Count Data Models with Correlated Unobserved Heterogeneity
As previously argued, the correlation between included and omitted regressors generally causes inconsistency of standard estimators for count data models. Non-linear instrumental variables estimation of an exponential model under conditional moment restrictions is one of the proposed remedies. This approach is extended here by fully exploiting the model assumptions and thereby improving efficiency of the resulting estimator. Empirical likelihood in particular has favourable properties in this setting compared with the two-step generalized method of moments, as demonstrated in a Monte Carlo experiment. The proposed method is applied to the estimation of a cigarette demand function. Copyright (c) 2010 Board of the Foundation of the Scandinavian Journal of Statistics.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 37 (2010)
Issue (Month): 3 ()
|Contact details of provider:|| Web page: http://www.blackwellpublishing.com/journal.asp?ref=0303-6898|
|Order Information:||Web: http://www.blackwellpublishing.com/subs.asp?ref=0303-6898|
When requesting a correction, please mention this item's handle: RePEc:bla:scjsta:v:37:y:2010:i:3:p:382-402. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.