CFDP 1960R2

CFDP Title: 

On the Choice of Test Statistic for Conditional Moment Inequalities

Publication Date: October, 2014

Revised: July, 2017

Pages: 45pp

Supplemental material

Pages: 17pp


This paper derives asymptotic approximations to the power of Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequalities in the case where the parameter is set identified. Combined with power results for Kolmogorov-Smirnov (KS) tests, these results can be used to choose the optimal test statistic, weighting function and, for tests based on kernel estimates, kernel bandwidth. The results show that, in the setting considered here, KS tests are preferred to CvM tests, and that a truncated variance weighting is preferred to bounded weightings.


Moment inequalities, Relative efficiency

JEL Classifications:

C10, C12, C14

JEL Classifications: C10C12C14