ECON 400 Course Notes

Lecture Notes By Topic¶

These notes are intended for my students and are a synthesis of numerous sources including:

• Bayesian Data Analyis, 3rd Edition (Gelmen et al.)
• Conteporary Bayesian Econometrics and Statistics (Geweke)
• Series of blog posts
  • Thomas Wiecke (http://twiecki.github.io/)
  • Jake Vanderplas (https://jakevdp.github.io/)
• Selected lecture notes by Patrick Lam (http://www.patricklam.org/)

Of course, all errors are my own.

Preliminaries and Review¶

Please install Anaconda Python following these instructions.

1. Maximum Likelihood (from ECON407).
2. Python Numpy Linear Algebra
3. Python Pandas Basics
4. Python Statistical Functions in Scipy Basics.

Bayesian Statistics and Python¶

1. Sampling Methods and Frequentist Statistics
2. Introduction to Bayesian Statistics
3. Bayes Rule and Monte Carlo Markov Chains
4. Properties of MCMC
5. Convergence Diagnostics
6. Inference
7. Introduction to PyMC3
8. Sampling Methods

Some Models¶

1. Heirarchical Models
2. Multinomial Probit
3. Time Series Applications
4. Switching Models
5. Time Series Models