City Research Online

Abstract

This paper proposes a new test that is consistent, achieves correct asymptotic size and is locally most powerful under local misspecification, and when any square-root-of-n-estimator of the nuisance parameters is used. The new test can be seen as an extension of the Bera and Yoon (1993) procedure that deals with non-ML estimation, while preserving its optimality properties. Similarly, the proposed test extends Neyman's (1959) C(a) test to handle locally misspecified alternatives. A Monte Carlo study investigates the finite sample performance in terms of size, power and robustness to misspecification.

Publication Type:	Article
Additional Information:	This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 5/8/16, available online: http://dx.doi.org/10.1080/03610926.2016.1177077
Publisher Keywords:	Specification testing, Rao's score test, Local misspecification, Neyman's C(α),
Subjects:	H Social Sciences > HB Economic Theory
Departments:	School of Policy & Global Affairs > Economics
SWORD Depositor:	Symplectic Administrator

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