Probit with Dependent Observations
Estimation of limited dependent variable models with dependent obse rvations has received relatively little attention due to the computational complexity of the maximum likelihood estimator. The authors develop a computationally-attractive and relatively efficient estimator for this case that utilizes the orthogonality conditions. The resulting generalized conditional moment estimators can be applied with a known or an unknown disturbance covariance matrix, alt hough the paper considers only the probit dependent models. Copyright 1988 by The Review of Economic Studies Limited.
(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:||01 Mar 1987|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.haas.berkeley.edu/groups/iber/wps/econwp.html
More information through EDIRC
|Order Information:|| Postal: IBER, F502 Haas Building, University of California, Berkeley CA 94720-1922|
When requesting a correction, please mention this item's handle: RePEc:ucb:calbwp:8734. 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: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.