HDSI Causal Seminar: Edward McFowland III, Harvard UniversityThursday, October 20, 20223:30 PM – 5:30 PM ESTHawes Hall, Classroom 203, Harvard Business SchoolRegister here
Edward McFowland IIIAsst. Professor, Technology & Operations Management UnitHarvard Business SchoolAchieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error ProblemCombining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy uses predictive modeling techniques to “mine” variables of interest from available data, then includes those variables into an econometric framework to estimate causal effects. However, because the predictions from machine learning models are inevitably imperfect, econometric analyses based on the predicted variables likely suffer from bias due to measurement error. Read more.
