An evolutionary Cournot model with limited market knowledge

  • G. I. Bischi*
  • , F. Lamantia
  • , Davide Radi
  • *Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo

Abstract

In this paper we analyze a dynamic game of Cournot competition with heterogeneous firms choosing between two different adaptive behavioral rules in deciding output strategies. The underlying oligopoly structure is standard: using a constant return to scale technology, N firms produce homogeneous goods, which are sold in a market characterized by constant price elasticity. In this setup, we assume that a fraction of firms employs a quite rough rule of thumb, the so-called Local Monopolistic Approximation (LMA), whereas the complementary fraction plays Best Reply (BR), a more demanding strategy in terms of information and computation requirements. The model is first considered with exogenously fixed fractions of firms in the two complementary groups. Then it is generalized by considering an endogenous evolutionary switching process between the two behavioral strategies based on profit-driven replicator dynamics. The role of the number of firms, information costs and inertia (or anchoring attitude) in production decisions is analyzed, as well as the influence in the evolutionary process of random noise in the demand function and memory of past profits. Global properties of the oligopoly with evolutionary pressure between behavioral rules are discussed, with particular regard to cases in which the Nash equilibrium is unstable.
Lingua originaleInglese
pagine (da-a)219-238
Numero di pagine20
RivistaJournal of Economic Behavior and Organization
Volume116
Numero di pubblicazioneN/A
DOI
Stato di pubblicazionePubblicato - 2015

All Science Journal Classification (ASJC) codes

  • Economia ed Econometria
  • Comportamento Organizzativo e Gestione delle Risorse Umane

Keywords

  • Evolutionary dynamics
  • Heterogeneous firms
  • Local Monopolistic Approximation
  • Nonlinear phenomena
  • Oligopolies

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