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AI 根据所提供的论文材料归类:摘要研究独立横截面中的通用条件矩检验,未明确涉及给定分类中的因果、面板、选择或其他专门领域。

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关注这篇论文的作者
Richard J. Smith

附加条件矩限制的检验

研究问题
在独立横截面数据中,如何检验既有条件矩限制之外的附加限制,并充分利用维持假设所包含的信息?
方法与思路
作者构造纳入维持假设条件矩信息的受限检验,采用 GMM 与广义经验似然,并分析零假设及局部备择下的渐近性质。
材料陈述的贡献
摘要称框架允许两组限制具有不同参数和条件变量;模拟中部分受限检验表现出较好的经验尺寸和尺寸调整后功效。
阅读关注点
应核对维持假设如何进入统计量、两组条件矩的参数关系,以及受限与非受限检验比较时的尺寸调整和局部备择设定。
阅读边界
所给出版社摘要未说明具体正则条件、模拟设计和推荐检验的适用范围;其模拟优势不能视为所有场景下的普遍优势。

原文摘要

The primary focus of this article is the provision of tests for the validity of a set of conditional moment constraints additional to those defining the maintained hypothesis that are relevant for independent cross-sectional data contexts. The point of departure and principal contribution of the paper is the explicit and full incorporation of the conditional moment information defining the maintained hypothesis in the design of the test statistics. Thus, the approach mirrors that of the classical parametric likelihood setting by defining restricted tests in contradistinction to unrestricted tests that partially or completely fail to incorporate the maintained information in their formulation. The framework is quite general allowing the parameters defining the additional and maintained conditional moment restrictions to differ and permitting the conditioning variates to differ likewise. GMM and generalised empirical likelihood test statistics are suggested. The asymptotic properties of the statistics are described under both null hypothesis and a suitable sequence of local alternatives. An extensive set of simulation experiments explores the practical efficacy of the various test statistics in terms of empirical size and size-adjusted power confirming the superiority of restricted over unrestricted tests. A number of restricted tests possess both sufficiently satisfactory empirical size and power characteristics to allow their recommendation for econometric practice.

笔记与分组