Evolutionary learning and the stability of wage posting equilibria

Robert Calvert Jump

Journal of Evolutionary Economics, 2016, vol. 26, issue 5, No 8, 1117-1135

Abstract: Abstract This paper presents results on the stability of the wage dispersion model presented in Mortensen (2003). Specifically, four learning processes are tested on a single parameterisation of the underlying model, and the most successful is submitted to a sensitivity analysis. The results illustrate an important problem in evolutionary dynamics first highlighted in Nelson and Winter (1982) - that to play a role in equilibrium, a strategy must be consistent with a previous disequilibrium. The results are ambiguous concerning the applicability of the equilibrium method of Mortensen (2003), as some of the learning processes are stable, whilst others are extremely unstable and exhibit complex dynamics.

Keywords: Price dispersion; Search market equilibrium; Reinforcement learning (search for similar items in EconPapers)
JEL-codes: B52 C63 D83 J31 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00191-016-0476-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:joevec:v:26:y:2016:i:5:d:10.1007_s00191-016-0476-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/191/PS2

DOI: 10.1007/s00191-016-0476-2

Access Statistics for this article

Journal of Evolutionary Economics is currently edited by Uwe Cantner, Elias Dinopoulos, Horst Hanusch and Luigi Orsenigo

More articles in Journal of Evolutionary Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().