Likelihood Based Estimation in a Panel Setting
This paper considers the extension to panel data of models that are specified cross-sectionally in terms of a likelihood. It considers specifically the estimation of stochastic frontier models but the same issue arises in many other models. The model can be estimated for any single value of the time-index t by maximizing a likelihood that depends on the distribution of yit given xit. Estimation in the panel could be based on the joint distribution of yi1,...,yiT given xi1,...,xiT. Many different joint distributions may exist that imply the given marginal distributions of the yit separately, however, and except in the normal case none is "obviously" correct. The paper observes the well-known fact that maximizing a quasi-likelihood that assumes independence yields consistent estimates, and it shows how to obtain asymptotically correct standard errors. It shows how to use GMM methods to improve on the quasi-MLE, without assuming any specific form of the joint distribution, and derives the condition under which there is or is not an improvement. Finally, it shows how copulas can be used to construct joint distributions. It addresses the question of whether or not there are any copulas with the robustness property that the quasi-MLE is consistent even if the assumed copula is incorrect.
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:||11 Aug 2004|
|Contact details of provider:|| Phone: 1 212 998 3820|
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ecm:ausm04:339. 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.