Course Schedule 2017

Monetary and Fiscal Policy Analysis with DSGE Models (JV17.34)

DSGE

TARGET GROUP | Mid- to senior-level officials involved in the macroeconomic analysis of monetary and fiscal policy issues with Dynamic Stochastic General Equilibrium (DSGE) models. Participants should have an advanced degree in economics or equivalent experience, strong quantitative skills, and a basic knowledge of MATLAB/Octave and Dynare/Iris. It is recommended that they have taken the online Macroeconometric Forecasting (MFx) course.

 

DESCRIPTION | This two-week course, presented by the IMF’s Institute for Capacity Development, focuses on building, using and interpreting DSGE models. The course will introduce participants to the models and techniques commonly used by policy-makers for analyzing monetary and fiscal issues. The course devotes a large number of lectures to the model design and implementation issues and relies on case studies relevant for the region to illustrate the application of these models and to show how they can be used as an input in the policymaking process. The course discusses the advantages and limitations of these models when used for policy analysis and advice.

 

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

• Describe the models and techniques (computation and estimation) used by policy-makers for analyzing monetary, fiscal and structural issues

• Build a basic DSGE model from first principles using data for a regional country case

• Augment or modify the model structure to address an economic policy question, using stylized evidence in the data

• Apply the DSGE models developed in the course to various policy questions and interpret their results

• Identify the advantages and limitations of these models when used for policy analysis and advice

• Start building a model based on their own country’s data

 


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Course Details

Start: 20171204Dec 04
End: 20171215Dec 15

Language: English

Sponsoring Organization: IMF

Admin Arrangements
Application Deadline: August 30, 2017

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