CFDP 1620

Validity of Subsampling and ‘Plug-in Asymptotic’ Inference for Parameters Defined by Moment Inequalities


Publication Date: July 2007

Pages: 43


This paper considers inference for parameters defined by moment inequalities and equalities. The parameters need not be identified. For a specified class of test statistics, this paper establishes the uniform asymptotic validity of subsampling, m out of n bootstrap, and “plug-in asymptotic” tests and confidence intervals for such parameters. Establishing uniform asymptotic validity is crucial in moment inequality problems because the test statistics of interest have discontinuities in their pointwise asymptotic distributions.

The size results are quite general because they hold without specifying the particular form of the moment conditions — only 2 + δ moments finite are required. The results allow for i.i.d. and dependent observations and for preliminary consistent estimation of identified parameters.


Asymptotic size, Confidence set, Exact size, m out of n bootstrap, Subsampling, Moment inequalities

JEL Classification Codes:  C12, C15

See CFP: 1268