Sunday, April 23
11:00 – 4:00 PM Training workshops on causal graphs and other topics. Instructors: Elias Bareinboim and Judea Pearl.
To see the curriculum for the methods training workshop click here.
Monday, April 24
8:00 – 9:00 AM Breakfast
9:00 – 9:15 AM Introductory Remarks
First Panel: Modeling, Graphs, and Machine Learning
9:15 – 10:00 AM Judea Pearl (UCLA Computer Science and Statistics) Eight Pillars of Causal Wisdom (or, what you can do with a graphical model that you cannot do without).
10:00 – 10:45 AM Rosa Matzkin (UCLA Economics) Identification in simultaneous equation models
10:45 – 11:00 AM Break
11:00 – 11:45 AM Niall Cardin (Google) Causal inference for machine learning systems that make decisions: The simple power of randomization
Lunch and Keynote Speaker
11:45 AM – 1:00 PM Lunch
1:00 – 2:00 PM
Angus Deaton (Princeton Economics) Understanding and misunderstanding randomized controlled trials
Second Panel: Causal Inference in Econometrics Training
2:00 – 2:30 PM Chris Auld (University of Victoria Economics) Trends in econometric pedagogy (no discussion)
2:30 – 3:00 PM Adnan Darwiche (UCLA Computer Science) On Model-Based versus Model-Blind Approaches to Artificial Intelligence
3:00 – 3:30 PM Ed Leamer (UCLA Economics) Open discussion, causal inference in econometric education
Third Panel: Identification in RCTs and Observational Designs
3:30 – 4:15 PM Karim Chalak (UVa Economics) Measurement Error without Exclusion: the Returns to College Selectivity and Characteristics
4:15 – 5:00 PM Rodrigo Pinto (UCLA Economics) Randomized Biased-controlled Trials: Connecting Incentives and RCTs
Tuesday, April 25
8:00 – 9:00 AM Breakfast
Fourth Panel: Graphs and Bayes Nets: Theory and Applications
9:00 – 9:45 AM Clark Glymour (Carnegie Mellon Philosophy) Explanatory Research vs Confirmatory Research: Undoing Ioannidis' Argument
9:45 – 10:30 AM Elias Barenboim (Purdue Computer Science) Causal Inference and the Data-Fusion Problem
10:30 – 11:15 AM Adam Glynn (Emory Political Science) Front-door approaches to causal inference without control units
11:15 - noon Karthika Mohan (UCLA Computer Science) Missing Data as a Causal Inference Problem -- New Results