Impossibility Results for Nondifferentiable Functionals

Keisuke Hirano and Jack Porter

MPRA Paper from University Library of Munich, Germany

Abstract: We examine challenges to estimation and inference when the objects of interest are nondifferentiable functionals of the underlying data distribution. This situation arises in a number of applications of bounds analysis and moment inequality models, and in recent work on estimating optimal dynamic treatment regimes. Drawing on earlier work relating differentiability to the existence of unbiased and regular estimators, we show that if the target object is not continuously differentiable in the parameters of the data distribution, there exist no locally asymptotically unbiased estimators and no regular estimators. This places strong limits on estimators, bias correction methods, and inference procedures.

Keywords: bounds analysis; moment inequality models; treatment effects; limits of experiments (search for similar items in EconPapers)
JEL-codes: C1 C13 C14 (search for similar items in EconPapers)
Date: 2009-06-29
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Impossibility Results for Nondifferentiable Functionals (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:15990

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