Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form
The authors show that the adaptive estimation result for the heteroskedasticity of an unknown form time-series (or cross-section) model can be generalized to the panel data error components model. The authors give recursive transformations that change the error term of a random effects model and the first differenced error term of a fixed effects model into classical errors. They also propose a modified Breusch-Pagan test for testing the random individual effects. Monte Carlo evidence suggests that the proposed estimator performs adequately in small samples. Copyright 1994 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
(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:||1993|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (519) 824-4120 ext. 53898
Fax: (519) 763-8497
Web page: https://www.uoguelph.ca/economics/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:gue:guelph:1993-4. 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: (Stephen Kosempel)
If references are entirely missing, you can add them using this form.