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A practical two-step method for testing moment inequalities

Joseph P. Romano, Azeem Shaikh () and Michael Wolf ()

No 90, ECON - Working Papers from Department of Economics - University of Zurich

Abstract: This paper considers the problem of testing a finite number of moment inequalities. We propose a two-step approach. In the first step, a confidence region for the moments is constructed. In the second step, this set is used to provide information about which moments are “negative.” A Bonferonni-type correction is used to account for the fact that with some probability the moments may not lie in the confidence region. It is shown that the test controls size uniformly over a large class of distributions for the observed data. An important feature of the proposal is that it remains computationally feasible, even when the number of moments is large. The finite-sample properties of the procedure are examined via a simulation study, which demonstrates, among other things, that the proposal remains competitive with existing procedures while being computationally more attractive.

Keywords: Bonferonni inequality; bootstrap; moment inequalities; partial identification; uniform validity (search for similar items in EconPapers)
JEL-codes: C12 C14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2012-08, Revised 2014-04
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Journal Article: A Practical Two‐Step Method for Testing Moment Inequalities (2014) Downloads
Journal Article: A Practical Two‐Step Method for Testing Moment Inequalities (2014) Downloads
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