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A Partially Linear Censored Quantile Regression Model for Unemployment Duration

Tereza Neocleous and Stephen Portnoy

No 2008-07, IRISS Working Paper Series from IRISS at CEPS/INSTEAD

Abstract: Censored Regression Quantile (CRQ) methods provide a powerful and flexible approach for the analysis of censored survival data when standard linear models are felt to be appropriate. In many cases however, greater flexibility is desired to go beyond the usual multiple regression paradigm. One area of common interest is that of partially linear models, where one (or more) of the explanatory variables are assumed to act on the response through a non-linear function. Here the CRQ approach (Portnoy, 2003) is extended to such partially linear setting. Basic consistency results are presented. A simulation experiment and analysis of unemployment data example justify the use of the partially linear approach over methods based on the Cox proportional hazards regression model and methods not permitting nonlinearity.

Keywords: quantile regression; partially linear models; B-splines; censored data; unemployment duration (search for similar items in EconPapers)
Pages: 27 pages
Date: 2008-09
New Economics Papers: this item is included in nep-ecm
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