Testing Criterion Validity of Benefit Transfer Using Simulated Data

dc.contributor.authorPrasai, Nilamen
dc.contributor.committeechairParmeter, Christopher F.en
dc.contributor.committeecochairBoyle, Kevin J.en
dc.contributor.committeememberKuminoff, Nicolai V.en
dc.contributor.committeememberPope, Jaren C.en
dc.contributor.departmentAgricultural and Applied Economicsen
dc.date.accessioned2014-03-14T20:43:57Zen
dc.date.adate2008-09-11en
dc.date.available2014-03-14T20:43:57Zen
dc.date.issued2008-08-05en
dc.date.rdate2008-09-11en
dc.date.sdate2008-08-21en
dc.description.abstractThe purpose of this thesis is to investigate how the differences between the study and policy sites impact the performance of benefit function transfer. For this purpose, simulated data are created where all information necessary to conduct the benefit function transfer is available. We consider the six cases of difference between the study and policy sites- scale parameter, substitution possibilities, observable characteristics, population preferences, measurement error in variables, and a case of preference heterogeneity at the study site and fixed preferences at the policy site. These cases of difference were considered one at time and their impact on quality of transfer is investigated. RUM model based on reveled preference was used for this analysis. Function estimated at the study site is transferred to the policy site and willingness to pay for five different cases of policy changes are calculated at the study site. The willingness to pay so calculated is compared with true willingness to pay to evaluate the performance of benefit function transfer. When the study and policy site are different only in terms of scale parameter, equality of estimated and true expected WTP is not rejected for 89.7% or more when the sample size is 1000. Similarly, equality of estimated preference coefficients and true preference coefficients is not rejected for 88.8% or more. In this study, we find that benefit transfer performs better only in one direction. When the function is estimated at lower scale and transferred to the policy site with higher scale, the transfer error is less in magnitude than those which are estimated at higher scale and transferred to the policy site with lower scale. This study also finds that transfer error is less when the function from the study site having more site substitutes is transferred to the policy site having less site substitutes whenever there is difference in site substitution possibilities. Transfer error is magnified when measurement error is involved in any of the variables. This study do not suggest function transfer whenever the study site's model is missing one of the important variable at the policy site or whenever the data on variables included in study site's model is not available at the policy site for benefit transfer application. This study also suggests the use of large representative sample with sufficient variation to minimize transfer error in benefit transfer.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-08212008-230551en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08212008-230551/en
dc.identifier.urihttp://hdl.handle.net/10919/34685en
dc.publisherVirginia Techen
dc.relation.haspartnilams_thesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectMeasurement Erroren
dc.subjectPreference Differenceen
dc.subjectRandom Parameteren
dc.subjectCharacteristics Differenceen
dc.subjectSubstitution Possibilitiesen
dc.subjectScale Parameteren
dc.subjectDiscrete Choice Modelingen
dc.subjectBenefit Transferen
dc.subjectCriterion Validityen
dc.titleTesting Criterion Validity of Benefit Transfer Using Simulated Dataen
dc.typeThesisen
thesis.degree.disciplineAgricultural and Applied Economicsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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