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Flexible quota constraints in positive mathematical programming models

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Author Info
Buysse, J.
Van der Straeten, B.
Claeys, D.
Lauwers, L.
Marchand, F.L.
Van Huylenbroeck, G.
Abstract

To explain over- and underuse of available quota, Buysse et al. (2007) have integrated the shadow cost of the quota constraint in a quota flexibility function in a positive mathematical programming model. This method and central hypothesis, formulated and tested for the case of Belgian sugar beet farms, is in current paper extended and confirmed for the cases of Flemish dairy quota and manure emission rights. Despite the different organisation, objectives and implementations of the diverse quota systems, the results are similar. A higher utilisation of quota is significantly driven by the quota rent, but farm characteristics are also important and the effect declines with increasing quota rent. Regardless the quota, the dairy quota flexibility behaviour of the sample of Flemish farms results in an output price elasticity of 0.6%. The quota flexibility functions can be used for policy analysis, model sophistication and farm advisory instrument.

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Paper provided by European Association of Agricultural Economists in its series 107th Seminar, January 30-February 1, 2008, Sevilla, Spain with number 6640.

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Date of creation: 2008
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Handle: RePEc:ags:eaa107:6640

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Related research
Keywords: Quota; flexibility; Positive Mathematical Programming; farm model; Common Agricultural Policy; Agricultural and Food Policy; Demand and Price Analysis; Research Methods/ Statistical Methods;

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  1. Alexandre Gohin & Jean-Christophe Bureau, 2006. "Modelling the EU sugar supply to assess sectoral policy reforms," European Review of Agricultural Economics, Oxford University Press for the Foundation for the European Review of Agricultural Economics, vol. 33(2), pages 223-247, June.
  2. Markus Lips & Peter Rieder, 2005. "Abolition of Raw Milk Quota in the European Union: A CGE Analysis at the Member Country Level," Journal of Agricultural Economics, Blackwell Publishing, vol. 56(1), pages 1-17. [Downloadable!] (restricted)
  3. Luhandjula, M.K., 2006. "Fuzzy stochastic linear programming: Survey and future research directions," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1353-1367, November. [Downloadable!] (restricted)
  4. Thomas Heckelei & Hendrik Wolff, 2003. "Estimation of constrained optimisation models for agricultural supply analysis based on generalised maximum entropy," European Review of Agricultural Economics, Oxford University Press for the Foundation for the European Review of Agricultural Economics, vol. 30(1), pages 27-50, March.
  5. Rommelfanger, Heinrich, 1996. "Fuzzy linear programming and applications," European Journal of Operational Research, Elsevier, vol. 92(3), pages 512-527, August. [Downloadable!] (restricted)
  6. Colman, David, 2000. "Inefficiencies in the UK milk quota system," Food Policy, Elsevier, vol. 25(1), pages 1-16, February. [Downloadable!] (restricted)
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