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One Sided Hypothesis Testing in Econometrics: A Survey

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  • Wu, P.X.
  • King, M.L.

Abstract

Any model is accompanied by a set of assumptions. These assumptions are based either on the underlying theory of the phenomena being modelled or on stylized statistical evidence, or more commonly on both. These, along with functional considerations such as variances being positive, often imply that values of some parameters characterizing a model are restricted to one side of a point in the parameter space. This information can be used to improve the power of hypothesis testing procedures. In this paper, we discuss some recent developments on testing against such one-sided alternative hypotheses with particular emphasis on the econometrics literature. The focus is on two main approaches: that based on maximum likelihood estimation and that based on local power optimization facilitated by the generalized Neyman-Pearson lemma. Both single parameter and multi-parameter testing problems are considered.
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Suggested Citation

  • Wu, P.X. & King, M.L., 1994. "One Sided Hypothesis Testing in Econometrics: A Survey," Monash Econometrics and Business Statistics Working Papers 6/94, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:1994-6
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    Cited by:

    1. Oliver Linton & Douglas Steigerwald, 2000. "Adaptive testing in arch models," Econometric Reviews, Taylor & Francis Journals, vol. 19(2), pages 145-174.
    2. Jahar L. Bhowmik & Maxwell L. King, 2005. "Deriving Tests of the Semi-Linear Regression Model Using the Density Function of a Maximal Invariant," Monash Econometrics and Business Statistics Working Papers 19/05, Monash University, Department of Econometrics and Business Statistics.
    3. Ping, Wu & King, Maxwell L., 1996. "Small-sample power of tests for inequality restrictions: The case of quarter-dependent regression errors," Economics Letters, Elsevier, vol. 52(2), pages 121-127, August.
    4. Jin Lee, 2000. "One-Sided Testing for ARCH Effect Using Wavelets," Econometric Society World Congress 2000 Contributed Papers 1214, Econometric Society.

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