Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
45.0 h + 7.5 h
Q2
Teacher(s)
Gaspart Frédéric (coordinator); Georges Benoît;
Language
English
Prerequisites
General skills for a bio-engineering bachelor, animal and vegetal productions, introductory management, micro-economics and introduction to game theory
Main themes
- Part 1 After an introduction on the agricultural production economy, the role of major production factors in the efficient management of agricultural firms is characterized. The mains tools for analysis and decision making are explained and used in practical exercises. The main agricultural and food branches are outlined. The development of the agricultural sector in Belgium and in Europe is analysed.
- Part 2 The course outlines, explains and compares various decision problems and decision-making tools within the unifying framework of game theory. It distinguishes (and shows the complementarities of) statistics and economic analysis. Complex decisions under uncertainty in situations with several interacting decision-makers are illustrated with relevant examples.
- Part 2 The course outlines, explains and compares various decision problems and decision-making tools within the unifying framework of game theory. It distinguishes (and shows the complementarities of) statistics and economic analysis. Complex decisions under uncertainty in situations with several interacting decision-makers are illustrated with relevant examples.
Aims
At the end of this learning unit, the student is able to : | |
| 1 |
a. Contribution de l'activité au référentiel AA (AA du programme) 1.1-1.5, 2.1-2.5 game theory, agency, farm management techniques 3.2-3.3 matching real situations with archetypal problems 3.4 solving mathematical models (game theory and operation research) 3.6-3.8 interpreting the results of abstract models (course+homeworks) 4.1-4.2 identifying typical problems in complex situations 4.4-4.7 drawing lessons from abstract models for complex, real situations 5.1-5.4 & 5.7 farm management techniques 5.8, 7.1 & 7.5 agency and contract theory (game theory) 6.2 & 6.6-6.7 homeworks b. Formulation spécifique pour cette activité des AA du programme At the end of the course, students will be able : (Part 1) - to identify and to compare specific characteristics of the major agricultural production factors from the viewpoint of economics and management. - to understand and to use the mains decision-making tools available at the farm level and at the regional level. - to analyse the structure, functioning and performance of the main agricultural production and agricultural branches. - to apply the concepts and analysis techniques in supervised exercises. (Part 2) - to understand in depth various decision problems and decision-making tools commonly relied upon in fields relevant for the students. - to formulate strategic (i.e. interactive) decision problems in a rigorous mathematical framework (game theory). - to pick up adequate methods for solving multi-agents decision problems under uncertainty. - to interpret the results of mathematical models of strategic interaction with a view to formulating practical recommandations for problem-solving. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Part 1)
1. Present discounted value
2. The main agricultural production factors
3. Decision making tools : global and partial budgets, linear programming, program planning, cluster and factorial analysis, risk analysis
4. The main agricultural branches (including agro-food branches)
5. Transversal issues : taxes, prices, energy costs, pollutions, animal feed, organic production,...
(Part 2)
1. Elements of games in developped forms (including VNM utility)
2. Non-cooperative bargaining (the Rubinstein model and variants)
3. Agency (1) : moral hazard and boiling-in-oil contracts
4. Agency (2) : screening vs statistical discrimination
5. Agency (3) : signaling
1. Present discounted value
2. The main agricultural production factors
3. Decision making tools : global and partial budgets, linear programming, program planning, cluster and factorial analysis, risk analysis
4. The main agricultural branches (including agro-food branches)
5. Transversal issues : taxes, prices, energy costs, pollutions, animal feed, organic production,...
(Part 2)
1. Elements of games in developped forms (including VNM utility)
2. Non-cooperative bargaining (the Rubinstein model and variants)
3. Agency (1) : moral hazard and boiling-in-oil contracts
4. Agency (2) : screening vs statistical discrimination
5. Agency (3) : signaling
Teaching methods
Classes and homeworks
Evaluation methods
Written exams, mainly exercises for both parts
Other information
This course can be given in English.
Online resources
Moodle
Faculty or entity
AGRO
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Agricultural Bioengineering
