Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25956
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dc.contributor.authorBudziński, Wiktoren_UK
dc.contributor.authorCampbell, Dannyen_UK
dc.contributor.authorCzajkowski, Mikołajen_UK
dc.contributor.authorDemšar, Urškaen_UK
dc.contributor.authorHanley, Nicken_UK
dc.date.accessioned2018-01-11T01:17:42Z-
dc.date.available2018-01-11T01:17:42Z-
dc.date.issued2018-09en_UK
dc.identifier.urihttp://hdl.handle.net/1893/25956-
dc.description.abstractIn this paper, we investigate the prospects of using geographically weighted choice models for modelling of spatially clustered preferences. We argue that this is a useful way of generating highly-detailed spatial maps of willingness to pay for environmental conservation, given the costs of collecting data. The data used in this study comes from a discrete choice experiment survey regarding public preferences for the implementation of a new country-wide forest management and protection program in Poland. We combine it with high-resolution spatial data related to local forest characteristics. Using locally estimated discrete choice models we obtain location-specific estimates of willingness to pay (WTP). Variation in these estimates is explained by characteristics of the forests in their place of residence. The results are compared with those obtained from a more typical, two stage procedure which uses Bayesian posterior means of the mixed logit model random parameters to calculate location-specific estimates of WTP. We find that there are indeed strong spatial patterns to the benefits of changes in management to national forests. People living in areas with more species-rich forests and those living nearer to higher areas of mixed forests have significantly different WTP values than those living in other locations. This kind of information enables a better distributional analysis of the gains and losses from changes to natural resource management, and better targeting of investments in forest quality.en_UK
dc.language.isoenen_UK
dc.publisherWiley-Blackwell for the Agricultural Economics Societyen_UK
dc.relationBudziński W, Campbell D, Czajkowski M, Demšar U & Hanley N (2018) Using Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferences. Journal of Agricultural Economics, 69 (3), pp. 606-626. https://doi.org/10.1111/1477-9552.12260en_UK
dc.rightsThis item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. This is the peer reviewed version of the following article: Budziński, W. , Campbell, D. , Czajkowski, M. , Demšar, U. and Hanley, N. (2018), Using Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferences. J Agric Econ, 69: 606-626, which has been published in final form at https://doi.org/10.1111/1477-9552.12260. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.en_UK
dc.subjectdiscrete choice experimenten_UK
dc.subjectcontingent valuationen_UK
dc.subjectwillingness to payen_UK
dc.subjectspatial heterogeneity of preferencesen_UK
dc.subjectforest managementen_UK
dc.subjectpassive protectionen_UK
dc.subjectlitteren_UK
dc.subjecttourist infrastructureen_UK
dc.subjectmixed logiten_UK
dc.subjectgeographically weighted modelen_UK
dc.subjectweighted maximum likelihooden_UK
dc.subjectlocal maximum likelihooden_UK
dc.titleUsing Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferencesen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2019-12-30en_UK
dc.rights.embargoreason[GWR paper JAE.pdf] Publisher requires embargo of 24 months after formal publication.en_UK
dc.identifier.doi10.1111/1477-9552.12260en_UK
dc.citation.jtitleJournal of Agricultural Economicsen_UK
dc.citation.issn1477-9552en_UK
dc.citation.issn0021-857Xen_UK
dc.citation.volume69en_UK
dc.citation.issue3en_UK
dc.citation.spage606en_UK
dc.citation.epage626en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.author.emaildanny.campbell@stir.ac.uken_UK
dc.citation.date29/12/2017en_UK
dc.contributor.affiliationUniversity of Warsawen_UK
dc.contributor.affiliationEconomicsen_UK
dc.contributor.affiliationUniversity of Warsawen_UK
dc.contributor.affiliationUniversity of St Andrewsen_UK
dc.contributor.affiliationUniversity of St Andrewsen_UK
dc.identifier.isiWOS:000445186800002en_UK
dc.identifier.scopusid2-s2.0-85039557343en_UK
dc.identifier.wtid517473en_UK
dc.contributor.orcid0000-0001-7467-2318en_UK
dc.date.accepted2017-09-26en_UK
dc.date.filedepositdate2017-10-05en_UK
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