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Positive Mathematical Programming: a Comparison of Different Specification Rules

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  • Fragoso, Rui Manuel de Sousa
  • Carvalho, Maria Leonor da Silva
  • Henriques, Pedro Damiao de Sousa

Abstract

In this paper, the prescriptive capacity of different types of positive mathematical programming models applied to the Alentejo agricultural sector is analysed. Model results are compared for 2000 and 2004 agricultural price and subsidies scenarios, regarding optimal combination of activities. Thus, it is tested, on one hand, models capacity to reproduce Alentejo agricultural sector behaviour, and by the other hand, their response and adjustment capacities to changes in prices and in agricultural policy.

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File URL: http://purl.umn.edu/44242
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Bibliographic Info

Paper provided by European Association of Agricultural Economists in its series 2008 International Congress, August 26-29, 2008, Ghent, Belgium with number 44242.

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Date of creation: 2008
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Handle: RePEc:ags:eaae08:44242

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Keywords: Positive mathematical programming; agricultural supply; Alentejo; Research Methods/ Statistical Methods;

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  1. Horner, G.L. & Corman, J. & Howitt, R.E. & Carter, C.A. & MacGregor, R.J., 1992. "The Canadian Regional Agriculture Model Structure, Operation and Development," Papers 1-92, Gouvernement du Canada - Agriculture Canada.
  2. Spreen, Thomas H., 2006. "Price Endogenous Mathematical Programming Models and Trade Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(02), August.
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Cited by:
  1. Rui Fragoso & Carlos Marques & Maria Raquel Lucas & Maria Belém Martins & Raúl Fernandes Jorge, 2009. "The Economic Effects of Common Agricultural Policy Trends on Montado Ecosystem in Southern Portugal," CEFAGE-UE Working Papers 2009_12, University of Evora, CEFAGE-UE (Portugal).
  2. Henseler, Martin & Wirsig, Alexander & Herrmann, Sylvia & Krimly, Tatjana & Dabbert, Stephan, 2009. "Modeling the impact of global change on regional agricultural land use through an activity-based non-linear programming approach," Agricultural Systems, Elsevier, vol. 100(1-3), pages 31-42, April.

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