[gov3009-l] Applied Stats Workshop: Patrick Lam on "Estimating Individual Causal Effects"
kkashin at fas.harvard.edu
Mon Apr 8 00:50:21 EDT 2013
We hope you can join us this Wednesday, April 10, 2013 from 12-1.30pm for
the Applied Statistics Workshop in CGIS Knafel 354. Patrick
a Ph.D. candidate from the Department of Government at Harvard University,
will give a presentation entitled "Estimating Individual Causal Effects". A
light lunch will be served at 12 pm and the talk will begin at 12.15.
> The literature on causal inference has focused primarily on estimating
> average treatment effects, which aggregate over many individual effects.
> However, this aggregation often misses treatment effect heterogeneity,
> which may be of extreme importance. In addition, researchers often estimate
> average effects but their real quantity of interest is individual effects.
> In this paper, I develop methods to estimate individual causal effects
> based on commonly used matching procedures. I show that predictive mean
> matching performs the best in imputing missing potential outcomes to
> estimate the individual effects. I then demonstrate the flexibility of
> estimating individual causal effects and how they can be used to explore
> questions of interest, recover any other causal quantity, and be adapted to
> more complicated data structures. I conclude with empirical examples from
> political science.
An up-to-date schedule for the workshop is available at
Ph.D. Candidate in Government
E-mail: kkashin at fas.harvard.edu
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