ADAPTIVE TESTS OF CONDITIONAL MOMENT INEQUALITIES
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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.