A new test for non-linear hypotheses under distributional and local parametric misspecification

Bera A. K., Doğan O., Taspinar S.

STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS, 2022 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1515/snde-2022-0043
  • Journal Name: STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, IBZ Online, International Bibliography of Social Sciences, ABI/INFORM, Business Source Elite, Business Source Premier, EconLit, zbMATH
  • Keywords: distributional misspecification, LM test, parametric misspecification, QMLE, Rao's score test, robust LM test, MAXIMUM-LIKELIHOOD-ESTIMATION, LM TESTS, MODEL
  • Istanbul Technical University Affiliated: Yes

Abstract

In this paper, we develop a new version of Rao's score (RS) statistic for testing a non-linear hypothesis under both distributional and local parametric misspecification. Our suggested test statistic is constructed through a size correction approach so that it becomes robust to both types of misspecification. We establish the asymptotic properties of the robust test statistic and provide several examples to illustrate its implementation. We also investigate the finite sample properties of our test along with some other well-known tests through simulations. Our simulation results demonstrate that the new test statistic has good finite sample properties in terms of empirical size and power.