Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures
In this paper, we review and unite the literatures on returns to schooling and Bayesian model averaging. We observe that most studies seeking to estimate the returns to education have done so using particular "and often different across researchers" model specifications. Given this, we review Bayesian methods which formally account for uncertainty in the specification of the model itself, and apply these techniques to estimate the economic return to a college education. The approach described in this paper enables us to determine those model specifications which are most favored by the given data, and also enables us to use the predictions obtained from all of the competing regression models to estimate the returns to schooling. The reported precision of such estimates also account for the uncertainty inherent in the model specification. Using U.S. data from the National Longitudinal Survey of Youth "NLSY", we also revisit several 'stylized facts' in the returns to education literature and examine if they continue to hold after formally accounting for model uncertainty. Copyright Blackwell Publishers Ltd, 2004.
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): 18 (2004)
Issue (Month): 2 (04)
|Contact details of provider:|| Web page: http://www.blackwellpublishing.com/journal.asp?ref=0950-0804|
|Order Information:||Web: http://www.blackwellpublishing.com/subs.asp?ref=0950-0804|
When requesting a correction, please mention this item's handle: RePEc:bla:jecsur:v:18:y:2004:i:2:p:153-180. 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 references are entirely missing, you can add them using this form.