Dear Applied Statistics Workshop Community,
Our next meeting will be on Wednesday, February 28 (12:00 EST). Phillip Heiler
presents "Heterogeneous Treatment Effect Bounds under Sample Selection with
an Application to the Effects of Social Media on Political Polarization."
<When>
February 28, 12:00 to 1:30 PM, EST
Lunch will be available for pick-up inside CGIS K354.
<Where>
In-person: CGIS K354
Zoom:
https://harvard.zoom.us/j/93217566507?pwd=elBwYjRJcWhlVE5teE1VNDZoUXdjQT09
<Abstract>
We propose a method for estimation and inference for bounds for
heterogeneous causal effect parameters in general sample selection models
where the treatment can affect whether an outcome is observed and no
exclusion restrictions are available. The method provides conditional
effect bounds as functions of policy relevant pre-treatment variables. It
allows for conducting valid statistical inference on the unidentified
conditional effects. We use a flexible debiased/double machine learning
approach that can accommodate non-linear functional forms and
high-dimensional confounders. Easily verifiable high-level conditions for
estimation, misspecification robust confidence intervals, and uniform
confidence bands are provided as well. We re-analyze data from a
large-scale field experiment on Facebook on counter-attitudinal news
subscription with attrition. Our method yields substantially tighter effect
bounds compared to conventional methods and suggests depolarization effects
for younger users.
The paper is available on
arXiv:https://arxiv.org/abs/2209.04329
<2023-2024 Schedule>
GOV 3009 Website:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Calendar:
https://calendar.google.com/calendar/u/0?cid=Y18zdjkzcGF2OWZqa2tsZHJidTlzbm…
Best,
Jialu
--
Jialu Li
Department of Government
Harvard University
*https://jialul.github.io/ <https://jialul.github.io/>*