Hodges-Lehmann Optimality For Testing Moment

This paper studies the Hodges and Lehmann (1956) optimality of tests in a general setup. The tests are compared by the exponential rates of growth to one of the power functions evaluated at a fixed alternative while keeping the asymptotic sizes bounded by some constant. The authors present two sets of sufficient conditions for a test to be Hodges-Lehmann optimal. These new conditions extend the scope of the Hodges-Lehmann optimality analysis to setups that cannot be covered by other conditions in the literature. The general result is illustrated by the applications of interest: testing for moment conditions and overidentifying restrictions.

Provided by: Yale University Topic: Big Data Date Added: Mar 2011 Format: PDF

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