This year's Gosnell Award winner for best paper on political methodology
given at a conference is Kevin Quinn from Harvard University.  His paper
"What Can be Learned from a Simple Table? Bayesian Inference and Sensitivity
Analysis for Causal Effects from 2x2 and 2x2xK Tables in the Presence of
Unmeasured Confounding, " was presented at the Northeast Political
Methodology meeting on April 18, 2008.

Quinn's paper offers a set of steps to improve inference with binary
independent and dependent variables and unmeasured confounds.  He derives
large sample, non-parametric bounds on the average treatment effect and
shows how these bounds do not rely on auxiliary assumptions.   He then
provides a graphical way to depict the robustness of inferences as one
changes assumptions about the confounds.  Finally, he shows how one can use
a Bayesian framework relying on substantive knowledge to restrict the set of
assumptions on the confounds to improve inference.

The paper has broad implications.  As one of the nominators put it:  the
paper promises "to change the way that researchers do work in fields where
the data are poor and experimentation is not possible; i.e., most of
empirical political science."

Congratulations to Kevin.  

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