Auctions

Auctions
• Methods for allocating goods, tasks, resources...
• Participants: auctioneer, bidders
• Enforced agreement between auctioneer & winning bidder(s)
• Easily implementable e.g. over the Internet
– Many existing Internet auction sites
• Auction (selling item(s)): One seller, multiple buyers
– E.g. selling a bull on eBay
• Reverse auction (buying item(s)): One buyer, multiple sellers
– E.g. procurement
• We will discuss the theory in the context of auctions, but same
theory applies to reverse auctions
– at least in 1-item settings

Auction settings
• Private value : value of the good depends only on
the agent’s own preferences
– E.g. cake which is not resold or showed off
• Common value : agent’s value of an item
determined entirely by others’ values
– E.g. treasury bills
• Correlated value : agent’s value of an item depends
partly on its own preferences & partly on others’
values for it
– E.g. auctioning a transportation task when
bidders can handle it or reauction it to others

Auction protocols: All-pay
• 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
• E.g. CS application: tool reallocation [Lenting&Braspenning ECAI-94]

The 4 common auctions
• English auction
• First price sealed bid
• Dutch auction
• Second price, sealed bid (Vickrey)

Auction protocols: 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
– No counterspeculation, but long bidding process
• Variations
– In correlated value auctions, auctioneer often increases price at
a constant rate or as he thinks is appropriate
– Open-exit: Bidder has to openly declare exit without re-entering
possibility => More info to other bidders about the agent’s
valuation

Auction protocols:
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

Example: 1st
price sealed-bid auction
2 agents (1 and 2) with values v1,v2 drawn uniformly from
[0,1].
Utility of agent i if it bids bi and wins the item is ui=vi-bi.
Assume agent 2’s bidding strategy is b2(v2)=v2/2
How should 1 bid? (i.e. what is b1(v1)=z?)
U1=sz=0
2z
(v1-z)dz = (v1-z)2z=2zv1-2z2
Note: given z=b2(v2)=v2/2, 1 only wins if v2<2z
Therefore, Maxz[2zv1-2z2
] when z=b1(v1)=v1/2
Similar argument for agent 2, assuming b1(v1)=v1/2.
We have an equilibrium

Strategic underbidding in first-price
sealed-bid auction…
• Example 2
– 2 risk-neutral bidders: A and B
– A knows that B’s value is 0 or 100 with
equal probability
– A’s value of 400 is common knowledge
– In Nash equilibrium, B bids either 0 or
100, and A bids 100 + ε (winning more
important than low price)

Auction protocols:
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

Dutch (Aalsmeer) flower auction

Auction protocols: 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 www.ebay.com,
www.webauction.com, www.onsale.com

Vickrey auction is a special
case of Clarke tax
mechanism
• Who pays?
– The bidder who takes the item away
from the others (makes the others
worse off)
– Others pay nothing
• How much does the winner pay?
– The declared value that the good would
have had for the others had the winner
stayed home = second highest bid

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!

Revenue equivalence ceases
to hold if agents are not
risk-neutral
• Risk averse bidders:
– Dutch, first-price sealed-bid ≥ Vickrey,
English
• Risk averse auctioneer:
– Dutch, first-price sealed-bid ≤ Vickrey,
English

Optimal auctions (risk-neutral,
asymmetric bidders)
• Private-value auction with 2 risk-neutral
bidders
– A’s valuation is uniformly distributed on [0,1]
– B’s valuation is uniformly distributed on [1,4]
• What revenue do the 4 basic auction types
give?
• Can the seller get higher expected revenue?
– Is the allocation Pareto efficient?
– What is the worst-case revenue for the seller?
– For the revenue-maximizing auction, see
Wolfstetter’s survey on class web page

Common Value Auctions
• In a common value auction, the item
has some unknown value, each agent
has partial information about the
value
– Examples: Art auctions and resale,
construction companies effected by
common events (eg weather), oil drilling

Common Value Auctions
• At time of bidding, the common value
is unknown
• Bidders may have imperfect
estimates about the value, but the
true value is only observed after the
auction takes place

Winner’s Curse
• No agent knows for sure the true value of the
item
• The winner is the agent who made the highest
guess
• If bidders all had “reasonable” information about
the value of the item, then the average of all
guesses should be correct
– i.e the winner has overbid! (the curse)
• Agents should shade their bids downward (even
in English and Vickrey auctions)

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
• Thrm (revenue non-equivalence ). With more than
2 bidders, the expected revenues are not the
same: English ≥ Vickrey ≥ Dutch = first-price
sealed bid

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

auctions...
• Asymmetric info among bidders
– E.g. 1: auctioning pennies in class
– E.g. 2: first-price sealed-bid common value auction
with bidders A, B, C, D
• A & B have same good info. C has this & extra
signal. D has poor but independent info
• A & B should not bid; D should sometimes
• => “Bid less if more bidders or your info is worse”
• Most important in sealed-bid auctions & Dutch

Vulnerability to bidder collusion
[even in private-value auctions]
• v1 = 20, vi = 18 for others
• Collusive agreement for English: e.g. 1 bids 6,
others bid 5. Self-enforcing
• Collusive agreement for Vickrey: e.g. 1 bids 20,
others bid 5. Self-enforcing
• In first-price sealed-bid or Dutch, if 1 bids
below 18, others are motivated to break the
collusion agreement
• Need to identify coalition parties

Vulnerability to shills
• Only a problem in non-private-value
settings
• English & all-pay auction protocols are
vulnerable
– Classic analyses ignore the
possibility of shills
• Vickrey, first-price sealed-bid, and
Dutch are not vulnerable

Vulnerability to a lying
auctioneer
• Truthful auctioneer classically assumed
• In Vickrey auction, auctioneer can overstate 2nd
highest bid to the winning bidder in order to increase
revenue
– Bid verification mechanisms, e.g. cryptographic
signatures
– Trusted 3rd party auction servers (reveal highest
bid to seller after closing)
• In English, first-price sealed-bid, Dutch, and all-pay,
auctioneer cannot lie because bids are public

Auctioneer’s other possibilities
• Bidding
– Seller may bid more than his reservation price
because truth-telling is not dominant for the
seller even in the English or Vickrey protocol
(because his bid may be 2nd highest & determine
the price) => seller may inefficiently get the
item
• In an expected revenue maximizing auction, seller
sets a reservation price strategically like this
[Myerson 81]
– Auctions are not Pareto efficient (not surprising in light
of Myerson-Satterthwaite theorem)
• Setting a minimum price
• Refusing to sell after the auction has ended

Undesirable private information
revelation
• Agents strategic marginal cost information revealed
because truthful bidding is a dominant strategy in
Vickrey (and English)
– Observed problems with subcontractors
• First-price sealed-bid & Dutch may not reveal this
info as accurately
– Lying
– No dominant strategy
– Bidding decisions depend on beliefs about others

Sniping
= bidding very late in the auction
in the hopes that other bidders
do not have time to respond
Especially an issue in electronic auctions
with network lag and lossy communication
links

Sniping…
Amazon auctions give automatic extensions, eBay does not
Antiques auctions have experts
[from Roth & Ockenfels]

Sniping…
[from Roth & Ockenfels]

Sniping…
• Can make sense to both bid through a
regular insecure channel and to snipe
• Might end up sniping oneself

Conclusions on 1-item auctions
• Nontrivial, but often analyzable with reasonable
effort
– Important to understand merits & limitations
– Unintuitive protocols may have better
properties
• Vickrey auction induces truth-telling &
avoids counterspeculation (in limited
settings)
• Choice of a good auction protocol depends on the
setting in which the protocol is used

Revenue equivalence theorem
• Even more generally: Thrm.
– Assume risk-neutral bidders, valuations drawn independently from potentially different
distributions with no gaps
– Consider two Bayes-Nash equilibria of any two auction mechanisms
– Assume allocation probabilities yi(v1, … v|A|) are same in both equilibria
• Here v1, … v|A| are true types, not revelations
• E.g., if the equilibrium is efficient, then yi = 1 for bidder with highest vi
– Assume that if any agent i draws his lowest possible valuation vi, his expected payoff is same in
both equilibria
• E.g., may want a bidder to lose & pay nothing if bidders’ valuations are drawn from same distribution, and
the bidder draws the lowest possible valuation
– Then, the two equilibria give the same expected payoffs to the bidders (& thus to the seller)
pi = probability of winning (expectation taken over others’ valuations)
ti = expected payment by bidder (expectation taken over others’ valuations)
By choosing his bid bi, bidder chooses a point on this curve
(we do not assume it is the same for different mechanisms)
pi*(vi)
ti(pi*(vi))
dti(pi*(vi)) / dpi*(vi) = vi Integrate both sides from pi*(vi)to pi*(vi): ti(pi*(vi)) - ti(pi*(vi)) = ∫pi*(vi)
pi*(vi)
vi(q) dq =
∫vi
vi
s dpi*(s)
Proof sketch. We show that expected payment by an arbitrary bidder i is the same in both equilibria.
By revelation principle, can restrict to Bayes-Nash incentive-compatible direct revelation mechanisms.
So, others’ bids are identical to others’ valuations.
ui = vi pi - ti <=> ti = vi pi - ui
utility increases
vi
Since the two equilibria have the same allocation probabilities yi(v1, … v|A|) and every bidder reveals
his type truthfully, for any realization vi, pi*(vi) has to be the same in the equilibria. Thus the RHS
is the same. Now, since ti(pi*(vi)) is same by assumption, ti(pi*(vi)) is the same. QED

Auctions

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Auctions