Simulations on Correlated Behavior and Social Learning
Andrea Blasco () and
Paolo Pin
Additional contact information
Andrea Blasco: Università di Bologna
A chapter in Progress in Artificial Economics, 2010, pp 89-100 from Springer
Abstract:
Abstract We consider a population of agents that can choose between two risky technologies: an old one for which they know the expected outcome, and a new one for which they have only a prior. We confront different environments. In the benchmark case agents are isolated and can perform costly experiments to infer the quality of the new technology. In the other cases agents are settled in a network and can observe the outcomes of neighbors. We analyze long–run efficiency of the models. We observe that in expectations the quality of the new technology may be overestimated when there is a network spread of information. This is due to a herding behavior that is efficient only when the new technology is really better than the old one. We also observe that between different network structures there is not a clear dominance.
Keywords: Social Learn; Random Network; Local Public Good; Herding Behavior; Correlate Behavior (search for similar items in EconPapers)
Date: 2010
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:spr:lnechp:978-3-642-13947-5_8
Ordering information: This item can be ordered from
http://www.springer.com/9783642139475
DOI: 10.1007/978-3-642-13947-5_8
Access Statistics for this chapter
More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().