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Internet auctions with artificial adaptive agents: A study on market design

  • Duffy, John
  • Ünver, M.Utku

We develop a model of internet auctions with the aim of understanding how rules for ending such auctions (a "hard"- or "soft"-close) affect bidding behavior. We model bidding strategies using finite automata and report results from simulations involving populations of artificial bidders who update their strategies using a genetic algorithm. Our model is shown to deliver late or early bidding behavior, depending on whether the auction has a hard- or soft-close rule in accordance with the empirical evidence. We report on other interesting properties of our model and offer some conclusions from a market design point of view.

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Article provided by Elsevier in its journal Journal of Economic Behavior & Organization.

Volume (Year): 67 (2008)
Issue (Month): 2 (August)
Pages: 394-417

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Handle: RePEc:eee:jeborg:v:67:y:2008:i:2:p:394-417
Contact details of provider: Web page: http://www.elsevier.com/locate/jebo

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  1. Paul Milgrom & Robert J. Weber, 1981. "A Theory of Auctions and Competitive Bidding," Discussion Papers 447R, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  2. McAfee, R Preston & McMillan, John, 1987. "Auctions and Bidding," Journal of Economic Literature, American Economic Association, vol. 25(2), pages 699-738, June.
  3. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
  4. Jim Engle-Warnick & Robert Slonim, 2006. "Inferring repeated-game strategies from actions: evidence from trust game experiments," Economic Theory, Springer, vol. 28(3), pages 603-632, 08.
  5. Axel Ockenfels & Alvin E. Roth, 2003. "Late and Multiple Bidding in Second Price Internet Auctions: Theory and Evidence Concerning Different Rules for Ending an Auction," CESifo Working Paper Series 992, CESifo Group Munich.
  6. David Lucking-Reiley, 1999. "Using Field Experiments to Test Equivalence between Auction Formats: Magic on the Internet," American Economic Review, American Economic Association, vol. 89(5), pages 1063-1080, December.
  7. Alvin E. Roth & Axel Ockenfels, . "Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet," Papers on Strategic Interaction 2002-32, Max Planck Institute of Economics, Strategic Interaction Group.
  8. Avery, Christopher, 1998. "Strategic Jump Bidding in English Auctions," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 185-210, April.
  9. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-71, May.
  10. Patrick Bajari & Ali Horta�su, 2004. "Economic Insights from Internet Auctions," Journal of Economic Literature, American Economic Association, vol. 42(2), pages 457-486, June.
  11. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, 03.
  12. Miller, John H., 1996. "The coevolution of automata in the repeated Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 87-112, January.
  13. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(03), pages 373-414, September.
  14. Abreu, Dilip & Rubinstein, Ariel, 1988. "The Structure of Nash Equilibrium in Repeated Games with Finite Automata," Econometrica, Econometric Society, vol. 56(6), pages 1259-81, November.
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