Nonparametric estimation in case of endogenous selection

Breunig, Christoph ; Mammen, Enno ; Simoni, Anna

DOI:	https://doi.org/10.18452/4607
URL:	https://edoc.hu-berlin.de/bitstream/handle/18452/5...
Document Type:	Working paper
Year of publication:	2015
The title of a journal, publication series:	SFB 649 Discussion Paper
Volume:	15-050
Place of publication:	Berlin
Publishing house:	Sonderforschungsbereich Ökonomisches Risiko
ISSN:	1860-5664
Publication language:	English
Institution:	Außerfakultäre Einrichtungen > Graduate School of Economic and Social Sciences - CDSE (Economics)
Subject:	330 Economics
Abstract:	This paper addresses the problem of estimation of a nonparametric regression function from selectively observed data when selection is endogenous. Our approach relies on independence between covariates and selection conditionally on potential outcomes. Endogeneity of regressors is also allowed for. In both cases, consistent two-step estimation procedures are proposed and their rates of convergence are derived. Also pointwise asymptotic distribution of the estimators is established. In addition, we propose a nonparametric specification test to check the validity of our independence assumption. Finite sample properties are illustrated in a Monte Carlo simulation study and an empirical illustration.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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Breunig, Christoph ; Mammen, Enno ; Simoni, Anna (2015) Nonparametric estimation in case of endogenous selection. SFB 649 Discussion Paper Berlin 15-050 [Working paper]

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