Machine Learning and Heterogeneous Effects

•Starting November 15th, 2023

The holy grail of causal inference is the individual-level treatment effect: how would a particular patient respond to a drug? Which users will respond most to a targeted ad? Would a given student be helped or harmed by a classroom intervention? This session introduces machine learning tools for estimating heterogeneous treatment effects like random causal forests. The course goes over the theory and concepts as well as the nitty-gritty of coding the methods up in python, R, and Stata using real-world examples. This course can be taken as a follow-up to the Machine Learning and Causal Inference mixtape session, or as a stand-alone course.

This is one of our advanced courses. These courses are designed assuming a solid foundation in the basics of machine learning and causal inference and will cover the frontiers of the topic. A good review is the intro course: https://github.com/Mixtape-Sessions/Machine-Learning.

All course material is available free and open source via our Github Repository .

Register Today

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WHAT'S INCLUDED

Attendance to the workshop with Prof. Brigham Frandsen.
Complete set of example code to implement the methods discussed.
PDF lecture slides and video recordings for later reference.

295 USD + Fees

Buy Your Ticket

$50 for Students•$1 for Low-income Countries

Our workshop will bring you to the cutting edge

November 15th

Day 1•6pm-9pm EST

Machine Learning and Heterogeneous Effects

Who will be hosting this session?

Brigham Frandsen is an associate professor at Brigham Young University after completing his Ph.D. in Economics at MIT, where his dissertation focused on econometric methodology and labor economics. After his Ph.D., Dr. Frandsen was selected as a Robert Wood Johnson Scholar in Health Policy Research at Harvard University where he spent two years in residence furthering his research in econometrics and labor economics, as well as adding health policy to his research agenda. Dr. Frandsen's methodological research focuses on causal inference on distributional effects. He applies these methodologies to questions about the impact of labor market institutions and interventions on education and earnings outcomes. His health policy research deals with the consequences of fragmentation in the U.S. health care system. In addition to research, Dr. Frandsen enjoys hiking and mountain biking with his wife, Christine, and their four children.

“
Insightful, well-explained and hands-on workshop that taught me a lot. Dr Frandsen was super helpful and explained concepts clearly. It was a great mix of interactive, practical exercises and theoretical explanations!
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Outstanding selection of content and case studies. Excellent instructor. You will come out of this workshop with a very decent overview of Machine Learning methods and their applications in causal inference.

Frequently Asked Questions

Are discounts available?: Yes! Students, postdocs, predocs and residents of middle-income countries can attend for $50 plus a few dollars in fees. To receive your promo code, please include a photo of your student ID. International folks from low-income countries can attend for $1. To receive promo codes, email us at causalinf@mixtape.consulting.
How do I access the material I need for the course?: The course material will be availabe forever on Github. We will also send you links to the video recordings on Vimeo after the workshop is completed.
How long will it take me to master this?: That's a great question. Causal inference, and econometrics more generally, is largely a “returns to experience” type of skill as much as it is a returns to education. The best way for you to learn anything in these classes is to work on projects that require it. Our class is designed as a fast track to both.
Will we practice programming?: Yes, I will distribute assignments with readings with directions the night before. We will help each other in Discord, asking questions, pointing out mistakes I'm making, and helping one another problem solve. I will usually assign more than we can do that faster workers always have something to work on. And in the end, I will distribute the solutions. It'll be fun I promise!
Will there be recordings?: We will upload recordings to Vimeo and they will be password protected, so that only attendees can watch the videos.
I'm nervous that I can't handle the difficulty of the class.: Don't be. I'm a good teacher. If I can learn this, so can you.