Farm-based modelling of the EU sugar reform: impact on Belgian sugar beet suppliers

Buysse, Jeroen; Fernagut, Bruno; Harmignie, Olivier; Frahan, Bruno Henry de; Lauwers, Ludwig; Polomé, Philippe; Huylenbroeck, Guido Van; Meensel, Jef Van

doi:10.1093/erae/jbm001

Cited by 45 publications

(27 citation statements)

References 13 publications

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“…Modeling farmers' behavior requires the definition of these three elements: decision variables ( ⃗ = ( 1 , … , , … , )), attributes ( ( ⃗ )) and constraints ( ⃗ ≤ ) 1 . Thus, the decision-making problem a farmer faces at the beginning of each cropping year can be represented as the following:…”

Section: Multi-attribute Utility Functions: a Literature Reviewmentioning

confidence: 99%

“…The feasible set is established by the inequalities and equalities constraining the farmer's decision problem (1). Among all the points defining the feasible set, we are only interested in the efficient set, since this is where the indifference or iso-utility curve lands and consequently where decision-makers maximize their utility function.…”

Section: Defining the Efficient Setmentioning

confidence: 99%

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Modeling at farm level: Positive Multi-Attribute Utility Programming

Gómez‐Limón

Gutiérrez‐Martín

Riesgo

2016

Omega

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This article proposes a new mathematical programming model for the simulation of farmers' decision-making. We have developed a model based on a multi-attribute utility approach that takes into consideration the most relevant attributes of farmers within a positive framework.This approach overcomes the limitations found in some mathematical models used in the literature to simulate farmers' behavior. A five-step procedure is presented in order to elicit the utility function that reproduces farmers' current decision-making. We illustrate this positive multi-attribute approach using a sample of farmers in an irrigated area in southern Spain, where our simulations demonstrate the accurateness of the model in reproducing actual farmers' decision-making. We also find evidence that the model is able to explain the heterogeneous behavior of farmers within a homogeneous agricultural system.

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Section: Multi-attribute Utility Functions: a Literature Reviewmentioning

confidence: 99%

Section: Defining the Efficient Setmentioning

confidence: 99%

Modeling at farm level: Positive Multi-Attribute Utility Programming

Gómez‐Limón

Gutiérrez‐Martín

Riesgo

2016

Omega

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“…This recovered additional information from the observed activity levels, enabling specification of a non-linear objective function such that the resulting non-linear model exactly reproduced the observed behavior of farmers [14][15][16][17]. In recent years, the PMP methodology has been applied in various research areas and has been improved to consider many relevant aspects [18][19][20][21][22][23][24][25][26]. Heckelei et al [27] recently reviewed the more important PMP models that have been development and used.…”

Section: Model Calibration: Risk Aversion and Positive Mathematical Pmentioning

confidence: 99%

Simulating Volumetric Pricing for Irrigation Water Operational Cost Recovery under Complete and Perfect Information

Giraldo

Cortignani

Dono

2014

Water

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This study evaluated the implementation of a volumetric and cost-recovery pricing method for irrigation water under symmetric information conditions without the inclusion of implementation costs. The study was carried out in two steps. First, a cost function was estimated for irrigation water supplied by a water user association to a typical Mediterranean agricultural area, based on a translog function. Second, the economic impact of a pricing method designed according to this cost function was simulated using a mathematical programming territorial model for the same agricultural area. The outcomes were compared with those for the current pricing method. The impacts of this pricing method are discussed in terms of its neutral effects on total farm income and, conversely, the importance of the redistributive effects.

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“…It brought a signifi cant intervention price reduction for sugar and sugar beet, merging of the quotas and incentives to reduce production (European Commission, 2006). Although some authors (Buysse et al, 2007) mention that additional actions would be necessary, the introduced measures caused the closure of 83 sugar factories and resulted in 22,000 direct and more than 100,000 indirect job losses (EFFAT, 2013).…”

Section: Introductionmentioning

confidence: 99%

European Sugar Market - Impact of Quota System

Benešová¹,

Řezbová²,

Smutka³

et al. 2016

Acta Univ. Agric. Silvic. Mendelianae Brun.

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The European agricultural market has been criticized for its heavy regulations and subsidization. The sugar market is one of the most regulated ones; however, this will change radically in 2017 when the current system of production quotas will end. The aim of this paper is to present the basic characteristics of the EU quota sugar market. The analysis identifi es the main drivers of EU sugar market and their position within the EU sugar market. The paper identifi es especially those drivers/ companies/alliances which take control over the EU sugar production realized under the quota production system. The paper also highlights the level of EU sugar market concentration and also identifi es those countries and companies which are the main leaders in the sugar production area realized under the quota system. Based on the results deriving from the paper, it is possible to characterize the EU sugar market as a heavily concentrated one -nearly 75% (10 mil. tonnes) of the quota is controlled by fi ve multinational companies only; these companies are operating more than 50% of all the available sugar plants located in the EU. These multinational alliances are also in control of the production capacities of their subsidiaries. In most countries, this causes serious problems as the given quota is controlled by one or two producers only. The EU sugar market is extremely concentrated especially if we take into consideration the location of each alliance's headquarters. The majority of production capacities are under (the) control of especially German and French companies. These two countries are also the main benefi ciaries in relation to the EU sugar production quota system.

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Farm-based modelling of the EU sugar reform: impact on Belgian sugar beet suppliers

Cited by 45 publications

References 13 publications

Modeling at farm level: Positive Multi-Attribute Utility Programming

Modeling at farm level: Positive Multi-Attribute Utility Programming

Simulating Volumetric Pricing for Irrigation Water Operational Cost Recovery under Complete and Perfect Information

European Sugar Market - Impact of Quota System

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