Nonparametric Inference Based on Conditional Moment Inequalities

Authors

Donald W.K. Andrews
Xiaoxia Shi

Document Type

Discussion Paper

Publication Date

12-1-2011

CFDP Number

1840R2

CFDP Revision Date

2013-10-01

CFDP Pages

44

Abstract

This paper develops methods of inference for nonparametric and semiparametric parameters defined by conditional moment inequalities and/or equalities. The parameters need not be identified. Confidence sets and tests are introduced. The correct uniform asymptotic size of these procedures is established. The false coverage probabilities and power of the CS’s and tests are established for fixed alternatives and some local alternatives. Finite-sample simulation results are given for a nonparametric conditional quantile model with censoring and a nonparametric conditional treatment effect model. The recommended CS/test uses a Cramér-von-Mises-type test statistic and employs a generalized moment selection critical value.

Comments

Supplement Materials, 57 pp

Recommended Citation

Andrews, Donald W.K. and Shi, Xiaoxia, "Nonparametric Inference Based on Conditional Moment Inequalities" (2011). Cowles Foundation Discussion Papers. 2199.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/2199