2018 Advanced Causal Inference Workshop

We would like to invite you to attend the Fourth Annual Advanced Workshop on Research Design for Causal Inference, which builds on our "main" workshop. 

Monday-Wednesday, June 25-27, 2018, at Northwestern Pritzker School of Law, 375 East Chicago Avenue, Chicago, IL

Our regular "Main" Workshop on Research Design for Causal Inference will be held this year on June 18-22, 2018, at Northwestern Pritzker School of Law.

Teaching Faculty and Organizers | Registration | Schedule | Hotels 

Workshop Overview

The advanced workshop provides in-depth discussion of selected topics that are beyond what we can cover in the main workshop.  Principal topics for 2018 include:  Day 1 (Mon.):  Principal stratification (generalization of causal-IV concepts and applications, including sample censoring through death or attrition.   Day 2 (Tues.):  Direct and indirect causal effects.  Synthetic controls and other advanced “matching” approaches with emphasis on panel data sets.  Day 3 (Wed.):  Application of machine learning methods to causal inference.

Target Audience for Advanced Workshop
Empirical researchers who are reasonably familiar with the basics of causal inference (from our main workshop or otherwise), and want to extend their knowledge. We will assume familiarity with potential outcomes notation, difference-in-differences, regression discontinuity, panel data, and instrumental variable designs, but will not assume expertise in any of these areas.

Teaching Faculty

We are fortunate to have recruited outstanding experts in causal research design to teach the workshop sessions. The faculty are listed in order of appearance.

  • Donald Rubin (Harvard University, Department of Statistics)
    Rubin is John L. Loeb Professor of Statistics, Harvard University. His work on the "Rubin Causal Model" is central to modern understanding of when one can and cannot infer causation from regression. Principal research interests: statistical methods for causal inference; Bayesian statistics; analysis of incomplete data. Wikipedia page
  • Fabrizia Mealli (University of Florence, Department of Statistics and Computer Science)
    Fabrizia Mealli is Professor of Statistics at the University of Florence and external research associate at the Institute for Social and Economic Research (ISER) at the University of Essex. Her research focuses on causal inference and simulation methods, program evaluation, missing data, and Bayesian inference. She is a fellow of the American Statistical Association, and associate editor of Journal of the American Statistical Association (JASA), Biometrics, and Annals of Applied Statistics.
  • Yiqing Xu (University of California, San Diego, Department of Political Science)
    Yiqing Xu is Assistant Professor of Political Science at University of California, San Diego. His main methods research involves causal inference with panel data.
  • Justin Grimmer (University of Chicago, Department of Political Science)
    Justin Grimmer is Associate Professor of Political Science at the University of Chicago.  His primary research interests include political representation, Congressional institutions, and text as data methods.

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
  • Mathew McCubbins (Duke University)
    Professor of Political Science and Law at Duke University, with positions in the Political Science Department and the Law School, and director of the Center for Law and Democracy.  Principal research interests: democratic institutions, legislative organization; behavioral experiments, communication, learning and decisionmaking; statutory interpretation, administrative procedure, research design; network economics. Papers on SSRN

Registration and Workshop Cost

Online registration is now closed. Please email laura.dimitrijevic@law.northwestern.edu if you are interested in registering.

Advanced workshop:  Tuition is $600 ($400 for graduate students and post-doctoral fellows).

Combined workshop discount:  $100 discount on the advanced workshop for those who attend both workshops. 

The workshop fees include all materials, temporary Stata 15 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 for meals and other expenses; we don’t pay ourselves.

You can cancel by May 21, 2018 for a 75% refund and by June 4, 2018 for a 50% refund (in each case, less credit card processing fee), but there are no refunds after that.  

Workshop Schedule

Monday, June 25 (Donald Rubin and Fabrizia Mealli): 

Principal Stratification and Censoring (9:00am-12:00pm, 1:00-4:00pm)
Generalizing the causal-IV strata of compliers-always takers-never takers-defiers. Which treatment effects can be estimated for which strata? Handling missing data and censoring through “death” or attrition.

Monday Reception (4:00pm-5:30pm)

Tuesday, June 26 (Donald Rubin, Fabrizia Mealli, and Yiqing Xu):

Direct and Indirect Causal Effects (Donald Rubin and Fabrizia Mealli, 9:00am-12:00pm)
“Mediation” analysis: Direct and indirect causal effects versus principal associative and dissociative effects.

Tuesday Lunch Talk: Bloopers II: How Other Smart People Get Causal Inference Wrong (Bernie Black, 12:30-1:30pm)
Examples, drawn from different areas, of how to get causal inference wrong.

Advanced Matching (Yiqing Xu, 1:45pm-4:45pm)
Advanced matching and reweighting methods, with an emphasis on panel data applications. Generalized synthetic controls. Relative strengths and weaknesses of different matching and reweighting approaches.

Wednesday, June 27 (Justin Grimmer):

Machine learning (predictive inference) meets causal inference (9:00am-12:00pm, 1:10-4:00pm)
Introduction to machine learning approaches. When and how can machine learning methods be applied to causal inference questions.


Hotels accommodations are available at the Residence Inn Chicago Downtown/Magnificent Mile at a rate of $224 per night. Reservations must be made by June 4, 2018 to receive this special rate. Click here to reserve your hotel room or call the hotel directly at 800-331-3131 and reference the "Northwestern Causal Inference Advanced Workshop" to book your room. 

If you are interested in a room share, email causalinference@law.northwestern.edu. A list of those interested will be shared at a later date. 

Questions about the workshop

Please email Bernie Black bblack@northwestern.edu or Mat McCubbins mathew.mccubbins@duke.edu for substantive questions or fee waiver requests, and Laura Dimitrijevic causalinference@law.northwestern.edu for logistics and registration.

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