Estimating Dynamic Random Effects Models from Panel Data Covering Short Time Periods
AbstractThis paper advocates the use of simultaneous equations estimators (especially LIML) to estimate dynamic random effects models from panel data. The methods are found to perform quite satisfactorily in Monte Carlo experiments. The LIML procedures are also extended to the case where some of the regressors are correlated with the effects and a theorem on identification is proved. Finally, the Michigan Panel is used for some illustrations.
(This abstract was borrowed from another version of this item.)
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 51 (1983)
Issue (Month): 6 (November)
|Contact details of provider:|| Phone: 1 212 998 3820|
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/
More information through EDIRC
|Order Information:|| Web: https://www.econometricsociety.org/publications/econometrica/access/ordering-back-issues Email: |
When requesting a correction, please mention this item's handle: RePEc:ecm:emetrp:v:51:y:1983:i:6:p:1635-59. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.