Bias Correction and Bootstrapping of Error Component Models for Panel Data: Theory and Applications
The wellknown Wallace-Hussain estimator is applied in pooled models with random individual effects, and the magnitude of the bias caused by the estimator is estimated by bootstrap methods. Furthermore, the significance of the bias is tested using an asymptotic test based on the bootstrap results.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" 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.
|Date of creation:||Nov 1988|
|Date of revision:|
|Contact details of provider:|| Postal: Koenigsworther Platz 1, D-30167 Hannover|
Phone: (0511) 762-5350
Fax: (0511) 762-5665
Web page: http://www.wiwi.uni-hannover.de
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:han:dpaper:dp-131. 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: (Heidrich, Christian)
If references are entirely missing, you can add them using this form.