AbstractObservational learning occurs when privately informed individuals sequentially choose among finitely many actions after seeing predecessorsâ€™ choices. We summarise the general theory of this paradigm: belief convergence forces action convergence; specifically, copycat â€˜herdsâ€™ arise. Also, beliefs converge to a point mass on the truth exactly when the private information is not uniformly bounded.This subsumes two key findings of the original herding literature: With multinomial signals, cascades occur, where individuals rationally ignore their private signals, and incorrect herds start with positive probability. The framework is flexible â€“ some individuals may be committed to an action, or individuals may have divergent cardinal or even ordinal preferences.
Download InfoIf 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.
This chapter was published in: Steven N. Durlauf & Lawrence E. Blume (ed.) , , pages , 2011, 4th quarter update.
This item is provided by Palgrave Macmillan in its series The New Palgrave Dictionary of Economics with number v:5:year:2011:doi:3870.
Contact details of provider:
Web page: http://www.palgrave-journals.com/
Find related papers by JEL classification:
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Sheeja Sanoj).
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.