ADAPTIVE TESTS OF CONDITIONAL MOMENT INEQUALITIES
ADAPTIVE TESTS OF CONDITIONAL MOMENT INEQUALITIES
复制标题
条件矩不等式的自适应检验
DOI：
10.1017/s0266466617000184
复制
发表时间：
2018
影响因子：
0.8
通讯作者：
D. Chetverikov
中科院分区：
文献类型：
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作者：
D. Chetverikov
许多经济模型都会产生条件矩不等式，可用于推断这些模型的参数。在本文中，我基于矩函数的学生化核估计，构建了条件矩不等式模型中参数假设的新检验。这些测试自动适应矩函数的未知平滑度，具有一致正确的渐近大小，并且针对某些类别的替代方案是速率最优的。一些现有的测试对于某种类型的 n−1/2-local 替代方案具有非凡的能力，而我的方法只允许针对这种类型的 (n / log n)−1/2-local 替代方案进行非凡的测试。然而，存在大量表现良好的替代方案序列，本文中开发的测试与这些替代方案相一致，而这些测试则不一致。
Many economic models yield conditional moment inequalities that can be used for inference on parameters of these models. In this paper, I construct new tests of parameter hypotheses in conditional moment inequality models based on studentized kernel estimates of moment functions. The tests automatically adapt to the unknown smoothness of the moment functions, have uniformly correct asymptotic size, and are rate-optimal against certain classes of alternatives. Some existing tests have nontrivial power against n−1/2-local alternatives of a certain type whereas my methods only allow for nontrivial testing against (n / log n)−1/2-local alternatives of this type. There exist, however, large classes of sequences of well-behaved alternatives against which the tests developed in this paper are consistent and those tests are not.