Title

On the Choice of Test Statistic for Conditional Moment Inequalities

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.

Comments

Supplement Materials, 17 pp

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