Colin Cameron: Machine Learning for Microeconometrics

ECN 240F SPRING 2024
Based on Simon Fraser University May 2022

SYLLABUS in 2022:   Syllabus

Key Reading: Chapter 28 "Machine Learning for Prediction and Causal Inference",
in
A. Colin Cameron and Pravin K. Trivedi (2022), Microeconometrics using Stata, Stata Press, forthcoming.

Key Text: ISL2: Gareth James, Daniela Witten, Trevor Hastie and Robert Tibsharani (2021), An Introduction to Statistical Learning: with Applications in R, Second Edition, Springer. A free legal pdf is at https://www.statlearning.com/

In 2023 a Python version of An Introduction to Statistical Learning was released. See
https://www.statlearning.com/

SLIDES UPDATED 2024  All slides zipped

ML_2024_part0_Overview                             Cover all

ML_2024_part1_CrossValidation                   Cover all

ML_2024_part2_Shrinkage_Estimators         Cover all

ML_2024_part3_Causal_Lasso                      Cover to end slide 36

ML_2024_part4_More_Methods                    Focus on regression trees and random forests

ML_2024_part5_More_Causal                       Focus on ATE with heterogeneity

ML_2024_part6_Classification_Unsupervised  Brief discussion

STATA CODE, OUTPUT AND DATASETS  All Stata material zipped

ML_2022_part1.do  (uses Stata addon crossfold, loocv, vselect)

ML_2022_part2.do

ML_2022_part3.do

ML_2022_part4.do  (uses Stata addon rforest)

ML_2022_part5.do

ML_2022_part6.do

mus203mepsmedexp.dta

mus228ajr.dta

ML_2022_part1.txt

ML_2022_part2.txt

ML_2022_part3.txt

ML_2022_part4.txt
ML_2022_part5.txt

ML_2022_part6.txt

A. Colin Cameron / UC-Davis Economics / http://cameron.econ.ucdavis.edu/