Modul: Advanced Policy Analysis Modelling (4201-420)

Personen:

• Prof. Dr. Christine Wieck (verantwortlich)

Studiengang:

• Agrarwissenschaften - Agricultural Economics (Master, PO vom 01.10.2014)
  3. Semester, Wahlpflicht

Bezug zu anderen Modulen:

This is an advanced methodological module which extends on the materials studied in the modules "Agricultural and Food Policy" and "Microeconomics". The knowledge acquired in this module introduces the student to research methods used to analyse political decisions and their impacts empirically and to the tools required for their practical implementation, and provides a solid understanding of the underlying methods and data to allow an educated judgement of the results and conclusions of such studies.

Teilnahme­vorraussetzungen:

A solid introduction to economics and policy analysis, equivalent to the contents of the modules "Basic Microeconomics", "Agricultural and Food Policy" and "Microeconomics" is required.

Sprache:

englisch

ECTS:

6 credits

Angebotshäufigkeit:

jedes WS

Dauer des Moduls:

1 Semester

Modulprüfung:

The final grade is a weighted grade of two parts: the results from homework assessments (20%) and one 120 minute written final exam (80%). A pass grade is required for each part separately to pass the module.

Prüfungsdauer:

120 Minuten

Arbeitsaufwand:

56 h Präsenz + 104 h Eigenanteil + Prüfung = 160 h Workload

Fachkompetenzen:

Students will
- have an overview about simulation models used in the analysis of agricultural markets and policies and understand which of the different model types are suited to answer specific types of questions,
- understand basic mechanisms of linear and non-linear programming models (LP and NLP),
- be able to formulate simple LP and NLP models in GAMS,
- understand the mechanisms of multi-market models of the agricultural sector,
- be able to formulate simple multi-market models in GAMS,
- understand the mechanisms of general equilibrium models,
- be able to formulate simple general equilibrium models in GAMS,
- understand the data requirements of simulation models,
- understand the driving forces of model results (model mechanisms, parameters, data),
- be able to distinguish between conclusions which can and which cannot be derived from model results.

Schlüsselkompetenzen:

Critical and analytical thinking, abstraction, application of sound economic reasoning, structured work with program and data files on a PC.

Lehrveranstaltungen