IDEAS home Printed from https://ideas.repec.org/p/ecm/wc2000/1569.html
   My bibliography  Save this paper

Identification and EM-Estimation of Panel Data Models with Non-Ignorable Attrition and Refreshment Samples

Author

Listed:
  • Pierre Hoonhout

    (Vrije Universiteit Amsterdam)

  • Geert Ridder

    (Johns Hopkins University)

Abstract

The benefits of panel data are well-documented but missing data problems are often more severe. In particular, units that respond in the first wave may drop out of the panel after one or more periods of participation. This paper focuses on identification and Maximum Likelihood estimation of panel data models when the process that governs this so-called attrition is possibly non-ignorable. In that case, conventional estimation procedures are inconsistent. We derive a multi-period nonparametric identification result and propose estimation by an EM-algorithm that exploits the availability of refreshment samples, consisting of new units randomly drawn from the original population. This additional data source reduces the informational incompleteness of the unbalanced panel in case of non-ignorable attrition. The algorithm is stated in terms of a general population model. Issues related to specific standard panel data models are discussed seperately. Problems caused by partially observed time-varying covariates are addressed along the way.

Suggested Citation

  • Pierre Hoonhout & Geert Ridder, 2000. "Identification and EM-Estimation of Panel Data Models with Non-Ignorable Attrition and Refreshment Samples," Econometric Society World Congress 2000 Contributed Papers 1569, Econometric Society.
    • Handle: RePEc:ecm:wc2000:1569
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/RePEc/es2000/1569.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    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:ecm:wc2000:1569. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.