“The Classics”

Our flagship Causal Inference Series

This three-part series is designed to survey the large and complicated field of causal inference following the structure of Scott Cunninghams’s book, Causal Inference: The Mixtape. We will review the theory behind each of these research designs in detail with the aim being comprehension, competency and confidence.

Causal Inference I

Prof. Scott Cunningham

Starting January 25th

Causal Inference Part I kickstarts a new 4-day series on design-based causal inference series. It covers the foundations of causal inference grounded in a counterfactual theory of causality built on the Neyman-Rubin model of potential outcomes. It will also cover randomization inference, independence, matching, regression discontinuity and instrumental variables. We will review the theory behind each of these designs in detail with the aim being comprehension, competency and confidence. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. To help accomplish this, we will hold ongoing discussions via Discourse, work through assignments and exercises together, and have detailed walk-throughs of code in R and Stata. This is the prequel to the Part II course that covers difference-in-differences and synthetic control.

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

  • Potential Outcomes

  • Matching Methods

  • Instrumental Variables

  • Regression Discontinuity

Causal Inference II

Prof. Scott Cunningham

Starting March 22nd

Causal inference Part II is a 4-day workshop in design based causal inference series. It will cover difference-in-differences starting from the basics and taking readers into more contemporary design elements with staggered adoption and the incorporation of covariates. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. We will review the theory behind each design, go into detail on the intuition of the estimation strategies and identification itself, as well as explore code in R and Stata and applications using these methods. The goal as always is that participants leave the workshop with competency and confidence. This class will be a sequel to the 4-day workshop on Causal Inference Part I and is followed by Causal Inference Part III.

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

  • Difference-in-Differences

  • Advanced Diff-in-Diff

  • Fuzzy Diff-in-Diff

Causal Inference III

Prof. Scott Cunningham

Starting April 26th

Synthetic control has been called the most important innovation in causal inference of the last two decades (Athey and Imbens 2018). It's use has been seen across the social sciences but even industry and government agencies. The method combines many design elements from unconfoundedness principles to difference-in-differences estimation to help find suitable estimates of counterfactuals in panel settings. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. We will review the theory behind several estimators, go into detail on the intuition of the estimation strategies and identification itself, as well as explore code in R and Stata and applications using these methods. The goal as always is that participants leave the workshop with competency and confidence. This class will be a sequel to the Causal Inference I and II.

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

  • Synthetic Control

  • Multiple Treated Units

“The Singles”

Approachable Introductions to Specific Methods

Discover the foundations of fascinating subjects with our highly accessible workshop series, "The Singles." Led by esteemed scholars, these workshops provide comprehensive introductions to specific topics and methods. Designed for beginners, each session starts from the basics, equipping you with a solid understanding of the subject matter. Embark on a transformative learning journey with our expert instructors, who will guide you through the essentials and ignite your passion for the subject.

The Hidden Curriculum

Everything You Weren't Taught in Graduate School about Doing Applied Research

Prof. Daniel Rees and Prof. D. Mark Anderson

Starting August 6th, 2025

This course is intended to be a practical guide for graduate students and early career economists doing applied research. The nuts and bolts of coming up with viable research topics, writing, publishing, and service to the profession are covered in two half-day sessions, each lasting roughly four hours (including short breaks). We begin by providing tips on how to start a research project, when to switch topics, and how to effectively manage multiple projects at once. Next, we provide practical advice on how to write an applied economics paper, from structing the introduction to crafting the conclusion. The second half of the course takes participants through the publication process. In addition, we discuss networking, refereeing for economics journals, getting the most out of conferences, and how to successfully navigate the academic job market.

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

“The Deep Cuts”

Advanced Courses Exploring the Frontiers of Causal Inference

Unleash the power of your existing knowledge with our advanced workshop series, "The Deep Cuts." Perfect for those well-versed in the basics of a methodology, these immersive courses take you on a captivating exploration into the cutting-edge of your chosen topic. Led by leading scholars, each session delves deep into the frontiers of a methodology. These courses are designed assuming a solid foundation in the basics of the methodology.

We don't have any upcoming sessions for this series. Check back soon!