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A Partially Linear Censored Quantile Regression Model for Unemployment Duration

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Author Info

  • Neocleous, Tereza

    (University of Glasgow)

  • Portnoy, Stephen

    (University of Illinois)

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    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.

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    Bibliographic Info

    Paper provided by IRISS at CEPS/INSTEAD in its series IRISS Working Paper Series with number 2008-07.

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    Length: 27 pages
    Date of creation: Sep 2008
    Date of revision:
    Publication status: Forthcoming in Lifetime Data Analysis, DOI: 10.1007/s10985-009-9117-5
    Handle: RePEc:irs:iriswp:2008-07

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    Related research

    Keywords: quantile regression ; partially linear models ; B-splines ; censored data ; unemployment duration;

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    Cited by:
    1. Sohn, Christophe & Reitel, Bernard & Walther, Olivier, 2009. "Cross-border metropolitan integration in Europe (Luxembourg, Basel and Geneva)," IRISS Working Paper Series 2009-02, IRISS at CEPS/INSTEAD.

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