Document Type
Discussion Paper
Publication Date
10-1-2014
CFDP Number
1960R2
CFDP Revision Date
2017-07-01
CFDP Pages
45
Abstract
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.
Recommended Citation
Armstrong, Timothy B., "On the Choice of Test Statistic for Conditional Moment Inequalities" (2014). Cowles Foundation Discussion Papers. 2371.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/2371
Supplemental material
Comments
Supplement Materials, 17 pp