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A Binary Ordinal Probit Model for CVM Data Based on On-Site Samples
Stockholm University, Faculty of Social Sciences, Department of Statistics.
Örebro Universitet.
2007 (English)Report (Other academic)
Abstract [en]

A commonly used sampling design in economic valuation studies such as theCVM, is on-site sampling. If this sampling design is used, the sampling inclu-sion probabilities may be correlated with respondents’ valuations, invalidatingwelfare measures derived from estimates of the probit model. This paper pro-poses a model based on the bivariate ordinal probit, a model that can be usedto analyze binary choice CV data gathered by on-site sampling. This paperpresents the model, derives the log-likelihood, and illustrates the MLE using asmall simulation study. The model is presented, the log-likelihood is derived andthe properties of the MLE’s are illustrated with a small simulation study. Thesimulation results show the proposed estimator to be an interesting alternative,but the estimator should be evaluated in more population models.

Place, publisher, year, edition, pages
2007.
Keyword [en]
On-site, ML-estimation, Bivariate ordered probit, Sample inclusion.
National Category
Social Sciences
Research subject
Statistics
Identifiers
URN: urn:nbn:se:su:diva-87055OAI: oai:DiVA.org:su-87055DiVA: diva2:600719
Available from: 2013-01-25 Created: 2013-01-25 Last updated: 2013-01-31
In thesis
1. On-Site Sampling in Economic Valuation Studies
Open this publication in new window or tab >>On-Site Sampling in Economic Valuation Studies
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

A commonly used sampling design in economic valuation studies is on-sitesampling. If this sampling design is used, the sampling inclusion probabil-ities may be correlated with respondents’ valuations, invalidating welfaremeasures derived from estimates of the probit model. This problem is re-ferred to a length-bias, a problem discovered in other fields of applicationof statistics.The first paper in this thesis outlines different application fields thathave length-bias problems and the suggested model solutions in the litera-ture are presented.The second paper of this thesis proposes a model based on the bivariateordinal probit, a model that can be used to analyze binary choice CV datagathered by on-site sampling. The models is presented, the log-likelihoodis derived, and the properties of the MLE’s are illustrated using a smallsimulation study. The simulation results show the proposed estimator tobe an interesting alternative.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2007. 11 p.
Series
Statistical studies / Department of Statistics, University of Umeå, ISSN 1100-8989 ; 36
Keyword
Sample inclusion; Length-bias; Poisson dis- tribution; ML-estimation; Bivariate ordered probit; CVM.
National Category
Social Sciences
Research subject
Statistics
Identifiers
urn:nbn:se:su:diva-87056 (URN)978-91-7264-405-2 (ISBN)
Supervisors
Available from: 2013-01-31 Created: 2013-01-25 Last updated: 2013-01-31Bibliographically approved

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