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An informative subset-based estimator for censored quantile regression

  • Yanlin Tang
  • Huixia Wang
  • Xuming He
  • Zhongyi Zhu

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    Quantile regression in the presence of fixed censoring has been studied extensively in the literature. However, existing methods either suffer from computational instability or require complex procedures involving trimming and smoothing, which complicates the asymptotic theory of the resulting estimators. In this paper, we propose a simple estimator that is obtained by applying standard quantile regression to observations in an informative subset. The proposed method is computationally convenient and conceptually transparent. We demonstrate that the proposed estimator achieves the same asymptotical efficiency as the Powell’s estimator, as long as the conditional censoring probability can be estimated consistently at a nonparametric rate and the estimated function satisfies some smoothness conditions. A simulation study suggests that the proposed estimator has stable and competitive performance relative to more elaborate competitors. Copyright Sociedad de Estadística e Investigación Operativa 2012

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    File URL: http://hdl.handle.net/10.1007/s11749-011-0266-y
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    Article provided by Springer in its journal TEST.

    Volume (Year): 21 (2012)
    Issue (Month): 4 (December)
    Pages: 635-655

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    Handle: RePEc:spr:testjl:v:21:y:2012:i:4:p:635-655
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    1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275.
    2. Roger Koenker, . "Censored Quantile Regression Redux," Journal of Statistical Software, American Statistical Association, vol. 27(i06).
    3. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of Semiparametric Models when the Criterion Function is not Smooth," STICERD - Econometrics Paper Series 450, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    5. Khan, Shakeeb & Powell, James L., 2001. "Two-step estimation of semiparametric censored regression models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 73-110, July.
    6. repec:cep:stiecm:/2003/450 is not listed on IDEAS
    7. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
    8. Wang, Huixia Judy & Wang, Lan, 2009. "Locally Weighted Censored Quantile Regression," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1117-1128.
    9. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.
    10. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
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