IDEAS home Printed from https://ideas.repec.org/p/mit/worpap/99-15.html
   My bibliography  Save this paper

Conditional Moment Restrictions in Censored and Truncated Regression Models

Author

Listed:
  • Whitney Newey

Abstract

Censored and truncated regression models with unknown distribution are important in econometrics. This paper characterizes the class of all conditional moment restrictions that lead to √n-consistent estimators for these models. The semiparametric efficiency bound for each conditional moment restriction is derived. In the case of a nonzero bound it is shown how an estimator can be constructed and that an appropriately weighted version can attain the efficiency bound. These estimators also work when the disturbance is independent of the regressors. The paper discusses combining conditional moment restrictions for more efficient estimation in this case.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Whitney Newey, 1999. "Conditional Moment Restrictions in Censored and Truncated Regression Models," Working papers 99-15, Massachusetts Institute of Technology (MIT), Department of Economics.
    • Handle: RePEc:mit:worpap:99-15
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Songnian & Zhou, Xianbo, 2012. "Semiparametric estimation of a truncated regression model," Journal of Econometrics, Elsevier, vol. 167(2), pages 297-304.
    2. Jonsson, Robert, 2008. "When does Heckman’s two-step procedure for censored data work and when does it not?," Research Reports 2008:2, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. 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.
    4. Aktas, Nihat & de Bodt, Eric & Roll, Richard, 2013. "Learning from repetitive acquisitions: Evidence from the time between deals," Journal of Financial Economics, Elsevier, vol. 108(1), pages 99-117.
    5. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    6. Frumento, Paolo & Bottai, Matteo, 2017. "An estimating equation for censored and truncated quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 53-63.
    7. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mit:worpap:99-15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Linda Woodbury (email available below). General contact details of provider: https://edirc.repec.org/data/edmitus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.