On ill-posedness of nonparametric instrumental variable regression with convexity constraints

Olivier Scaillet

This note shows that adding monotonicity or convexity constraints on the regression function does not restore well-posedness in nonparametric instrumental variable regression. The minimum distance problem without regularisation is still locally ill-posed

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Year of publication:	January 2016 ; First draft: January 2016
Authors:	Scaillet, Olivier
Publisher:	[Geneva] : Swiss Finance Institute
Subject:	Nonparametric Estimation \| Instrumental Variable \| Ill-Posed Inverse Problems \| Nichtparametrisches Verfahren \| Nonparametric statistics \| IV-Schätzung \| Instrumental variables \| Schätztheorie \| Estimation theory \| Nichtparametrische Schätzung \| Nonparametric estimation \| Regressionsanalyse \| Regression analysis

Extent:	1 Online-Ressource (circa 6 Seiten) Illustrationen
Series:	Research paper series / Swiss Finance Institute. - Geneva, ZDB-ID 2392286-2. - Vol. no. 16-06
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Arbeitspapier ; Working Paper ; Graue Literatur ; Non-commercial literature
Language:	English
Other identifiers:	10.2139/ssrn.2720312 [DOI]
Classification:	C13 - Estimation ; C14 - Semiparametric and Nonparametric Methods ; c26
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011515736