Competing risks quantile regression at work : in-depth exploration of the role of public child support for the duration of maternity leave

Stephan DLUGOSZ, Ming Sum, Simon LO, Ralf A. WILKE

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

Abstract

Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.
Original languageEnglish
JournalJournal of Applied Statistics
VolumeAdvance online publication
DOIs
Publication statusPublished - 11 Apr 2016

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Competing Risks
Quantile Regression
Regression Model
Public Policy
Proportional Hazards Model
Empirical Analysis
Multivariate Data
Empirical Study
Incidence
Economics
Model
Children
Maternity leave
Child support
Competing risks
Quantile regression
Regression model

Cite this

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title = "Competing risks quantile regression at work : in-depth exploration of the role of public child support for the duration of maternity leave",
abstract = "Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.",
author = "Stephan DLUGOSZ and LO, {Ming Sum, Simon} and WILKE, {Ralf A.}",
year = "2016",
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Competing risks quantile regression at work : in-depth exploration of the role of public child support for the duration of maternity leave. / DLUGOSZ, Stephan; LO, Ming Sum, Simon; WILKE, Ralf A.

In: Journal of Applied Statistics, Vol. Advance online publication, 11.04.2016.

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

TY - JOUR

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AU - LO, Ming Sum, Simon

AU - WILKE, Ralf A.

PY - 2016/4/11

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N2 - Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.

AB - Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.

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