This repo contains lab materials (and other helpful Julia resources) for David Evans' Spring 2021 PhD Core Macro III course at University of Oregon.
All lab work will be done using Jupyter Notebook.
Materials will be updated and new materials will be posted as we progress into the Spring quarter. I will email the class about all major updates/additions as they happen. You can also stay on top of all changes by frequently pulling from the repo.
The goal of this lab is to:
- Set up GitHub (to keep track of repo updates);
- Set up our work environment (download and install Julia + Jupyter);
- Cover some Jupyter Notebook basics;
- Cover some Julia basics.
Note: Completing the above is crucial for the remaining quarter!
The materials for this week can be found in the week01
folder, which contains:
lab01.ipynb
-- week 1 lab notebook.
You should be able to view rendered versions of both of the above documents by navigating to them here on GitHub.
This lab will cover:
- User-defined functions;
- Loops;
- Linear algebra applications;
- Modeling finite Markov chains.
The materials for this week can be found in the week02
folder, which contains:
lab02.ipynb
-- week 2 lab notebook.
This week's lab will cover:
- The McCall Search Model;
- Value function iteration.
The materials for this week can be found in the week03
folder, which contains:
lab03.ipynb
-- week 3 lab notebook.
This week's lab will cover:
- Using the Negishi algorithm to compute equilibria in Arrow-Debreu economies.
The materials for this week can be found in the week04
folder, which contains:
lab04.ipynb
-- week 4 lab notebook.
This week we'll take a little break from Julia, and instead go through a practice midterm.
This week's lab will cover:
- A basic growth model;
- Dynamic programming;
- Finding policy functions using value function iteration.
The materials for this week can be found in the week06
folder, which contains:
lab06.ipynb
-- week 6 lab notebook.
This week's lab will cover:
- Solving for recursive competitive equilibria using both centralized and decentralized approaches;
- Finding policy functions using value function iteration;
- Finding optimal price systems under recursive competitive equilibria;
- Simulating recursive competitive equilibria.
The materials for this week can be found in the week07
folder, which contains:
lab07.ipynb
-- week 7 lab notebook.
This week we'll go through assignment #5. No Julia.
This week's lab will cover:
- Computing for the stationary equilibrium of a Huggett model.
The materials for this week can be found in the week09
folder, which contains:
lab09.ipynb
-- week 9 lab notebook.
We will finish the quarter (and the year) off with a practice exam.