ADMISSIBLE, SIMILAR TESTS: A CHARACTERIZATION
可容许相似检验的刻画AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要主要贡献是含干扰参数检验的一般决策理论刻画，工具变量示例不足以明确归入所列应用细分。
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可容许相似检验的刻画
- 研究问题
- 在含干扰参数的精确原假设检验中，可容许性与相似性是否能通过受约束的加权平均功效最大化来完整刻画？
- 方法与思路
- 作者研究相似性约束下的加权平均功效最大化，并在同方差工具变量模型中提出结构参数权重及对应检验。
- 材料陈述的贡献
- 摘要称，文章补充受约束功效最大化本质上的必要性结果，与已有充分性结合，形成可容许相似检验的刻画。
- 阅读关注点
- 应核对“本质上必要”的限定、允许的权重函数与检验类，以及全向量推断范围和工具变量应用的比较条件。
- 阅读边界
- 仅依据所给 Crossref 摘要；该刻画明确不适用于子向量推断，具体比较指标未说明，也不能据此声称新检验更优。
原文摘要
This article studies a classical problem in statistical decision theory: a hypothesis test of a sharp null in the presence of a nuisance parameter. The main contribution of this article is a characterization of two finite-sample properties often deemed reasonable in this environment: admissibility and similarity . Admissibility means that a test cannot be improved uniformly over the parameter space. Similarity requires the null rejection probability to be unaffected by the nuisance parameter. The characterization result has two parts. The first part—established by Chernozhukov, Hansen, and Jansson (2009, Econometric Theory 25, 806–818)—states that maximizing weighted average power (WAP) subject to a similarity constraint suffices to generate admissible, similar tests. The second part—hereby established—states that constrained WAP maximization is ( essentially ) a necessary condition for a test to be admissible and similar. The characterization result shows that choosing an admissible, similar test is tantamount to selecting a particular weight function to report weighted average power. This result applies to full vector inference with a nuisance parameter, not to subvector inference. The article also revisits the theory of testing in the instrumental variables model. Specifically—and in light of the relevance of the weighted average power criterion in the main theoretical result—the article suggests a weight function for the structural parameters of the homoskedastic instrumental variables model, based on the priors proposed by Chamberlain (2007). The corresponding test is, by construction, admissible and similar. In addition, the test is shown to have finite- and large-sample properties comparable to those of the conditional likelihood ratio test.