Nearly Optimal Tests When a Nuisance Parameter Is Present Under the Null Hypothesis.
This paper considers nonstandard hypothesis testing problems that involve a nuisance parameter. We establish an upper bound on the weighted average power of all valid tests, and develop a numerical algorithm that determines a feasible test with power close to the bound. The approach is illustrated i...
| Publicado en: | Econometrica Vol. 83; no. 2; pp. 771 - 812 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Mar2015
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | This paper considers nonstandard hypothesis testing problems that involve a nuisance parameter. We establish an upper bound on the weighted average power of all valid tests, and develop a numerical algorithm that determines a feasible test with power close to the bound. The approach is illustrated in six applications: inference about a linear regression coefficient when the sign of a control coefficient is known; small sample inference about the difference in means from two independent Gaussian samples from populations with potentially different variances; inference about the break date in structural break models with moderate break magnitude; predictability tests when the regressor is highly persistent; inference about an interval identified parameter; and inference about a linear regression coefficient when the necessity of a control is in doubt. |
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