Workshop on Parameterizing Macroprudential Models

Download workshop leaflet

Format

• Lectures accompanied by simulation exercises

Content

This workshop equipped participants with the knowledge and tools to effectively parameterize macroprudential models. Through a combination of lectures, discussions, and hands-on exercises, participants gained a deep understanding of:

• The inherent difficulties associated with calibrating macroprudential models.
• Calibration versus estimation: When to use each approach and the pitfalls of traditional methods.
• Common calibration strategies and their applications: Explore effective techniques tailored for macroprudential models.
• Addressing unique model features: Learn how to handle nonlinearities and asymmetries during calibration.
• Model verification and "smell tests": Ensuring your model is well-calibrated and reflects real-world behavior.
• Data requirements for successful calibration: Identify the necessary data types and considerations.

The workshop was based on the in-house GIMM modeling framework implemented in Python.

Benefits

Participants received the following:

• Complete modeling framework - equations, documentation, understanding of key transmission channels
• Commented codes - model files, simulation files, data files, reporting files
• Presentations

When, where

Dates: October 7-10, 2024, 4 day event

Place: Prague, Czech Republic