis and cross-study comparison In 1973, the U.S. Water Resources Council began publishing unit day estimates for recreation activities relates to water projects In 1980, the U.S. Forest Service began publishing Resources Planning Act values for recreation (per person per day) First synthesis study mid to late 1980s Today, applied to issues involving values for recreation, water quality, fishing, air quality, wetlands, biodiversity

Types of BT Value Transfer Function Transfer Single point transfer Measure of central tendency Single point transfer adm. approved Benefit/ Demand Function Meta-Analysis Function Adapt function to policy site Use estimate at policy site Use tailored estimate at policy site

The basis for any benefit transfer analysis The basis is a formal literature review The original research studies are screened for relevance how well they correspond to the policy context the quality of research what kind of information is provided Advantages include a much larger sample of data, different analytical techniques, and different analysts The main disadvantage is that one typically only has access to published results, which are always incomplete

Value transfer: Point estimates Point estimate transfer typically uses a single measure Example: The U.S. Army Corps of Engineers was considering the removal of four dams on the Lower Snake River from its confluence with the Columbia River One of the benefits would be the restoration of spawning habitat for native salmon populations (by about 47,500 fish) The agency was interested in the passive use value based on per household annual WTP The literature search found four studies that provided values for salmon population

Other value transfer The measure of central tendency entails using a mean, median or other measures of central tendency based on all or a subset of original research outcomes Same example as above; great disparity between average marginal passive use value ($40,620) and median value ($3,197) Administratively approved estimate transfer is the simplest approach Estimates are derived from empirical evidence in the literature, expert judgment, and political screening Problems: Criteria for political screening are unknown, selection might be biased and only updated every so often

Function transfer Value transfer requires a strong similarity between the study site and the policy site is required Function transfers are generally considered to perform better than value transfers Unlike value transfers, they may be tailored to fit some of the characteristics of the policy site Function transfers entails the application of a statistical function that relates the summary statistics of original research to the specifics of the study site There are two types of function transfers Demand/Benefit function transfer Meta-regression analysis

Demand/benefit function transfer For benefit function transfer additional information is required We need a function that models the statistical relationship between the summary measures of interest and characteristics of the original site This function is then adjusted to specific characteristics of the policy site

Example Case study by VandenBerg, Poe and Powell (2001) estimates the benefits of improving groundwater quality used for drinking to a very safe level in 12 towns in New York, Massachusetts, and Pennsylvania The authors use a contingent valuation survey with a payment card question format To perform the benefit function transfer all of the survey data except for one town are pooled and a WTP equation is estimated

OLS regression, dependent variable is mean WTP/HH/year, n=667

Validity of benefit transfer A number of studies performed the following test: Estimate the value of something at two sites, and predict the value of the one site from the observations of the other Resources or activities include Sport fishing (distance, harvest, quality) Recreation (costs, size, substitutes, population, age) Rafting (flow, costs, intensity, reason for visit, home, income, sex, age, education) Water quality (costs, size, depth, accessibility, quality, use, income) Water quality (bid, use, education, age, user)

Sources of error Generalisation error Measurement error When estimates from study sites are adapted to represent different policy sites The error is inversely related to the degree of correspondence between the sites Measurement error Occurs when researcher’s decision affect the accuracy of the transferability of values Methodological choices, non-reporting of study characteristics Publication selection error There is a preference for publishing statistically significant results that conform theoretical expectations Authorship effect

Meta-regression analysis A drawback of the demand function transfer is the assumption that the statistical relationship between the dependent and independent variables are the same for both study as well as policy site Also, demand function transfer relies mostly on a single study Meta-regression analysis summarises and syntheses outcomes from several studies Meta-analysis not only provides a rigorous synthesis of the literature, it is also able to explain the variation found across empirical studies and to identify outlier studies, knowledge gaps, and priors for further analysis Meta-analysis is a technique that originates in medical science

Meta-regression analysis (2) Some of the variation in value estimates may be due to identifiable characteristics among the different studies themselves valuation method, survey mode, geographic location, time etc. These characteristics are not explanatory variables in the original studies as they are constant Advantage of the method: it does not prejudge research findings on the basis of the original study‘s quality (input) , while it avoids a differential subjective weighting of studies in the interpretation of findings (output side) However, the publication selection error still applies

Example: Meta-regression analysis Brouwer, Langford, Bateman and Turner (1999) is one of the early applications of meta-regression analysis Analysis covers 30 studies of the WTP per person for wetland preservation in temperate climate zones in developed economies in North America and Europe In total, 103 data points as some studies reported more than one observation (split sample) Wetlands were made comparable by looking at their types and functions: flood control, water supply, water purification, and nature/recreation Each observation was associated with one or more functions

Wetlands/Brouwer Additional explanatory variables included payment vehicle (tax or other) elicitation format (open-ended or other) value type (use value, non-use value or both) country (USA or Canada, Europe) Quality was measured by response rate, but as an explanatory variable All studies are CVM studies In the regression analysis wetland size and income were excluded due to data availability

Regression results Parameter Estimate Standard error GLS model specification Parameter Estimate Standard error Payment vehicle (tax) 1.576*** 0.362 Elicitation (open-ended) -0.376* 0.183 Country (North America) 1.629*** 0.363 Response rate 30-50% -1.722*** 0.451 Response rate >50% -1.461** 0.450 Flood control 1.134* 0.456 Water supply 0.441 0.479 Purification 0.659* 0.327 *** significant at 0.001; ** significant at 0.01; * significant at 0.05; R2 0.38

Wetlands/Brouwer (2) On average, people are willing to pay $93/person/year for wetland preservation Note that the median is only $51 Taxes attract higher contributions Open ended questions lead to smaller answers North Americans are willing to pay more Higher response rates imply lower values Less differences between functionality of wetlands

Conclusion Benefit transfer can perform no better than the quality of original studies The underlying questions of accuracy and appropriateness of non-market methods are not solved in benefit transfer However, some type of benefit estimates are subject to less controversy Benefit transfers are defensible as long as they are based on organised research agenda and seek to expand knowledge There‘s a great deal of pragmatism in policy-decision making – not all decisions require the same level of accuracy