Abstract
Classical models of private value auctions assume that bidders know their own private value for the item being auctioned. We explore games where players have a private value, but can only learn this value through experimentation, a scenario that is typical in AdAuctions. We consider this question in a repeated game context, where early participation in the auction can help the bidders learn their own value. We consider what is a good bidding strategy for a player in this game, and show that with low enough competition new bidders will enter and experiment, but with a bit higher level of competition, initial credit offered by the platform can encourage experimentation, and hence ultimately can increase revenue.
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References
Abraham, I., Athey, S., Babaioff, M., Grubb, M.: Peaches, lemons, and cookies: Designing auction markets with dispersed information. In: ACM Conference on Economic Commerce (2013)
Iyer, K., Johari, R., Sundararajan, M.: Mean Field Equilibria of Dynamic Auctions with Learning. In: ACM Conference on Economic Commerce (2011)
Bulow, J., Klemperer, P.: Auctions Versus Negotiations. American Economic Review (1996)
Gummadi, R., Key, P., Proutiere, A.: Optimal Bidding Strategies and Equilibria in Repeated Auctions with Budget Constraints. In: Ad Auctions Workshop (2012)
Lahaie, S., McAfee, R.P.: Efficient Ranking in Sponsored Search. In: Chen, N., Elkind, E., Koutsoupias, E. (eds.) WINE 2011. LNCS, vol. 7090, pp. 254–265. Springer, Heidelberg (2011)
Milgrom, P.R., Weber, R.J.: A theory of auctions and competitive bidding. Econometrica 50(5), 1089–1122 (1982)
Syrgkanis, V., Kempe, D., Tardos, E.: Information Asymmetries in Common-Value Auctions with Discrete Signals. In: Ad Auctions Workshop (2013)
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Dikkala, N., Tardos, É. (2013). Can Credit Increase Revenue?. In: Chen, Y., Immorlica, N. (eds) Web and Internet Economics. WINE 2013. Lecture Notes in Computer Science, vol 8289. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45046-4_11
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DOI: https://doi.org/10.1007/978-3-642-45046-4_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45045-7
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