Hi all,
Our next virtual meeting will be at 12pm (EST) Wednesday, February 10,
where we will hear Dean Knox <http://www.dcknox.com/> (University of
Pennsylvania) presents research on "ε-sharp Bounds for Partially Observed
Causal Processes: Testing for Racial Bias in Policing by Fusing Incomplete
Records."
*Authors:*
Guilherme Duarte, Dean Knox, Jonathan Mummolo
*Abstract*:
Social scientists often possess fragmented information about subsets and
aspects of the complex causal processes they study. Research on
police-civilian interactions, for example, is complicated not only by
undocumented interactions, but inconsistent recording of events within
documented interactions. These data constraints can lead to a proliferation
of incompatible analytic approaches relying on contradictory unstated
assumptions, impeding scientific progress on important questions like the
severity of racial bias in policing. Nonparametric sharp bounds, or the
tightest possible range of answers consistent with available data, offer a
path forward: claims outside the bounds can be immediately rejected, and
claims inside the bounds must explicitly justify the additional assumptions
that enable tightening. However, we show proving sharpness is NP-hard for
broad classes of data constraints and causal quantities, rendering this
approach computationally infeasible for even moderately sized causal
processes. We present an efficient spatial branch-and-bound procedure with
a theoretical guarantee that we term "ε-sharpness," indicating the
worst-case looseness factor of the relaxed bounds relative to the (unknown)
completely sharp bounds. The procedure is guaranteed to attain complete
sharpness with sufficient computation time. We present results on
asymptotic validity of and conservative statistical inference for ε-sharp
bounds. The technique is illustrated using simulations using common
research designs in the study of policing.
*Zoom link: *
https://harvard.zoom.us/j/97787602526?pwd=Uzh3bVVVS0F4TEVYQTJlV3BQNjcydz09
*Schedule of the workshop:*
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Looking forward to seeing you all on Wednesday!
Best,
Soichiro