Hi everyone!
This week at the Applied Statistics Workshop we will be welcoming *Anton
Strezhnev*, graduate student in the Harvard Government Department. He will
be presenting his job talk entitled *Robust principal scores for estimating
survivor causal effects with application to analyses of litigation outcomes*.
Please find the abstract below and on the Applied Stats website here
<https://projects.iq.harvard.edu/applied.stats.workshop-gov3009>.
As usual, we will meet at noon in CGIS Knafel Room 354 and lunch will be
provided. See you all there!
-- Dana Higgins
*Title:* *Robust principal scores for estimating survivor causal effects
with application to analyses of litigation outcomes*
*Abstract:* In many studies, outcomes are unobserved or undefined for some
units under analysis. This is common in empirical studies of the outcomes
of legal disputes where a large fraction of cases settle before a decision
is rendered. Analyses that condition on settlement failure are biased for
the causal effect even when the treatment of interest is randomly assigned
if that treatment also affects the probability of settlement. When outcomes
are truncated in this way, a valid causal quantity of interest is the
treatment effect among the ``principal stratum'' of units that would fail
to settle regardless of treatment. Principal score methods estimate these
effects by assuming ignorability of stratum membership given observed
covariates and weighting to eliminate covariate imbalances across strata.
These weights are estimated using a model for principal stratum membership
and can be highly sensitive to changes in model specification. I develop an
estimator for principal score weights that is more robust to
mis-specification of the principal score model by directly incorporating
known covariate balance conditions using a generalized method-of-moments
approach. I illustrate this new approach in a study of win-rates in
international investor-state arbitration.
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