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ADAPTIVE TESTS OF CONDITIONAL MOMENT INEQUALITIES

Published online by Cambridge University Press:  05 June 2017

Denis Chetverikov
Denis Chetverikov*
Affiliation:
UCLA
*
*Address correspondence to Denis Chetverikov, Economics Department, UCLA, Los Angeles, CA, USA; e-mail: chetverikov@econ.ucla.edu.
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Abstract

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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.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 34 , Issue 1 , February 2018, pp. 186 - 227
Copyright
Copyright © Cambridge University Press 2017 

Footnotes

I thank Victor Chernozhukov for his guidance, numerous discussions and permanent support. I am also grateful to Isaiah Andrews, Tim Armstrong, Jin Hahn, Jerry Hausman, Kengo Kato, Anton Kolotilin, Simon Lee, Rosa Matzkin, Anna Mikusheva, and Adam Rosen for useful comments and discussions.

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