IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Job Duration and Bayesian Learning: Evidence from Germany

Listed author(s):
  • Yannis Georgellis

In a job matching context, Bayesian learning is assumed in order to provide an optimising framework for the analysis of workers' labour turnover decisions. This framework allows workers' labour turnover behaviour to be affected not only by the wage rate but also by a vector of non-wage job attributes and self-reported satisfaction variables. Assuming that workers' behaviour sufficiently conforms with the normative guidelines suggested by such a Bayesian learning model, the importance of the wage rate relative to the importance of satisfaction and non-wage variables in determining job duration in Germany is examined using econometric survival analysis. To capture the dynamic nature of workers' labour turnover behaviour, survival analysis with "time-varying" covariates is used. The empirical results, based on information from the German Socio-Economic Panel data set, confirm the importance of non-wage attributes and satisfaction variables in determining job duration and they are broadly consistent with the non-monotonic hazard function for job separations suggested by the above theoretical framework.

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 School of Economics, University of Kent in its series Studies in Economics with number 9604.

in new window

Date of creation: Mar 1996
Handle: RePEc:ukc:ukcedp:9604
Contact details of provider: Postal:
School of Economics, University of Kent, Canterbury, Kent, CT2 7NP

Phone: +44 (0)1227 827497
Web page:

Order Information: Email:

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:ukc:ukcedp:9604. 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: (Tracey Girling)

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.