All the course material is written inside notebooks. Notebooks whose filename ends with _slides_ are meant to be viewed with Rise or Voila-reveal. Those ending with _tutorial are meant to be run and filled by students.
Each student is expected to have a clone of the course repository, and commit his completed tutorials by Friday night. Intermediary assignments must be done in the same fashion by the next Friday.
During the course, each student will be ased to choose and present one Julia library.
The tutorial in the last session will be the final exam.
To make the most of the course, it is recommended to install
- JuliaPro 1.4 (or Julia 1.4 + a good text editor + JupyterLab)
- Git
Each session is 4 hours, and expected to be evenly but not contiguously divided between lectures and hands-on tutorials.
- General Introduction
- Git + Linux
- Setup
- Julia: Basics
- ...
- Tutorial: contagion model
- Math: Optimization
- Julia: Packages
- Models: Static Trade and Production models
- Cournot
- Computational General Equilibrium
- Math: Series Convergence, Markov Chains
- Julia: Types, Multiple Dispatch
- Models: Discrete Dynamic Programming
- job search
- ressource management
- Julia: performance (1)
- Math: Probabilities and Integration, Distributions
- Simulation heavy models:
- asset pricing (1)
- Math: Differentiation, Perturbation, Linear Algebra
- Local Rational Expectations Models (DSGE)
- neoclassical model
- RBC model
- Math: Function Approximation, Solution Methods (VFI)
- Rational Expectations Models (2)
- consumption-savings
- Math: Weighted Residuals, Solution Methods (TI, ITI)
- Rational Expectations (3)
- Rational Expectations Models (2): DSGE modeling
- FRBNY?
- Exam