Bias-corrected estimation in dynamic panel data models
This study develops a new bias-corrected estimator for the fixed-effects dynamic panel data model and derives its limiting distribution for fixed T and N large. The bias-corrected estimator is derived as a bias correction of the least-squares dummy variable (within) estimator. It does not share some of the drawbacks of recently developed IV and GMM estimators and is relatively easy to compute. Monte Carlo experiments provide evidence for the bias-corrected estimator to perform well even in small samples. The paper contains an application to a model of unemployment dynamics at the U.S. state level for the 1991-2000 period.
|Date of creation:||2002|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +31 (0)43 38 83 830
Web page: http://www.maastrichtuniversity.nl/Email:
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:unm:umamet:2002025. 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: (Charles Bollen)
If references are entirely missing, you can add them using this form.