Inference on scalar parameters in set–identified affine models

• Departmental Seminar

Date and Location

Friday, January 20, 2017, 10:30 AM - 11:50 AM
ARE Library Conference Room, 4101 Social Sciences and Humanities

Abstract

This paper proposes both point-wise and uniform confidence intervals (CIs) for an element Θ₁ of a parameter vector Θ ∈ 2 R^d that is partially identified by affine moment equality and inequality conditions. The CIs are based on an estimator of a regularized support function of the identified set and have a closed–form. I provide examples in which my CIs are shorter (with probability approaching 1) than those in the existing literature. Furthermore, unlike much of the existing literature, the proposed CIs can be computed as a solution to a convex optimization problem, which leads to a substantial decrease in computation time (relative to the existing uniform procedures). My approach can be used, for instance, to compute a CI for the returns to schooling using income bracket data without strong distributional assumptions.