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MPAFx

Model-Based Monetary Policy Analysis and Forecasting (MPAFx)

Deadline passed

Session No.: OL 24.180

Location: Course conducted online

Date: May 1, 2024 - August 31, 2024 (18 weeks)

Delivery Method: Online Training

Primary Language: English

    Target Audience

    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.

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    Qualifications

    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.

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    Course Description

    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.

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    Course Objectives

    Upon completion of this course, participants should be able to:

    • Explain the key building blocks of a canonical semi-structural QPM.
    • Interpret the key model equations from a macroeconomic point of view.
    • Implement a simple QPM using a specialized software for macroeconomic modelling.
    • Distinguish the key elements of a QPM in a state-space form (i.e., shocks, observable and unobservable variables, measurement and transition equations, steady-state parameters, equation coefficients).
    • Identify necessary codes for data transformation, filtration and evaluation of the QPM properties.
    • Apply the basic IRIS Toolbox functions for solving the model.
    • Create output reports using model codes.
    • Develop a basic calibration of the QPM.
    • Produce a baseline forecast and alternative scenarios using the QPM.
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