Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/97375 
Year of Publication: 
2014
Series/Report no.: 
cemmap working paper No. CWP05/14
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
This paper introduces a new hypothesis test for the null hypothesis H0 : f(Ø) = Y0, where f(.) is a known function, Y0 is a known constant, and Ø is a parameter that is partially identified by a moment (in)equality model. The main application of our test is sub-vector inference in moment inequality models, that is, for a multidimensional Ø, the function f(Ø) = Øk selects the kth coordinate of Ø. Our test controls asymptotic size uniformly over a large class of distributions of the data and has better asymptotic power properties than currently available methods. In particular, we show that the new test has asymptotic power that dominates the one corresponding to two existing competitors in the literature: subsampling and projection-based tests
Subjects: 
Partial Identification
Moment Inequalities
Sub-vector Inference
Hypothesis Testing
JEL: 
C01
C12
C15
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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