Rules of Thumb for Social Learning
AbstractThis paper studies agents who consider the experiences of their neighbors in deciding which of two technologies to use. We analyze two learning environments, one in which the same technology is optimal for all players and another in which each technology is better for some of them. In both environments, players use exogenously specified rules of thumb that ignore historical data but may incorporate a tendency to use the more popular technology. In some cases these naive rules can lead to fairly efficient decisions in the long run, but adjustment can be slow when a superior technology is first introduced.
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.
Bibliographic InfoPaper provided by Harvard University Department of Economics in its series Scholarly Articles with number 3196332.
Date of creation: 1993
Date of revision:
Publication status: Published in Journal of Political Economy
Other versions of this item:
- Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 101(4), pages 612-43, August.
- Ellison, Glenn & Fudenberg, Drew, 1992. "Rules of Thumb for Social Learning," IDEI Working Papers, Institut d'Ãconomie Industrielle (IDEI), Toulouse 17, Institut d'Économie Industrielle (IDEI), Toulouse.
- G. Ellison & D. Fudenberg, 2010. "Rules of Thumb for Social Learning," Levine's Working Paper Archive, David K. Levine 435, David K. Levine.
- Allison, G. & Fudenberg, D., 1992. "Rules of Thumb for Social Learning," Working papers, Massachusetts Institute of Technology (MIT), Department of Economics 92-12, Massachusetts Institute of Technology (MIT), Department of Economics.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kandori, M. & Mailath, G.J., 1991.
"Learning, Mutation, And Long Run Equilibria In Games,"
Papers, Princeton, Woodrow Wilson School - John M. Olin Program
71, Princeton, Woodrow Wilson School - John M. Olin Program.
- Kandori, Michihiro & Mailath, George J & Rob, Rafael, 1993. "Learning, Mutation, and Long Run Equilibria in Games," Econometrica, Econometric Society, Econometric Society, vol. 61(1), pages 29-56, January.
- M. Kandori & G. Mailath & R. Rob, 1999. "Learning, Mutation and Long Run Equilibria in Games," Levine's Working Paper Archive, David K. Levine 500, David K. Levine.
- Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 2010.
"A theory of Fads, Fashion, Custom and cultural change as informational Cascades,"
Levine's Working Paper Archive, David K. Levine
1193, David K. Levine.
- Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 100(5), pages 992-1026, October.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. 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: (Ben Steinberg).
If references are entirely missing, you can add them using this form.