BENEFIT TRANSFERS: ARE THEY A SATISFACTORY INPUTTO BENEFIT COST ANALYSIS? AN AIRPORT NOISE

NUISANCE CASE STUDY

KIRK JOHNSON and KENNETH BUTTON*The Institute of Public Policy, 3C6, George Mason University, Fairfax, VA 22030-4444, U.S.A.

(Received 10 December 1996; accepted 30 March 1997)

AbstractÐBene®t cost analysis in a variety of guises has established itself as a useful tool in public policy-making. It is an approach widely adopted in appraising a wide range of infrastructure investments and hasbeen regularly used in legal proceedings. In the context of this study, it forms a common procedure forassisting in the assessment of the social bene®ts and costs of airport investment. It is not, however, a techni-que without its limitations. Beside a range of technical concerns, conducting a comprehensive bene®t costanalysis can be resource-intensive and time-consuming. Recently, there have been e�orts to make its appli-cation more e�cient by adopting bene®t transfer procedures. This involves making use of ®ndings from onestudy as inputs into other policy-making activities. While applying secondary data to a new policy issue has along pedigree, new areas of application involve taking non-market valuations of externalities from one studyand transferring them to a di�erent policy site. This paper looks at some of the limitations of employingbene®t transfers and uses noise nuisance aspect of airport investment policy appraisal as an illustrative case.Based upon a meta-regression assessment of hedonic price models, the ®ndings suggest that caution should beexercised in conduction bene®t transfers. # 1997 Elsevier Science Ltd

1. INTRODUCTION

Bene®t cost analysis, in one way or another, now forms the backbone for much of the analysis thatunderlies public policy-making. For example, U.S. federal requirements are that major regulatoryprograms must ``..not be undertaken unless the potential bene®ts...outweigh the potential costs...''(National Archives and Records Administration, 1985). The bene®t cost approach is not, however,without critics, and questioning ranges from such details as the legitimacy of attempting to placemonetary values on all items in the bene®t cost account to the intellectual validity of using partialequilibrium analysis in public policy-making (e.g. Hoehn and Randall, 1989).

The focus here is on the more detailed level of assessing the viability of a particular approach tobene®t cost analysis and particularly the increasing use made of bene®t transfers when conductingsuch analysis. Bene®t transfers involve deploying valuations based on primary data gathering in aspeci®c study to estimate changes in consumer's surplus with regard to another policy{. Theimplicit assumption in doing this is that parameters derived in one location, at one time and forone type of policy-making decision, can legitimately be employed in other decision-making exer-cises. This implies that either some common parameter is applicable to all studies or at least onecan explain variations between studies so that parameters taken from one exercise can adequatelybe modi®ed for use in a second exercise. If neither of these conditions hold, original independentanalyses may be required for each case study.

The issue is one of degree. No modeling exercise produces a completely accurate picture, andbene®t transfers are no exception. The practical point is whether bene®t transfers provide su�-ciently acceptable accuracy for the task at hand. Acceptance criteria are likely to di�er quite

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*Author for correspondence.{Bene®ts here may be viewed as either cost or bene®t items in a bene®t cost calculation, with a cost simply being a negative

bene®t. Much of the early analysis using the technique was in the water resources ®eld and involved transferring mone-tary values of such things as recreational bene®ts from one `study site' to another `policy site'. The term now often takesa wider meaning and many of the controversies surrounding its use apply to the general transfer of economic parameters.

considerable across a range of applications (Smith, 1992)*. The focus here is on one particulartype of transfer relating to the use of aircraft noise nuisance valuations, although the ®ndings mayhave wider implications.

This study is concerned with examining which bene®t transfers may be legitimate in the contextof applying aircraft noise nuisance valuations derived at one airport location to decision-makingat other sites. Airports are considered environmentally intrusive, but as air transport is growingrapidly, there are pressures for both the expansion of air transport infrastructure and a moreextensive use of existing facilities. Bene®t cost procedures now normally form an integral part ofassessing any major developments of large airports and are increasingly being used in appraisals ofsmaller, local facilities. High levels of aircraft noise are usually the main concerns expressed byobjectors to expanding airports infrastructure or when there are e�orts to push more tra�cthrough existing terminals.

There is a well-developed methodology for placing monetary values on aviation-related noisenuisance, but the approach, to date, has generally been to rely on individual case studies for eachassessment. For reasons of economy and to speed-up decision-making, bene®t transfer may beseen to o�er a tractable method of improving current practices. This study initially elaborates onboth the bene®t transfer concept and the airport noise nuisance issue prior to conducting an ana-lysis of variations in noise nuisance values that have been found in a range of individual cases. Theunderlying hypothesis being that if there are wide and di�cult to explain variations in the valuesfound, then it is di�cult to legitimize the use of bene®t transfers in this context.

2. BENEFIT TRANSFERS

The underlying idea of bene®t transfers is that one can take ®ndings or parameters from onecase study and adopt them to assist in policy-making elsewhere{. Conceptually, this is not a par-ticularly new idea, and economists have a long tradition of applying parameters such as demandelasticities in consumer analysis or input±output coe�cients in macroeconomic policy assessmentsin work other than that from which they were initially derived. Even in public appraisal proce-dures where non-market factors are of importance, bene®t transfer has a long pedigree; in theU.K.'s Department of Transport's computerized COBA framework of road investment appraisal,standardized values and parameters synthesized from previous studies are often included in thebene®t cost calculus. This has included values for reduced risks of accidents, for travel time savingsand for changes in vehicle operating costs. In the United States, unit-day values were used as earlyas 1962 to evaluate recreational resources.

In practice, bene®t transfer applications can be divided into three broad types: estimates basedupon expert opinion; estimates based upon observed, revealed behavior; and estimates based uponstated, preference elicitation mechanisms (Brookshire and Neill, 1992). The distinctions, however,are somewhat blurred. Expert opinion, for example, is seldom formed in a vacuum but normallyrelies on judgments arrived at after assessing either revealed or stated preferences studies. Thebasis of these assessments are subjective and usually opaque.

The recent interest in bene®t transfer is mainly associated with more fully incorporating envir-onmental externalities into the bene®t cost framework{. The issue is whether one can legitimatelytransfer non-market valuations of these externalities, particularly those valuations deploying sta-ted preference (contingent) valuation techniques that have become a major focus of the literature(O'Doherty, 1995). This may be seen as a belated switch in emphasis from methodological

*Brookshire (1992) o�ers some guidance as to the degree of accuracy required in estimated bene®ts and costs according tothe use they are put to. These considerations may in¯uence the extent to which bene®t transfers may be deemed accep-table.

{Brookshire and Neill (1992) de®ne bene®t transfers as, ``. . .an application of a data set that was developed for one parti-cular use to a quite distinct alternative application''. Boyle and Bergstrom (1992) talk of ``. . .the transfer of existingestimates of non-market values to a new study which is di�erent from the study for which the values were originallyestimated. . .(T)his is simply the application of secondary data to a new policy issue''. This is the broad form of de®nitionadopted in other studies, e.g. Opaluch and Mazzota (1992). The journal, Water Resources Research carried a specialedition on bene®t transfers in Volume 28, Number 3, 1992.

{Some of the issues were highlighted in the U.K. in the context of road investment appraisal (UK Department of Transport,1992). Demand for valuation studies in the U.S. rose at the federal level with the enactment of Executive Order 12291that caused the Environmental Protection Agency to use bene®t cost analysis to assess policy (Freeman, 1984).

224 Kirk Johnson and Kenneth Button

concerns about the intellectual legitimacy of alternative non-market evaluation techniques toquestions of application and policy relevance of empirical ®ndings.

While there have been important developments in evaluation methods in terms of revealed andstated preference methodologies, external environmental costs and bene®ts are often given onlysparse and partial coverage in many bene®t cost analyses. Increasing public concern about envir-onmental implications of various policy options is leading to a broader approach to bene®t costanalysis being sought. This is also taking place at a time when many inter-governmental (rangingfrom the European Union to World Bank), national and local agencies are being committed to theadoption of comprehensive appraisals of policy options and project proposals.

From a pragmatic perspective, bene®t transfer has a number of attractions. In terms of ®nancialexpediency, taking parameters from one study or a synthesis of a set of previous studies andemploying them more widely is much less costly than conducting separate evaluations for eachindividual decision made. Linked is a growing body of studies providing estimates of case-speci®cparameters, and it appears sensible to see if they can usefully be mined for additional and usefulinsights (Bergh et al., 1997). Bene®t transfer can also help streamline decision-making. Deployingpreviously derived monetary valuations estimates of environmental externalities can signi®cantlyspeed-up what is often considered a lengthy process of information collection, collation, and analysis.

From a methodological viewpoint, bene®t transfer may be seen to introduce a degree of con-sistency into decision-making through the use of common parameters across studies. This may beparticularly relevant when the degree of accuracy in parameters does not have to be very high; asin the initial screening of projects. Luken et al. (1992), for example, discuss bene®t transfers interms of establishing limits within which parameters may lie. It is also relevant when a largenumber of relatively standard but linked policy issues are being addressed.

In addition to public policy-making, legal requirements to provide forms of compensation tothose adversely a�ected by environmental degradation and legal processes often seek out evidencefrom earlier cases as precedents.

Bene®t transfers, however, are not without their limitations. A central issue is the decisionregarding which values can legitimately be transferred and which are study-speci®c. In the lattercase, bene®t transfers may remain legitimate if appropriate adjustments can be made to allow forspeci®city in individual case studies*. One criterion for deciding on the potential transferability ofresults is to examine the variability between previous case studies and to explore the extent towhich that can be explained and allowed in subsequent transfers.

3. AIRPORT NOISE STUDIES

As a result of rising incomes, increased leisure time, the growing importance of service sectoractivities and improvements in air transport technology, air passenger tra�c since 1960 has grownworldwide at an average rate of 9% a year and freight and mail tra�c by some 11% and 7%,respectively. Further, all the indications are that as a sector, it will continue to expand into theforeseeable future, albeit at di�erential rates in various geographical sub-markets. It seems likelythat passenger tra�c will grow at a rate of between 5% and 7% into the foreseeable future (BoeingCommercial Airplane Group, 1996).

This growth has taken place when there has been comparatively limited expansion in the phy-sical capacity of airport infrastructure. Initial excess capacity and better utilization of existingspace have been the main facilitators of growth. The ability of segments of airport infrastructureto handle the forecast growth in tra�c is now in doubt. Capacity has already been reached at 10 ofthe largest 46 airports in Europe and is being approached at another 16. As a consequence, thereare pressures for additional physical capacity to be built (Comite de Sages for Air Transport,1994). Similar problems exist in several parts of North America.

Investments in new airports and expansions together, with the updating of existing ones are®nancially costly. Airports also generally impose a variety of serious adverse environmental e�ectson those living nearby. Despite much improved technology, residents and businesses experienceconsiderable aircraft noise. For these reasons, airport investments are generally the subject of

*McConnell (1992) essentially argues that, at present, bene®t transfer is rather more an art than a science and, ``(t)here is nosimple, acceptable way mechanically to transfer a model''.

An airport noise nuisance case study 225

bene®t cost analysis. Placing a monetary value on the aircraft noise nuisances stemming fromairport development as part of bene®t cost calculations has a long pedigree dating back at least tothe seminal work of the Commission on the Third London Airport (1971). The vast majority ofevaluations has been case-speci®c, and the methodologically generally deploys some form ofrevealed preference, hedonic price approach. These studies sought to indirectly place a non-marketmonetary value on the noise nuisance by examining the impact on property values in residentialareas adjacent to an airport*. Traditionally, they have looked at marginal changes in real estatevalues associated with additional units of airport-related noise nuisance.

Recently, there have been a number of innovations in the evaluation methods employed, andseveral stated preference models deploying contingent valuation techniques have sought to directlyelicit from individuals their willingness-to-pay for aircraft noise abatement (e.g. Feitelson et al.,1996). This broad dichotomy of approaches poses some problems for bene®t transfers. Revealedpreference and stated preference frameworks are based upon di�ering sets of underlying assump-tions. The appropriate use of one or the other requires that the entire bene®t cost framework intowhich they are ®tted conform to their underlying theoretical basis. This is not a problem in itself,but it does mean there are inherent limitations to its general application.

More problematic is the considerable diversity of values generated both within and between thetwo groups of evaluation methodologies. With the hedonic pricing method, conventional surveyshave produced a range of estimates of the impact of airport noise on local property values. Nelson(1980), for example, looked at 13 studies and produced a property value discount range of0.4±1.1% for each additional decibel of aircraft noise nuisance. These values compare to the2.4±4.1% for home owners in Feitelson et al. (1996) stated preference work.

4. META-ANALYSIS

Meta-analysis was initially developed in the physical sciences and involves the statistical synth-esis of existing case studies to extract additional information concerning, for example, represen-tative parameters or factors (moderator variables) that result in study-speci®c results. Glass (1976)provides a widely accepted formal de®nition as, ``...the analysis of analysis...the statistical analysisof a large collection of analysis results from individual studies for the purpose of integrating the®ndings. It connotes a rigorous alternative to the casual, narrative discussions of research studieswhich typify our attempts to make sense of the rapidly expanding research literature''.

Most of the statistical synthesis work concerned with environmental evaluation has employedsome form of meta-regression procedure. In particular, it has been concerned with moderatorvariables that account for di�erences in the values of environmental externalities found in variouscase studies. Meta-regression analysis takes the general form (Stanley and Jarrell, 1989):

bj � ����kZjk � uj �j � 1; 2; :::L� �k � 1; 2; :::M� �1�

where bj is the reported estimate of the relationship of interest in the jth study from a total of Lstudies; � is the summary value of b, Zjk are variable that re¯ect the relevant characteristics of anempirical study that could explain variations amongst studies; �k are the coe�cients of the Mdi�erent study characteristics that are controlled for; and uj is the error term.

Transport-induced noise nuisance values can be explored in this framework. The general func-tional form that seems appropriate when seeking meta-analysis moderator variables in this contextcan be summarized along the lines of eqn (1). The right-hand side of the equation e�ectivelyextends the argument of Hunter et al. (1982) that much of the observed variance in correlationsacross studies can be accounted for by three statistical artifacts: unreliable data due to smallsample size, inter study di�erences in the reliability with which dependent and independent vari-ables are measured, and inter-study di�erences in restrictions of range.

Y � f�P;X;R;T;L� � Error �2�

*These calculations have taken the general form: lnH=�0+�1NEF+P�1lnX+u where �1 is the noise coe�cient, NEF is a

measure of noise nuisance, �1 are non-noise coe�cients, X are corresponding property characteristics and u is an errorterm.

226 Kirk Johnson and Kenneth Button

. Y represents an outcome of interested. This may be a single measure, such dbA in the case ofnoise, or it may re¯ect a variety of di�ering e�ects such as level, duration and pitch;

. P can be treated as the speci®c cause of the problem (such as air tra�c levels and proximityto source);

. X represents features of those a�ected by the nuisance (such as individuals' age and income);

. R, since the analysis is not based upon primary data but rather the combination of otherstudies, represents the characteristics of the research methods used in each study (e.g. such aseconometric or survey) and the data used (e.g. time series or cross-sectional);

. T indicates the period covered by each study to allow for any underlying dynamic e�ects(such as systematic changes in social preferences); and

. L is the location of the study (which could be spatial, such as urban and rural, or may relateto the country forming the basis for each data set).

Justi®cation for this type of framework is necessary. First, much of the work using meta-ana-lysis in the physical sciences tends to focus on P and X in eqn (2). This is mainly because of theability of those working in these ®elds to compare strict experiments, where methodologies areidentical, and results tend to be reported in a more standardized way. The importance of so-called`artifact e�ects', that are normally embraced in R in the social sciences, would seem to be muchgreater where the need for quasi-experimentation has often resulted in a considerable range ofdiverse model speci®cations, information gathering procedures and econometric estimation meth-ods being adopted. This obviously poses practical problems when attempting to express variousstudies' approaches consistent with the inherently numerical variables that are the basis of mostscienti®c meta-analysis.

The question of estimation methodology may also be particularly important in many sub-areasof economics now expanding. Such is the case with several aspects of the environmental economicsbecause di�erent procedures can embrace di�ering components of cost (Pearce and Markandya,1989). In part, this is due to the elements that make up the external cost of many environmentalconsiderations. Boulding and Lundstedt (1988), for example, argue that individuals' values in¯u-ence behavior in at least three ways; observed choice (i.e. revealed preference), peoples' conversa-tions (i.e. stated preference), and adaptations as part of the learning process. Smith (1989) suggeststhat all three provide insights into measuring the economic value placed on environmental ame-nities, although there is no reason to expect the values to be the same. A simpler breakdown arguesthat individuals' preference for environmental protection consists of three components:

Total Economic Value � User Value�Option Value� Existence Value �3�User value is that which may be observed from behavior, option value is the result of individualsdesiring to keep an environmental asset in case they wish to use it in the future, and existence valueis the importance individuals attach to the very existence of an asset, even if they never have per-sonal contact with it. These categories can be further re®ned, but the point is that estimationtechniques that rely only on revealed preference tend to understate option and existence values.Stated preference techniques can embrace them more fully, thus yielding a higher valuation*.Similar types of issues can emerge in other areas of economics.

The same sort of argument applies to T and L, especially when time series and cross-sectionalwork is combined in the meta-analysis or there is considerable geographical variation in thesources of the data used. The importance of when and where the studies were conducted stem fromthe underlying economic preference model. At one level, preferences are context-speci®c, and dif-fering contexts may result in varied valuations. One of these element is information. Before the1960s lead additive was added to fuel and was felt to have negligible environmental e�ects. How-ever, medical work brought this into question and thus, preferences were changed. We are nowmoving back in the other direction and concerns are being expressed about the health implicationsof the additives being used in place of lead. Equally, local conditions can be important becausethey can in¯uence the choice set. A wealthy country or region could provide a richer choice set

*This may be seen as a further form of potential upward bias in bene®t cost ratios which are the subject of Heohn andRandall's (1989) critique of bene®t cost methods.

An airport noise nuisance case study 227

than a poorer one and preferences may be a�ected. Added to this are the constraints imposed bypolitical and technical environments that are often space-speci®c.

Applying meta-analysis to environmental evaluations has been done before, generally in thecontext of revealed preference valuations of externalities*. Smith (1989) considered the empiricalwork of 35 hedonic price studies and found consistency in the results that emerged once allowancewas made for local conditions and assumptions. Smith and Huang (1995) examined some 167hedonic models of the marginal willingness to pay for reducing particulate matter in the air,although their meta-analysis forced them to rely on only 86. Their results show that market con-ditions and the procedures used to implement the hedonic models were important in explainingvariations in the values individual studies produced.

Work by Smith and Kaoru (1990), looked at some 200 studies of recreational demand employ-ing travel cost evaluation methods. They used regression-based meta-analysis to examine theresults of 77 of these studies. One of the main conclusions that can be drawn from this body ofanalysis is that variations across studies can often be explained in terms of the speci®c nature of therecreational resources and the underlying assumptions made in the estimation models employed.

While variations exist in the parameters examined, the evidence from this body of environmen-tal literature is that they can, in part, be explained in a way that potentially allows for adjustmentsif they are adopted in bene®t transfers. Findings from other related areas are less strong. Waters'(1996) meta-analytical work on travel time savings values and Button and Kerr's (1996) work onthe e�ectiveness of urban tra�c restraint policies do not o�er any statistical con®dence that bene®ttransfers can readily be recommended in these ®elds. Similar conclusions can be drawn from themeta-analysis of the output elasticities of infrastructure investment (Button and Rietveld, 1997).

In terms of placing monetary values on airport noise nuisance, empirical ®ndings of 18 eco-nomic studies deploying hedonic price techniques are examined using a simple meta-regressionanalysis{. Looking at results produced through the application of a single revealed preferenceevaluation methodology is likely to produce conservative estimates of any limitations in adoptingbene®t transfers, since the technique has been more uniformly applied than contingent valuationmethods. If there is little consistency across hedonic price studies then there is likely to be even lessacross contingent valuation estimates.

Results of these studies, all based on hedonic price index methods and o�ering a commonmeasure of noise value (the change in property value associated with a change in noise level) pro-vide a range of estimated airport noise nuisance values (see Table 1). The set of estimated valueshas a standard deviation of 1.28. The studies do di�er, however, in terms of when they were con-ducted, location of the airport considered and the level of aggregation at which the hedonic esti-mation was completed. To assess the importance of these case-speci®c features and re¯ect thearguments of some advocates of bene®t transfer, there is a need to transfer the entire demandfunction. The meta-regression embraces such e�ects in the form of dichotomous variables (Boyleand Bergstrom, 1992).

Table 2 shows the parameters from the meta-regression exercise, together with indicators oftheir statistical signi®cance{. The results provide little by way of overall explanation for thevariability in results or of any important in¯uence that may be relevant. The low overall degreeof explanation for variations in the noise nuisance values provided by the meta-regression,even allowing for the essentially cross-sectional nature of the analysis, o�ers lite objective supportfor adopting any of the reported values, or averages of them, for bene®t transfer purposes.

This does not mean bene®t transfers are invalid; any one of the values found in the case studymay be appropriate for transfer in speci®c situations. The problem is rather instead one ofselection. The mean value of case study parameters would certainly not seem appropriate.

*A more comprehensive account of this literature is to be found in Bergh et al. (1997).{Selecting a set of case studies for a meta-analysis is thwarted with problems. In this instance, a standard computerized

search was conducted. Studies were then selected, in part, according to the information made available within them.Studies were not included if information of the main variables in the regression were missing. Since the aim is not toactually ®nd a representative parameter nor to seek out appropriate moderator variables, the possible lack of a full set ofcase studies would tend to bias the rests in favor of bene®t transfers.

{A previous meta-analysis that looked at a range of transport noise nuisance evaluation studies covering a variety oftransport modes, including a limited number of airport studies, could only explain 40% of the variation in the valuesreported (Button and Nijkamp, 1997).

228 Kirk Johnson and Kenneth Button

Any selection of a noise nuisance value from these previous studies would inevitably be subjective.Although the importance of expert opinion should not automatically be discounted (Button,1997), this must inevitably raise questions about the widespread usefulness of bene®t transfers ifthey amount to little more than legitimizing established judgments.

The argument about judgments in bene®t transfers can actually be extended into the evaluationprocess itself. While all bene®t cost exercises require making a large number of assumptions, thereal issue is making these as transparent as possible. Therefore, if it does ultimately come down tothe analyst selecting a particular case study's parameter to transfer, justi®cation for the selectionshould be transparent.

5. CONCLUSIONS

Bene®t transfers are increasingly seen as cost e�ective and expeditious in incorporating envir-onmental e�ects into bene®t cost studies. In some areas, with due care and caution, there is evi-dence that one can adopt parameters derived in similar contexts for some aspects of bene®t costanalysis. A major issue, however, is the generality with which this can be done across various typesof parameters, especially when dealing with non-market valuations of external bene®ts and costs.

Examination of a range of values obtained for noise nuisances associated with airports indicatesthat there is little justi®cation for applying bene®t transfer procedures at this time. The relativelywide range of airport noise nuisance values previously obtained and the di�culty of explaining italso raises further questions involving the overall legitimacy of the techniques that have beenemployed. The range of parameters cannot be explained by factors such as the country concernedor the data base employed and this raises concern about the overall usefulness of the hedonicmethod or, at the very least, the way it is applied.

Before bene®t transfers are too widely adopted in this age of comparative research austerity,there are grounds for advocating a more systematic and rigorous analysis of individual legitimacy.

Table 2. Meta-regression parameters

Variable Coe�cient Standard error 2-tail signi®cance

Constant 0.3761 1.3552 0.7854USA ÿ0.1563 0.9779 0.8753Year 0.0562 0.0479 0.2604Disaggregated data ÿ0.0351 0.9303 0.9704

R-squared 0.1340Standard error of regression: 1.3085Log likelihood ÿ28.1201

Table 1. Studies used in meta-analysis

Study Year % of house price Country Data

Abelson 1979 0.45 Australia DisaggregateCollins and Evans 1994 0.45 U.K. DisaggregateDe Vany 1976 0.80 U.S.A. AggregateDygert 1973 0.60 U.S.A. AggregateEmerson 1969 0.57 U.S.A. DisaggregateGautrin 1975 0.35 U.K. DisaggregateLevesque 1994 1.30 Canada DisaggregateMaser 1977 0.62 U.S.A. AggregateMcMillan 1978 0.50 Canada DisaggregateMcMillan 1980 0.87 Canada DisaggregateMieszkowski and Saper 1978 0.40 Canada DisaggregateNelson 1979 1.10 U.S.A. AggregateO'Byrne et al. 1985 0.52 U.S.A. AggregateO'Byrne et al. 1985 0.57 U.S.A. DisaggregatePaik 1972 0.65 U.S.A. DisaggregatePennington et al. 1990 0.60 U.K. DisaggregatePrice 1974 0.83 U.S.A. AggregateUyeno et al. 1993 1.13 Canada Disaggregate

An airport noise nuisance case study 229

This testing should cover a range of approaches, not just the meta-regression or even the broadermeta-analytical approaches, which is favored here. Taking values from current studies and back-casting them into earlier bene®t cost studies could prove insightful, as might splitting samples usedin externality evaluations and exploring whether the parameters estimated di�er signi®cantlybetween them. To test for temporal stability of parameters, follow-ups should be fostered with newcase studies replicating old ones that use the same samples and methodology.

Our ®ndings may also have implications on the ways primary studies are conducted. In the past,they have been case-speci®c and little, if any, thought has been given to their potential deploymentin bene®t transfers. Recognition of this may lead to reconsidering how case studies are conductedand their results reported. There are arguments, for example, that on-going case studies be moresystematic so that the results presented may be assessed more completely by anyone wanting toconsider them for a bene®t transfer exercise.

In conducting the case studies, an analyst may also take the view that the explanatory variablesemployed should be selected and speci®ed in such a way that parallels information available forother potential case policy study sites. At the more fundamental level, the arguments of Loomis(1992) that more headway would be made by seeking an acceptable bene®t function transfermethodology rather than simply looking to transfer parameters has intellectual merit and wouldmake transparent the underlying assumptions transferred. None of this rules out the need forcontinued basic research into improving fundamental parameter estimation procedures.

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