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Module 7100
Applied Computable General Equilibrium Modelling

Instructors

The course is offered at the International Agricultural Trade and Development Group, Faculty of Life Sciences, Humboldt-Universität zu Berlin, Hannoversche Str. 27, Haus 12. The instructors are:

PD Dr. Khalid Siddig. Tel.: 030 2093 46813, Email: khalid.siddig@hu-berlin.de
Prof. Dr. Harald Grethe. Tel.: 030 2093 46810, Email: grethe@hu-berlin.de
Dr. Jonas Luckmann. Tel.: 030 2093 46811, Email: luckmann@hu-berlin.de

Objectives

Students

Course description

This course is designed for advancing the experience of participants with basic knowledge and experience in CGE modelling in GAMS and prepare them for using and adapting state of the art/standard CGE models for own research. It starts by a brief refreshment on the basics of CGE modeling in GAMS and SAM estimation before running real-world experiments in open economy multi-sectoral CGE models.
Acknowledging that CGE models produce comprehensive results, the course dedicates some time to providing hands-on training on how to better analyze and present CGE results. Afterwards, participants will produce and assess results under different model settings considering various assumptions and parametrizations.
After assuring that participants are familiar with designing, running and analyzing experiments in standard CGE models, the course will propose and highlight various options of extending standard CGE models in various dimensions. For the time being, these include:

The course is a combination of lectures, PC demonstrations, group work and assignments. During the course, participants will work in subgroups in parallel and prepare a presentation on a selected topic. On the last day of the course, the groups present and discuss their findings with all participants. Instructors will provide feedback and will be available during the group work phases to help with technical problems and/or to answer related questions.

Course schedule and outline

Date Content

Before the course

  • Read mandatory background readings,
  • Scan optional readings on various model documentations, GAMS, SAM estimation, etc.

Monday

  • Introduction to the course,
  • Recap on GAMS and viewing reference files and GDX in GAMS IDE,
  • Brief introduction to simple CGE models in GAMS.

Tuesday

  • Methods of SAM estimation,
  • Policy simulations using the STAGE model,

Reviewing CGE results under various closure rules and assumptions.

Wednesday

  • Discussion on selected extensions of standard CGE models including (note: these extensions could change every year):
    • options of labor mobility and employment,
    • working with satellite accounts,
    • options for modeling quotas and technological change,
    • integration of stochastics.
  • Elaborative introduction to two selected model extensions, namely:
    • options of labor mobility and employment,
    • options for modeling quotas and technological change.
  • Assigning groups for presentations and distribution of topics in relation to the two selected model extensions

Thursday

  • Exercises
  • Group work

Friday

  • Presentations
  • Exams (voluntary; 15 minutes per person)

Teaching methods

Lectures (20%), Student presentations (15%), PC-demonstrations (15%), Hands-on-exercises (50%)

Grading (if desired): Presentations (30%), Assignments (30%), Oral exam (40%)

Credit points: 3

Workload: 40 contact hours during the course; 50 hours of pre- and during course self-study

Requirements

References (background reading)

If you face difficulties to access any of the background reading materials, please contact the course instructor to receive them by email in pdf format.
On GAMS:

Basic CGE modeling in GAMS:

On SAM estimation and analysis:

On standard CGE modeling in GAMS:

On labor mobility and employment:

On water-focused CGEs with satellite accounts for water:

On tariff-rate quotas in CGE models:

Other optional readings:

Software: GAMS with GDX Viewer: free demo-version available from: https://www.gams.com/

Language: English

Organization and time: This is a one-week, full day, blocked course.