Rank estimation of partially linear index models

Abrevaya, J; Shin, Y

Rank estimation of partially linear index models

Abrevaya, J Shin, Y

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Publication Type:: Journal Article
Citation:: Econometrics Journal, 2011, 14 (3), pp. 409 - 437
Issue Date:: 2011-10-01

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Field	Value	Language
dc.contributor.author	Abrevaya, J	en_US
dc.contributor.author	Shin, Y https://orcid.org/0000-0002-2711-6906	en_US
dc.date.issued	2011-10-01	en_US
dc.identifier.citation	Econometrics Journal, 2011, 14 (3), pp. 409 - 437	en_US
dc.identifier.issn	1368-4221	en_US
dc.identifier.uri	http://hdl.handle.net/10453/112678
dc.description.abstract	Summary We consider a generalized regression model with a partially linear index. The index contains an additive non-parametric component in addition to the standard linear component, and the model is characterized by an unknown monotone link function. We propose weighted rank estimation procedures for estimating (a) the coefficients for the linear component, (b) the non-parametric component (and its derivative) and (c) the average derivative for the non-parametric component. The method is applied to study the non-linear relationship between household income and children's cognitive development. © 2011 The Author(s). The Econometrics Journal © 2011 Royal Economic Society.	en_US
dc.relation.ispartof	Econometrics Journal	en_US
dc.relation.isbasedon	10.1111/j.1368-423X.2011.00352.x	en_US
dc.subject.classification	Econometrics	en_US
dc.title	Rank estimation of partially linear index models	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	14	en_US
utslib.for	1403 Econometrics	en_US
utslib.for	0104 Statistics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	14	en_US

Abstract:

Summary We consider a generalized regression model with a partially linear index. The index contains an additive non-parametric component in addition to the standard linear component, and the model is characterized by an unknown monotone link function. We propose weighted rank estimation procedures for estimating (a) the coefficients for the linear component, (b) the non-parametric component (and its derivative) and (c) the average derivative for the non-parametric component. The method is applied to study the non-linear relationship between household income and children's cognitive development. © 2011 The Author(s). The Econometrics Journal © 2011 Royal Economic Society.

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http://hdl.handle.net/10453/112678