Conditional Inference with a Functional Nuisance Parameter
38 Pages Posted: 25 Sep 2014
Date Written: September 22, 2014
Abstract
This paper shows that the problem of testing hypotheses in moment condition models without any assumptions about identification may be considered as a problem of testing with an infinite-dimensional nuisance parameter. We introduce a sufficient statistic for this nuisance parameter and propose conditional tests. These conditional tests have uniformly correct asymptotic size for a large class of models and test statistics. We apply our approach to construct tests based on quasi-likelihood ratio statistics, which we show are efficient in strongly identified models and perform well relative to existing alternatives in two examples.
Keywords: weak identification, similar test, conditional inferences
JEL Classification: C30
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