Intended to implement multiple-indicator, multiple-cause (MIMIC) modelling with discrete indicators in R.
Teaching material for Lectures in Dynamic Programming
Replication of Networks in Conflict Econometrica Paper
"Computational Methods for Economists using Python", by Richard W. Evans. Tutorials and executable code in Python for the most commonly used computational methods in economics.
Econometrics lecture notes with examples using the Julia language
Labor Mobility with Environmental Regulation
Implementing the BLP method for random effects choice model using Julia.
A Python version of Miranda and Fackler's CompEcon toolbox
Collection of published papers that estimate dynamic programming models
Python and Julia Code for Structural Behavioral Economics
Structural Applied Micro Graduate Course Problem Set
promotional material for our work on Eckstein-Keane-Wolpin models
Collection of published papers that estimate dynamic programming models
design, solve and estimate discrete dynamic programs.
An applied-micro tutorial using Python on Jupyter notebook showing how to perform a structural estimation excercise using finite dependence and bootstrapping.
Topics in Advanced Econometrics (ResEcon 703). University of Massachusetts Amherst. Taught by Matt Woerman
Code to solve exercises from Adda and Cooper's "Dynamic Economics" book
MACS 40200 (Winter 2020): Structural Estimation
Teaching materials from DSE2019 summer school at Chicago Booth
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