How can modern causal analytics improve evidence-based policy analyses, decisions, and retrospective evaluations? This was the theme of a March 15 workshop at the Society for Benefit-Cost Analysis (SBCA). Participants were enthusiastic: a typical response was “I was very impressed with the causal analytics workshop at the SBCA conference. I am already thinking of applications for some of the tools.” The course covered different types of causality (probabilistic, associational, attributive, counterfactual, predictive, manipulative, and mechanistic) and introduced concepts and software, including CAT, for assessing causality from data to inform evidence-based policy making and evaluation.
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