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Testing the conjoint analysis technique for the measurement of passive use values of forest health

dc.contributor.authorHaefele, Michelle A., author
dc.contributor.authorLoomis, John B., advisor
dc.contributor.authorMcCollum, Daniel, committee member
dc.contributor.authorSparling, Ed, committee member
dc.contributor.authorKling, Robert, committee member
dc.date.accessioned2026-04-06T18:23:59Z
dc.date.issued1999
dc.description.abstractThis dissertation is composed of three papers each examining issues associated with the use of the conjoint technique to estimate passive use values of forest health. The first paper will test the equivalence of conjoint question formats to estimate the use and non-use values associated with programs to prevent forest pest infestations. Two response formats, ranking and rating, were applied to two independent samples. As has been done in the past, ratings were converted into implied rankings which were then compared with actual rankings. Further a ratings difference model was constructed with the dependent variable being the difference in rating between a "status quo" situation and a management change. This model was then compared with the actual and constructed rankings models. It was found that the constructed rankings were not statistically different than the actual rankings. This has implications for survey design as it is felt that the ratings task is less difficult for respondents. The second paper examines the use of panel estimators for conjoint analysis. Most conjoint studies require respondents to rate multiple product profiles, thereby generating a panel data set. To date, published conjoint analyses have not employed panel estimators. A comparison of random effects panel ordered probit and ordered probit finds improvement in significance levels on individual forest health attribute coefficients and gains in precision of confidence intervals on the marginal values of the attributes as well as gains in overall model goodness-of-fit with a random effects specification. The final paper uses conjoint analysis to explore the difference between resident and non-resident preferences for the attributes of forest management programs directed at western spruce budworm infestations in Oregon. Estimating national values for passive use attributes of forest health presents a challenge since it may be the case that residents' and non-residents' values will be different. It was found that non-residents do have different preferences for such programs than residents. Especially interesting is the fact that Oregon residents are more likely to favor management programs which enhance or protect commercial timber, while non-residents are not. Residents and non-residents are more likely to oppose a program which involves a risk of contamination from spraying if they are members of an environmental organization.
dc.format.mediumdoctoral dissertations
dc.identifier.urihttps://hdl.handle.net/10217/244018
dc.identifier.urihttps://doi.org/10.25675/3.026684
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof1980-1999
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.licensePer the terms of a contractual agreement, all use of this item is limited to the non-commercial use of Colorado State University and its authorized users.
dc.subjectforestry
dc.titleTesting the conjoint analysis technique for the measurement of passive use values of forest health
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineAgricultural and Resource Economics
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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