Participants are expected to have a background in undergraduate macroeconomics, statistics, and econometrics. Participants are provided with guidance on how to access Matlab or Octave software.
Deadline passed
Session No.: OL 25.238
Location: Course conducted online
Date: September 1, 2025 - December 31, 2025 (18 weeks)
Delivery Method: Online Training
Primary Language: English
All government officials are welcome to register. The course is particularly well-suited for officials in central banks that are in the early stages of introducing Forecasting and Policy Analysis Systems (FPAS) with IMF assistance. The course is offered in English.
This online course, presented by the Institute for Capacity Development, introduces participants to a semi-structural macroeconomic model often used as a core of FPAS (Forecasting and Policy Analysis Systems) at the central banks. It also shows how to implement the key equations of a canonical quarterly projection model (QPM) in a macroeconomic modeling software. This course uses detailed country data highlighting an inflation targeting central bank, for hands-on historical filtration, forecasting, and calibration exercises.The course covers two main technical aspects: introduction to a canonical New Keynesian model structure and its key properties; and implementation of the QPM in Matlab/Octave and the application of IRIS toolbox for solving and maintaining the QPM, as well as forecasting with the QPM.
Upon completion of this course, participants should be able to:
English | August 13, 2025 - April 15, 2026 | Online Training | Course conducted online
Apply online by April 1, 2026
English | May 1, 2025 - April 15, 2026 | Online Training | Course conducted online
Apply online by April 1, 2026
English | May 1, 2025 - April 15, 2026 | Online Training | Course conducted online
Apply online by April 1, 2026
Spanish | May 1, 2025 - April 15, 2026 | Online Training | Course conducted online
Apply online by April 1, 2026
English | May 1, 2025 - April 15, 2026 | Online Training | Course conducted online
Apply online by April 1, 2026
