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Sustainable reputations with rating systems

  • Ekmekci, Mehmet

In a product choice game played between a long lived seller and an infinite sequence of buyers, we assume that buyers cannot observe past signals. To facilitate the analysis of applications such as online auctions (e.g. eBay), online shopping search engines (e.g. BizRate.com) and consumer reports, we assume that a central mechanism observes all past signals, and makes public announcements every period. The set of announcements and the mapping from observed signals to the set of announcements is called a rating system. We show that, absent reputation effects, information censoring cannot improve attainable payoffs. However, if there is an initial probability that the seller is a commitment type that plays a particular strategy every period, then there exists a finite rating system and an equilibrium of the resulting game such that, the expected present discounted payoff of the seller is almost his Stackelberg payoff after every history. This is in contrast to Cripps, Mailath and Samuelson (2004) [5], where it is shown that reputation effects do not last forever in such games if buyers can observe all past signals. We also construct finite rating systems that increase payoffs of almost all buyers, while decreasing the seller[modifier letter apostrophe]s payoff.

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Article provided by Elsevier in its journal Journal of Economic Theory.

Volume (Year): 146 (2011)
Issue (Month): 2 (March)
Pages: 479-503

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Handle: RePEc:eee:jetheo:v:146:y:2011:i:2:p:479-503
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/622869

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  1. Cripps,M.W. & Mailath,G.J. & Samuelson,L., 2002. "Imperfect monitoring and impermanent reputations," Working papers 17, Wisconsin Madison - Social Systems.
  2. Michihiro Kandori & Ichiro Obara, 2006. "Less is more: an observability paradox in repeated games," International Journal of Game Theory, Springer, vol. 34(4), pages 475-493, November.
  3. Kandori, Michihiro, 1992. "The Use of Information in Repeated Games with Imperfect Monitoring," Review of Economic Studies, Wiley Blackwell, vol. 59(3), pages 581-93, July.
  4. Liu, Qingmin & Skrzypacz, Andrzej, 2009. "Limited Records and Reputation," Research Papers 2030, Stanford University, Graduate School of Business.
  5. Christopher Phelan, 2001. "Public trust and government betrayal," Staff Report 283, Federal Reserve Bank of Minneapolis.
  6. Bakos, Yannis & Dellarocas, Chrysanthos, 2003. "Cooperation Without Enforcement? A comparative analysis of litigation and online reputation as quality assurance mechanisms," Working papers 4295-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
  7. Wiseman, Thomas, 2008. "Reputation and impermanent types," Games and Economic Behavior, Elsevier, vol. 62(1), pages 190-210, January.
  8. Heski Bar-Isaac, 2003. "Reputation and Survival: Learning in a Dynamic Signalling Model," Review of Economic Studies, Wiley Blackwell, vol. 70(2), pages 231-251, 04.
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