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.

翻译：经济模型可能因是否包含策略互动、自选择或状态依赖等政策相关特征而表现出不完备性。我们提出了一种新的模型不完备性检验方法，并分析了其渐近性质。关键发现是，无需了解选择机制即可识别出最具挑战性的局部备择假设检测场景中的最不利参数模型。我们基于该模型的得分函数构建了不完备性的稳健检验。由于仅需在模型完备性的原假设下估计干扰参数，即使存在干扰参数，该检验流程仍保持计算可行性。我们通过市场进入模型和具有集值控制函数的三角模型的应用实例展示了该检验方法。