Learning and strategic pricing

Dirk Bergemaimn, Juuso Välimäki

Research output: Contribution to journalArticleScientificpeer-review

102 Citations (Scopus)

Abstract

We consider the situation where a single consumer buys a stream of goods from different sellers over time. The true value of each seller's product to the buyer is initially unknown. Additional information can be gained only by experimentation. For exogeneously given prices the buyer's problem is a multi-armed bandit problem. The innovation in this paper is to endogenize the cost of experimentation to the consumer by allowing for price competition between the sellers. The role of prices is then to allocate intertemporally the costs and benefits of learning between buyer and sellers. We examine how strategic aspects of the oligopoly model interact with the learning process. All Markov perfect equilibria (MPE) are efficient. We identify an equilibrium which besides its unique robustness properties has a strikingly simple, seemingly myopic pricing rule. Prices below marginal cost emerge naturally to sustain experimentation. Intertemporal exchange of the gains of learning is necessary to support efficient experimentation. We analyze the asymptotic behavior of the equilibria.

Original languageEnglish
Pages (from-to)1125-1149
Number of pages25
JournalEconometrica
Volume64
Issue number5
DOIs
Publication statusPublished - Sep 1996
MoE publication typeA1 Journal article-refereed

Keywords

  • Dynamic oligopoly
  • Experimentation
  • Infinite stochastic game
  • Learning
  • Markov perfect equilibrium
  • Multi-armed bandit

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