ComputationalMethodsClass

Materials for 47-809 Computational Methods for Economics at Carnegie Mellon

Notes and other materials descend from previous versions of the class due to Y. Kryukov, K. Judd, and U. Doraszelski

Lectures and Materials

The class is organized into topic lectures, some of which are accompanied by demonstration notebooks, in Julia and/or Python.

1. Computational Methods General Intro

• Julia Notebook: Code Intro
• Python Notebook: Code Intro

2. Linear Equations

3. Nonlinear Equations

4. Optimization

• Julia Notebook: Optimization

5. Function Approximation

• Julia Notebook: Chebyshev Methods
• Python Notebook: Chebyshev Methods

6. Integration

• Julia Notebook: Integration
• Python Notebook: Integration

7. Functional Equations

• Julia Notebook: ODEs
• Python Notebook: ODEs

8. Dynamic Programming: A: Discrete and B: Continuous

9. Optimal Control

• Julia Notebook: Pontryagin and HJB
• Python Notebook: Pontryagin and HJB

10. Perturbation

• Julia Notebook: Perturbation via DifferentiableStateSpaceModels.jl
• Dynare Model Example: First install and run Dynare

11. Heterogeneous Agents

• Julia Repo

12. Neural Network Methods

• Guest Lecture: Arnav Sood
• Python Notebook: Pytorch