dynamic-auctions - DYNAMIC AUCTIONS A SURVEY By Dirk...

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DYNAMIC AUCTIONS: A SURVEY By Dirk Bergemann and Maher Said March 2010 Revised May 13, 2010 COWLES FOUNDATION DISCUSSION PAPER NO. 1757R COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY Box 208281 New Haven, Connecticut 06520-8281 http://cowles.econ.yale.edu/
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DYNAMIC AUCTIONS: A SURVEY DIRK BERGEMANN AND MAHER SAID MAY 13, 2010 A BSTRACT : We survey the recent literature on designing auctions and mechanisms for dy- namic settings. Two settings are considered: those with a dynamic population of agents whose private information remains fixed throughout time; and those with a fixed popula- tion of agents whose private information changes across time. Within each of these settings, we discuss both efficient (welfare-maximizing) and optimal (revenue-maximizing) mecha- nisms. K EYWORDS : Dynamic auctions and mechanisms, Random arrivals and departures, Chang- ing private information, Incentive compatibility JEL C LASSIFICATION : C73, D43, D44, D82, D83. D EPARTMENT OF E CONOMICS , Y ALE U NIVERSITY , DIRK . BERGEMANN @ YALE . EDU M ICROSOFT R ESEARCH N EW E NGLAND AND O LIN B USINESS S CHOOL , W ASHINGTON U NIVERSITY IN S T . L OUIS , SAID @ WUSTL . EDU
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DYNAMIC AUCTIONS 1. I NTRODUCTION Many important economic problems have been studied with the tools of auction theory and mechanism design more generally. Much of the literature, however, studies a static, one-time de- cision. In many problems of interest, more than a single decision needs to be made; instead, a sequence of decisions need to be made. These decisions often depend crucially on the dynamic aspects of the environment. For example, in the classical airline revenue management problem, an airline must decide how to price seats on a flight in response to its changing inventory as well as to the evolution of the customer base. A search engine must choose how to allocate its advertising in- ventory in response to changing search queries and advertiser budgets. Network capacity (either bandwidth or computational resources) needs to be dynamically reallocated in response to the arrival of new computational tasks of varying priority. Private and public procurement agencies must decide how to assign new contracts in response to the changing experience, competencies, and availabilities of contractors. The theory of auctions and mechanism design has been extremely successful in tackling a wide variety of problems. Unfortunately, solutions to static problems often do not translate directly to dynamic settings. Consider, for instance, the standard second-price auction for a single object with private values. Buyers are asked to submit bids for the good, which is then allocated to the highest bidder. This winning bidder then pays the second-highest of the submitted bids. As first demonstrated by Vickrey ( 1961 ), it is a (weakly) dominant strategy for buyers to bid their true values. Thus, the object is allocated efficiently: the buyer who values the object the most receives it.
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