We propose a novel statistic for testing the structural parameters in Instrumental Variables Regression. The statistic is straightforward to compute and has a limiting distribution that is pivotal with a degrees of freedom parameter that is equal to the number of tested parameters. It therefore differs from the Anderson-Rubin statistic, whose limiting distribution is pivotal but has a degrees of freedom parameter that is equal to the number of instruments, and the Likelihood based, Wald, Likelihood Ratio and Lagrange Multiplier, statistics, whose limiting distributions are not pivotal. We analyze the relationship between the statistic and the concentrated likelihood of the structural parameters and show that its' limiting distribution is not affected by weak instruments. We discuss examples of the non-standard shapes of the asymptotically pivotal confidence sets that can be constructed using the statistic and investigate its power properties. To show its importance for practical purposes, we apply the statistic to the Angrist-Krueger (1991) data and find similar results as in Staiger and Stock (1997).
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机译：我们提出了一种新的统计量，用于测试工具变量回归中的结构参数。该统计信息易于计算，并且具有一个极限分布，该极限分布的自由度参数等于测试参数的数量。因此，它不同于Anderson-Rubin统计量（其极限分布是关键的，但具有一个等于工具数量的自由度参数），以及基于可能性的Wald，似然比和Lagrange乘数统计，其极限分布为不关键。我们分析了统计量与结构参数集中可能性之间的关系，并表明其极限分布不受弱仪器的影响。我们讨论了可以使用统计量构造的渐近关键置信度集合的非标准形状的示例，并研究了其幂属性。为了显示其实际意义，我们将统计数据应用于Angrist-Krueger（1991）数据，并发现与Staiger and Stock（1997）类似的结果。
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