SICSS-UCLA

The 2026 program will focus on the following topics:

• Foundations of Causal Inference:
  • Identification, Directed Acyclic Graph, Potential Outcomes Framework, Structural Causal Model
• Causal estimation for selecting on observables:
  • Matching, Weighting, Doubly Robust Estimation, Machine Learning and Causal Trees
• Effect heterogeneity
• Sensitivity analysis
• Data and Workflow for Causal Inference

A detailed daily schedule is currently being finalized and will be available soon. To provide an overview of the program’s structure, we have included schedules from previous years below. Please note that we are transitioning to a more intensive one-week format for 2026 to better accommodate our participants’ travel and budgetary considerations. While the range and depth of topics can vary each year, the topics listed above highlight the core curriculum for this year.

2023-2025 Schedules