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Robust Inference for Inverse Stochastic Dominance

Bibliographic Data

ID19418005
AuthorsFrancesco Andreoli (0000-0002-0751-5520, Living Conditions Department, Luxembourg Institute of Socio-Economic Research (LISER), L-4366 Esch-sur-Alzette/Belval Campus, Luxembourg (), corresponding author)
Year2018
Volume36
Issue1
Pages146-159
Publication date2018-01-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Business and Economic Statistics (JOURNAL)
Journal identifiersISSN: 0735-0015 • E-ISSN: 1537-2707
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/07350015.2015.1137758
OpenAlexW2562613355
LanguageEN
Citations received4
References cited41

The notion of inverse stochastic dominance is gaining increasing support in risk, inequality, and welfare analysis as a relevant criterion for ranking distributions, which is alternative to the standard stochastic dominance approach. Its implementation rests on comparisons of two distributions’ quantile functions, or of their multiple partial integrals, at fixed population proportions. This article develops a novel statistical inference model for inverse stochastic dominance that is based on the influence function approach. The proposed method allows model-free evaluations that are limitedly affected by contamination in the data. Asymptotic normality of the estimators allows to derive tests for the restrictions implied by various forms of inverse stochastic dominance. Monte Carlo experiments and an application promote the qualities of the influence function estimator when compared with alternative dominance criteria

Econometrics · Estimator · Inference · Inverse · Mathematical optimization · Population · Quantile · Statistics · Stochastic dominance · Advanced Causal Inference Techniques · Computer Science · Economic and Environmental Valuation · Mathematics · Statistical Methods and Bayesian Inference · Applied Mathematics · Artificial Intelligence

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Unique citing works4
Citations per year0,57
Citation span2019 - 2021 (3)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 4

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