measuring the economic benefits of water quality ......department of economics, appalachian state...

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American Fisheries Society Symposium X:xxx–xxx, 2005© 2005 by the American Fisheries Society

Measuring the Economic Benefits of Water QualityImprovement with Benefit Transfer: An Introduction for

Noneconomists

CHRISTOPHER F. DUMAS, PETER W. SCHUHMANN

Department of Economics and Finance, University of North Carolina at WilmingtonWilmington, North Carolina 28403-5945, USA

JOHN C. WHITEHEAD*

Department of Economics, Appalachian State University, Boone, North Carolina 28608-2051, USA

Abstract.—In this paper, we provide an introduction to water quality benefit estimation fornoneconomists. Net water quality benefits are typically measured using the concept of consumersurplus, which is estimated using a number of economic valuation methodologies. These are dividedinto direct and indirect methods. Direct methods involve questioning survey respondents to deter-mine their consumer surplus. Indirect methods use data from consumer market behavior to estimateeconomic values. When limited time or funding preclude costly data collection and the developmentof new consumer surplus estimates, the method of benefit transfer is used to tailor preexistingconsumer surplus estimates to fit new policy situations. We provide an example of benefit transfer byestimating the value of water quality improvements for the Cape Fear River in North Carolina.Benefit transfer methods are used with three valuation approaches to estimate the benefits of waterquality improvement.

* Corresponding author: [email protected]

Introduction

Urbanization has negative impacts on river and streamwater quality and associated economic benefits. Thischapter will describe categories of water quality ben-efits, discuss the economic methodologies commonlyused to estimate the values of these benefits, explorethe relatively new techniques of benefit transfer usedto estimate benefits of a given water quality improve-ment using information from other locations or timeperiods, and apply benefit transfer techniques in acase study of the benefits of water quality improve-ment in the Cape Fear River basin, North Carolina.The discussion illustrates how economic methodolo-gies can be used to document the economic benefitsof maintaining water quality and associated ecologicalfunctions.

Water quality provides two broad classes of eco-nomic benefits, withdrawal benefits, and instreambenefits (Feenberg and Mills 1980). Withdrawal ben-efits include municipal water supply and domestic

use (e.g., household drinking, cooking, washing, andcleaning) benefits, agricultural irrigation and livestockwatering benefits, and industry process water ben-efits. If water quality is low, withdrawn water must betreated before it can be used, and the economic ben-efits (net of treatment costs) associated with its use arelower. Instream benefits (i.e., the benefits of waterquality arising from water left “in the stream” and notwithdrawn) include two subcategories: use benefitsand nonuse benefits. Instream use benefits includeswimming, boating, and sport-fishing benefits—ben-efits associated with direct human interaction withwater in the stream/river. Other instream use benefitsinclude the esthetic value of water quality that mayaccrue to nearby picnickers, streamside trail hikers, andstreamside property owners. Instream nonuse benefitsof water quality include stewardship value, altruisticvalue, bequest value, and existence value. Nonuse ben-efits accrue to individuals regardless of whether or notthey have direct interaction with water. Stewardshipvalue arises from a belief (often moral or religious) thathumans are responsible for maintaining some level of

2 DUMAS ET AL.

water quality even in cases where no withdrawal orinstream use benefits result. Altruistic value arises fromthe enjoyment some people receive from simply know-ing that other people enjoy withdrawal or instreamuse benefits. Bequest value arises from a belief thatcurrent human generations are responsible for main-taining some level of water quality to “bequest” tofuture human generations. Existence value arises fromthe enjoyment some people receive from simply know-ing that some level of environmental quality exists. Ifwater quality is allowed to deteriorate, then steward-ship, bequest, and existence goals may not be met,and associated benefits fall.

The impacts of urbanization on water qualitybenefits are mediated by aquatic ecosystems. Increasesin stream nutrient levels that lead to algae blooms canreduce swimming and boating benefits. Reductionsin dissolved oxygen that lead to fish kills can reducefishing and streamside property value benefits. In-creases in disease-causing bacteria due to urban andsuburban storm water runoff can increase water treat-ment costs and reduce swimming, fishing, and boat-ing benefits. Reductions in aquatic species populationsor diversity caused by stream sedimentation or toxicchemical discharges can reduce stewardship, altruistic,bequest, and existence values. Economic valuationmethodologies typically trace changes in water qualityvariables through changes in aquatic ecosystem pa-rameters to changes in economic benefits. Often, it is achange in an aquatic ecosystem parameter, such as afish population, algae population, or disease-causingbacteria population, that is the ultimate cause of achange in economic benefits.

The economic valuation methodologies vary de-pending on the category of water quality benefit. Ap-propriate methodologies are used to estimate thebenefits arising from each category, and the resultingbenefits are then added to arrive at a measure of theoverall value of water quality. Market prices can beused together with traditional economic valuation andbenefit cost analysis methodologies to derive estimatesof most withdrawal benefits. However, many instreambenefits lack direct market prices and have public goodcharacteristics that make benefit estimation using tra-ditional economic methodologies difficult. Specifically,many instream benefits exhibit the public good char-acteristics of nonrivalry and nonexcludability. Nonrivalrymeans that more than one consumer can enjoy thequality of a given body of water at the same time(whether or not this enjoyment is associated with di-rect use). Nonexcludability means that it is difficult(costly) to prevent one individual from enjoying the

benefits created by another individual’s actions. If in-dividuals cannot be excluded, then they will not payprices to gain the benefits (instead, they will “free ride”),and therefore, price data will not be available.

This paper will focus on the estimation of theinstream benefits of water quality changes because thesetypes of benefits are more difficult to estimate andthey are most pertinent to the theme of this book.Instream benefits are typically estimated usingnonmarket valuation methodologies. Nonmarket tech-niques have been developed to estimate economic val-ues in situations where direct market prices are lackingand where public good characteristics are significant.Nonmarket valuation methodologies include direct orstated preference and indirect or revealed preferenceapproaches. The contingent valuation, contingentbehavior, and conjoint/choice analysis methods areexamples of direct approaches. The travel cost, avert-ing behavior, and hedonic price methods are indirectapproaches. Each of these methods requires primarydata collection. When the cost of primary data collec-tion is prohibitive and/or time is short, the benefittransfer approach can be used to develop economicbenefit estimates.

With benefit transfer, benefit estimates from ex-isting direct or indirect valuation case studies are spa-tially and/or temporally transferred to a new case study.There are four types of benefit transfer approaches:benefit estimate transfer, benefit function transfer,meta-analysis, and preference calibration. Benefit esti-mate transfer uses summary measures of the environ-mental benefit estimates directly. Researchers simplyobtain a benefit estimate from a similar study con-ducted elsewhere and use it for the current policyanalysis case study. With benefit function and meta-analysis transfer, researchers use statistical models totransfer benefits. Characteristics of the current policysituation or case study (e.g., population demograph-ics, site characteristics) are substituted into a statisticalmodel to translate benefit estimates more accurately.Preference calibration uses an analytical model to rec-oncile existing benefit estimates derived from differ-ent methodological approaches and develop consistentbenefit estimates for the new policy study.

The remainder of this paper is organized as fol-lows. In the second section of the paper, we presentthe economic theory and some definitions used inbenefit–cost analysis and describe the water qualityvaluation methodologies. In the third section, we dis-cuss the benefit transfer approach to estimating waterquality benefits. In the fourth section, we present acase study: water quality improvement in the Cape

3MEASURING THE ECONOMIC BENEFITS OF WATER QUALITY IMPROVEMENT WITH BENEFIT TRANSFER

Fear River. In this example, benefit transfer methodsare used with three valuation approaches to estimatethe benefits of water quality improvement. The fifthsection is a summary of our findings.

Economic Theory

Whenever a government project or policy is imple-mented, there are economic winners and losers. Theeconomic efficiency criterion requires that the gains tothe winners exceed the losses imposed on the losers.Economic efficiency is one of several criteria (othersinclude equity and risk) used to assess the desirabilityof government projects, such as water quality improve-ment projects. Benefit–cost analysis is a method usedto calculate and compare monetary gains and losses forthe purpose of assessing efficiency (Boardman et al.2001). When government pursues a water qualityimprovement policy, such as the regulation of pollut-ing firms or the implementation of urban land usecontrols (e.g., zoning), gains and losses are distributedto consumers and firms. Losses are typically relativelystraightforward to measure by considering reductionsin firm profits and increases in consumer costs. How-ever, gains are often more difficult to measure, espe-cially when they come in the form of public goodssuch as water quality.

The concept of consumer surplus is the basis formeasuring net economic benefits. Considering a mar-ket good, for example a car, the consumer surplus isthe difference between what the consumer is willing(and able) to pay and the market price (amount actu-ally spent) for the car. Consumer surplus is also callednet willingness to pay (net WTP) since it is willingnessto pay net of the costs. The consumer may be willingand able to pay the manufacturer’s suggested retailprice of $35,000 for a new Ford Mustang. However,if the agreed-upon price is $31,000 then the con-sumer surplus is $4,000—the difference between theconsumer’s maximum willingness to pay and the mar-ket price.

Nonmarket goods such as water quality also pro-vide consumer surplus (Freeman 1993). In the con-text of water quality valuation, suppose a catch-and-release freshwater angler is willing and able to payup to $125 for a good day of urban fishing. If the costof the day trip is $25, then his consumer surplus is$125 – $25 = $100. Now suppose that a zoning lawis enacted that leads to a water quality improvementthat, in turn, increases the angler’s expected catch pertrip. With the increase in expected catch, the angler’swillingness to pay might increase to, say, $160. If so,

the angler’s consumer surplus per trip after the waterquality improvement is $160 – $25 = $135. Theangler’s economic gain from the water quality improve-ment is the change is his or her consumer surplus, or$135 – $100 = $35. The empirical challenge, ofcourse, is to determine the angler’s willingness to payand consumer surplus before and after the water qual-ity change.

Economics students may remember the graphi-cal depiction of demand and consumer surplus (Fig-ure 1). The demand curve (denoted D

1) is a downward

sloping line with market price on the vertical axis andquantity purchased/consumed on the horizontal axis.The demand curve slopes downward due to the factthat lower prices are required to convince consumersto purchase larger quantities. Typically, the position ofthe demand curve is estimated using data on marketprices and quantities purchased by the consumer. Therectangle below the current market price is the initialexpenditure on the good (i.e., the product of price perunit and quantity of units purchased, noted as EXP inFigure 1). Changes in consumer surplus and notchanges in expenditures (DEXP) should be used inbenefit–cost analysis (Edwards 1991). In Figure 1,consumer surplus (CS) is the triangular area above thecurrent market price and below the demand curve.The area of the consumer surplus triangle increases ordecreases with changes in demand (i.e., with shifts inthe position of the demand curve). Changes in con-sumer income, prices of related goods, consumer tastes,or most importantly for the present discussion, thequality of the good can cause shifts in demand. Forexample, an improvement in quality would increasedemand, shifting it to the right (from D

1 to D

2 as

shown in Figure 1). When the demand curve shifts tothe right the associated consumer surplus area increases(DCS). This change in consumer surplus is the changein net economic benefits from the quality improve-ment. In practice, changes in consumer surplus havebeen found to be good approximations of more theo-retically correct measures of economic benefit (Willig1976; Randall and Stoll 1980). See Johansson (1987)for additional detail on the theory of environmentalvaluation.

Estimation of consumer surplus is relativelystraightforward if market data exist. Typically, the de-mand curve equation is estimated statistically usingdata on market prices, quantities purchased by con-sumers, and other related variables such as consumerincomes and prices of related goods. Without marketdata, a number of methodologies have been devel-oped to estimate consumer surplus. Consumer sur-

4 DUMAS ET AL.

plus for nonmarket goods such as water quality im-provements can arise from two sources: use value andnonuse value. Both use and nonuse values can be esti-mated using direct and indirect methodologies, al-though the latter are typically better suited for theestimation of use values, while the former are bettersuited for estimating nonuse values.

Indirect “Revealed Preference” Methods

The travel cost method (Bockstael 1995) is a revealedpreference method that is most often used to estimatethe benefits of outdoor recreation (e.g., improved fish-ing opportunities following water quality improve-ment). The travel cost method begins with the insightthat the major cost of outdoor recreation is the traveland time costs incurred to get to the recreation site.Since individuals reside at varying distances from therecreation site, the variation in distance and the num-ber of trips taken are used to trace out a demand curvefor the recreation site. The demand curve is then usedto derive the consumer surplus associated with usingthe site. With data on appropriate demand curve shiftvariables (i.e., independent variables such as measuresof water quality), the economic benefits (i.e., changesin consumer surplus) associated with changes in the

shift variables (i.e., changes in water quality) can bederived.

A variation of the travel cost method is the ran-dom utility model (RUM) (e.g., Bockstael et al. 1989).Unlike the traditional travel cost model which focuseson one recreation site, a RUM uses information frommultiple recreation sites. Individuals choose a recre-ation site based on differences in trip costs and sitecharacteristics (e.g., water quality) between the alter-native sites. Statistical analysis of the relationship be-tween site characteristics and recreationists’ site choicesenables estimation of any consumer surplus changesarising from any changes in site characteristics, such aswater quality.

The averting behavior method (Smith 1991)begins with the recognition that individuals seek toprotect themselves when faced with environmentalrisk such as contaminated drinking water. Defensivebehavior requires expenditures that would not nor-mally be made. For example, purchases of bottled wateror water filters may increase when the risk of contami-nated drinking water increases. These increases in ex-penditures represent a lower bound on the economicbenefits of policy that reduces drinking water risk.

The hedonic price method (Palmquist 1991; Free-man 1993) exploits the relationship between charac-

Quantity

Market price($)

EXP

CS

D2 D1

CS

EXP

Current marketprice

Initial quantity

purchased

Quantity purchased

after quality improvement

FIGURE 1. Relations among demand (D), consumer surplus (CS), and expenditure (EXP).


teristics of land and labor markets, including waterquality, and housing prices and wages. For example,land parcels in close proximity to water bodies withhigh quality water command higher prices than par-cels adjacent to water with lower quality. Job marketswith greater environmental amenities (such as highquality water) are associated with lower wages relativeto other job markets because individuals are willing toaccept lower wages in order to gain greater amenities.Housing and labor market differences can thereforebe used to trace out the demand for water quality andused to measure economic benefits.

The travel cost, averting behavior, and hedonicmethods are considered indirect valuation methodsbecause they estimate the benefits of water qualityimprovement (or other nonmarket goods) throughan examination of demands for related goods such asrecreational trips and housing. The major strength ofindirect approaches is that they are based on datareflecting actual market choices, where individualsbear the actual costs and benefits of their actions.However, indirect methods are generally only suit-able for the estimation of use value, as nonuse valuemay not be reflected in market choices and behavior.The major weakness of indirect approaches is theirreliance on historical data. Policies often are beyondthe range of historical experience. For example, fewresidents of an urban area located near a long-de-graded stream may have experienced a fishable stream.Without variation in the historical water quality data,it is difficult to predict how an improvement in wa-ter quality would shift the residents’ demand curveand change their consumer surplus. Analysis of theeconomic benefits of water quality policy is oftendifficult when indirect valuation methods are usedexclusively.

Direct “Stated Preference” Methods

The contingent valuation method (Mitchell and Carson1989; Bateman and Willis 1999) is a stated preferenceapproach that directly elicits willingness (and ability) topay statements from survey respondents. In other words,respondents are directly asked about their willingnessto pay (i.e., change in consumer surplus) for environ-mental improvement or willingness to accept (i.e.,amount of monetary compensation required to allow)environmental degradation.

The method involves the development of a hy-pothetical market via in-person, telephone, mail, orother types of surveys. In the hypothetical marketrespondents are informed about the current prob-

lem and the policy designed to mitigate the prob-lem. The state of the environment before and afterthe policy is described. Other contextual details aboutthe policy are provided such as the policy implemen-tation rule (e.g., majority voting) and the paymentvehicle (e.g., increased taxes or utility bills). Finally, ahypothetical question is presented that asks respon-dents to choose between improved water quality withincreased costs or the status quo. The choice is oftenframed as a referendum vote in order to make thesituation more realistic. Respondents can be presentedwith multiple scenarios and make multiple choices.Statistical analysis of these data leads to the develop-ment of willingness to pay and consumer surplusestimates.

The contingent behavior approach is similar tothe contingent valuation method in that it involveshypothetical questions. In contrast, the questions in-volve changes in hypothetical behavior instead ofhypothetical changes in willingness to pay. For ex-ample, respondents can be asked about hypotheticalrecreation trips with and without water quality im-provements (Whitehead et al. 2000). Conjoint analy-sis is a type of contingent behavior approach thatasks about hypothetical recreation site choice andother discrete choices (Louviere 1988; Adamowiczet al. 1999). Again, respondents can be presentedwith multiple scenarios and make multiple choices.Contingent behavior and conjoint analysis responsesare treated as behavioral data and are analyzed usingthe same statistical methods as are used in the indi-rect approaches.

A strength of the direct or stated preference ap-proaches is their flexibility. Water quality policies areoften new policies with no historical precedent. Ab-sent a natural policy experiment, the historical (i.e.,revealed preference) data does not contain observa-tions related to the policy. Direct approaches can beused to construct realistic policy scenarios for any newpolicy. Oftentimes, hypothetical choices are the onlyway to gain policy relevant nonmarket benefit infor-mation. Another strength of the direct approaches,especially contingent valuation, is the ability to mea-sure nonuse values, such as the value of improvingaquatic ecosystems. The major weakness of the directapproaches is their hypothetical nature. Respondentsare placed in unfamiliar situations in which completeinformation may not be available. At best, respon-dents give truthful answers that are limited only bytheir unfamiliarity. At worst, respondents give uncon-sidered answers due to the hypothetical nature of thescenario.

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Benefit Transfer

The benefit transfer approach to environmental valu-ation was developed for situations in which the timeand/or money costs of primary data collection fororiginal direct and indirect studies are prohibitive.With benefit transfer, environmental benefit estimatesfrom existing case studies (i.e., the study sites) arespatially and/or temporally transferred to a new,policy case study (i.e., the policy site). The more com-mon type of benefit transfer is the spatial transfer,where consumer surplus from the study site is trans-ferred to the policy site at the same point in time.Less common is the temporal transfer in which con-sumer surplus from one time period is transferred toanother time period.

Benefit transfer has been widely used to informpolicy analysis since the 1950s (Smith 1992; Bergstromand DeCivita 1999). Yet, it was not until a 1992special issue of Water Resources Research that attentionwas focused on the theory and practice of benefit trans-fer (Brookshire and Neil 1992). Research focusing onbenefit transfer has rapidly increased since the specialissue. Four benefit transfer methodologies haveemerged: benefit estimate transfer, benefit functiontransfer, meta-analysis transfer, and most recently, pref-erence calibration transfer. Each of these transfer meth-odologies can be used to transfer benefit estimatesobtained from a variety of benefit estimation method-ologies, such as travel cost, contingent valuation, andhedonic valuation.

Brouwer (2000) proposes some necessary condi-tions for a valid benefit transfer. First, consumer sur-plus from the study site must be theoretically andmethodologically valid. Second, the populations inthe study and policy sites must be similar. Third, thedifference between prepolicy and postpolicy quality(or quantity) levels must be similar across study andpolicy sites. Fourth, the study and policy sites must besimilar in terms of environmental characteristics. Fifth,the distribution of property rights and other institu-tions must be similar across sites. Accuracy of benefittransfer will suffer if any of these conditions is vio-lated. Yet, as will be shown below, the degree to whichaccuracy is impacted depends greatly upon the mea-sures used and the assumptions made.

Benefit Estimate and Function Transfer

Benefit function transfer should be distinguished frombenefit estimate transfer. Benefit estimate transfer usesenvironmental benefit estimates developed for a study

site at the policy site. Researchers simply obtain abenefit estimate from a similar study conducted else-where and use it for the current policy analysis casestudy (e.g., Luken et al. 1992). In contrast, benefitfunction transfer uses a statistical model of benefitsdeveloped at the study site to estimate benefits at thepolicy site (e.g., Desvousges et al. 1992). Character-istics from the policy site are substituted into themodel from the study site to tailor benefit estimatesfor the policy site.

Loomis (1992) argues that benefit function trans-fer can be more powerful than benefit estimate trans-fer in situations where demographic or environmentalquality factors (for example) at the study site differfrom those at the policy site. However, empirical re-sults concerning the superiority of benefit functiontransfer are mixed. In a study of Wisconsin lake recre-ation, Parsons and Kealy (1994) find that benefit func-tion transfer estimates are within 4% of the originalmodel estimates, while benefit estimate transfers arewithin 34%. Brouwer and Spaninks (1999) also findthat benefit function transfer is more accurate (within22%) than benefit estimate transfer. Loomis (1992)finds that recreational fishing benefits developed us-ing the travel cost method transfer from one state toanother with between 5% and 15% accuracy. Loomiset al. (1995) find that per capita reservoir recreationbenefit estimates from a travel cost model transfer ac-curately across sites.

In contrast, Barton (2002) finds that benefit es-timate transfer, with transfer errors of 20% and 30%,outperforms benefit function transfer in the case ofwater quality improvements in Costa Rica. In a studyof marine recreational fishing using the contingentvaluation method, Downing and Ozuna (1996) findthat few benefit functions transfer and, of those thatdo, few benefit estimates generated from the benefitfunctions transfer accurately. Similarly, in a study ofrecreation sites in Arizona and New Mexico using con-tingent valuation, Kirchhoff et al. (1997) find thatbetween 55% and 90% of the benefit function trans-fer estimates are not accurate.

Meta-Analysis Transfer

Meta-analysis is a general term for any methodologythat summarizes results from several studies. In thecase of environmental benefit transfer, benefit esti-mates gathered from several studies serve as the de-pendent variable in regression analysis, and character-istics of the individual studies (e.g., water quality, typeof survey methodology) serve as the independent vari-


ables. Benefit transfer using meta-analysis has threeadvantages over benefit function transfer (Shresthaand Loomis 2001). First, by employing a large num-ber of studies, benefit estimates will be more rigorous.Second, meta-analysis may be used to control for dif-ferences in functional form and other methodologicaldifferences across studies (Smith and Kaoru 1990a).Third, differences between the study site and thepolicy site can be better controlled.

Several meta-analysis studies focus on one valua-tion method and one type of environmental com-modity. Smith and Kaoru (1990a, 1990b) conducteda meta-analysis of the benefit estimates derived fromtravel cost recreation demand models. Smith andHuang (1993, 1995) conducted a meta-analysis ofair quality benefits derived from hedonic propertyvalue models. These studies confirm that study meth-odology influences benefit transfer estimates. The au-thors recommend that meta-analysis be used as acomplement to other benefits transfer methods. Smithand Osborne (1996) conducted a meta-analysis of airvisibility benefits. They found that benefit estimatestend to conform to important economic principlesthat confirm their validity, but this conclusion is sub-ject to variation in research methods used in the stud-ies. Loomis and White (1996) conducted a meta-analysis of studies of rare and endangered species. Theirmodel is able to explain more than 50% of the varia-tion in these values. They conclude that meta-analysisis a promising technique for benefit transfer.

Two meta-analysis studies compare alternativeenvironmental valuation methods for a single envi-ronmental commodity. Walsh et al. (1992) conducteda meta-analysis of outdoor recreation value estimatesfrom travel cost and contingent valuation studies.Woodward and Wui (2001) conducted a meta-analy-sis of studies of wetland values using travel cost, con-tingent valuation and other methods. Both studiesconclude that the contingent valuation method tendsto generate lower benefit estimates relative to othermethods. A similar result is found by Carson et al.(1996).

Rosenberger and Loomis (2000) compare na-tional and census region meta-analysis functions. Thenational and census region models produce benefitestimates that differ from those in the original studiesby 54% and 71%, respectively. Benefit transfers aremore accurate for activities with many existing studiesin the database, such as fishing, than for activitieswith only a few studies, such as skiing. Shrestha andLoomis (2001) use results from U.S. studies to fore-cast benefits for international policy sites. They find

that average prediction error is between 24% and 30%after adjusting for inflation and exchange rates.

Finally, Smith and Pattanayak (2002) provide areview of the meta-analysis literature. They argue thatfew existing meta-analyses should be used for benefittransfer due to inconsistent definitions of the benefitestimates (e.g., pooling estimates from contingent valu-ation and travel cost methods) and environmentalcommodities (e.g., value derived for use versus nonusevalues).

Preference Calibration Transfer

Smith et al. (2002) and Pattanayak et al. (in press) arguethat a new approach to benefit transfer, preference cali-bration, is needed because the majority of the evidenceappears to indicate that benefit function transfer is notaccurate. As with benefit function transfer, preferencecalibration exploits benefit estimates from other stud-ies. In contrast, preference calibration uses estimates frommultiple methods to develop a preference function con-sistent with economic theory. Importantly, preferencecalibration ensures that benefit estimates do not violatethe consumer’s ability to pay requirement when thescale of the environmental change is large. In otherwords, preference calibration ensures that consumerscan afford to pay the amounts indicated by the trans-ferred willingness to pay estimates.

Smith et al. (2002) used preference calibrationto estimate the benefits of improved water qualityusing contingent valuation, travel cost demand, andhedonic property value studies. They found thatconventional benefit estimate transfer understatebenefits by 83% for the travel cost studies and 3%for the hedonic property value studies. Conventionaltransfer overstate benefits by 64% for the contin-gent valuation study. Pattanayak et al. (in press) foundthat conventional benefit estimate transfer under-state water quality benefits by 66% for travel coststudies and 16% for contingent valuation studies.The contingent valuation method performs betterin the second study because it includes nonuse val-ues as well as use values.

An Assessment

Three preferred types of benefit transfer are emerging:benefit function transfer, meta-analysis transfer, andpreference calibration. Meta-analysis transfer has sev-eral advantages over benefit function transfer. A majoradvantage is that meta-analysis is able to control fordifferences in study methodologies. However, meta-

8 DUMAS ET AL.

analysis suffers from (1) reporting errors and omis-sions in the original studies, (2) inconsistent defini-tions of environmental commodities and values, and(3) large random errors. In addition, the developmentof a meta-analysis function is costly in terms of timeand money relative to benefit function transfer due tothe larger number of studies required.

Preference calibration has been proposed as a so-lution to the problems associated with benefit func-tion transfer and meta-analysis transfer. A major benefitof preference calibration is its recognition that willing-ness to pay is constrained by income in situations in-volving large changes in policy variables. However,there are several problems with preference calibration.Preference calibration does not tailor the benefit esti-mates to the demographics and other characteristics ofthe policy site as does benefit function transfer andmeta-analysis transfer. Preference calibration is moretime consuming than benefits function transfer dueto the increased analytical burden. Also, preferencecalibration has yet to be vetted by tests of transferaccuracy.

Numerous and restrictive conditions are neces-sary for the successful application of each of the threeemerging benefit transfer methods. It is not surprisingthat many studies evaluating benefit transfer methodsreject transfer accuracy. In other words, the differencesbetween benefits from a primary study and transferredbenefits are statistically significant. Nonetheless, thebenefits from a primary study and transferred benefitsare typically of the same order of magnitude and dif-ferences are typically much less than 100%. Whenprimary data collection is not feasible, there are nocurrent alternatives to benefit transfer. The practice ofbenefit transfer is sure to continue.

Policy Study: Cape Fear River

In this section, we use benefit transfer methods toestimate the benefits of hypothetical water qualityimprovement policies for residents of an urban area.Although it would be an interesting methodologicalexercise to estimate the benefits of a water quality im-provement for the same policy using alternative benefittransfer methods to test their validity, the purpose ofthis paper is to illustrate the empirical use of existingmethods. Given the limited scope of this study, we donot employ the time-intensive meta-analysis or prefer-ence calibration approaches to benefit transfer. Instead,we apply the benefit estimate and benefit functiontransfer approaches using the travel cost, hedonic price,and contingent valuation methods of estimating will-

ingness to pay and consumer surplus. The analysisillustrates how the benefit transfer approaches are usedin combination with the valuation methods to obtainbenefit estimates.

The case study site is the portion of the lowerCape Fear River that flows through New HanoverCounty, located in the southeastern corner of NorthCarolina (Figure 2). The Cape Fear River basin is thelargest river basin in North Carolina (North CarolinaDepartment of Environment and Natural Resources2000). It originates near Greensboro and flows eastpast the Chapel Hill-Durham area and southeast toWilmington (population = 75,838) in New HanoverCounty (population = 165,712) where it drains intothe Atlantic Ocean. The Cape Fear River basin is com-prised of the Haw, Deep, upper Cape Fear, Black,northeast Cape Fear, and lower Cape Fear watersheds.

The Cape Fear River is subject to point-sourcewater pollution from industrial and municipal wastetreatment facilities and nonpoint source pollution fromagricultural runoff, storm water runoff from urbanand suburban areas, and sediment from newly urban-izing areas. As of 1999, there were 280 point-sourcesof wastewater in the Cape Fear River basin permittedunder the National Pollutant Discharge EliminationSystem (NPDES), with a total permitted flow of 1.34million m3/d (353 million gallons/d, MGD) (NorthCarolina Department of Environment and NaturalResources 2000). Of these, 58 were major sources,each emitting more than 3,700 m3/d (1 MGD). Thelower Cape Fear contains more than 50% of the agri-cultural hog production operations in North Caro-lina. Nutrients from treated hog waste sprayed ontofield crops as fertilizer flow into tributary waters dur-ing high rainfall events. Although one-half of the landarea is forested, the Cape Fear River basin is a rapidlyurbanizing area. For example, Wilmington experiencedsignificant economic growth during the 1990s, itspopulation increasing by 29.4%. Land clearing andconstruction activities associated with developmentincrease the sediment load in the river. As of 1999,623 general stormwater permits (typically construc-tion projects affecting two or more hectares) and forty-eight individual (large municipal and industrial)stormwater permits were issued within the basin un-der the stormwater program of the 1990 Clean WaterAct.

Multiparameter water quality sampling for theCape Fear River has been conducted by the LowerCape Fear River Program (LCFRP) since June 1995(Mallin et al. 2002). The LCFRP currently encom-passes 35 water sampling stations throughout the Cape


FIGURE 2. The Cape Fear River basin, North Carolina, showing Lower Cape Fear River Program water quality samplingstation locations (Lower Cape Fear River Program 2003).

10 DUMAS ET AL.

Fear, Black, and northeast Cape Fear River watersheds.The LCFRP sampling program includes physical,chemical, and biological water quality measure- ments,analyses of the benthic and epibenthic macroinver-tebrate assemblages, and assessment of the fish assem-blages.

The main-stem lower Cape Fear River is charac-terized by somewhat turbid water containing highlevels of inorganic nutrients. It is fed by two largeblackwater rivers (the Black and northeast Cape Fearrivers) that have low levels of turbidity, but darklycolored water (due to naturally occurring tannins),with less inorganic nutrient content than the mainstem. While nutrients are reasonably high in the riverchannels, algal blooms are rare because light is attenu-ated by water color or turbidity and flushing is high.Periodic algal blooms are seen in the tributary streamstations, some of which are impacted by point sourcedischarges. Below some point sources, nutrient load-ing can be high and fecal coliform contamination oc-curs. Other stream stations drain blackwater swampsor agricultural areas, some of which periodically showelevated pollutant loads or effects.

During the 2001–2002 sampling period, a pro-longed drought had a significant positive effect uponwater quality. As a result of the drought conditions, aconsiderably lower number of stations were impairedby fecal coliform contamination than in the past sev-eral years. The impaired locations were a mixture ofareas impacted by point and nonpoint source inputs.Against this background, we estimate the benefits ofwater quality improvement with the benefit transferapproach.

Benefit Estimate Transfer:Travel Cost Method

To illustrate a temporal benefit estimate transfer us-ing the travel cost method of valuation, we applyestimates of the benefits of ambient water qualityimprovements in river basins and watersheds inNorth Carolina from Phaneuf (2002). Phaneuf(2002) used data from the Environmental Protec-tion Agency’s (EPA) national water-based recreationalsurvey, which are combined with chemical measuresof water quality. The random utility model (RUM)version of the travel cost method is employed to modelbehavioral responses to changes in water quality inorder to aid in the design and implementation oftotal maximum daily load (TMDL) policies in NorthCarolina. As noted above, given that travel costs serveas an implicit price of a recreation visit, changes in

recreational site choices in response to changes in waterquality can be used to estimate the use value of waterquality improvements.

Phaneuf (2002) estimated the benefits of fourpotential changes: the loss of individual watershedsfrom recreation use, water quality improvements inindividual watersheds, water quality improvementsacross an entire river basin, and reductions in ammo-nia and phosphorous. The specific water quality im-provement for the second of these measures is definedas a reduction in pollution loadings such that a maxi-mum of 10% of monitoring station readings for pH,dissolved oxygen, phosphorous, and ammonia are outof compliance for the watershed and is most appli-cable for our purposes here—to illustrate benefits trans-fer for a specific watershed. In addition to quantifyingthe value of reductions in pollutant loadings usingindividual measures of the pollutants, Phaneuf (2002)also derived the willingness to pay for the same im-provements as measured by the EPA’s index of water-shed indicators (IWI) (U.S. Environmental ProtectionAgency 2002). This index is a scale of 1–6, with 1indicating the highest water quality.

For the watersheds in the Cape Fear River basin,willingness to pay per trip to maintain (i.e., to preventthe loss of ) existing recreation access is $0.29 for theupper Cape Fear River, $0.39 for the lower Cape FearRiver, and $0.80 for the northeast Cape Fear River(Phaneuf 2002). Further, the willingness to pay pertrip for the water quality improvement was found to be$0.10 for the upper and lower Cape Fear River and$0.24 for the northeast Cape Fear River. The meanwillingness to pay per trip estimates across all water-sheds in the state were $0.41 for access and $0.17 forthe improvement. The ranges of these estimates were$0.05 to $2.91 and $0.00 to $1.44.

Phaneuf (2002) found that the per trip willing-ness to pay for a reduction in pollution loadings suchthat a maximum of 10% of readings are out of criteriafor the entire Cape Fear River basin (as opposed to asingle watershed within the basin) are between $1.00and $6.29, depending on the specification of the sta-tistical model and which water quality data are used.The per trip willingness to pay value found using theIWI is $2.25 (Phaneuf 2002). In terms of the benefitstransfer, a lower bound on the aggregate benefits ofbasin-wide improvements over the entire season isapproximated by multiplying these per trip benefitsby the total number of freshwater angling days inNorth Carolina. The U.S. Fish and Wildlife Serviceestimated that 675,000 resident anglers fished 11.4million freshwater days in North Carolina in 2001


(U.S. Department of the Interior, Fish and WildlifeService and U.S. Department of Commerce, U.S. Cen-sus Bureau 2002). These estimates lead to an aggre-gate value of $31.8 million (2003 dollars) for thebasin-wide water quality improvements using the IWIestimate. Using the range of values estimated for the10% out-of-criteria improvements, this annual aggre-gate benefit measure is between $14.1 million and$88.9 million (2003 dollars).

We also obtain an aggregate estimate for NewHanover County by using data on North Carolinafreshwater angler-days and population estimates forthe state and county (New Hanover County containsapproximately 2% of the North Carolina population).Assuming that the proportion of anglers in the popu-lation is constant across counties, this amounts to13,500 resident anglers fishing 228,000 freshwaterdays in New Hanover County. These estimates lead toan aggregate value of $636,000 (2003 dollars) for thebasin-wide water quality improvements using the IWIestimate. Using the range of values estimated for the10% out-of-criteria improvements, the value to NewHanover County anglers is between approximately$283,000 and $1.86 million (2003 dollars).

Benefit Function Transfer:Hedonic Price Method

The existing hedonic studies of the value of waterquality typically use water clarity or fecal coliform as ameasure of water quality. We select fecal coliform, agroup of bacteria widely used as an indicator of thepresence of disease-producing bacteria, as our measureof water quality for the hedonic analysis. Water claritywould not be a good measure of water quality for theNew Hanover county area, as several tributaries of theCape Fear River are naturally low-visibility, low-clar-ity waters in their pristine states (due to naturally oc-curring tannins in the water). Fecal coliformmeasurements vary by an order of magnitude aboveand below the state health standard for human con-tact waters (200 CFU/100 mL) in the Lower CapeFear River. During the 2001–2002 monitoring pe-riod, the state standard was exceeded six times (NorthCarolina Department of Environment, Health, andNatural Resources 1996). (The standard is typicallyviolated more frequently; the 2001–2002 period hada relatively low number of violations due to low run-off conditions during a drought.)

For the benefit transfer application, we selectLeggett and Bockstael’s (2000) hedonic pricing studyof the effect of fecal coliform water pollution on Chesa-

peake Bay shoreside property values. In addition to itsfocus on fecal coliform pollution, Leggett and Bockstael(2000) utilized relatively recent data (late 1990s) andconsidered coastal estuarine properties in the mid-At-lantic region of the United States, properties similar tothose in our study region. We recalibrate the Leggettand Bockstael (2000) hedonic price model to NewHanover conditions. The recalibration accounts fordifferences in parcel area, distance to urban centers,and baseline fecal coliform levels between the Leggettand Bockstael (2000) study area and New HanoverCounty. The model is not recalibrated for differencesbetween the two study areas in neighborhood landuses or distances to point sources of water pollution.For these variables, we use the mean values fromLeggett and Bockstael (2000).

Land parcel and tax data for 2001 were providedby the New Hanover County Planning Department.Industrial, government, commercial and utility right-of-way parcels are excluded from the analysis. Theremaining 334 residential and residential/farm parcelsadjacent to the Cape Fear and northeast Cape Fearrivers in New Hanover County in 2001 occupy atotal of 3,554 ha. The mean land value per parcel(excluding the value of any structures) is approximately$121,000 for residential land use (n = 331) and$300,000 for residential/farm land use (n = 3). Fecalcoliform is measured at LCFRP water quality moni-toring field station NAV, just north (upstream) ofWilmington, North Carolina (see Figure 2). From1997–2002, monthly average fecal coliform readingsvaried from a minimum of 6 CFU/100 mL to a maxi-mum of 4,453 CFU/100 mL, depending on season,rainfall, and point source and nonpoint source pollu-tion discharges, with a geometric mean of 31 CFU/100 mL.

The policy scenario consists of a hypotheticalwater quality program that would prevent deteriora-tion of water quality from a baseline yearly medianfecal coliform count of 40 CFU/100 mL, a level ap-proximating current conditions, to the level of thestate health standard for human contact waters, 200CFU/100 mL. Using the Leggett and Bockstael(2000) model recalibrated for the Cape Fear region,we found that the 334 riverfront residential proper-ties in New Hanover County have an aggregate landvalue (excluding the value of any structures) of ap-proximately $42.4 million (2003 dollars) underbaseline water quality conditions of 40 CFU/100 mL.If water quality were allowed to deteriorate to the levelof the state health standard for human contact waters(200 CFU/100 mL), land value would fall to an esti-

12 DUMAS ET AL.

mated level of $39.1 million, a loss of $3.3 million.This is equivalent to a 7.7% decrease in land value.The maximum decrease in value for any single prop-erty is $510,000 (for a 538-ha parcel slated for subdi-vision), the minimum decrease is $12, the meandecrease is $9,800, and the median decrease is $4,400.

Benefit Function Transfer: ContingentValuation Method

The contingent valuation method literature containsa number of studies that estimate the economic valuesof river water quality. Several of these are focused onNorth Carolina river basins, but none focuses on theCape Fear River basin. A recent study estimated theeconomic value of water quality protection in theCatawba River basin (Kramer and Eisen-Hecht 2002).The Catawba River basin is similar to the Cape FearRiver basin in that it originates near an urban area,Charlotte, and flows southeast to the Atlantic coast. Itdiffers in that the Catawba River basin is dominatedby reservoirs and most of the basin is located in SouthCarolina. Nevertheless, we choose this as the study sitedue to its similarities to the policy site and the richnessof the statistical valuation function relative to otherNorth Carolina river basin valuation studies.

Kramer and Eisen-Hecht (2002) used a combi-nation of mail and telephone survey methods. Thesample is mailed an information booklet that describesa water quality management plan for the CatawbaRiver. The booklet includes maps that show the po-tential deterioration in water quality given currentpopulation and land use changes as predicted by awater quality model. The proposed management planwould focus on several water quality problems: sedi-ment, nutrients, toxic substances, bacteria, and viruses.The management plan would include the use of bestmanagement practices for construction and agricul-ture within the basin, develop a basin-wide land useplan, improve and increase the capacity of sewage treat-ment plants within the basin, and provide for thepurchase and protection of land that is important forthe protection of water quality.

Respondents were asked to vote for or against themanagement plan given that it would be financed bya specified increase in state income taxes over the fol-lowing 5 years. The specified increase in state incometaxes varied across survey respondents, ranging from$5 to $250 per year. Without further water qualityinformation, the contingent valuation method can-not be used to place a monetary value on a specificwater quality improvement (i.e., a change in pH or

fecal coliform units). The benefit estimate from thisapplication of the contingent valuation method is thewillingness to pay for protection of current water qualitywith the proposed water quality management plan.Additional information from the water quality modelthat was used to estimate the potential degradation inwater quality could be used to develop estimates forspecific improvements. However, this level of analysisis beyond the scope of this paper.

Kramer and Eisen-Hecht (2002) statistically ana-lyzed the survey data to develop a willingness to paymodel. The model includes a number of variables thatcan be used to examine the validity of the hypotheti-cal votes. For example, the probability of a vote for themanagement plan should fall as the tax amount in-creases and should rise with increases in respondentincome. Such results were obtained in this study andindicate that respondents responded rationally to thestated cost of the policy relative to their income levels.These results strongly suggest that the hypotheticalvotes reveal valid economic values for Catawba Riverwater quality.

Kramer and Eisen-Hecht (2002) estimated thatrespondent annual willingness to pay is $194 (1998$) for 5 years for the Catawba River. The CatawbaRiver willingness to pay model is calibrated for NewHanover County residents. Calibration involves sub-stitution of relevant values from the policy site (NewHanover County) for the values used in the study site(Catawba River basin).

There are no objective measures for New HanoverCounty residents for most variables in the willingnessto pay model. For these variables, we used the meanvalues from the Catawba River basin sample (Eisen-Hecht and Kramer 2002). These include study specificvariables, such as knowledge and attitudes about waterquality, and variables specific to the survey design. Thewillingness to pay also includes a variable for whetherthe respondent is from North Carolina or South Caro-lina. We set this variable equal to South Carolina, as-suming that downstream New Hanover Countyresidents are more similar to respondents in South Caro-lina than the upstream, urban North Carolina respon-dents. This choice has significant effects on willingnessto pay. The alternative assumption would decrease an-nual willingness to pay estimates by almost $62.

For the demographic variables measuring respon-dent age, education, sex, and household income, wedeveloped estimates of the mean values for NewHanover County residents 18 years or older usingU.S. Census Bureau data. We assume that respon-dents would rate the use of the river as important and


that drinking water is important. In order to differen-tiate between use and nonuse values, we alternativelyassumed that altruistic, bequest, and existence valuesare zero and positive. The means from the CatawbaRiver sample are used for all other variables.

Assuming that the willingness to pay functions forthe Catawba River and the Cape Fear River are similar,these estimates represent the willingness to pay of NewHanover County residents to maintain water qualitythrough a Cape Fear River basin-wide managementplan. The willingness to pay of New Hanover Countyhouseholds is $175 per person, per year, for 5 yearswhen nonuse values are equal to zero and $326 perperson, per year, for 5 years when nonuse values arepositive (2003 dollars). When nonuse value is consid-ered the residual between total value and use value, thisimplies that nonuse values are 46% of the total value.

Comparison of Methods

The benefits of water quality improvement in theLower Cape Fear River varied with method (Table 1).Willingness to pay estimates developed from the travelcost, hedonic price, and contingent valuation meth-ods are aggregated by the number of New HanoverCounty angler-days (n = 13,500), New HanoverCounty residential properties in vicinity of the CapeFear River (n = 334 properties), and New HanoverCounty households (n = 68,183), respectively. Theraw value estimates from the transfer studies are notdirectly comparable for two reasons. First, the esti-mates refer to different time periods: the contingent

valuation estimates are annual values for each of 5years, the travel cost estimates are annual values re-ceived each year in perpetuity, and the hedonic pricemethod estimate is a capitalized, present value. To makethe estimates comparable, we calculated the presentvalue of the annual amounts (using a 5-year time ho-rizon for the contingent valuation estimates and a 30time horizon for the travel cost method), and we an-nualized the hedonic price method estimate.

Second, each benefit transfer example focuses ona different policy context. The travel cost method will-ingness to pay estimate is appropriate for a policy thatleads to a reduction in pollution loadings such that amaximum of 10% of readings are out of criteria forthe entire Cape Fear River basin (as measured by a oneunit change in a water quality index). In contrast, thehedonic price method and contingent valuationmethod estimates are appropriate for a water qualitymanagement plan that protects the current level ofwater quality, though the two estimates are based ondifferent definitions of the current level of water qual-ity and different definitions of the water quality man-agement plan.

We used two discount rates for the present valuecalculations. The first discount rate, 2%, is a fre-quently used approximation of the real discount ratebased on market interest rates and is recommendedby the Congressional Budget Office (Hartman1990). The second and higher discount rate, 7%, isrequired for benefit–cost analysis by the U.S. Officeof Management and Budget (Office of Managementand Budget 1992). The higher rate is based on the

TABLE 1. Aggregate benefits for Lower Cape Fear River water quality (millions of 2003 dollars).

Annual Present valueUnad- Unad-

Method Aggregation Policy justed CBO1 OMB2 justed CBO1 OMB2

Travel 228,000 Avoidance of 10% of water quality $0.64 $14.33 $7.94cost angler- monitoring stations being out of

days complianceHedonic 334

price proper- Protection of water quality to avoid $0.15 $0.27 $3.30ties increase in fecal coliform from

current levelContin- 68,183 Protection of current water quality $22.20 $104.62 $91.01

gent house- with a water quality managementvalua- holds plantion

1 Value adjusted based on the Congressional Budget Office discount rate of 2%.2 Value adjusted based on the U.S. Office of Management and Budget discount rate of 7%.

14 DUMAS ET AL.

market rate of return of housing and corporate bor-rowing costs.

With discount rates of 2% and 7% the presentvalue of aggregate benefits for anglers using the travelcost method are $14 million and $8 million. The he-donic price method gives the present value (capitalizedvalue) of aggregate benefits for riverfront property own-ers directly; this value is $3.30 million. Using the he-donic price method estimate of $3.30 million anddiscount rates of 2% and 7%, the annualized value ofthe aggregate benefits for property owners are $0.15million per year and $0.27 million per year. Using thecontingent valuation method and discount rates of 2%and 7%, the present value of aggregate benefits (totalvalue including nonuse value) for all households in thecounty (not just riverfront) are $105 million and $91million.

This comparison illustrates the limitations of thealternative methods. The travel cost and hedonic pricemethods are applicable to particular populations andare not able to measure nonuse values. The contingentvaluation method can be used to estimate nonuse val-ues and is applicable to the entire population thatmight enjoy nonuse values. However, it is difficult todisentangle use and nonuse values from the total valueestimate with the contingent valuation method.

It is tempting to add the estimates from the threemethods to generate an estimate of the total benefit ofthe water quality improvement. However, this temp-tation is misguided for two reasons. First, the benefitestimates are for different policies as described above.Second, the total benefit estimate would be prone todouble counting of benefits. The travel cost methodprimarily estimates the water quality benefits that areenjoyed by those who participate in outdoor recre-ation. The hedonic price method estimates the ben-efits of water quality improvements that accrue toproperty owners. Since proximity to recreation sites isan incentive for property owners to purchase housingnear water, the benefits accruing to property ownersmight include recreation benefits. The contingent valu-ation method estimates the use values, including rec-reation benefits, for the general population. Addingthe benefits from the travel cost method, the hedonicprice method, and the contingent valuation methodmight include recreation benefits for three overlap-ping populations.

Summary

In this paper, we provide an accessible primer on theeconomics of water quality valuation. Consumer sur-

plus, the net benefits of a particular good, can be esti-mated using a number of valuation methodologies,including direct and indirect methods. These meth-ods typically require the collection of new data. Yet,policy analysis is often constrained by time and money.In these situations, benefit transfer methods can beused to develop estimates of consumer surplus forpolicy analysis. Benefit transfer involves therecalibration of existing consumer surplus estimates.Existing estimates are tailored to fit a new policy situ-ation. We provide an example of benefit transfer byestimating the value of water quality improvementsfor the Cape Fear River in North Carolina. Benefittransfer methods are used with three valuation ap-proaches (travel cost, hedonic pricing, and contingentvaluation) to estimate the benefits of water qualityimprovements.

The successful application of benefit transfermethods remains a challenge. Brouwer (2000) pro-vides some restrictive conditions for a successful ben-efit transfer. Many studies evaluating benefit transfermethods that adhere to most of Brouwer’s (2000)conditions reject the statistical accuracy of benefittransfer estimates. However, benefit transfer meth-ods typically obtain accuracy within an order of mag-nitude. The role of the benefit estimate in the policyprocess and the costs of a wrong decision are the twomajor issues that must be addressed when decidingwhether to use a benefit transfer method instead ofcollecting primary data (Bergstrom and DeCivita1999). Typically, benefit cost analysis is only oneinput into the policy decision process. When gov-ernment water quality policy decisions do not hingeon whether the present value of net benefits is posi-tive or negative, in other words, when the benefitcost analysis is advisory, the use of benefit transfer isa an acceptable approach to obtain order of magni-tude estimates of benefits.

When major government decisions are made,such as reauthorization of the Clean Water Act, thecosts of a wrong decision could be in the millions, oreven billions, of dollars. When determining whetherto conduct a study based on primary data, the cost ofthe study must be compared to the potential cost ofa wrong decision. For example, a benefit cost analysisthat uses benefit transfer to estimate benefits mayconclude that the present value of net benefits of apolicy is $2 million. Based on the criterion of effi-ciency, the policy analyst would recommend that thepolicy should be pursued. However, a benefit costanalysis that uses new, primary data to estimate ben-efits may conclude that the present value of net ben-


efits of the same policy is –$2 million. In this case,the policy analyst would recommend that the policyshould not be pursued. If the study based on new,primary data costs $500,000, then it is an invest-ment with a net gain of $1.5 million (i.e., the $0.5million study prevents a $2 million mistake). In thiscase, the study based on new, primary data are pre-ferred to benefit transfer. For most water quality poli-cies the costs of a wrong decision are much smaller. Inmany of these cases, the benefit transfer approachmay be preferred.

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measuring the economic benefits of water quality ......department of economics, appalachian state...

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