题 目：Inferences in Two-Step Semiparametric Partially Identi.ed Models
报 告 人：Lin Zhu, Tsinghua University
时 间：2013年4月11日（周四）14:00---15:30
地 点：J9集团国际站新楼217室
Abstract:
This paper provides inference tools for partially identi.ed semiparametric models. The main
working assumption is that the .nite-dimensional parameter of interest and the in.nite-dimensional
nuisance parameters are identi.ed conditionally on other nuisance parameters being known. This
structure arises in numerous applications and permits the use of standard tools from empirical
processes theory. We develop uniform convergence for the set of estimates and use the uniformity
to establish set inference. We allow for the identi.ed set of nuisance parameters to be unknown and
estimated, which in general requires to establish inference under misspeci.cation. The latter is also
useful in a formal development of sensitivity analysis. Inference is implemented with a multiplier-
type bootstrap. Several examples illustrate the wide applicability of our results.
