Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments
线性矩条件定义的集合识别参数泛函的简便推断
This article proposes a new approach to obtain uniformly valid inference for linear functionals or scalar subvectors of a partially identified parameter defined by linear moment inequalities. The procedure amounts to bootstrapping the value functions of randomly perturbed linear programming problems, and does not require the researcher to grid over the parameter space. The low-level conditions for uniform validity rely on genericity results for linear programs. The…