On Least Squares Estimation when the Dependent Variable is Grouped
Models estimated from censored samples are now familar in the econometrics literature. For many cases Least Squares approximations to the Maximum Likelihood estimators are now well established. This paper is concerned with a more general problem ; that of estimating an equation on the basis of data in which the dependent variably is only observed to fall in a certain range on a continuous scale, its actual value remaining unobserved. The date are also censored in the usual sense in that both end ranges are assumed to be open-ended. A number of Least Square approximations to the Maximum Likelihood estimator are derived and compared. The results of Greene (1981) on the asymptotic bias of OLS are extended to this case. The question of information loss as a result of the grouping is also considered.
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:||1982|
|Contact details of provider:|| Postal: CV4 7AL COVENTRY|
Phone: +44 (0) 2476 523202
Fax: +44 (0) 2476 523032
Web page: http://www2.warwick.ac.uk/fac/soc/economics/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:wrk:warwec:207. 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: (Margaret Nash)
If references are entirely missing, you can add them using this form.