INVESTIGADORES
MONTES ROJAS Gabriel Victorio
artículos
Título:
A new robust and most powerful test in the presence of local misspecification
Autor/es:
BERA, ANIL K.; MONTES-ROJAS, GABRIEL; SOSA-ESCUDERO, WALTER
Revista:
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Editorial:
TAYLOR & FRANCIS INC
Referencias:
Año: 2017 vol. 46 p. 8187 - 8187
ISSN:
0361-0926
Resumen:
This article proposes a new test that is consistent, achieves correct asymptotic size, and is locally most powerful under local misspecification, and when any root-n-estimator of the nuisance parameters is used. The newtest can be seen as an extension of the Bera and Yoon (1993) procedure that deals with non maximum likelihood (ML) estimation, whilepreserving its optimality properties. Similarly, the proposed test extendsNeyman?s (1959) C(alpha) test to handle locally misspecified alternatives. A Monte Carlo study investigates the finite sample performance in termsof size, power, and robustness to misspecification.