Nonparametric Inference Based on Conditional Moment Inequalities
نویسندگان
چکیده
This paper develops methods of inference for nonparametric and semiparametric parameters de ned by conditional moment inequalities and/or equalities. The parameters need not be identi ed. Con dence sets and tests are introduced. The correct uniform asymptotic size of these procedures is established. The false coverage probabilities and power of the CSs and tests are established for xed alternatives and some local alternatives. Finite-sample simulation results are given for a nonparametric conditional quantile model with censoring and a nonparametric conditional treatment e¤ect model. The recommended CS/test uses a Cramér-von-Mises-type test statistic and employs a generalized moment selection critical value. Keywords: Asymptotic size, kernel, local power, moment inequalities, nonparametric inference, partial identi cation. JEL Classi cation Numbers: C12, C15.
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