Main Causal Inference Workshop

Monday – Friday, August 8-12, 2022

After a COVID break during 2020 and 2021, we are excited to be holding our 11th annual workshop on Research Design for Causal Inference at Northwestern Law School in Chicago, IL. We invite you to attend. 

What’s special about this workshop are the speakers. The workhop will be taught by world-class causal inference researchers. In the past we have filled the main workshop quickly, and we expect there may be pent up demand after the 2-year COVID break, so please register soon.

Our Advanced Workshop on Research Design for Causal Inference will be held this year on August 15-17, 2022.


Northwestern Pritzker School of Law
375 East Chicago Avenue, Chicago, IL 60611

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

Main Workshop Overview

We will cover the design of true randomized experiments and contrast them to natural or quasi experiments and to pure observational studies, where part of the sample is treated in some way, the remainder is a control group, but the researcher controls neither which units are treated vs. control, nor administration of the treatment.  We will assess the causal inferences one can draw from specific “causal” research designs, threats to valid causal inference, and research designs that can mitigate those threats.

Most empirical methods courses survey a variety of methods.  We will begin instead with the goal of causal inference, and how to design a research plan to come closer to that goal, using messy, real-world datasets with limited sample sizes. The methods are often adapted to a particular study. 

Target Audience

Quantitative empirical researchers (faculty and graduate students) in social science, including law, political science, economics, many business-school areas (finance, accounting, management, marketing, etc.), medicine, sociology, education, psychology, etc. – anywhere that causal inference is important.

We will assume knowledge, at the level of an upper-level college econometrics or similar course, of multivariate regression, including OLS, logit, and probit; basic probability and statistics including confidence intervals, t-statistics, and standard errors; and some understanding of instrumental variables.  This course should be suitable both for researchers with recent PhD-level training in econometrics and for empirical scholars with reasonable but more limited training.

Teaching Faculty

  • Donald Rubin (Harvard University)
    Donald Rubin is John L. Loeb Professor of Statistics Emeritus, at Harvard. His work on the “Rubin Causal Model” is central to modern understanding of causal inference with observational data. Principal research interests: statistical methods for causal inference; Bayesian statistics; analysis of incomplete data.  Wikipedia page
  • Pedro Sant’Anna (Vanderbilt University and Microsoft)
    Pedro SantAnna is Assistant Professor of Economics at Vanderbilt University. His research focus is on microeconometrics, including causal inference methods and program evaluation.  
  • Rocio Titiunik (Princeton University)
    Rocío Titiunik is Professor of Politics at Princeton University. She specializes in quantitative methodology for the social sciences, with emphasis on quasi-experimental methods for causal inference
  • Matias Cattaneo (Princeton University)
    Matias Cattaneo is Professor in the Department of Operations Research and Financial Engineering at Princeton University, with positions in Princeton’s Department of Economics, Center for Statistics and Machine Learning, and Program in Latin American Studies. His research focus is econometrics, statistics, data science and decision science, with particular interests in program evaluation and causal inference. 

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, international corporate governance.  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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Registration and Workshop Cost

Tuition for the Main Workshop is $900 ($600 for post-docs and graduate students PhD, SJD, or law; $500 if you are Northwestern affiliated).

Tuition for the Advanced Workshop is $600 ($400 for post-docs and graduate students; $300 if you are Northwestern affiliated).

There is a $200 discount for attending both workshops ($100 if Northwestern-affiliated).

Zoom option: We’ve decided to charge 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, depending on how travel and COVID-19 risk looks by mid-summer.

Vaccination Recommended:  Northwestern no longer requires proof of vaccination for on-campus events. However, we still strongly recommend that you be vaccinated against COVID-19 (2-doses) and have received a booster shot if the second dose was more than 6 months before the start of the workshop. If you have been infected with COVID – especially if recently infected with the Omicron variant – this can be considered as the rough equivalent to one vaccine dose.

For special circumstances, please contact Professor Black at

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

We know the workshop is not cheap. We use the funds to pay our speakers and expenses; we don’t pay ourselves.

Registration is limited to 125 participants.

Register Now

You can cancel by July 1, 2022 for a 75% refund (or carry over your registration to next year for full credit) and by July 15, 2022 for a 50% refund (in each case, less credit card processing fee), but there are no refunds after that, because we can't realistically replace you. If the workshop is canceled, we will offer a full refund.

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Workshop Schedule

Plan on full days, roughly 9:00-5:00. Breakfast will be available at 8:30.

Monday, August 8 

Introduction to Modern Methods for Causal Inference
Donald Rubin

Overview of causal inference and the Rubin “potential outcomes” causal model.  The “gold standard” of a randomized experiment.  Treatment and control groups, and the core role of the assignment (to treatment) mechanism.  Causal inference as a missing data problem, and imputation of missing potential outcomes.  Rerandomization.  One-sided and two-sided noncompliance. 

Tuesday, August 9 

Matching and Reweighting Designs for “Pure” Observational Studies
Pedro Sant’Anna

The core, untestable requirement of selection [only] on observables.  Ensuring covariate balance and common support.  Matching, reweighting, and regression estimators of average treatment effects.  Propensity score methods.

Wednesday, August 10

Panel Data and Difference-in-Differences
Pedro Sant’Anna

Panel data methods:  pooled OLS, random effects, and fixed effects.  Simple two-period DiD and panel data extensions.  The core “parallel trends” assumption.  Testing this assumption.  Event study (leads and lags) and distributed lag models.  Accommodating covariates.  Triple differences.  Robust and clustered standard errors. 

Thursday, August 11 

Regression Discontinuity
Rocio Titiunik or Matias Cattaneo

Regression discontinuity (RD) designs: sharp and fuzzy designs; continuity-based methods and bandwidth selection; local randomization methods and window selection; empirical falsification of RD assumptions; extensions and generalizations of canonical RD setup: discrete running variable, multi-cutoff, multi-score, and geographic designs.  RD software website

Friday, August 12: Morning 

Instrumental variable methods
Matias Cattaneo or Rocio Titiunik

Causal inference with instrumental variables (IV) : th e role of the exclusion restriction and first stage assumption; the monotonic ity assumption and local average treatment effect (LATE) interpretation; applications to randomized experiments with imperfect compliance , including intent-to-treat designs and two-stage estimation.  Connections between IV and fuzzy RD designs.  

Friday, August 12: Afternoon

Feedback on your own research

Attendees will present their own research design questions from current work in breakout sessions and receive feedback on research design.  Session leaders:  Bernie Black, Scott Cunningham, Rocio Titiunik or Matias Cattaneo).  Additional parallel sessions if needed to meet demand.

Stata and R code

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

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There are many hotels within walking distance to Northwestern Law School, in all price ranges. There are also many air B&B options. If you want to share with another attendee, please send an email to Sarah Shoemaker at and we will circulate a list of interested attendees as we get closer to the workshop data. Please be aware that hotel rates will likely increase as we get closer to the conference. 

Millennium Knickerbocker Hotel

  • 163 E Walton Place, 0.5 miles from Northwestern
  • Current Rate as of 4/13/22: $105 

Selina Chicago

  • 100 E Chestnut Ave, 0.5 miles from Northwestern
  • Current Rate as of 4/13/22: $108
  • Please note, they have shared room options. 

Warwick Allerton

  • 701 N Michigan Ave, 0.4 miles from Northwestern
  • Current Rate as of 4/13/22: $166 

Hampton Inn

  • 160 E Huron St , 0.4 miles from Northwestern
  • Current Rate as of 4/13/22: $175

Questions about the Workshop

Please email Bernie Black or Scott Cunningham for substantive questions or fee waiver requests, and Sarah Jane King Shoemaker for logistics and registration.

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