Evaluation without Experimentation
causal
An introduction to inverse propensity of treatment weighting for program evaluation with applications to Two Million Texans’ relational organizing campaign during the 2022 midterms
In this four-minute lightning talk, I explain the motivation for using observational versus experimental methods when measuring the impact of GOTV (voter turnout) efforts. Next, I provide a high-level explanation of a specific method (inverse propensity of treatment weighting) and demonstrate the method’s ability to balance baseline traits and historical performance of a synthetic control population for credible effect estimation.
This talk is based on my related blog post and summarizes my work as a Bluebonnet Data Fellow with the Two Million Texans relational organizing campaign during the 2022 midterms.