Assessing the prediction capacity of an agricultural supply positive mathematical programming model

dc.contributor.authorFragoso, Rui Manuel de Sousa
dc.contributor.authorCarvalho, Maria Leonor da Silva
dc.contributor.authorHenriques, Pedro Damião de Sousa
dc.date.accessioned2011-12-05T13:54:05Z
dc.date.available2011-12-05T13:54:05Z
dc.date.issued2011
dc.date.updated2011-11-17T23:34:42Z
dc.description.abstractIn this paper, the calibration and prediction capacity of a supply response positive mathematical programming model (PMP) for the Alentejo region are evaluated. The model is calibrated with prices and agricultural subsidies of the base year (2000), using the specification rules of the cost function standard, Paris standard, average cost and exogenous elasticities. Then, the model is utilised for prediction of crop and livestock supply with prices and subsidies of 2004. Model results for 2000 and 2004 agricultural price and subsidies are compared, with available data, regarding optimal combination of activities to test model’s capacity to reproduce Alentejo agricultural sector behaviour in response to the changes in prices and agricultural policy. Results showed that the PMP model reproduces exactly the observed activity levels on the base year, whatever the rule used to specify the cost function, and that PMP is an efficient instrument to predict agricultural supply, mainly using the exogenous elasticities specification rule.por
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.citationFragoso, Rui Manuel de Sousa; Carvalho, Maria Leonor da Silva; Henriques, Pedro Damião de Sousa. Assessing the prediction capacity of an agricultural supply positive mathematical programming model, International Journal of Sustainable Society, 3, 2, 209-220, 2011.por
dc.identifier.urihttp://hdl.handle.net/10174/2909
dc.language.isoporpor
dc.peerreviewednopor
dc.rightsopenAccesspor
dc.titleAssessing the prediction capacity of an agricultural supply positive mathematical programming modelpor
dc.typearticlepor

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