论文标题
在存在滋扰参数的情况下，模型不完整的强大测试
Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters
论文作者
论文摘要
经济模型可能会表现出不完整，具体取决于他们是否承认某些与政策相关的特征，例如战略互动，自我选择或国家依赖性。我们开发了模型不完整的新测试，并分析了其渐近特性。一个关键观察是，人们可以识别最不利的参数模型，该模型代表了在不了解选择机制的情况下检测本地替代方案最具挑战性的情况。我们对从这种模型构建的分数函数上建立了不完整的测试。即使使用滋扰参数，提出的程序仍可以在计算上进行计算，因为仅在模型完整性的零假设下才能对其进行估算。我们通过将测试应用于市场进入模型和具有设置值控制功能的三角形模型来说明该测试。
Economic models may exhibit incompleteness depending on whether or not they admit certain policy-relevant features such as strategic interaction, self-selection, or state dependence. We develop a novel test of model incompleteness and analyze its asymptotic properties. A key observation is that one can identify the least-favorable parametric model that represents the most challenging scenario for detecting local alternatives without knowledge of the selection mechanism. We build a robust test of incompleteness on a score function constructed from such a model. The proposed procedure remains computationally tractable even with nuisance parameters because it suffices to estimate them only under the null hypothesis of model completeness. We illustrate the test by applying it to a market entry model and a triangular model with a set-valued control function.
