Econometrics

“… all models are approximations. Essentially, all models are wrong, but some are useful. However, the approximate nature of the model must always be borne in mind…” – George Box

Free Material

Software
  1. A short STATA primer that I wrote for a class of second-year undergraduate students when I was a TA.
  2. A Very Short Introduction to R and RStudio by Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer. This is part of a general free online textbook called Introduction to Econometrics with R.
  3. Introduction to Python at Kaggle.com
Time series forecasting
  1. Point forecast evaluation
Bayesian Econometrics

I taught a Ph.D. level, Introduction to Bayesian Econometrics in Julia. Topics include

  1. What is Bayesian Econometrics?
  2. Introduction to Monte Carlo Sampling
  3. Markov chain Monte Carlo (MCMC)
  4. Linear Regression with Normally distributed errors
  5. Linear Regression with Student’s t-distributed errors
  6. Vector Autoregressions
  7. State-space models

For more content, I recommend the free notes on Bayesian Macroeconometrics by Joshua Chan.

Algorithms for State Space Models
  1. The Kalman Filter with the estimation of an unobserved components model in MATLAB.
  2. Durbin and Koopman Simulation Smoother with the estimation of an unobserved components model in MATLAB.
  3. Precision Sampler with the estimation of an unobserved components model – MATLAB code is provided by Joshua Chan here.

Recommended Textbooks

Introduction to Classical Econometrics
  1. Introduction to Econometrics by James Stock and Mark Watson
    •  I recommend this book to anyone who is taking their first course in econometrics. It is by far the nicest introduction to econometrics that I’ve come across. They also have a complete list of solutions to odd-numbered exercises.
Introduction to Bayesian Econometrics
  1. Bayesian Econometrics by Gary Koop
    • This textbook is a classic in Bayesian econometrics. It is self-contained and focuses on fundamental models. Gary also provides each of the programs and data sets used in the chapters on the website. I recommend it to anyone who wants to learn the basics of Bayesian Econometrics.
  2. Bayesian Econometric Methods (Econometric Exercises) 2nd Edition, by Joshua CC Chan, Gary Koop, Dale Poirier and Justin Tobias
    • This textbook contains over 100 exercises and solutions on most topics in Bayesian statistics. It’s an excellent complement to Gary’s book “Bayesian Econometrics”. It also has MATLAB code on the website. I recommend it to anyone who wants to learn how to solve Bayesian models.
 Time Series Analysis
  1. Applied Econometric Time Series by Walt Enders
    • This is the standard textbook for applied macroeconometrics courses at most universities. It provides a good introduction for basic ideas in time series analysis. One weakness is that it doesn’t provide any insight on how to code the models; which is an important skill to have.