Methods Clinic: Causal Inference Workshop with Anand Murugesan

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The course provided an introduction to key methods for causal inference, essential for evidence-based policymaking. Through case studies and hands-on examples, students learnt how to apply these methods to evaluate real-world programs and policies. Emphasis was placed on practical applications.

Topics covered included covariate adjustments, experiments (RCTs), matching methods, regression discontinuity designs, panel data fixed effects, and difference-in-differences. The course began with causal graphs to build an understanding of cause-and-effect relationships, followed by an introductory look at each method and its applications.