ENGLISH

공지사항

[일반] [대학원] 14th Annual Workshop on Research Design for Causal Inference

2025-03-07l 조회수 256
14th Annual Workshop on Research Design for Causal Inference

This workshop brings together leading experts in causal inference and provides an excellent opportunity for researchers to enhance their methodological skills.

Workshop Dates

  • Main Workshop: Monday – Friday, July 28 – August 1, 2025
  • Advanced Workshop: Sunday – Wednesday, August 3 – 6, 2025

Why Attend?

These workshops feature world-class speakers, each of whom is a leading expert in their respective topics. Please see the link below for speaker details.


Target Audience

The workshops are designed for quantitative empirical researchers, including faculty, graduate students, post-doctoral researchers, and other scholars in social sciences, such as:
  • Law, Political Science, Economics
  • Business disciplines (Finance, Accounting, Management, Marketing, etc.)
  • Medicine, Sociology, Education, Psychology
  • Any other field where causal inference is a key research concern

Registration Details

  • In-person attendance is limited to 125 participants per workshop.
  • Zoom option is available, but we highly encourage in-person participation for the best experience.

Registration & More Information


Main Workshop Schedule

Monday, July 28

  • Donald Rubin (Harvard University)
    Introduction to Modern Methods for Causal Inference

Tuesday, July 29

  • Jens Hainmueller (Stanford University)
    Matching and Reweighting Designs for “Pure” Observational Studies

Wednesday, July 30

  • Jens Hainmueller (Stanford University)
    Panel Data and Difference-in-Differences

Thursday, July 31

  • Heather Royer (UC Santa Barbara)
    Regression Discontinuity

Friday, August 1

  • Morning: Tymon Słoczy?ski (Brandeis University)
    Instrumental Variable Methods
  • Afternoon: Feedback on your own research

Advanced Workshop Schedule

Sunday, August 3 (Optional Session)

  • Christian Hansen (University of Chicago)
    Primer on Machine Learning Approaches to Prediction

Monday, August 4

  • Christian Hansen
    Applications of Machine Learning to Causal Inference

Tuesday, August 5

  • Andrew Goodman-Bacon (Federal Reserve Board)
    Advanced Difference-in-Differences

Wednesday, August 6

  • Peter Hull (Brown University)
    Advanced Instrumental Variables

Stata and R coding

On selected days, parallel coding sessions in Stata and R will be offered to illustrate code implementation for the research designs covered in the lectures.

Workshop Organizers

  • Bernie Black (Northwestern University)
  • Scott Cunningham (Baylor University)
For content-related questions or fee waiver requests, please contact:
For logistics and registration inquiries, please contact: