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Additive Nonparametric Regression in the Presence of Endogenous Regressors

In this paper we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient and free from the curse of dimensionality. Monte Carlo simulations support the asymptotic developments. We employ a partially linear extension of our model to study the relationship between child care and cognitive outcomes. Some of our (average) results are consistent with the literature (e.g., negative returns to child care when mothers have higher levels of education). However, as our estimators allow for heterogeneity both across and within groups, we are able to contradict many findings in the literature (e.g., we do not find any significant differences in returns between boys and girls or for formal versus informal child care)
Year of publication:
2014
Authors: Ozabaci, Deniz
Other Persons: Henderson, Daniel J. (contributor) ; Su, Liangjun (contributor)
Publisher: [2014]: [S.l.] : SSRN
Subject: Regressionsanalyse | Regression analysis | Nichtparametrisches Verfahren | Nonparametric statistics | Schätztheorie | Estimation theory
Extent:
1 Online-Ressource (53 p)
Series:
Type of publication: Book / Working Paper
Language: English
Other identifiers:
10.2139/ssrn.2432428 [DOI]
Classification: C14 - Semiparametric and Nonparametric Methods ; c36 ; I21 - Analysis of Education ; J13 - Fertility; Family Planning; Child Care; Children; Youth
Source:
ECONIS - Online Catalogue of the ZBW
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013054589
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