Additive nonparametric regression in the presence of endogenous regressors

In this article 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...

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Main Authors: OZABACI, Deniz, HENDERSON, Daniel J., SU, Liangjun
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/soe_research/1634
https://ink.library.smu.edu.sg/context/soe_research/article/2633/viewcontent/AdditiveNonParametricRegressorsEndogenous.pdf
https://ink.library.smu.edu.sg/context/soe_research/article/2633/filename/0/type/additional/viewcontent/UBES_A_917590_Supplement.pdf
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spelling sg-smu-ink.soe_research-26332020-03-31T06:01:24Z Additive nonparametric regression in the presence of endogenous regressors OZABACI, Deniz HENDERSON, Daniel J. SU, Liangjun In this article 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). Supplementary materials for this article are available online. 2014-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1634 info:doi/10.1080/07350015.2014.917590 https://ink.library.smu.edu.sg/context/soe_research/article/2633/viewcontent/AdditiveNonParametricRegressorsEndogenous.pdf https://ink.library.smu.edu.sg/context/soe_research/article/2633/filename/0/type/additional/viewcontent/UBES_A_917590_Supplement.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Additive regression Endogeneity Generated regressors Oracle estimation Structural equation Econometrics Economics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Additive regression
Endogeneity
Generated regressors
Oracle estimation
Structural equation
Econometrics
Economics
spellingShingle Additive regression
Endogeneity
Generated regressors
Oracle estimation
Structural equation
Econometrics
Economics
OZABACI, Deniz
HENDERSON, Daniel J.
SU, Liangjun
Additive nonparametric regression in the presence of endogenous regressors
description In this article 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). Supplementary materials for this article are available online.
format text
author OZABACI, Deniz
HENDERSON, Daniel J.
SU, Liangjun
author_facet OZABACI, Deniz
HENDERSON, Daniel J.
SU, Liangjun
author_sort OZABACI, Deniz
title Additive nonparametric regression in the presence of endogenous regressors
title_short Additive nonparametric regression in the presence of endogenous regressors
title_full Additive nonparametric regression in the presence of endogenous regressors
title_fullStr Additive nonparametric regression in the presence of endogenous regressors
title_full_unstemmed Additive nonparametric regression in the presence of endogenous regressors
title_sort additive nonparametric regression in the presence of endogenous regressors
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/soe_research/1634
https://ink.library.smu.edu.sg/context/soe_research/article/2633/viewcontent/AdditiveNonParametricRegressorsEndogenous.pdf
https://ink.library.smu.edu.sg/context/soe_research/article/2633/filename/0/type/additional/viewcontent/UBES_A_917590_Supplement.pdf
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