Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions
In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.
|Date of creation:||1998|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (514) 343-6540
Fax: (514) 343-5831
Web page: http://www.sceco.umontreal.ca
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:mtl:montde:9813. 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: (Sharon BREWER)
If references are entirely missing, you can add them using this form.