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1. Program development
   • Study the steps eBay takes (if any) to discourage crawling of their site. In other words: Exactly what does eBay do to make Assignment 1 hard?
   • Is it true that when eBay uses anonymized user IDs like e***m they are consistent from auction to auction---at least some of time?
   • Can you identify dealers in anonymized bid histories by looking at the ratio of total feedback points to number of bids?
   • Automatically assemble a catalog of current prices in a particular subfield (Limoge China, US state spoons...). Easily updated of course. Compare to published catalogs in some areas?
   • Track effect of news events on prices in some areas: people in the news and autographs, deaths and photos, autographs, etc.
   • Search automatically for bidder wars on eBay. In what categories and in what circumstances are they more likely to occur?
   
   
2. Literature survey and review of a specialized field of auction theory or experiment. The goal here is to determine the current state of knowledge in a fairly narrow aspect of auction theory or practice, to review the recent work critically, and perhaps extend or interpret creatively. Examples:
   • Combinatorial auctions and complexity theory
   • Budget constraints, financial constraints
   • Risk aversion
   • Interdependent values. The classic reference is P. R. Milgrom and R. J. Weber, "Theory of auctions and competitive bidding," Econometrica, vol. 50, no. 5, Sept. 1982, pp. 1089-1122. (Can you derive their revenue ranking more simply using a model more restrictive than affiliated? Perhaps correlated?) I'm interested in this for class presentation; the definition of "affiliated" is not very transparent.
   • Common-value auctions
   • Resale
   • Collusion
   • Efficiency in multiunit auctions
   • Auctions with discrete value distributions
   
   
3. Measurement study of some aspect of online auctions. The goal here is to learn something from downloaded data, or data you obtain yourself in experiments. Examples:
   • Study the effect of eBay's change in reputation system, which begins May 1, 2008 (I think). This may be a unique opportunity to study the dynamics of feedback score change as the new system is put to use.
   • Effects of special features on eBay, such as featured item listing, highlighting, bold face, etc.
   • Use of Buy-It-Now feature on eBay
   • Effects of listing choices on eBay, such as time of listing, length of auction, opening bid, hidden reserve, reputation, shipping costs, use of PayPal, etc.
   • Cross-venue comparison of like items, such as Penbid vs. eBay
   • Cross-venue study of the effect of extending deadlines vs. sharp deadlines
   • Correlation of slabbed (US) coin prices with third-party certification companies (for example, click here for a fourth party's comments on the third party companies.) Are there any other categories with third-party certifications?
   • Is there a correlation between bidders who have raised their own bids and winning?
   • To what extent are auctions in certain specialized areas and closing times becoming completely determined by snipers, and hence in some sense equivalent to Vickrey auctions?
   • Do buyers and sellers in particular subareas tend to gather at certain auction ending times? I suspect so, and this would be analogous to like businesses accumulating in certain sections of cities (the diamond exchange in NYC, for example, or the fishmarket).
   • Study auctions that have developed in Massively Multiplayer Online Role-Playing Games: what formats are used, how are the forms suited to the games, what behavior is observed?
   • Compare buy-it-now prices and non-buy-it-now prices. Can you develop a theory of the value of time?
   
   
4. Laboratory experiments
   • Repeat any of the classic experiments: overbidding in first-price IPV auctions, learning in second-price, effect of clock speed in Dutch, etc.
   • Figure out a way to distinguish between risk aversion and spite (anyone doing fMRI?) as an explanation for overbidding in first-price auctions. Here's an ambitious suggestion: have the same bidders participate in three different games. One game "measures" spite; a second "measures" risk aversion; a third is a sealed-bid first-price auction. Then determine whether the correlation is better between overbidding and spite, or overbidding and risk aversion.
   • Correlate risk aversion with cultural background of subjects.
   • Correlate spiteful behavior with cultural background of subjects. (I think at least one such study has been published, one that studies the possible effect of nationality.)
   
   
5. Simulation or numerical study of equilibrium strategies in cases too complicated to analyze. Examples:
   • Simulate swoopo. Or my suggested zero-price abstraction: "throwing good Sacawagea dollars after bad".
   • Equilibria and revenue ranking in hard-to-analyze cases: Interdependent values, combinatorial auctions, risk averse bidders, asymmetrical bidders, spiteful bidders, etc.
   • Effect of market-clearing mechanisms in repeated double-auctions
   • Learning in auction-based competition
   • Automated fraud detection
   • Build a competitive environment with two geographic domains: one where pairwise competition determines survival, and the other where overall fitness does. Study through simulation the emergence of adaptive species in this environment.
   • Simulate machine learning of equiibria in auctions.
   
   
6. Sociological, legal, or ethical studies of internet auctions. Analysis of the impact of auctions in these fields. Examples:
   • Fraud
   • Ethical boundaries of behavior: collusion, shilling, sniping, baiting, etc.
   • Legal aspects of internet auctions: international considerations, libel, copyright, general intellectual property issues, etc.
   • Ethical boundaries of sale items: human organs, items objectionable on grounds of politics, race, gender, etc.
   • Study the self-policing of a subarea of eBay by looking for news groups and their possible effects on bidding. (For example, in coins, there's a "fakes" newsgroup.)
   • Study of racial bias (see Prof. Salganik, Dept. of Sociology). Can you think of a clever way to find a proxy for race? Gender? Prove it!
   
   
7. Theoretical
   • In what order should I auction off items with a distribution of values? I believe real-life auctioneers often sell the lower-value items first.
   • Study sequential auctions in general. (After first reviewing the literature.)
   • Given an auction mechanism with expected profit functional EP(bidding strategy), call it transitive if, in pairwise matches, EP(A) ≥ EP(B) and EP(B) ≥ EP(C) ⇒ EP(A) ≥ EP(C), for all bidding strategies A, B, and C. Which auctions are transitive? Any? Do you have to restrict the class of strategies? Start with IPV auctions and uniform distributions.
   • (Thanks to D. Stavens) Study Princeton's Registrar's own "web bidding" for limited enrollment courses. The budget constraints. These may result in NP-complete problems for the registrar! The general subject of what are called "combinatorial" auctions would be interesting to study and review, see above.
   • Model machine learning in auctions.
   • Study auctions with no pure equilibria. Can there be auctions with mixed equilibria?
   • Study the variance of the revenue in various auctions.
   • Analyze the all-pay auction for risk-averse bidders: can you prove they will they shun such an auction? Similarly for risk-averse bidders in other autions.
   • Study the susceptibility of various auction forms to bid-taker cheating, bidder collusion, and other forms of cheating.
   • Auctions with a continuum of bidders? (Weird.)