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The word auction is derived from the Latin augere, which means, “to ascend” or “increase.” The concept of auctioning, however, is not confined solely to bidding processes in which the price is raised successively until only one bidder remains. Rather, the term encompasses a variety of trading methods and is broadly understood as “a market institution with explicitly set rules, which determine resource allocation and prices on the basis of bids from market participants” (see McAfee and McMillan 1987, p. 701).
History of Auctions
Auctions have been used since antiquity and have a colorful history. One of the earliest written records of an auction is a description by Herodotus and dates back to 500 BCE (see Cassady 1967, p. 26). At that time in Babylon, women were sold annually as brides in auctions. Auctions were also used in ancient Rome for commercial trade and for the sale of almost anything from slaves to plundered booty and debtor’s property. Martin Shubik (1983) provides an entertaining sketch of the history of auctions in the Roman and Babylonian empires, while Ralph Cassady Jr. (1967) discusses the types of auctions used in England and America in the seventeenth and eighteenth centuries and the establishment of the world-renowned auction houses Sotheby’s and Christie’s.
Standard Auction Types
Despite the variety of auction methods, only four basic types of auctions are commonly used: the ascending bid auction, the descending bid auction, the first-price auction, and the second-price auction. In the ascending-bid auction (also called English or open outcry auction), the price is successively raised until only one bidder remains, and that bidder wins the auction at the final price. This auction form is most familiar to the general public and is usually used to sell art and other collectibles. In the descendingbid auction (also called Dutch auction, as it has been used for the sale of flowers in the Netherlands), the auctioneer starts at a very high price. The price is gradually lowered until one bidder accepts paying the current price for the auctioned item. This auction is commonly used to sell perishables like fish or flowers. In the other two standard auction formats—first-price sealed bid and second-price sealed bid auctions—bids are submitted in sealed envelopes. In both sealed bid auction formats, the winner is the person with the highest bid. The auctions differ in their payment requirements, however: In the first-price auction, the winner pays the amount they have bid; in the second-price auction, the winner pays the second-highest bid. These auctions are most commonly used for procurement of government contracts.
Although auctions have existed for many centuries, the theory of auctions is a relatively new field in economics. Auctions are market institutions with well-defined rules that determine how the winner is selected and what the payments are, depending on the bids. For that reason auctions are typically modeled and analyzed as bidding games of incomplete information. The first treatment of auctions, which identified the strategic aspect of bidding, is found in the work of William S. Vickrey (1961). Vickrey assumed that each bidder knows precisely how highly he values the item, but does not know anyone else’s valuation of the item. The other bidders’ valuations are perceived to be uncertain; they are drawn from the same probability distribution and are stochastically independent. All bidders are considered risk neutral. Vickrey’s major contribution is the celebrated revenue equivalence theorem. It states that under the above premises all four auctions generate the same average revenue for the seller. His model is known as the independent private value model and is well suited to situations in which consumers buy an item for their own use. If the item is bought for the purpose of resale, however, it has a single, objective value (the resale value), though bidders may have different guesses about what this value would be. To analyze such a situation, one would need to employ a common value model. The most general treatment of the auction problem, which allows for interdependence among bidder’s valuations and includes the common value and the private value models as special cases, was developed by Paul R. Milgrom and Robert J. Weber (1982). This entry will establish a revenue ranking for the four standard auction formats, and show that on average, revealing information about the quality of the item put up for sale increases equilibrium bids and, consequently, seller’s proceeds.
The purpose of auction theory is twofold. On the one hand, auction theory attempts to explain the existence of certain trading institutions and the functioning of the price formation and exchange processes. On the other hand, it provides a guide on how to tailor the trading mechanism to certain information environments and suggests improvements in already existing institutions. A line of inquiry of both practical and theoretical interest is the design of optimal auctions—auctions generating the highest expected revenue for the seller. In an influential paper, Roger B. Myerson (1981) introduced a method that allows one to design the best-performing trade mechanism for a wide class of environments. Jeremy I. Bulow and D. John Roberts (1989) made Myerson’s approach accessible to a much broader audience of economists by recasting it in terms of marginal revenues and marginal cost and linking it to the theory of monopoly pricing. The theoretical work on auctions continues to grow rapidly— by December 2006 the Econ Lit Database contained more than two thousand entries with the words auction or auctions, about half of them theoretical.
Auction Experiments and Computer Simulations
Experimental studies of competitive bidding in auctions first appeared in the early 1980s, with a primary focus on testing the theoretical properties of the standard auction formats. The experimental results established several facts about behavior relative to the theoretical predictions. For instance, the revenue equivalence theorem concerning private value auctions fails in the laboratory. Bids in firstprice auctions are higher than in Dutch auctions and bids in second-price auctions are higher than in English auctions. These results remain consistent when the number of bidders is changed. The comparative static predictions of the equilibrium model, however, remain valid. Bidders with higher valuations bid higher and bids generally increase with an increased number of bidders. This picture changes in common value auction environments. In a common-value auction, bidders face a more complicated strategic problem because such auctions involve a combination of competitive bidding and value estimation. Inexperienced bidders often fall prey to the winner’s curse: The bidder who ends up winning the auction has the most optimistic estimate of the value of the auctioned item. This leads to excessively high bids and to winners who pay prices higher than the value of the item on sale. John H. Kagel (1995) provides a comprehensive overview of the experimental literature on auctions. The use of computer simulations to study the performance of market institutions has been proposed by researchers on the crossroad between economics and engineering (for a discussion, see Roth 2002.)
Online Auctions: Phenomena and Psychology of Bidding
Since the 1990s online auction sites have been a popular place to trade a variety of goods. By far the most popular online auction site is eBay, which was founded in 1995 and has evolved from a simple online mechanism for buying and selling collectibles to a major marketplace, where in 2001 about $9 billion worth of goods were traded. This is three times more than, for instance, the total sales of Amazon for that year. A phenomenon widely observed on eBay is the tendency of bidders to submit bids in the last seconds of bidding. (This phenomenon, called last-minute bidding or sniping, is pertinent only to eBay-style auctions, which have a predetermined deadline. Amazon-style auctions do not have a hard close. Rather, they have an automatic extension rule that allows bidding to continue if bidding activity is registered in the last ten minutes of an auction.) Explanations for the practice of last-minute bidding have fallen into two categories. One idea, advanced by Patrick Bajari and Ali Hortacsu (2003), attributes this effect to the existence of experts, who wait until the very end of the auction because they do not want to reveal their interest in the item on sale. This argument is valid for common value auctions where expert opinion matters. The late bidding phenomenon also exists in private value auctions and Roth and Axel Ockenfels (2006) provide another rationale for bidding close to an auction’s end in these circumstances. Waiting until the end allows bidders to acquire an item at a lower price by preventing “bidding wars” (the successive escalation of bids). Other issues of interest to both psychologists and economists are the effect of minimum bid and secret reserve prices on bidding behavior. Bajari and Hortacsu (2004) provide an extensive review of the economic research on Internet auctions.
- Bajari, Patrick, and Ali Hortacsu. 2003. The Winner’s Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions. Rand Journal of Economics 4 (2): 329–355.
- Bajari, Patrick, and Ali Hortacsu. 2004. Economic Insights from Internet Auctions. Journal of Economic Literature 42 (2): 457–486.
- Bulow, Jeremy I., and D. John Roberts. 1989. The Simple Economics of Optimal Auctions. Journal of Political Economy 97 (5): 1060–1090.
- Cassady, Ralph, Jr. 1967. Auctions and Auctioneering. Berkeley: University of California Press.
- Kagel, John H. 1995. Auctions: A Survey of Experimental In Handbook of Experimental Economics, ed. John H. Kagel and Alvin E. Roth, 501–585. Princeton, NJ: Princeton University Press.
- McAfee, R. Preston, and John McMillan. 1987. Auctions and Bidding. Journal of Economic Literature 25 (2): 699–738.
- Milgrom, Paul R., and Robert J. Weber. 1982. A Theory of Auctions and Competitive Bidding. Econometrica 50 (5): 1089–1122.
- Myerson, Roger B. 1981. Optimal Auction Design. Mathematics of Operations Research 6 (1): 58–73.
- Roth, Alvin E. 2002. The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics. Econometrica 70 (4): 1341–1378.
- Roth, Alvin E., and Axel Ockenfels. 2006. Late and Multiple Bidding on Second Price Internet Auctions: Theory and Evidence Concerning Different Rules for Ending an Auction. Games and Economic Behavior 55 (2): 297–320.
- Shubik, Martin. 1983. Auctions, Bidding, and Markets: An Historical Sketch. In Auctions, Bidding, and Contracting: Uses and Theory, ed. Richard Engelbrecht-Wiggans, Martin Shubik, and Robert M. Stark, 33–52. New York: New York University Press.
- Vickrey, William S. 1961. Counterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance 16 (1): 8–37.
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