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Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models

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  • Myoung-jae Lee
  • Maria Karlsson

Abstract

For a linear regression model subject to left-truncation and right-censoring where the truncation and censoring points are known constants (or always observed if random), Karlsson and Laitila (Stat Probab Lett 78:2567–2571, 2008 ) proposed a semiparametric estimator which deals with left-truncation by trimming and right-censoring by ‘winsorizing’. The estimator was motivated by a zero moment condition where a transformed error term appears with trimmed and winsorized tails. This paper takes the semiparametric estimator further by deriving the asymptotic distribution that was not shown in Karlsson and Laitila (Stat Probab Lett 78:2567–2571, 2008 ) and discusses its implementation aspects in practice, albeit brief. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Myoung-jae Lee & Maria Karlsson, 2015. "Trimmed and winsorized semiparametric estimator for left-truncated and right-censored regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(4), pages 485-495, May.
    • Handle: RePEc:spr:metrik:v:78:y:2015:i:4:p:485-495
    DOI: 10.1007/s00184-014-0513-9
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    References listed on IDEAS

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    1. Newey, Whitney K. & Powell, James L., 1990. "Efficient Estimation of Linear and Type I Censored Regression Models Under Conditional Quantile Restrictions," Econometric Theory, Cambridge University Press, vol. 6(3), pages 295-317, September.
    2. Newey, Whitney K., 2001. "Conditional Moment Restrictions In Censored And Truncated Regression Models," Econometric Theory, Cambridge University Press, vol. 17(5), pages 863-888, October.
    3. Karlsson, Maria & Laitila, Thomas, 2008. "A semiparametric regression estimator under left truncation and right censoring," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2567-2571, November.
    4. Lee, Myoung-jae, 1993. "Quadratic mode regression," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 1-19.
    5. Lee, Myoung-Jae, 1992. "Winsorized Mean Estimator for Censored Regression," Econometric Theory, Cambridge University Press, vol. 8(3), pages 368-382, September.
    6. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    7. Pao-sheng Shen, 2009. "A class of rank-based test for left-truncated and right-censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 461-476, June.
    8. Maria Karlsson, 2006. "Estimators of Regression Parameters for Truncated and Censored Data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 63(3), pages 329-341, June.
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