论文标题
使用双重预测的广义倾向得分的规范测试
Specification tests for generalized propensity scores using double projections
论文作者
论文摘要
本文提出了一类新的非参数测试，以根据条件力矩限制对模型的正确规范进行正确的规范，并特别注意广义倾向得分模型。测试程序基于两个不同的投影参数，导致测试统计量适用于许多协变量的设置，并且（渐近）不变，用于估计估算滋扰参数的估计方法。我们表明，我们提出的测试能够以通常的参数速率检测一类众多的局部替代方案，并通过模拟说明其有吸引力的功率属性。我们还将建议扩展到测试参数或半参数单折射类型模型。
This paper proposes a new class of nonparametric tests for the correct specification of models based on conditional moment restrictions, paying particular attention to generalized propensity score models. The test procedure is based on two different projection arguments, leading to test statistics that are suitable to setups with many covariates, and are (asymptotically) invariant to the estimation method used to estimate the nuisance parameters. We show that our proposed tests are able to detect a broad class of local alternatives converging to the null at the usual parametric rate and illustrate its attractive power properties via simulations. We also extend our proposal to test parametric or semiparametric single-index-type models.
