About Mixtape Sessions

I believe in democratizing causal inference methods, and try to do so through writing and teaching. Covid showed that it’s possible to teach people using technology. The technology scales, is stable and student expectations have adjusted. That’s what Mixtape Sessions was started for.

Several times a year, I and some others will provide short workshops aimed to train others in skills based contemporary causal methodology at prices that we hope can accommodate a range of people with differing ability and willingness to pay through bundling and price discrimination, as well as with unique add ons like office hours.

But sometimes departments and firms may prefer that I come to them. It would allow their entire department of students and others to receive intense training on their turf. And that’s also great — I’ve done dozens of those around the world. These “in person workshops” can be worked out directly with my assistant, Emmi Scott.

Causal Inference

Mixtape Session

Causal inference is a specialization within economics and statistics that grew out of the labor economics tradition to evaluate the causal effects of programs. While physical randomization was widely known to yield unbiased estimates of causal effects, it was not often used in economics. A wave of new labor economists starting in the late 1970s and mid 1980s changed that as they pushed for focus on exploiting quasi random assignment in natural experiments or through imposed modeling assumptions on counterfactuals. This work in conjunction with pioneering work in econometrics led to the sharpening of such research designs as instrumental variables and difference-in-differences. This workshop will cover foundational elements of modern practices of causal inference such as the potential outcomes model as well as discuss in detail the most common designs: regression discontinuity, instrumental variables, difference in differences, comparative case studies using synthetic control and if time permitting matching. It will be accompanied by efforts to introduce students to basic practices in programming as well as good research practices more generally.

Your Own Workshop

Get in touch!

We can host a custom workshop for your company in person!

Difference-in-Differences

Mixtape Session

The most common quasi-experimental method in the quantitative social sciences is the difference-in-differences research design. This methodology has undergone substantial updates over the last few years as econometricians and statisticians have begun investigating the historical use of panel fixed effects estimators more closely as well as devising alternative models that perform best under heterogenous treatment effects and heterogenous policy adoption. This 1-day workshop will cover the most important new theoretical papers with an aim towards intuition and implementation. It will also include substantial group programming assignments.

Your Own Workshop

Get in touch!

We can host a custom workshop for your company in person!

Instrumental Variables

Mixtape Session

Instrumental variables (IV) is a powerful tool for leveraging external quasi-experimental variation to estimate the causal effects of otherwise confounded (or “endogenous”) variables. This two-day workshop will introduce the basics of IV through different practical examples, formalize the requirements of a valid and powerful IV in the language of both potential outcomes and causal graphs, and discuss common IV implementation issues. Special focus will be paid on interpreting linear IV under heterogeneous treatment effects and recent methodological advances. The course will include substantial group programming exercises, where different IV methods will be illustrated.

Instructor
9 Dates
Your Own Workshop

Get in touch!

We can host a custom workshop for your company in person!

We’ve got more coming...

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