CGE Microsimulations for Poverty & Food Security

CGE Model Linked Microsimulations for Poverty & Food Security

6-Days Online Workshop       Nov. 2025

 

Deadline:  15th Nov

Standard Fees: €480

Group Fees (3+) / GEM/CGE program graduate / Affiliates: 320€

Student Fees (valid ID required): 180€


We Proudly Trained Teams from

world bank IMF ECA Qatar Sydney

Workshop Description:

Download the workshop's training plan here

Modeling global land allocation

By the end of this workshop, participants will be able to conduct policy-relevant simulations, interpret model outputs, and produce evidence-based insights to inform strategies for sustainable and inclusive development.

This hands-on training is designed to equip participants with the technical and analytical skills needed to link microsimulation techniques with Computable General Equilibrium (CGE) modeling for in-depth welfare and poverty analysis. The workshop provides a comprehensive understanding of how household-level data can be integrated with macroeconomic model outputs to analyze the impacts of policies on poverty, food security, and nutrition outcomes.


Using the MIRAGRODEP-POVANA framework and GAMS software, participants will learn how to design, run, and interpret models that bridge the gap between macroeconomic policy simulations and household-level welfare impacts.


Key Learning Objectives

Participants will learn to:

  • Develop and run a simple household welfare model linked to CGE model outcomes.
  • Utilize household survey data to analyze production and consumption patterns.
  • Conduct poverty, food, and nutrition security assessments using the MIRAGRODEP-POVANA model.
  • Simulate and evaluate policy interventions at both national and global levels.


Comprehensive Policy Analysis

To equip public officials, researchers and academic staff with the skills and knowledge necessary for conducting comprehensive policy analysis and economic modeling.

CGE Microsimulation

To provide practical training on building CGE microsimulations  for conducting policy simulations about poverty and food security. 

Workshop Highlights



  • 6-Day online weekend (Saturdays and Sundays) workshop, totalling 12 hours.


  • Practical simulation tutorials using GAMS


  • Live interactions with a moderator will be

    facilitated, offering participants the opportunity to ask questions and engage in extended discussions.


  • Real policy modeling scenarios, findings, and

    Recommendations will be provided, which can be utilized in reports, white papers, and policy briefs.



saudi arabia
saudi arabia

Meet The 


Moderator

IFPRI profile link

A. Mamun is a Senior Research Analyst at the International Food Policy Research Institute (IFPRI) and an Adjunct Professor at the University of the District of Columbia. He is a quantitative economist with over a decade of expertise in econometric analysis, computable general equilibrium (CGE) modeling, and microsimulations for poverty and food security impact analysis. He holds a PhD in Economics from the University of Bordeaux, France, and an MS in Economics from the University of Wisconsin-Madison

Target Participants

  • Graduates of M&S Research Hub’s GEM/CGE programs who wish to sharpen and complement their modeling and microsimulation skills through practical applications using the MIRAGRODEP-POVANA framework.
  • Government officials and policy analysts from ministries of economy, agriculture, planning, and social development engaged in evidence-based policy making.
  • Researchers and academics specializing in applied economic modeling, development economics, or impact evaluation.
  • Experts from international organizations such as the FAO, UNDP, and World Bank working on poverty, food security, or sustainability assessments.
  • Economists and consultants from think tanks and NGOs interested in combining macroeconomic modeling with household data analysis.


Policy Areas of Interest Covered in Workshop

labor market saudi arabia

Poverty analysis

neom

Household data analysis

VAT adjustments

Food Security & Agricultural Productivity

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