Testing multiple inequality hypotheses: a smoothed indicator approach

Le-Yu Chen and Jerzy Szroeter
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Jerzy Szroeter: Institute for Fiscal Studies

No CWP16/12, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: This paper proposes a class of origin-smooth approximators of indicators underlying the sum-of-negative-part statistic for testing multiple inequalities. The need for simulation or bootstrap to obtain test critical values is thereby obviated. A simple procedure is enabled using fixed critical values. The test is shown to have correct asymptotic size in the uniform sense that supremum finite-sample rejection probability over null-restricted data distributions tends asymptotically to nominal significance level. This applies under weak assumptions allowing for estimator covariance singularity. The test is unbiased for a wide class of local alternatives. A new theorem establishes directions in which the test is locally most powerful. The proposed procedure is compared with predominant existing tests in structure, theory and simulation. This paper is a revised version of CWP13/09.

Keywords: Test; Multiple inequalities; One-sided hypothesis; Composite null; Binding constraints; Asymptotic exactness; Covariance singularity; Indicator smoothing (search for similar items in EconPapers)
JEL-codes: C1 C4 (search for similar items in EconPapers)
Date: 2012-07-06
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: Testing multiple inequality hypotheses: A smoothed indicator approach (2014)
Working Paper: Testing multiple inequality hypotheses: a smoothed indicator approach (2012)
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