Border's theorem

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In auction theory and mechanism design, Border's theorem gives a necessary and sufficient condition for interim allocation rules (or reduced form auctions) to be implementable via an auction.

It was first proven by Kim Border in 1991,[1] expanding on work from Steven Matthews,[2] Eric Maskin and John Riley.[3] A similar version with different hypotheses was proven by Border in 2007.[4]

Preliminaries

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Auctions

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Auctions are a mechanism designed to allocate an indivisible good among N bidders with private valuation for the good – that is, when the auctioneer has incomplete information on the bidders' true valuation and each bidder knows only their own valuation.

Formally, this uncertainty is represented by a family of probability spaces (Ti,𝒯i,Ξ»i) for each bidder i=1,...,N, in which each ti∈Ti represents a possible type (valuation) for bidder i to have, 𝒯i denotes a Οƒ-algebra on Ti, and Ξ»i a prior and common knowledge probability distribution on Ti, which assigns the probability Ξ»i(ti) that a bidder i is of type ti. Finally, we define 𝑻=∏i=1NTi as the set of type profiles, and π‘»βˆ’i=∏jβ‰ iTi the set of profiles tβˆ’i=(t1,...,tiβˆ’1,ti+1,...,tN).

Bidders simultaneously report their valuation of the good[nb 1], and an auction assigns a probability that they will receive it. In this setting, an auction is thus a function q:𝑻→[0,1]N satisfying, for every type profile tβˆˆπ‘»

βˆ‘i=1Nqi(t)≀1

where qi is the i-th component of q=(q1,q2,...,qN). Intuitively, this only means that the probability that some bidder will receive the good is no greater than 1.

Interim allocation rules (reduced form auctions)

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From the point of view of each bidder i, every auction q induces some expected probability that they will win the good given their type, which we can compute as

Qi(ti)=∫Tβˆ’iqi(t)dΞ»i(tβˆ’i|ti)

where Ξ»i(tβˆ’i|ti) is conditional probability of other bidders having profile type tβˆ’i given that bidder i is of type ti. We refer to such probabilites Qi as interim allocation rules, as they give the probability of winning the auction in the interim period: after each player knowing their own type, but before the knowing the type of other bidders.

The function 𝑸:𝑻→[0,1]N defined by 𝑸(t)=(Q1(t1),...,QN(tN)) is often referred to as a reduced form auction. Working with reduced form auctions is often much more analytically tractable for revenue maximization.[3]

Implementability

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Taken on its own, an allocation rule 𝑸:Tβ†’[0,1]N is called implementable if there exists an auction q:𝑻→[0,1]N such that

Qi(ti)=∫Tβˆ’iqi(t)dΞ»i(tβˆ’i|ti)

for every bidder i and type ti∈Ti.

Statement

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Border proved two main versions of the theorem, with different restrictions on the auction environment.[1][4]

i.i.d environment

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The auction environment is i.i.d if the probability spaces (Ti,𝒯i,Ξ»i)=(T,𝒯,Ξ») are the same for every bidder i, and types ti are independent. In this case, one only needs to consider symmetric auctions[nb 2],[3] and thus Qi=Q also becomes the same for every i. Border's theorem in this setting thus states:[1]

Proposition: An interim allocation rule Q:Tβ†’[0,1] is implementable by a symmetric auction if and only if for each measurable set of types Aβˆˆπ’―, one has the inequality

N∫AQ(t)dΞ»(t)≀1βˆ’Ξ»(Ac)N

Intuitively, the left-hand side represents the probability that the winner of the auction is of some type t∈A, and the right-hand side represents the probability that there exists some bidder with type t∈A. The fact that the inequality is necessary for implementability is intuitive; it being sufficient means that this inequality fully characterizes implementable auctions, and represents the strength of the theorem.

Finite sets of types

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If all the sets Ti are finite, the restriction to the i.i.d case can be dropped. In the more general environment developed above, Border thus proved:[4][5]

Proposition: An interim allocation rule 𝑸:𝑻→[0,1]N is implementable by an auction if and only if for each measurable sets of types A1βˆˆπ’―1,A2βˆˆπ’―2,...,ANβˆˆπ’―N, one has the inequality

βˆ‘i=1N∫AiQi(ti)dΞ»i(ti)≀1βˆ’βˆi=1N(1βˆ’βˆ‘ti∈AiΞ»i(ti))

The intuition of the i.i.d case remains: the left-hand side represents the probability that the winner of the auction is some bidder i with type ti∈Ai, and the right-hand side represents the probability that there exists some bidder i with type ti∈Ai. Once again, the strength of the result comes from it being sufficient to characterize implementable interim allocation rules.

Notes

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  1. ^ More generally, bidders could report any bid, not necessarily their true valuation. But we can, without loss of generality, concentrate on direct-revelation mechanisms and let the payment functions restrict the auction's incentive compatibility constraints .[1]
  2. ^ An auction q is symmetric if, for any permutation Ο€ over {1,...,N} and every bidder i, we have qi(t)=qΟ€βˆ’1(i)(tΟ€(1),...,tΟ€(N)). Intuitively, this means that a bidder i's identity does not matter, only their valuation ti.

References

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  1. ^ a b c d Lua error in Module:Citation/CS1/Configuration at line 2172: attempt to index field '?' (a nil value).
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