Estimating Internet Users' Demand Characteristics
We investigate two parametric approaches and one non-parametric approach to estimating Internet users' value-of-time, an important characteristic of demand for Internet services. The advantages of these approaches are made clear and their limitations discussed. The models are tested with data generated from our simulation model of the Internet economy. Given the characteristics of the data, we investigate parametric count-data models first. While reasonably good results are obtained on all medium and large-sized jobs, the method fails on small-sized ones. Second, we develop a nonparametric quasi-Bayesian update algorithm for retrieving the underlying distribution function of Internet users' value-of-time purely from observations on their choices. Compared with the parametric count-data models, good results are obtained in every case. Copyright 2001 by Kluwer Academic Publishers
Volume (Year): 17 (2001)
Issue (Month): 2-3 (June)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=100248|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:17:y:2001:i:2-3:p:203-18. 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: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.