A Discussion of Causal Modeling Strategies including the Difference-in-Difference (DiD) technique

Last week Professors John Gray (The Ohio State University) and Sachin Modi (Wayne State University) co-hosted a virtual workshop on two statistical techniques that are increasingly being used to investigate causal relationships using observational data. The primary technique that was discussed was difference-in-difference (DiD) modeling.  DiD models are used by researchers to study the impact of some plausibly exogenous event that affects a “treatment group” but does not affect a “control group.”  Another technique that was briefly discussed was regression discontinuity. Professors Gray and Modi provided an overview on how these techniques are used and offered some suggestions on how to start using them to investigate supply chain research questions.
The full Webinar and presentation slides are available above, and below

Professor John Gray is a Professor of Operations at The Ohio State University. He received his PhD from the University of North Carolina.   Dr. Gray teaches courses on data analysis and global sourcing. Professor Gray serves as a department editor for the Journal of Operations Management’s Public Policy Department and a senior editor for Production and Operations Management’s Industry Studies and Public Policy Department.

Dr. Sachin Modi is a Professor of Global Supply Chain Management at Wayne State University.  He received his PhD from Indiana University.   Dr. Modi teaches supply chain analytics, sourcing, and operations management courses.  He serves on the editorial review boards of several journals and as an Associate Editor for the Journal of Operations Management.

For all enquiries please contact dcantor@iastate.edu