Learning To Be Thoughtless: Social Norms and Individual Computation

J.M. Epstein

Working Papers from Brookings Institution - Working Papers

Abstract: This paper extends the literature on the evolution of norms with an agent-based model capturing a phenomenon that has been essentially ignored, nam ely that individual thought -- or computing -- is often inversely related to the strength of a social norm. In this model, agents learn how to behave (what norm to adopt), but -- under a strategy I term Best Reply to Adaptive Sample Evidence -- they also learn how much to think about how to behave. How much they're thinking affects how they behave, which -- given how others behave -- affects how much they think. In short, there is feedback between the social (inter-agent) and internal (intra-agent) dynamics. In addition, we generate the sylized facts regarding the spatio-temporal evolution of norms: local conformity, global diversity, and punctuated equilibria

Keywords: BEHAVIOUR; SOCIAL NORMS (search for similar items in EconPapers)
JEL-codes: C70 C90 C92 (search for similar items in EconPapers)
Pages: 12 pages
Date: 1999
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fth:brooki:6

Access Statistics for this paper

More papers in Working Papers from Brookings Institution - Working Papers THE BROOKINGS INSTITUTION, 1775 MASSACHUSETTS AVE N.W. WASHINGTON D.C. 20036 U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().