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Atlas / Mathematics / The Decision Thread

Field · Emerged 1770 – 1981

Social Choice and Mechanism Design

Can individual preferences be combined into a collective decision without arbitrariness, and can a procedure be built so that honesty is each participant's best policy?

4 chapters7 min read6 turning points1 open problem

Branched from
Game Theory
Branched into
Algorithmic Game Theory
Figures
Jean-Charles de Borda, Marquis de Condorcet, Kenneth Arrow, Amartya Sen, Allan Gibbard, Mark Satterthwaite, William Vickrey, Roger Myerson

In brief

Two commissioners of the French Academy of Sciences discovered the subject's central difficulty before the Revolution. Jean-Charles de Borda showed that plurality voting can elect a candidate whom a majority ranks last. The Marquis de Condorcet showed something worse: majority preference can cycle, with the electorate preferring A to B, B to C and C to A, so that there is no candidate a majority would not rather replace. Neither result is about bad voters or bad luck. They are properties of the aggregation itself.

Kenneth Arrow turned this into a theorem in 1951. Write down four mild requirements on any rule that converts individual rankings into a social ranking, and no rule satisfies all of them except dictatorship. Gibbard and Satterthwaite then proved the corresponding result about honesty: any non-trivial deterministic voting rule can sometimes be manipulated by a voter who lies about their preferences. The constructive response was mechanism design, which asks what can be achieved: William Vickrey showed in 1961 that in a sealed-bid auction where the winner pays the second-highest bid, bidding one's true value is optimal no matter what anyone else does, and Roger Myerson showed in 1981 how to find the revenue-maximising mechanism for a whole class of such problems.

Key ideas

Condorcet cycleEnters 1770 – 1785

Majority preference need not be transitive. With three groups of voters ranking three options in rotation, each option loses a head-to-head majority vote against another, so no option is unbeatable.

Independence of irrelevant alternativesEnters 1950 – 1951

The social ranking of A against B should depend only on how voters rank A against B, not on where C sits. It is the most demanding of Arrow's conditions and the one most rules violate — Borda counts, for instance, can be reversed by adding a candidate nobody supports.

Arrow's impossibility theoremEnters 1950 – 1951

No rule converting individual rankings into a transitive social ranking satisfies unrestricted domain, unanimity, independence of irrelevant alternatives and non-dictatorship simultaneously.

StrategyproofnessEnters 1973 – 1975

A rule is strategyproof if no participant can ever gain by misreporting their preferences. Gibbard and Satterthwaite showed that for deterministic choices among three or more outcomes, only dictatorial rules achieve it.

Second-price auctionEnters 1961

The highest bidder wins and pays the second-highest bid. Because a bidder's payment does not depend on their own bid, bidding one's true valuation is a dominant strategy, and the seller learns the valuations without having to ask.

Revelation principleEnters 1979 – 1981

Anything achievable by some mechanism in which participants strategise is achievable by a mechanism in which they report truthfully. This collapses the search over all conceivable procedures into a search over truthful ones, which is what made mechanism design tractable.

Chapter I

Two Commissioners and a Bad Surprise

In 1770 Jean-Charles de Borda pointed out to the Académie des Sciences that its elections could go wrong in a specific way. If three candidates stand and the vote splits, the winner on first preferences may be the candidate whom most voters place last. His remedy was to score candidates by position on every ballot and sum.

The Marquis de Condorcet objected that the proper criterion is simpler: a candidate should win if they would beat each rival in a head-to-head majority vote. Then he found that this criterion can fail to pick anybody. For some distributions of preferences, A beats B, B beats C, and C beats A, all by majorities. Collective preference, built from perfectly transitive individual preferences, need not be transitive itself.

This is not a paradox in the sense of a puzzle to be dissolved. It is a fact about majority aggregation, and it means that "what the electorate wants" may not name anything.

Chapter II

Impossibility, Twice

Kenneth Arrow turned the eighteenth-century objections into a theorem by asking what any acceptable aggregation rule must satisfy, and then showing the requirements are jointly unsatisfiable. His conditions are modest individually. The rule must handle every possible profile of individual rankings, since a procedure that fails on some electorates is no procedure. If everyone prefers A to B, so must the social ranking. The social ranking of A against B must depend only on how individuals rank A against B, and not on where some third option sits. And no individual's preference may prevail regardless of everyone else's.

No rule satisfies all four. The proof is a page of combinatorics, and it has generated seventy years of argument about which condition to give up rather than about whether the theorem is right. Independence is the usual casualty, because insisting on it discards all information about how strongly options are preferred — which is why the Borda count, which uses the whole ranking, violates it, and why rules that satisfy it end up relying on pairwise comparisons that can cycle. The theorem's lasting effect was to turn the question from "which voting rule is correct?" into "which failure is acceptable here?".

Amartya Sen added a second impossibility in 1970 with a different moral. Grant each person decisiveness over at least one matter that is plainly their own business — which book they read, which way up they sleep — and also require the Pareto criterion, that a unanimously preferred outcome be chosen. Sen constructs preferences, involving two people who each care what the other reads, for which no social ranking satisfies both. Minimal individual rights and unanimity are logically incompatible once people have preferences about each other's private affairs, which is not a defect of any procedure but a property of the two principles.

Chapter III

A Closer Look: Three Rules, One Set of Ballots, Three Winners

Take an electorate of 100 voters with these preferences:

VotersRanking
40A > C > B
35B > C > A
25C > B > A

Plurality. Count first preferences only: A has 40, B has 35, C has 25. A wins.

Pairwise majorities. Compare each pair across all ballots.

  • A vs B: A is preferred by the 40; B by the 35 and the 25, so 40 to 60. B beats A.
  • A vs C: A by the 40; C by the 35 and the 25, so 40 to 60. C beats A.
  • B vs C: B by the 35; C by the 40 and the 25, so 35 to 65. C beats B.

C beats both rivals head to head, so C is the Condorcet winner — with the fewest first preferences. And A, the plurality winner, loses to each of the other two by 60 to 40. Sixty per cent of the electorate prefers anyone to the person plurality elects.

Borda count. Award 2 points for a first place, 1 for second, 0 for third.

A=40(2)+0+0=80,B=35(2)+25(1)=95,C=25(2)+40(1)+35(1)=125.\begin{aligned} A &= 40(2) + 0 + 0 = 80,\\ B &= 35(2) + 25(1) = 95,\\ C &= 25(2) + 40(1) + 35(1) = 125. \end{aligned}

The totals sum to 300, as they must with 100 voters and 3 points each. C wins, agreeing with Condorcet here but not in general.

The three rules are all defensible and they do not agree, and nothing in the ballots adjudicates between them. Note also what happens to the Borda count if a fourth candidate D, whom everyone ranks last, is added: nothing. But if D is inserted in the middle of some voters' rankings, the gaps between A, B and C change, and the Borda winner can flip without a single voter altering their opinion about A, B or C. That is a violation of independence of irrelevant alternatives, the condition Arrow's theorem says cannot be kept alongside the other three — and here it is, in a worked ballot count, rather than as an abstraction.

Chapter IV

Honesty as a Design Problem

Allan Gibbard and Mark Satterthwaite showed the strategic counterpart to Arrow's result. Any deterministic rule that can select among three or more outcomes, and is not a dictatorship, can be manipulated: there is some situation in which a voter does better by submitting a ranking that misstates their preferences. Tactical voting is therefore structural. The familiar advice not to "waste" a vote on a third candidate is not a failure of civic virtue but a correct response to a feature of the rule.

Faced with two impossibilities, the field turned the question around. Instead of asking which rule is best, ask what is achievable, and design the procedure to make the behaviour you want into each participant's self-interest. William Vickrey gave the founding example in 1961, and it is worth stating exactly because the argument is three lines.

In a sealed-bid auction, let the highest bidder win and pay the second-highest bid. Suppose your value is 100. If you bid 100 and the next bid is 80, you win and pay 80, gaining 20. Could you do better by bidding 90? Only if that changes the outcome — and it changes it only when the highest rival bid is between 90 and 100, in which case you now lose an auction you would have won at a profit. Could you gain by bidding 110? Only when the highest rival bid is between 100 and 110, in which case you win and pay more than the item is worth to you. In every other case your bid makes no difference, because the price is set by someone else. Truthful bidding is a dominant strategy: optimal whatever anyone else does, with no need to guess at their values at all.

Vickrey also proved the first revenue equivalence result: the familiar formats raise the same expected revenue when values are drawn independently from the same distribution. With two bidders whose values are uniform on [0,1][0,1], the second-price auction collects the lower of two draws, whose expectation is 1/31/3. In a first-price auction the equilibrium is to bid half one's value, so the seller receives half the higher draw, and the higher of two uniform draws averages 2/32/3 — giving 1/31/3 again. The strategic behaviour differs completely and the revenue is identical.

Roger Myerson completed the framework in 1981 with two results. The revelation principle says that anything achievable by any mechanism is achievable by one in which participants simply tell the truth, which collapses an unmanageable search over procedures into an optimisation over truthful ones. And the revenue-maximising auction for a single item turns out to be the second-price auction with a reserve price — the reserve chosen exactly as a monopolist facing one buyer would choose a price, ignoring competition entirely.

That clean answer has resisted every attempt to extend it to more than one item, which is the open problem above, and the reason real multi-item auctions — spectrum, advertising, electricity — are designed by judgement and simulation rather than derived. The further constraint, that a mechanism must also be computable when there are exponentially many possible allocations, is where this field meets computational complexity, in algorithmic game theory.

Applications

Where it is used

  • Electoral systems

    Choosing a voting rule is choosing which failure to accept

    Plurality can elect a candidate a majority ranks last; Borda counts can be reversed by adding a hopeless candidate; instant-runoff can eliminate a candidate who would beat everyone head to head; Condorcet methods must specify what to do when there is a cycle. Arrow's theorem guarantees that there is no rule without such a defect, so the design question is which defect matters least for a given electorate — a mathematical result with direct constitutional consequences.

    › Sources (1)
    • Brams, S. J. & Fishburn, P. C. (2002). Voting procedures. In Handbook of Social Choice and Welfare, volume 1: 173–236. Elsevier.
  • Public asset sales

    Spectrum auctions

    Governments have sold radio spectrum by auction since 1994, with designs drawn directly from this theory, and the differences between designs have been worth billions. The 1990s British 3G auction raised £22.5 billion from a simultaneous ascending design, while an otherwise similar Swiss auction raised a twentieth as much per head after bidders were allowed to merge, leaving too few to compete. The lesson that has survived is that attracting entry matters more than the fine structure of the rules.

    › Sources (2)
    • Klemperer, P. (2002). What really matters in auction design. Journal of Economic Perspectives 16: 169–189.
    • Milgrom, P. (2004). Putting Auction Theory to Work. Cambridge University Press.
  • Computing

    Mechanisms that must also run fast

    Search advertising, cloud resource allocation and spectrum reallocation all require mechanisms that are not merely incentive-compatible but computable at scale, which turns out to constrain the designs available: the general truthful mechanism for combinatorial problems requires solving an NP-hard allocation exactly, and approximating it usually destroys truthfulness. Reconciling the two is the subject of algorithmic game theory.

    › Sources (1)
    • Nisan, N. & Ronen, A. (2001). Algorithmic mechanism design. Games and Economic Behavior 35: 166–196.

Open problems

Where the map runs out

Open

The optimal way to sell several items

Open as of 2026; no general characterisation exists even for one buyer and two items.

Myerson solved the revenue-maximising sale of a single item completely. For two or more items sold to a single buyer with independently drawn values, the optimal mechanism is unknown in general, and the known examples are strange: the best mechanism may require offering randomised bundles rather than deterministic prices, the revenue can be a discontinuous function of the distributions, and the number of distinct offers needed can be infinite for perfectly ordinary value distributions.

Why it is hard

With one item the buyer's private information is a single number and the incentive constraints reduce to a monotonicity condition. With several items it is a vector, the constraints become a partial differential inequality on a multidimensional domain, and the one-dimensional machinery has no known replacement. Most progress is on approximation — simple mechanisms that guarantee a constant fraction of the unknown optimum.

What resolving it unlocks

Nearly every real auction sells multiple goods: spectrum licences, advertising slots, electricity across a network, landing rights. Knowing the optimum, or that a simple mechanism is close to it, determines how billions of pounds of public assets should be sold.

› Sources (2)
  • Hart, S. & Nisan, N. (2017). Approximate revenue maximization with multiple items. Journal of Economic Theory 172: 313–347.
  • Daskalakis, C., Deckelbaum, A. & Tzamos, C. (2017). Strong duality for a multiple-good monopolist. Econometrica 85: 735–767.

Further reading

  1. Arrow, K. J. (1951). Social Choice and Individual Values. Wiley.

    Short, readable, and the source of the argument; the second edition's added essay is worth the detour.

  2. Sen, A. (2017). Collective Choice and Social Welfare, expanded edition. Harvard University Press.

    The impossibility results placed in the context of what welfare judgements require.

  3. Milgrom, P. (2004). Putting Auction Theory to Work. Cambridge University Press.

    Mechanism design as practised, by someone who designed auctions that sold real spectrum.