Identification and EM-Estimation of Panel Data Models with Non-Ignorable Attrition and Refreshment Samples
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.
|Date of creation:||01 Aug 2000|
|Contact details of provider:|| Phone: 1 212 998 3820|
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ecm:wc2000:1569. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
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.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.