Matthew Blackwell (Department of Government), "Difference-in-differences Designs for Controlled Direct Effects"
Political scientists are increasingly interested in controlled direct effects, which are important quantities of interest for understanding why, how, and when causal effects will occur. Unfortunately, their identification has usually required strong and often unreasonable selection-on-observeables assumptions for the mediator. In this paper, we show how to identify and estimate controlled direct effects under a difference-in-differences design where we have measurements of the outcome and mediator before and after treatment assignment. This design allows us to weaken the identification assumptions to allow for linear, time-constant unmeasured confounding between the mediator and the outcome. Furthermore, we develop a semiparametrically efficient and multiply robust estimator for these quantities and apply our approach to a recent experiment evaluating the effectiveness of short conversations at reducing intergroup prejudice. An open-source software package implements the methodology with a variety of flexible, machine-learning algorithms to avoid bias from misspecification.
The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers.
More information is available at the Gov 3009 website: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
All interested Harvard affiliates are invited to attend.