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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/5735
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dc.contributor.authorLien, Gudbranden
dc.contributor.authorHardaker, J Brianen
dc.contributor.authorvan Asseldonk, Marcel A P Men
dc.contributor.authorRichardson, James Wen
dc.date.accessioned2010-04-29T10:12:00Z-
dc.date.issued2009-
dc.identifier.citationAnnals of Operations Researchen
dc.identifier.issn1572-9338en
dc.identifier.issn0254-5330en
dc.identifier.urihttps://hdl.handle.net/1959.11/5735-
dc.description.abstractA Monte Carlo procedure is used to demonstrate the dangers of basing (farm) risk programming on only a few states of nature and to study the impact of applying alternative risk programming methods. Two risk programming formulations are considered, namely mean-variance (E,V) programming and utility efficient (UE) programming. For the particular example of a Norwegian mixed livestock and crop farm, the programming solution is unstable with few states, although the cost of picking a sub-optimal plan declines with increases in number of states. Comparing the E,V results with the UE results shows that there were few discrepancies between the two and the differences which do occur are mainly trivial, thus both methods gave unreliable results in cases with small samples.en
dc.languageenen
dc.publisherSpringer New York LLCen
dc.relation.ispartofAnnals of Operations Researchen
dc.titleRisk programming analysis with imperfect informationen
dc.typeJournal Articleen
dc.identifier.doi10.1007/s10479-009-0555-yen
dc.subject.keywordsAgricultural Economicsen
local.contributor.firstnameGudbranden
local.contributor.firstnameJ Brianen
local.contributor.firstnameMarcel A P Men
local.contributor.firstnameJames Wen
local.subject.for2008140201 Agricultural Economicsen
local.subject.seo2008919999 Economic Framework not elsewhere classifieden
local.profile.schoolEconomicsen
local.profile.schoolEconomicsen
local.profile.schoolEconomicsen
local.profile.schoolEconomicsen
local.profile.emailgudbrand.lien@hil.noen
local.profile.emailbhardake@une.edu.auen
local.profile.emailmarcel.vanasseldonk@wur.nlen
local.profile.emailjwrichardson@tamu.eduen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20100423-154252en
local.publisher.placeUnited States of Americaen
local.identifier.scopusid80053133019en
local.peerreviewedYesen
local.contributor.lastnameLienen
local.contributor.lastnameHardakeren
local.contributor.lastnamevan Asseldonken
local.contributor.lastnameRichardsonen
dc.identifier.staffune-id:bhardakeen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:5876en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleRisk programming analysis with imperfect informationen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorLien, Gudbranden
local.search.authorHardaker, J Brianen
local.search.authorvan Asseldonk, Marcel A P Men
local.search.authorRichardson, James Wen
local.uneassociationUnknownen
local.identifier.wosid000295271900018en
local.year.published2009en
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