Unemployment Benefits and Labor Market Transitions: A Multinomial Logit Model with Errors in Classification
This paper utilizes validation data on survey response error in the Current Population Survey to generalize the standard multinomial logit model to allow for spurious events that result from classification error. The authors' basic approach could be used with other stochastic models of discrete events as well. They illustrate their algorithm by studying the effect of unemployment insurance on transitions from unemployment to employment and on labor-force withdrawal. Their results confirm earlier work suggesting that unemployment insurance lengthens unemployment spells and show that correcting for classification error strengthens the apparent effect of unemployment insurance on spell durations. Copyright 1995 by MIT Press.
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): 77 (1995)
Issue (Month): 2 (May)
|Contact details of provider:|| Web page: http://mitpress.mit.edu/journals/|
|Order Information:||Web: http://mitpress.mit.edu/journal-home.tcl?issn=00346535|
When requesting a correction, please mention this item's handle: RePEc:tpr:restat:v:77:y:1995:i:2:p:207-16. 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: (Kristin Waites)
If references are entirely missing, you can add them using this form.