Advanced Causal Inference Workshop

Sunday-Wednesday, August 4-7, 2024

Including Optional Machine Learning Primer:  Sunday afternoon, August 4

We would like to invite you to attend the Advanced Workshop on Research Design for Causal Inference. This workshop assumes knowledge at the level of the main workshop, and covers selected advanced topics in causal inference.

What’s special about these workshops are the speakers. The session will be taught by world-class causal inference researchers, who are experts in the topics they will discuss.

In person registration is limited to 125 participants for each workshop. 

There will also be a Zoom option, but please come in-person if you can. The online experience is not the same.


Northwestern Pritzker School of Law
375 East Chicago Avenue, Chicago, IL

Overview  |  Teaching Faculty and Organizers  |  Schedule  |  Registration  |  Hotels

Advanced Workshop Overview

The advanced workshop provides in-depth discussion of selected topics that are beyond what we can cover in the main workshop. The principal topics for 2024 are application of machine learning methods to causal inference; difference-in-differences methods for staggered treatments (applied to different units at different times); and advanced instrumental variable methods.

Target Audience

Empirical researchers who are familiar with the basics of causal inference (from our main workshop or otherwise), and want to extend their knowledge.  We will assume familiarity, but not expertise, with potential outcomes, difference-in-differences, and panel data methods.

Teaching Faculty

  • Christian Hansen (University of Chicago)
    Christian Hansen is Wallace W. Booth Professor of Econometrics and Statistics at the University of Chicago, Booth School of Business. His research includes use of machine learning methods in estimation of causal and policy effects, estimation of panel data models, inference using clustered standard errors, quantile regression, and weak instruments.
  • Andrew Goodman-Bacon (Federal Reserve Board, Minneapolis)
    Andrew Goodman-Bacon is Senior Economist at the Opportunity and Inclusive Growth Institute at the Federal Reserve Bank of Minneapolis. His research interests include economic history, health economics, public economics, and applied econometrics.  
  • Peter Hull (Brown University)
    Peter Hull is Professor of Economics at Brown University. His research interests include applied econometrics, crime, discrimination, education, and healthcare.   

Conference Organizers

  • Bernard Black (Northwestern University)
    Bernie Black is Nicholas J. Chabraja Professor at Northwestern University, with positions in the Pritzker School of Law, the Institute for Policy Research, and the Kellogg School of Management, Finance Department. Principal research interests: health law and policy; empirical legal studies, law and finance. Papers on SSRN
  • Scott Cunningham (Baylor University)
    Scott Cunningham is Professor of Economics at Baylor University. Principal research interests: mental healthcare; suicide; corrections; sex work; abortion policy; drug policy.

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Advanced Workshop Outline

You should plan on full days, roughly 9:00-4:30 on Monday-Wednesday. Breakfast will be available at 8:30.

An informal wine-and cheese reception for all attendees will follow on Monday, August 5. 

Sunday afternoon, August 4 (optional)

Primer on machine learning approaches to prediction 
Christian Hansen

Introduction to "machine-learning" approaches to prediction algorithms, aimed at attendees with limited knowledge of machine learning methods. Shrinking a large set of potential predictors. Predicting without overpredicting: training and test sets; cross-validation. Lasso, regression trees, random forests, and deep nets. High-dimensional model selection (function classes, regularization, tuning). Combining models (ensemble models, bagging, boosting), model evaluation, and implementation.

Monday, August 5

Applications of machine learning to causal inference
Christian Hansen

When and how can machine learning methods be applied to causal inference questions. Limitations (prediction vs estimation) and opportunities (data pre-processing, prediction as quantity of interest, high-dimensional nuisance parameters), with examples from an emerging empirical literature.

Tuesday, August 6

Advanced Difference-in Differences
Andrew Goodman-Bacon

New developments in causal inference in difference-in-differences designs. Limitations of two-way fixed effects regressions. Comparison of alternative estimation strategies that have been proposed to address these weaknesses and to accommodate complex treatment variables. Ways to weaken the parallel trends assumption and to diagnose and/or deal with violations of parallel trends.

Wednesday, August 7

Advanced Instrumental Variables
Peter Hull

Design vs. model-based identification, weak and many instrument bias, estimating complier characteristics, judge IV, shift-share IV and other "formula" instruments. 

Stata and R coding

On selected days, we will run parallel Stata and R sessions, following the main lectures, to illustrate code for the research designs discussed in the lectures. Some speakers will also build Stata or R code into their lecture slides. Presenters: Scott Cunningham (Stata) and Joshua Lerner (R).

We will also provide a repository of datasets and code to illustrate the methods presented in the workshop. 

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Registration and Workshop Cost

The workshop fee includes all materials, breakfast, lunch, snacks, and an evening reception on the first workshop day.

Main Workshop: Tuition is $900 ($600 for post-docs and graduate students; $500 if you are Northwestern-affiliated). The workshop fee includes all materials, breakfast, lunch, snacks, and an evening reception on the first workshop day.

Advanced Workshop: Tuition is $650 ($450 for post-docs and graduate students; $300 if you are Northwestern affiliated). 

Discount for attending both workshops: There is a $250 discount for non-Northwestern persons attending both workshops, for combined cost of $1,300 ($800 for post-docs and graduate students; $150  additional discount for Northwestern affiliates).

Zoom option: We are charging the same amount for in-person and virtual attendance. Partly, we want to encourage in-person attendance. We also want to allow attendees to switch from one format to the other.

We know the workshop is not cheap. We use the funds to pay our speakers and expenses. Professor Black does not pay himself. 

Register Now

You can cancel either workshop five weeks in advance, for a 75% refund – June 24, 2024, for the Main Workshop and July 1, 2024, for the Advanced Workshop – or carry over your registration to next year for full credit. There is a 50% refund after these dates, but three weeks before each workshop. After these dates there are no refunds, but you can carry over the registration fee to a future workshop.

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To be announced.

Many attendees find an Airbnb or equivalent to be a good option.

Questions about the Workshop

Please email Bernie Black or Scott Cunningham for substantive questions or fee waiver requests, and Sebastian Bujak for logistics and registration.


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