Investigating the effect of changes in Signals, Noise and Agent Types in Cascade Models
Smith and SÃ¸renson (2002) depart from Bikhchandani, Hirshleifer and Welshâ€™s (1999) herding framework in three ways; non-discrete signals, noise and multiple rational agent types. They refer to the standard model of a single type with no noise as a â€œherdingâ€ model, and differentiate themselves by referring to the more general model as a â€œcascade.â€ They find that differing preferences lead to â€œconfounded learningâ€ whereby an incorrect equilibrium can arise regardless of the accuracy of the signal space, due to alternate actions taken due to preferences. In this paper we break down the three alterations from the BHW (1999) model, and analyze through agent based techniques the effect that each one has on the outcome, in an effort to determine which of the three different specifications has the greatest impact on herding and learning in the cascade model.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
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.
|Date of creation:||11 Nov 2005|
|Date of revision:|
|Contact details of provider:|| Web page: http://comp-econ.org/Email: |
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf5:296. 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: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.