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Special Workshop on Macroeconomic Modeling and Simulation

The Center for Positive/Empirical Analysis of Political Economy will offer special workshop series on Macroeconomic Modeling and Simulation by Prof. Junior Maih of the Norges Bank and Norwegian Business School. Please find more detail including registration information.

TGU Workshop on Macroeconomic Modeling and Simulation

Presenter: Prof. Junior Maih (Norges Bank, Norwegian Business School)

Date: from October 26 to December 7, Every Monday from 14:45 to 16:30

Open to students, faculty members and the general public (Free webinar)

Language: English

Venue: Webinar


This is an introductory workshop to the modeling of macroeconomy.
While the workshop is meant for graduate students and professionals, it does not require prior knowledge of the complexities involved in DSGE (DSGE) modeling and or the RISE toolbox, which will be used for applications.

The intention of the introductory workshop is not to train participants to become specialists in the field but instead for them to understand a basic exposure to the main techniques involved in solving and analyzing DSGE models so that they may start using those techniques in their work. Although no prior knowledge of DSGE modeling is assumed it is a fast-paced training and additional reading is provided to help participants to consolidate material. By the end of the workshop participants should:-Understand the economic foundations of DSGE models and how they relate to policy issues-Be able to write dynamic models in a general form suitable for solution, simulation and estimation in a computer using the RISE toolbox.-Implement basic solution and simulation techniques to analyze DSGE models, showing how the model economies respond to different shocks.


Planning of the Workshop (7 sessions x 90 minutes)

Lecture 1: Constant-parameter DSGE modeling and Introduction to RISE (10/26)

A prototypical DSGE model Solution strategies The RISE programming environment Implementation of the model Calibration Deterministic solutions

Lecture 2: Stochastic solution via first-order perturbation (11/2)

The steady state The dynamics Basic usages of the solution

Lecture 3: Advanced simulations (11/9)

Anticipated shocks filtering historical decompositions Scenarios Unconditional forecasting Conditional forecasting

Lecture 4: Bayesian Estimation (11/16)

Implementation of priors Measurement errors: importance and implementation Posterior maximization Posterior simulation Illustrating uncertainty

Lecture 5: Optimal policy (11/23)

Commitment Discretion Loose commitment

Lecture 6 & 7: Introduction to the simulation of SIR-Macro models (11/30, 12/7)


Required environment: Matlab (core matlab, optimization toolbox, statistics toolbox) MikTex, dropbox, oxedit (optional)

For subscription please contact: [email protected]

Sponsor: Center for Positive/Empirical Analysis of Political Economy, Top Global University Project, Waseda University

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Thu, 15 Oct 2020

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