Optimal testing in a class of nonregular models
Statistics Theory
2025-10-07 v2 Econometrics
Methodology
Statistics Theory
Abstract
This paper studies optimal hypothesis testing for nonregular econometric models with parameter-dependent support. We consider both one-sided and two-sided hypothesis testing and develop asymptotically uniformly most powerful tests based on a limit experiment. Our two-sided test becomes asymptotically uniformly most powerful without imposing further restrictions such as unbiasedness, and can be inverted to construct a confidence set for the nonregular parameter. Simulation results illustrate desirable finite sample properties of the proposed tests.
Cite
@article{arxiv.2403.16413,
title = {Optimal testing in a class of nonregular models},
author = {Yuya Shimizu and Taisuke Otsu},
journal= {arXiv preprint arXiv:2403.16413},
year = {2025}
}