ScPo-CompEcon CoursePack¶
This website contains the course material for the computational economics course at Sciences Po taught by Florian Oswald.
For the assosciated homeworks, please go to our github organization, which lists all of them. Instructions contained within.
Much of the below material is derived from the excellent QuantEcon project. Thanks to the entire team for making this material available. Each quantecon-derived notebook will clearly indicate that on top.
Course Materials¶
You can look at the material in a variety of formats. All content is created as IJulia notebooks, which you can edit on your computer, and from those notebooks I create html rendered versions, pdfs and html slides.
Slides¶
Most of those are HTML slides. You should be connected to the internet to look at them.
- Intro: Why Julia?
- Getting Started
- Tools and Editors
- Julia By Example
- Fundamental Types
- Julia Essentials
- The Need for Speed
- Data and Statistical Packages
- Plots.jl
- Testing
- Numerical Integration
- Function Approximation
- Optimization I
- Optimization II
- Dynamic Programming
- Julia HPC
Rendered Notebooks¶
These are IJulia notebooks that I rendered for you. You cannot enter code into those (you can interact with some graphics though). For the actual notebooks, please see next section.
- Getting Started
- Tools and Editors
- Julia By Example
- Fundamental Types
- Julia Essentials
- The Need for Speed
- Benchmarking against other languages
- Data and Statistical Packages
- Plots.jl
- Testing
- Numerical Integration
- Function Approximation
- Optimization I
- Optimization II
- Dynamic Programming
- Julia HPC
Notebooks¶
You can download those to follow along with the steps I'll be doing in class. You will need to run the notebook either through jupyter or by calling notebook() from within Julia. There is a link to access the quantecon version wherever applicable.
- Getting Started
- Tools and Editors
- Julia By Example
- Fundamental Types
- Julia Essentials
- The Need for Speed
- Benchmarking against other languages
- Data and Statistical Packages
- Plots.jl
- testing
- Numerical Integration
- Function Approximation
- Optimization I
- Optimization II
- Dynamic Programming
- Julia HPC
- Solving the Growth Model in 7 Ways
Pdf¶
- Intro: Why Julia?
- Numerical Integration
- Function Approximation
- Optimization I
- Optimization II
- Dynamic Programming
- Estimating DP models
- MPEC for starters
Term Project¶
How to build this¶
You should only worry about this section if you want to rebuild the site yourself.
Requirements¶
#python
#latex
#ruby
pip install jupyter
pip install pandoc
Building¶
in the root of this repo do
rake # builds all
rake html # builds only html
rake slides # builds slides
rake offline # builds offline slides; mathjax doesn't work properly offline.