RSS02.D11 Causal Inference with Natural Experiments: DiD, RDD, IV, & Matched Designs

This course is an introduction to causal inference for the social using observational data. We will discuss:

• the nature of causal research,
• how to design research to answer different types of causal questions,
• how to analyze observational data to enable causal interpretations of phenomena
• that were not randomized,
• how to implement analysis using the R statistical language,
• and how to interpret the results of causal analyses.

Specific topics will include:

• potential outcomes,
• ideal experiments,
• observational matching,
• sensitivity analysis,
• instrumental variables,
• discontinuity designs,
• difference-in-differences,
• multiple time period difference-in-differences designs,
• synthetic controls,
• and other special topics as permitted, including causal mediation and dynamic or time-varying treatments.