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Local polynomial regression with truncated or censored response

Author

Listed:
  • Karlsson, Maria

    (Department of Statistics, Umeå University)

  • Cantoni, Eva

    (Department of Econometrics, University of Geneva)

  • de Luna, Xavier

    (Department of Statistics, Umeå University)

Abstract

Truncation or censoring of the response variable in a regression model is a problem in many applications, e.g. when the response is insurance claims or the durations of unemployment spells. We introduce a local polynomial re­gression estimator which can deal with such truncated or censored responses. For this purpose, we use local versions of the STLS and SCLS estimators of Powell (1986) and the QME estimator of Lee (1993) and Laitila (2001). The asymptotic properties of our estimators, and the conditions under which they are valid, are given. In addition, a simulation study is presented to investigate the finite sample properties of our proposals.

Suggested Citation

  • Karlsson, Maria & Cantoni, Eva & de Luna, Xavier, 2009. "Local polynomial regression with truncated or censored response," Working Paper Series 2009:25, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2009_025
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    File URL: http://www.ifau.se/upload/pdf/se/2009/wp09-25.pdf
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    References listed on IDEAS

    as
    1. Arthur Lewbel & Oliver Linton, 2002. "Nonparametric Censored and Truncated Regression," Econometrica, Econometric Society, vol. 70(2), pages 765-779, March.
    2. Songnian Chen & Gordon B. Dahl & Shakeeb Khan, 2005. "Nonparametric Identification and Estimation of a Censored Location-Scale Regression Model," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 212-221, March.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Karlsson, Maria & Lindmark, Anita, 2014. "truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i14).

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    More about this item

    Keywords

    Non-parametric regression; truncation; censoring; asymptotic properties;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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