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

Dados Bibliográficos

ID9708151
AutoresDavid J Cooper (0000-0003-3391-3538, University of Pittsburgh), Susan Garvin (University of Pittsburgh), John H Kagel (0000-0002-6870-814X, University of Pittsburgh)
Ano1997
Volume107
Fascículo442
Páginas553-575
Data de publicação1997-05-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoThe Economic Journal (JOURNAL)
Identificadores do periódicoISSN: 0013-0133 • E-ISSN: 1468-0297
EditoraOxford University Press (OUP) (PUBLISHER)
DOI10.1111/j.1468-0297.1997.tb00027.x
OpenAlexW2045704638
IdiomaEN
Citações recebidas3
Referências citadas22

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

Adaptive expectations · Adaptive Learning · Bayesian game · Bayesian probability · Econometrics · Economics · Equilibrium selection · Game theory · Limit (mathematics · Mathematical economics · Mathematical optimization · Microeconomics · Rational expectations · Repeated game · Sequential equilibrium · Artificial Intelligence · Computer Science · Experimental Behavioral Economics Studies · Game Theory and Applications · Mathematics · Opinion Dynamics and Social Influence