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Issue title: Estimation, Testing and Forecasting in Econometrics
Subtitle:
Guest editors: Jiti Gao and Maxwell L. King
Article type: Research Article
Authors: King, Maxwell L.a; * | Sriananthakumar, Sivagowryb
Affiliations: [a] Department of Econometrics and Business Statistics, Monash University, Victoria, Australia | [b] School of Economics, Finance and Marketing, RMIT University, Melbourne, Australia
Correspondence: [*] Corresponding author: Maxwell L. King, Department of Econometrics and Business Statistics, Monash University, Victoria, Australia. E-mail:[email protected]
Abstract: In the absence of uniformly most powerful (UMP) tests or uniformly most powerful invariant (UMPI) tests, King [80] suggested the use of Point Optimal (PO) tests, which are most powerful at a chosen point under the alternative hypothesis. This paper surveys the literature and major developments on point optimal testing since 1987 and suggests some areas for future research. Topics include tests for which all nuisance parameters have been eliminated and dealing with nuisance parameters via (i) a weighted average of p values, (ii) approximate point optimal tests, (iii) plugging in estimated parameter values, (iv) using asymptotics and (v) integration. Progress on using point-optimal testing principles for two-sided testing and multi-dimensional alternatives is also reviewed. The paper concludes with thoughts on how best to deal with nuisance parameters under both the null and alternative hypotheses, as well as the development of a new class of point optimal tests for multi-dimensional testing.
Keywords: Local to unity asymptotics, Neyman-Pearson lemma, nuisance parameters, power envelope, unit root testing
DOI: 10.3233/MAS-150323
Journal: Model Assisted Statistics and Applications, vol. 10, no. 3, pp. 179-196, 2015
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