Introduction to DSGE models Level 1

This seminar is the first part of a two-session course on dynamic stochastic general equilibrium (DSGE) models.
Dynamic stochastic general equilibrium (DSGE) models are important tools for central banks to assess the macroeconomic impact of monetary and fiscal policy and run macroeconomic forecasting. These structural models where the general equilibrium results from the interaction of agents of which objectives and constraints have been modelled allow to better explicit the impact of policies or scenarios on the economy and its sectors. Since the latest financial crises, academics and economists have worked to enhance the integration of financial frictions and non-linear effects in DSGE models. Also, DSGE models have been used to assess the effects of unconventional monetary policy on the economy.


Dates: 18 - 22 January 2021

Apply before: 15 November 2020

Language: English (with video replays in English and French)

Venue: Online

Contacts: Michel Juillard / Louis Bê Duc



This seminar will be organised and run by Michel Juillard, scientific advisor at Banque de France and initiator of the DYNARE Project. Dynare is a free software developed mainly by a core team of researchers at CEPREMAP (see Other presenters will be Banque de France economists, experts in DSGE for economic analysis and research.

Mornings will be dedicated to presentations of the main concepts, afternoons to case studies based on the DYNARE platform. The seminar will comprise the following sessions:

  • Introduction to DYNARE

  • The neoclassical growth model

  • Neo-Keynesian extensions

  • Introduction to Bayesian econometrics

  • Case studies: a full-fledged example


This seminar is intended principally for central bank economists working in the field of macroeconomics and monetary policy.

Participants will have prerequisites in economic modelling:

  • Academic training (PhD in economics, possibly Master only if relevant experience)

  • Actual experience for several years in economic modelling including DSGE

  • Prior knowledge of Matlab or Octave software will be appreciated

  • A detailed CV is required

Participants are expected to bring their own PC with Matlab or Octave software.


Updated on: 11/04/2020 18:37