Here are some useful teaching resources.
Structural Econometrics in Python and Julia
This set of documents sets up and solves a simple labor economics structural model in Julia. It contains a few introductory exercises and then it develops estimation of both static and dynamic versions of a women labor supply model. Here is the GitHub repository of the complete set of files.
- Handout, written solution. Code (Julia: static simulation, static estimation, static multiple simulation, static multiple estimation, static multiple parallel estimation file 1 and file 2, static bootstrap, static parallel bootstrap file 1 and file 2, dynamic simulation, dynamic estimation, dynamic multiple parallel simulation file 1 and file 2. Python: static simulation, static estimation, dynamic simulation, dynamic estimation).
- Warmup, written solution. Code (Julia: integration and likelihood; Python: integration and likelihood).
- Probit solution. Code (Julia code; Python code).
The Ben Porath and Beyond
- We develop various generalizations of the Ben Porath model here.