Notebooks | Schedule | Exercises |
Resources
These turorials provide an introduction to computational methods for macroeconomics.
Most of the material will also be made available via SUNLearn. However, for the most up to date version of the work you can refer here.
It is not required that you know how Git and Github works in order to work through the tutorials. I will give some basic instructions in the first tutorial, so those that want to delve more into version control are able to get started.
Below are my details. You can contact me via email.
| Dawie van Lill | |
|---|---|
| [email protected] | |
| Office | Schumann 511 |
| GitHub | DawievLill |
In order to run these tutorials online, without installing anything, you can follow the link below:
NB: Wait for the program to finish running. Once the program has finished running you need to go to the notebooks folder and then click on the appropriate notebook. You can then run the code in the cells one by one.
You can also view the notebooks in their HTML form by clicking on the link below.
Finally, you can view the notebook at nbviewer by copying and pasting the notebook URL.
If you are still struggling, you can go to the PDF folder on this repository and view the PDF.
For those of you who want to run the notebooks locally (on your own computer), find the installation instructions at section 1.3 of the QuantEcon site here
This course schedule will be updated frequently, so please check before the tutorial for the video recording and notes. The links to the notebooks can also be found below. However, these are not interactive, so you can not run them unless you have Python, Julia and Jupyter installed on your computer. You will only be able to view their content. I will speak about this some more in the lecture.
Compulsory content: The slides contain all the compulsory content and are a shortened version of the full notebooks.
If you want a deeper understanding of the material you can access the notebooks for more in depth explanations. However, if you are only interested in completing the problem sets then the information in the slides will be enough.
If you are considering postgraduate studies in Economics I recommend that you read all the content in the notebooks. This will greatly help with your preparation.
There are also optional sections in the notebooks that are meant for students who have an interest in computational methods. These sections are generally a bit more difficult.
| Tutorial | Topic | Notebook | Slides | Problem Set |
|---|---|---|---|---|
| #1 | Introduction to Julia | [deepnote / .ipynb / .html] | [.ipynb / .html] | [.ipynb / .html] |
| #2 | Data, statistics and basic math | [.ipynb / .html] | [.ipynb / .html] | |
| #3 | Optimisation and the consumer problem | [.ipynb / .html] | [.ipynb / .html] | |
| #4 | The Solow-Swan model | [.ipynb / .html] | [.ipynb / .html] |
In this class we will be doing several tutorial exercises. Some of them will be done by hand and others on computer. The exercises for each week will be posted on this Github page as soon as possible. I will also post them on SUNLearn if that is easier to access for students.
For a good introduction to Julia I would recommend,
- [Julia] QuantEcon. Getting Started with Julia. https://julia.quantecon.org/getting_started_julia/index.html
- [Julia] Paul Soderlind. Julia Tutorial. https://github.com/PaulSoderlind/JuliaTutorial
- [Julia] Czech Technical University. Julia for Optimasation and Learning. https://juliateachingctu.github.io/Julia-for-Optimization-and-Learning/stable/
- [Julia] Ben Lauwens and Allen Downey (2018). Think Julia: How to Think Like a Computer Scientist. https://benlauwens.github.io/ThinkJulia.jl/latest/book.html
Good introductory notes for computational economics that use Python are the following
- [Python] Fedor Iskhakov. Foundations of Computational Economics. https://fedor.iskh.me/compecon
- [Python] Jeppe Druedahl. Introduction to Programming and Numerical Analysis. https://numeconcopenhagen.netlify.app/
I have used these resources to compile these notes and tried to give the proper acknowledgment throughout.
Textbook: Williamson, S. Macroeconomics. 4th edition.