(B) While one of my interests is causal inference in data science, and I have been studying causal inference for business applications in particular the life cycle of products, I was not aware of how much research has been done for causal inference in econometrics. This obviously has changed when I learned about Professor Guido Imbens from Stanford University that won the Nobel Prize in economics in 2021 with Professor Joshua Angrist (who had as a PhD student Esther Duffo another Nobel Prize winner) “for their methodological contributions to the analysis of causal relationships”. Note that Stanford also had two economists Paul Milgrom and Robert Wilson who won the Nobel Prize in economics in 2020 “for improvements to auction theory and inventions of new auction formats.”
- Identification of causal effects using instrumental variables
- Identification and estimation of local average treatment effects
- Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics (see Judea Perl’s response: On Imbens’s Comparison of Two Approaches to Empirical Economics)
- Machine Learning Methods Economists Should Know About (with his wife Professor Susan Athey)
- Causal Forest (work from Professor Athey)
Professor Imbens’ Nobel Prize lecture:
A recent lecture from Professor Imbens on Causality & Econometrics at the University of Virginia:
Professor Imbens keynote at CDSM21: “A Design Approach to Synthetic Controls”
A recent interview of Professor Imbens at the Online Causal Inference Meetings:
Note: The picture above is one Galette des Rois, two Paris-Brest, one Pain aux Raisins, and one Kouign Amman. Everything is from Adorable French Bakery & Catering in Santa-Cruz.
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