Publication Type

Journal Article

Version

Preprint

Publication Date

10-2014

Abstract

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.

Keywords

Additive regression, Endogeneity, Generated regressors, Oracle estimation, Structural equation

Discipline

Econometrics | Economics

Research Areas

Econometrics

Publication

Journal of Business and Economic Statistics

Volume

32

Issue

4

First Page

555

Last Page

575

ISSN

0735-0015

Identifier

10.1080/07350015.2014.917590

Publisher

Taylor and Francis

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1080/07350015.2014.917590

Included in

Econometrics Commons

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