Hypothesis Testing with a Restricted Parameter Space

This paper considers hypothesis tests for nonlinear econometric models when the parameter space is restricted under the alternative hypothesis. Multivariate one-sided tests are a leading example. Asymptotically optimal tests are derived using a weighted average power criterion. In addition, the likelihood ratio test is shown to be asymptotically admissible and to maximize asymptotic power against alternatives that are arbitrarily distant from the null hypothesis. For Gaussian linear regression models with known variance, analogous exact finite sample results are established.