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AI & MLSpecializedAIML-CAU-006

Quasi-Experimental Designs: Instruments and Difference-in-Differences

Natural experiments when randomisation is impossible: instrumental variables, difference-in-differences, regression discontinuity.

Difficulty
5 / 5
Importance
3 / 5
Study time
1–2 h
Kind of work
Mixed

Why it matters

The learner can match a policy-evaluation scenario to an IV, DiD, or RD design and state the identifying assumption each requires.

The route to this topic

Route AIML-CAU-006
Natural Numbers What Is a Model? Variables & Constants Learning from Data Tasks: Regression, Classification, and Beyond Features and Targets Correlation vs Causation Classification Framing Linear Regression I: Prediction and Residuals Prediction versus Causation Scores and Logits Loss and Fitting: Squared Error Potential Outcomes and Treatment Effects Sigmoid and Probabilities Logistic Regression Propensity Scores and Inverse Probability Weighting Quasi-Experimental Designs: Instruments and Difference-in-Differences