Economics at your fingertips  

Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources

Narine Udumyan (), Juliette Rouchier () and Dominique Ami ()

Computational Economics, 2014, vol. 43, issue 2, 199-231

Abstract: Overexploitation of renewable resources, and more particularly fisheries, is often driven by the lack of information about the state and dynamics of the resource. A solution to this problem stemming from the resource users is proposed in this paper. We use an agent-based model composed of a bio-economic model of Gordon–Schaefer where agents make choices following a very simple learning model. We modify the Roth–Erev learning model so that agents explain their profit not only by current action but also by past action. This modification radically changes the dynamics of the resource use, which turns out to be sustainable. Copyright Springer Science+Business Media New York 2014

Keywords: Natural resources; Agent-based simulation; Roth–Erev model; Incomplete information; Bioeconomic model of fishery (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) (text/html)
Access to full text is restricted to subscribers.

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:

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-013-9375-x

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2021-03-28
Handle: RePEc:kap:compec:v:43:y:2014:i:2:p:199-231