IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Count Data Models with Viriance of Unknown Form - An Application to a Hedonic Model of Worker Absenteeism

  • Delgado, M.A.
  • Kniesner, T.J.

We examine an econometric model of counts of worker absences due to illness in a sluggishly adjusting hedonic labor market. We compare three estimators that parameterize the conditional variance--least squares, Poisson, and negative binomial pseudo maximum likelihood--to generalized least squares (GLS) using nonparametric estimates of the conditional variance. Our data support the hedonic absenteeism model. Semiparametric GLS coefficients are similar in sign, magnitude, and statistical significance to coefficients where the mean and variance of the errors are specified ex ante. In our data, coefficient estimates are sensitive to a regressor list but not to the econometric technique, including correcting for possible heteroskedasticity of unknown form. © 1997 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

(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 options:
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.

Paper provided by Indiana - Center for Econometric Model Research in its series Papers with number 94-011.

in new window

Length: 21 pages
Date of creation: 1994
Date of revision:
Handle: RePEc:fth:indian:94-011
Contact details of provider: Postal: Indiana University, Center for Econometric Model Research, Department of Economics; Bloomington, IN 47405.
Phone: 812-855-1021
Fax: 812-855-3736
Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:fth:indian:94-011. 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: (Thomas Krichel)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.