Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/5105
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dc.contributor.authorPEETERS, Ludo-
dc.contributor.authorSurry, Y.-
dc.date.accessioned2007-12-20T15:55:40Z-
dc.date.available2007-12-20T15:55:40Z-
dc.date.issued2003-
dc.identifier.isbn0-662-32079-4-
dc.identifier.urihttp://hdl.handle.net/1942/5105-
dc.description.abstractAgriculture and Agri-Food Canada (AAFC) has an ongoing research program to provide information on the effect of potential agriculture policy and technology scenarios on the environment and economic conditions, behavior and performance in the agriculture sector. Included in this work program is a project to improve our farm level data on cost of production and farm management practices for economic and environmental analysis. As part of this effort to improve our data, this report evaluates an analytical method, called Maximum Entropy (ME), for its effectiveness in extracting detailed, enterprise level, cost of production information from whole-farm data. The ME method has been shown to be a promising and cost-effective option for obtaining these enterprise-level estimates from whole-farm data sets already available.-
dc.relation.ispartofseries(Technical report ; 2121/E)-
dc.titleFarm cost allocation based on the maximum entropy methodology: the case of Saskatchewan crop farms-
dc.typeResearch Report-
local.bibliographicCitation.jcatR1-
local.type.specifiedResearch Report-
dc.bibliographicCitation.oldjcatB1-
item.fulltextWith Fulltext-
item.fullcitationPEETERS, Ludo & Surry, Y. (2003) Farm cost allocation based on the maximum entropy methodology: the case of Saskatchewan crop farms.-
item.accessRightsOpen Access-
item.contributorPEETERS, Ludo-
item.contributorSurry, Y.-
Appears in Collections:Research publications
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