Adaptive Learning vs. Equilibrium Refinements in an Entry Limit Pricing Game

23 Pages Posted: 31 Jan 2012

See all articles by David Cooper

David Cooper

University of Pittsburgh

Susan Garvin

affiliation not provided to SSRN

John H. Kagel

Ohio State University (OSU) - Economics

Date Written: May 1997

Abstract

Signalling models are studied using experiments and adaptive learning models in an entry limit pricing game. Even though high cost monopolists never play dominated strategies, the easier it is for other players to recognise that these strategies are dominated, the more likely play is to converge to the undominated separating equilibrium and the more rapidly limit pricing develops. This is inconsistent with the equilibrium refinements literature (including Cho‐Kreps’ intuitive criterion) and pure (Bayesian) adaptive learning models. An augmented adaptive learning model in which some players recognise the existence of dominated strategies and their consequences predicts these outcomes.

Suggested Citation

Cooper, David and Garvin, Susan and Kagel, John H., Adaptive Learning vs. Equilibrium Refinements in an Entry Limit Pricing Game (May 1997). The Economic Journal, Vol. 107, Issue 442, pp. 553-575, 1997. Available at SSRN: https://ssrn.com/abstract=1995927 or http://dx.doi.org/10.1111/j.1468-0297.1997.tb00027.x

David Cooper

University of Pittsburgh

135 N Bellefield Ave
Pittsburgh, PA 15260
United States

Susan Garvin

affiliation not provided to SSRN

No Address Available

John H. Kagel

Ohio State University (OSU) - Economics ( email )

1945 North High Street
Columbus, OH 43210-1172
United States

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