Dear Applied Statistics Workshop Community,
Our next meeting of the semester will be on November 2 (12:00 EST). Edward
Kennedy will present "Doubly robust capture-recapture methods for
estimating population size."
Please note that this meeting will take a hybrid format. Professor Kennedy
will join us on Zoom, but we will gather in CGIS K354 (I will use the
projection screen in K354 to display the Zoom window). Lunch will be
provided.
<Where>
Hybrid: CGIS K354 or Zoom
Bagged lunches are available for pick-up at 11:40 (CGIS K354).
Zoom:
https://harvard.zoom.us/j/99181972207?pwd=Ykd3ZzVZRnZCSDZqNVpCSURCNnVvQT09
<Abstract>
Estimation of population size using incomplete lists (also called the
capture-recapture problem) has a long history across many biological and
social sciences. For example, human rights and other groups often construct
partial and overlapping lists of victims of armed conflicts, with the hope
of using this information to estimate the total number of victims. Earlier
statistical methods for this setup either use potentially restrictive
parametric assumptions, or else rely on typically suboptimal plug-in-type
nonparametric estimators; however, both approaches can lead to substantial
bias, the former via model misspecification and the latter via smoothing.
Under an identifying assumption that two lists are conditionally
independent given measured covariate information, we make several
contributions. First, we derive the nonparametric efficiency bound for
estimating the capture probability, which indicates the best possible
performance of any estimator, and sheds light on the statistical limits of
capture-recapture methods. Then we present a new estimator, and study its
finite-sample properties, showing that it has a double robustness property
new to capture-recapture, and that it is near-optimal in a non-asymptotic
sense, under relatively mild nonparametric conditions. Next, we give a
method for constructing confidence intervals for total population size from
generic capture probability estimators, and prove non-asymptotic
near-validity. Finally, we study our methods in simulations, and apply them
to estimate the number of killings and disappearances attributable to
different groups in Peru during its internal armed conflict between 1980
and 2000.
<2022 Schedule>
GOV 3009 Website:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Calendar:
https://calendar.google.com/calendar/embed?src=c_3v93pav9fjkkldrbu9snbhned8…
Best,
Shusei