Training Program
Monetary and Fiscal Policy Analysis with DSGE Models (DSGE)
Apply online by May 31, 2026 Deadline extended
Session No.: JV 26.29
Location: Vienna, Austria
Date: August 31, 2026 - September 11, 2026 (2 weeks)
Delivery Method: In-person Training
Primary Language: English
Apply NowTarget Audience
Mid-level to senior officials who use Dynamic Stochastic General Equilibrium (DSGE) models in the macroeconomic analysis of monetary and fiscal policy issues.
Qualifications
Participants are expected to have an advanced degree in economics or equivalent experience, solid quantitative skills, and a basic knowledge of MATLAB/Octave and Dynare/Iris – specific knowledge of these is not required. It is recommended that applicants have completed the online Monetary Policy Analysis and Forecasting (MPAFx) course.
Course Description
This course, presented by the Institute for Capacity Development, focuses on building, using, and interpreting DSGE models. It aims to familiarize participants with the models and techniques commonly employed by policymakers to analyze monetary and fiscal matters. The course dedicates numerous lectures to addressing model design and implementation issues. It uses region-specific case studies to demonstrate the practical application of these models and their potential contributions to the policymaking process. Additionally, the course explores the benefits and limitations of utilizing these models for policy analysis and advice.
Course Objectives
Upon completion of this course, participants should be able to:
- Describe the models and techniques (simulation and estimation) that policy makers use in analyzing monetary, fiscal, and structural issues.
- Augment or modify the model structure to address an economic policy question.
- Apply the DSGE models developed in the course to various policy questions and interpret their results.
- Identify the advantages and limitations of the models when used for policy analysis and advice.
- Participants will learn to construct a basic DSGE model from first principles using data specific to their own country in the region.
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