1. Auction Theory an introduction
DAI Hards
October 16th

2. Introduction Auctions are the most widely-studied economic mechanism.
Auctions refer to arbitrary resource allocation problems with self-motivated participants: Auctioneer and bidders
Auction (selling item(s)): one buyer, multiple bidders)
e.g. selling a cd on eBay
Reverse Auction (buying item(s)): one buyer, multiple sellers
e.g. procurement
We’ll discuss auction, though the same theory holds for reverse auction

3. Historical note Reports that auctions was used in Babylon 500 B.C.
193 A.D. After having killed Emperor Pertinax, Prætorian Guard sold the Roman Empire by means of an Auction

4. Where auctions are used nowadays?
Treasury auctions (bill, notes, Treasury bonds, securities)
Has been used to transfer assets from public to private sector
Right to drill oil, off-shore oil lease
Use the EM spectrum
Government and private corporations solicit delivery price offers of products
Private firms sell products (flowers, fish, tobacco, livestock, diamonds)
Internet auctions

5. Questions
Information problem: the seller has usually incomplete information about buyers’ valuations (else, he just need to set the price as the maximum valuation of the buyer)  what pricing scheme performs well even in incomplete information setting (is auction better suited for a given problem? Does a type of auction yield greater revenue?)
For the buyer, what are good bidding strategies?

6. Terminology Criterion of comparison:
Revenue: expected selling price
Efficiency: the object ends up in the hands of the person who values it the most (resale does not yield to efficiency)
Private Value: no bidder knows with certainty the valuation of the other bidders, and knowledge of the other bidders’ valuation would not affect the value of the particular bidder
Pure common value: the actual value is the same for ever bidders but bidders have different private information about the what that value actually is (e.g. auction of an oil field and the amount of oil is unknown, different bidders have different geological signals, learning another signal would change the valuation of a bidder).
Correlated value: agent’s value of an item depends partly on its own preferences and partly on others’ values for it

7. Agents care about utility, not valuation
Auctions are really lotteries, so you must compare expected utility rather than utility.
Risk attitude speak about the shape of the utility function:
linear utility function refers to risk-neutrality
 optimize her/his expected payoff
Concave utility function refers to risk-aversion (u’>0 and u’’<0)
convex utility function refers to risk-seeking (u’>0 and u’’>0)
The types of utility functions, and the associated risk attitudes of agents, are among the most important concepts in Bayesian games, and in particular in auctions. Most theoretical results about auction are sensitive to the risk attitude of the bidders.

8. Outline Single-item Auctions Multi-unit Auction Multi-item Auction
Common auctions forms
Equivalence between auctions
Revenue equivalence
Multi-unit Auction
Multi-item Auction

9. Single Item Auction

10. English (first-price open-cry = ascending)
Protocol: Each bidder is free to raise his bid. When no bidder is willing to raise, the auction ends, and the highest bidder wins the item at the price of his bid
Strategy: Series of bids as a function of agent’s private value, his prior estimates of others’ valuations, and past bids
Best strategy: In private value auctions, bidder’s dominant strategy is to always bid a small amount more than current highest bid, and stop when his private value price is reached
Variations:
In correlated value auctions, auctioneer often increases price at a constant rate or as he thinks is appropriate (japonese auction)
Open-exit: Bidder has to openly declare exit without re-entering possibility => More info to other bidders about the agent’s valuation

11. First-price sealed-bid
Protocol: Each bidder submits one bid without knowing others’ bids. The highest bidder wins the item at the price of his bid
Single round of bidding
Strategy: Bid as a function of agent’s private value and his prior estimates of others’ valuations
Best strategy: No dominant strategy in general
Strategic underbidding & counterspeculation
Can determine Nash equilibrium strategies via common knowledge assumptions about the probability distributions from which valuations are drawn
Variant: kth price

12. Example Values are uniformly distributed on [0,1]
The equilibrium bid is (N-1)*x/N
Where
x is the valuation of the bidder
N is the number of bidders
(proof)

13. Dutch (descending)
Protocol: Auctioneer continuously lowers the price until a bidder takes the item at the current price
Strategically equivalent to first-price sealed-bid protocol in all auction settings
Strategy: Bid as a function of agent’s private value and his prior estimates of others’ valuations
Best strategy: No dominant strategy in general
Lying (down-biasing bids) & counterspeculation
Possible to determine Nash equilibrium strategies via common knowledge assumptions regarding the probability distributions of others’ values
Requires multiple rounds of posting current price
Dutch flower market, Ontario tobacco auction, Filene’s basement, Waldenbooks

14. Vickrey (= second-price sealed bid)
Protocol: Each bidder submits one bid without knowing (!) others’ bids. Highest bidder wins item at 2nd highest price
Strategy: Bid as a function of agent’s private value & his prior estimates of others’ valuations
Best strategy: In a private value auction with risk neutral bidders, Vickrey is strategically equivalent to English. In such settings, dominant strategy is to bid one’s true valuation
No counterspeculation
Independent of others’ bidding plans, operating environments, capabilities...
Single round of bidding
Widely advocated for computational multiagent systems
Old [Vickrey 1961], but not widely used among humans
Revelation principle --- proxy bidder agents on

15. All Pay (e.g.lobbying activity)
Protocol: Each bidder is free to raise his bid. When no bidder is willing to raise, the auction ends, and the highest bidder wins the item. All bidders have to pay their last bid
Strategy: Series of bids as a function of agent’s private value, his prior estimates of others’ valuations, and past bids
Best strategy: ?
In private value settings it can be computed (low bids)
Potentially long bidding process
Variations
Each agent pays only part of his highest bid
Each agent’s payment is a function of the highest bid of all agents

16. In a Nutshell Sealed Bid Format Open Format Second-Price Sealed Bid
Weak
Second-Price Sealed Bid
i.e Vickrey
English Auction
Private Value
First-Price Sealed Bid
Dutch Descending Price
Strong

17. Setting for Private Value Auctions
N potential bidders. Bidder i is assigned a value of Xi to the object
Each Xi is i.i.d. on some interval [0,ω] according to the cumulative distribution F
Bidders I knows her/his xi and also that other bidders values are i.i.d. according to F
Bidders are risk neutral (seek to maximize their expected payoffs)
The number of bidders and the distribution F are common knowledge.
Symmetry
The distribution of values is the same for all bidders. WE can consider that all bidders are alike, hence an optimal bidding strategy for one should also be an optimal strategy for the others  symmetric equilibrium

18. Results for private value auctions
Dutch strategically equivalent to first-price sealed-bid
Risk neutral agents => Vickrey strategically equivalent to English
All four protocols allocate item efficiently (assuming no reservation price for the auctioneer)
English & Vickrey have dominant strategies  no effort wasted in counterspeculation
Which of the four auction mechanisms gives highest expected revenue to the seller?
Assuming valuations are drawn independently & agents are risk neutral: The four mechanisms have equal expected revenue!

19. Reserve Price in Private Values
A seller can reserve the right to not sell the object if the price is below a reserved price r
Bidders with value x<r are excluded from the auction
Bidders change their strategy (can be computed)
A revenue maximizing seller should always set a reserve price r that exceeds her or his valuation x0
Proof: compute the expected payoff of the seller, differentiate it with respect to the reserve price and observe it the derivative is positive at x0
Entry Fees: the auctioneer can use an entry fee: a nonrefundable amount that the bidder has to pay to participate to the auction.
Note : there is a way to fix the entry fee such it is equivalent to using a reserved price as far as the agents that are excluded are concerned.
Trade-off: may improve revenue at the expense of efficiency (if seller set a reservation price which is too high)

20. Revenue Equivalence Theorem
In all auctions for k units with the following properties
Buyers are risk neutral
Private Value, with values independently and identically distributed over [a,b] (technicality – distribution must be atomless)
Each bidder demands at most 1 unit
Auction allocates the units to the k highest bids (efficiency)
The bidder with the lowest valuation has a surplus of 0 (i.e. a bidder with a value of 0 has an expected payment of 0)
a buyer with a given valuation will make the same expected payment, and therefore all such auctions have the same expected revenue

21. Application of the Revenue Equivalence Theorem
Helps to find some equilibrium strategy
Ex: compute the equilibrium bid in an all pay auction or in a third price auction
In the case where the number of bidders is uncertain, we can compute the equilibrium bid strategy for a first price auction

22. Revenue equivalence ceases to hold if agents are not risk-neutral
Risk averse Agents
for bidders:
Dutch, first-price sealed-bid ≥ Vickrey, English
Compared to a risk neutral bidder, a risk averse bidder will bid higher (“buy” insurance against the possibility of loosing)
(utility of winning with a lower bid <utility consequence loosing the object)
For auctioneer auctioneer:
Dutch, first-price sealed-bid ≤ Vickrey, English
Risk-Seeking Agents
The expected revenue in third-price is greater than the expected revenue in second-price (English)
Under constant risk-attitude: (k+1)-price is preferable to k-price

23. Revenue equivalence ceases to hold if it is not Private Value
Results for non-private value auctions
Dutch strategically equivalent to first-price sealed-bid
Vickrey not strategically equivalent to English
All four protocols allocate item efficiently
Winner’s curse: each bidder must recognize that she/he wins the objects only if she/he has the highest signal, failure to take into account the bad news about others’ signal can lead the bidder to pay more than the prize it is worth.
Common value auctions:
Agent should lie (bid low) even in Vickrey & English Revelation to proxy bidders?
Thrm (revenue non-equivalence ). With more than 2 bidders, the expected revenues are not the same:
English ≥ Vickrey ≥ Dutch = first-price sealed bid ˜ v 1 = E [ | ˆ , b ( 2 )
< ),
..., N )]

24. Results for non-private value auctions
Common knowledge that auctioneer has private info
Q: What info should the auctioneer release ?
A: auctioneer is best off releasing all of it
“No news is worst news”
Mitigates the winner’s curse

25. The revelation principle (mechanism Design)
In a revelation mechanism agents are asked to report their types (e.g.valuations for the good), and an action (e.g. decision on the winner and his/her payment) will be based the agents’ announcement.
In general, agents may cheat about their types, but:
Any mechanism that implements certain behavior (e.g. a good is allocated to the agent with the highest valuation,v, and he pays (1-1/n)v) can be replaced by another mechanism that implements the same behavior and where truth-revealing is in equilibrium.

26. Multi-unit Auction

27. Auctions with multiple indistinguishable units for sale
Examples
IBM stocks
Barrels of oil
Pork bellies
Trans-Atlantic backbone bandwidth from NYC to Paris …

28. Setting for sealed bid auctions
Each bidder sends a “bid vector” indicating how much she/he is willing to pay for each additional unit
 Can be understood as a demand function
Value of the bid
Number of units

29. Pricing rules Auctioning multiple indistinguishable units of an item
The discriminatory (or “pay your bid”) auction
The uniform price auction
The Vickrey auction

30. Discriminatory auction
Each bidder pays an amount equal to the sum of his bids that are among the K highest of the N*K bids submitted.

31. Uniform-price Auction
Any price between the highest loosing bid and the lowest winning bid is possible
 can choose the highest losing bid

32. Vickrey Auction
Basic principle is the same as the Vickrey-Clarke-Groves mechanism (see Mechanism Design)
A bidder who wins k units pays the k highest losing bids of the other bidders
For bidder i to win the kth unit, i’s kth highest bid must defeat the kth lowest competing bid

33. Some Open Auctions
Dutch Auctions
English Auctions
Ausubel Auctions

34. multiple distinguishable items for sale
Multi-item auctions
multiple distinguishable items for sale

35. Bundle bidding scenario

36. Bundle bidding scenario

37. Bundle bidding scenario
(console, television, cd player $1000)

38. Bundle bidding scenario
(television, music system, computer, $1600)

39. Bundle bidding scenario
(cd player, console, music system $400)

40. Bundle bidding scenario
((console, television, cd player $1000),
(television, music system, computer, $1600),
(cd player, console, music system $ 400))

41. Bundle bidding scenario
((Computer, television, cd player $1000),
(television, music system, console, $600),
(cd player, console, music system $400))

42. Bundle bidding scenario
((Computer, television, cd player $1000),
(television, music system, console, $600),
(cd player, console, music system $400))

43. Bundle bidding scenario
((Computer, television, cd player $1000),
(television, music system, console, $600),
(cd player, console, music system $400))

44. Multiple-item auctions
Auction of multiple, distinguishable items
Bidders have preferences over item combinations
Combinatorial auctions
Bids can be submitted over item bundles
Winner selection: combinatorial optimization
NP-complete

45. Source Vijay Krishna: Auction Theory (Academic Press)
Paul Klemperer: Auction Theory: A guide to the literature (Journal of Economics Survey)
Elmar Wolfstetter: Auctions An Introduction
Tuomas Sandholm COURSE: CS Foundations of Electronic Marketplaces (CMU)