Course on Applying Quantitative Models for Integrated Policy Analysis

Macroeconomic outcomes are the results of very complex interactions of different factors operating in an economy, and a model is just a simplified abstraction of how the actual economy works. Even so, models that draw on economic theory and practical experience have great advantages. They make it possible to analyze interdependent relationships and to estimate a comprehensive picture of economic outcomes, which is particularly helpful when comparing alternative policy options. 

With these considerations in mind, economists from the IMF’s Monetary and Capital Markets Department (MCM) developed the QIPF model. The model constitutes a key element and implementation of the Fund’s Integrated Policy Framework (IPF) – a new analytical approach to help countries respond to fluctuations in international capital flows. The IPF acknowledges that such flows can provide significant long-term benefits but can also pose some challenges in the short run. As a consequence, full exchange rate flexibility may not always be desirable, especially in the face of the financial frictions and vulnerabilities that many emerging markets and low-income countries face. The QIPF model is already being used successfully to support the IMF’s Article IV consultations and help expand modeling capacity in a number of central banks. 

To learn more about the QIPF model and how to practically use it for quantitative policy analysis, 21 officials from the JVI region’s policymaking institutions gathered in Vienna in the second week of August to attend the Quantitative Integrated Policy Analysis course. It was delivered by MCM economists Marcin Kolasa (former JVI course participant and now instructor!), Ruy Lama, and Jesper Lindé. 

The course combined lectures with hands-on workshops focused on applying the QIPF model to inform monetary, foreign exchange intervention, and macroprudential policy decisions. The participants explored topics such as modeling small open economies, financial frictions, and scenario analysis. The course also demonstrated how model estimation can be used to account for country-specific characteristics, and how the estimation outputs can be used to help interpret economic developments. The participants applied the theory that they learned in practical hands-on sessions and presented a final group project analyzing trade-offs and implications of alternative policy options in a vulnerable small open economy. 

The workshop sparked lively discussions on how model-based analysis can support central bank policy decisions. Feedback was very positive, with participants appreciating the balance between theoretical content and practical exercises. 

Marcin Kolasa, Senior Financial Sector Expert, IMF