1. week 11 COS 444 Internet Auctions: Theory and Practice Spring 2010 Ken Steiglitz ken@cs.princeton.edu

2. week 12 Mechanics COS 444 home page Classes: - assigned reading: come ready to discuss - theory (ppt + chalk) - practice/discussion/news - experiments Grading: - problem sets, programming assignments - class participation - term paper

3. week 13 Background Freshman calculus, integration by parts Basic probability, order statistics Statistics, significance tests Game theory, Nash equilibrium Java or UNIX tools or equivalent

4. week 14 Why study auctions? Auctions are trade; trade makes civilization possible Auctions are for selling things with uncertain value Auctions are a microcosm of economics Auctions are algorithms run on the internet Auctions are a social entertainment

5. week 15 Goals The central theory, classic papers A bigger picture Even bigger picture Experimental and empirical technique

6. week 16 Who could forget, for example, riding up the Bosporus toward the Black Sea in a fishing vessel to inspect a fishing laboratory; visiting a Chinese cooperative and being the guest of honor at tea in the New Territories of the British crown colony of Hong Kong; watching the frenzied but quasi-organized bidding of would-be buyers in an Australian wool auction; observing the "upside-down" auctioning of fish in Tel Aviv and Haifa; watching the purchasing activities of several hundred screaming female fishmongers at the Lisbon auction market; viewing the fascinating "string selling" in the auctioning of furs in Leningrad; eating fish from the Seas of Galilee while seated on the shore of that historic body of water; … Cassady on the romance of auctions (1967)

7. week 17 Cassady on the romance of auctions (1967)... observing "whispered“ bidding in such far-flung places as Singapore and Venice; watching a "handshake" auction in a Pakistanian go-down in the midst of a herd of dozing camels; being present at the auctioning of an early Van Gogh in Amsterdam; observing the sale of flowers by electronic clock in Aalsmeer, Holland; listening to the chant of the auctioneer in a North Carolina tobacco auction; watching the landing of fish at 4 A.M. in the market on the north beach of Manila Bay by the use of amphibious landing boats; observing the bidding of Turkish merchants competing for fish in a market located on the Golden Horn; and answering questions about auctioning posed by a group of eager Japanese students at the University of Tokyo.

8. week 18 Auctions: Methods of Study Theory (1961--) Empirical observation (recent on internet) Field experiments (recent on internet) Laboratory experiments (1980--) Simulation (not much) fMRI (?)

9. week 19 History

10. week 110 History

11. week 111 History

12. week 112 History

13. week 113 History

14. week 114 History

15. week 115 History Route 6: Long John Nebel pitching hard

16. week 116 Google Ad Auctions Google Ad Auctions – Hal Varian

17. week 117 Standard theoretical setup One item, one seller n bidders Each knows her value v i (private value) Each wants to maximize her surplus i = v i – payment i Values usually randomly assigned Values may be interdependent

18. week 118 English auctions: variations Outcry ( jump bidding allowed ) Ascending price Japanese button Truthful bidding is dominant in Japanese button auctions Is it dominant in outcry? Ascending price?

19. week 119 Vickrey Auction: sealed-bid second-price Vickrey wins Nobel Prize, 1996 William Vickrey, 1961

20. week 120 Truthful bidding is dominant in Vickrey auctions Japanese button and Vickrey auctions are (weakly) strategically equivalent

21. week 121 Dutch descending-price Aalsmeer flower market, Aalsmeer, Holland, 1960’s

22. week 122

23. week 123 Sealed-Bid First-Price Highest bid wins Winner pays her bid How to bid? That is, how to choose bidding function Notice: bidding truthfully is now pointless!

24. week 124 Dutch and First-Price auctions are (strongly) strategically equivalent So we have two pairs, comprising the four most common auction forms

25. week 125 Enter John Nash Equilibrium translates question of human behavior to math How much to shade? Nash wins Nobel Prize, 1994

26. week 126 Equilibrium A strategy (bidding function) is a (symmetric) equilibrium if it is a best response to itself. That is, if all others adopt the strategy, you can do no better than to adopt it also. Note: Cannot call this “optimal”

27. week 127 Simple example: first-price n=2 bidders v 1 and v 2 uniformly distributed on [0,1] Find b (v 1 ) for bidder 1 that is best response to b (v 2 ) for bidder 2 in the sense that E [surplus ] = max Note: We need some probability theory for “uniformly distributed” and “E[ ]”

28. week 128 Verifying a guess Assume for now that v/ 2 is an equilibrium strategy Bidder 2 bids v 2 / 2 ; Fix v 1. What is bidder 1’s best response b (v 1 ) ? E[surplus] = … the average is over the values of v 2 when 1 wins Bidders 1’s best choice of bid is b = v 1 / 2 … QED.

29. week 129 and Hurwicz + Myerson + Maskin win Nobel prize in 2007 for theory of mechanism design

30. week 130 New directions: Simulation Agent-Based Simulation of Dynamic Online Auctions,“ H. Mizuta and K. Steiglitz, Winter. Simulation Conference, Orlando, FL, Dec. 10- 13, 2000

31. week 131 New directions: Sociology M. Shohat and J. Musch “Online auctions as a research tool: A field experiment on ethnic discrimination” Swiss Journal of Psychology 62 (2), 2003, 139-145

32. week 132 New directions: Category clustering Courtesy of Matt Sanders ’09 Categories connected by mutual bidders Darker lines mean higher probability that two categories will share bidders Categories with higher totals near center Color random Only top 25% lines by weight are shown Based on 278,593 recorded auctions from bid histories of 18,000 users