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Egalitarian rule

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(Redirected fromEgalitarian social choice rule)
Rawlsian decision rule for social choice

Insocial choice andoperations research, theegalitarian rule (also called themax-min rule or theRawlsian rule) is a rule saying that, among all possible alternatives, society should pick the alternative which maximizes theminimum utility of all individuals in society. It is a formal mathematical representation of theegalitarian philosophy. It also corresponds toJohn Rawls' principle of maximizing the welfare of the worst-off individual.[1]

Definition

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LetX{\displaystyle X} be a set of possible `states of the world' or `alternatives'. Society wishes to choose a single state fromX{\displaystyle X}. For example, in asingle-winner election,X{\displaystyle X} may represent the set of candidates; in aresource allocation setting,X{\displaystyle X} may represent all possible allocations.

LetI{\displaystyle I} be a finite set, representing a collection of individuals. For eachiI{\displaystyle i\in I}, letui:XR{\displaystyle u_{i}:X\longrightarrow \mathbb {R} } be autility function, describing the amount of happiness an individuali derives from each possible state.

Asocial choice rule is a mechanism which uses the data(ui)iI{\displaystyle (u_{i})_{i\in I}} to select some element(s) fromX{\displaystyle X} which are `best' for society. The question of what 'best' means is the basic question ofsocial choice theory. Theegalitarian rule selects an elementxX{\displaystyle x\in X} which maximizes theminimum utility, that is, it solves the following optimization problem:

maxxXminiIui(x).{\displaystyle \max _{x\in X}\min _{i\in I}u_{i}(x).}

Leximin rule

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Often, there are many different states with the same minimum utility. For example, a state with utility profile (0,100,100) has the same minimum value as a state with utility profile (0,0,0). In this case, the egalitarian rule often uses theleximin order, that is: subject to maximizing the smallest utility, it aims to maximize the next-smallest utility; subject to that, maximize the next-smallest utility, and so on.

For example, suppose there are two individuals - Alice and George, and three possible states: statex gives a utility of 2 to Alice and 4 to George; statey gives a utility of 9 to Alice and 1 to George; and statez gives a utility of 1 to Alice and 8 to George. Then statex is leximin-optimal, since its utility profile is (2,4) which is leximin-larger than that ofy (9,1) andz (1,8).

The egalitarian rule strengthened with the leximin order is often called theleximin rule, to distinguish it from the simpler max-min rule.

The leximin rule for social choice was introduced byAmartya Sen in 1970,[1] and discussed in depth in many later books.[2][3][4][5]: sub.2.5 [6]

Properties

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Conditions for Pareto efficiency

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The leximin rule is Pareto-efficient if the outcomes of every decision are known with certainty. However, by Harsanyi's utilitarian theorem, any leximin function is Pareto-inefficient for a society that must make tradeoffs under uncertainty: There exist situations in which every person in a society would be better-off (ex ante) if they were to take a particular bet, but the leximin rule will reject it (because some person might be made worse off ex post).

Pigou-Dalton property

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The leximin rule satisfies thePigou–Dalton principle, that is: if utility is "moved" from an agent with more utility to an agent with less utility, and as a result, the utility-difference between them becomes smaller, then resulting alternative is preferred.

Moreover, the leximin rule is the only social-welfare ordering rule which simultaneously satisfies the following three properties:[5]: 266 

  1. Pareto efficiency;
  2. Pigou-Dalton principle;
  3. Independence of common utility pace - if all utilities are transformed by a common monotonically-increasing function, then the ordering of the alternatives remains the same.

Egalitarian resource allocation

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The egalitarian rule is particularly useful as a rule forfair division. In this setting, the setX{\displaystyle X} represents all possible allocations, and the goal is to find an allocation which maximizes the minimum utility, or the leximin vector. This rule has been studied in several contexts:

See also

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References

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  1. ^abSen, Amartya (2017-02-20).Collective Choice and Social Welfare. Harvard University Press.doi:10.4159/9780674974616.ISBN 978-0-674-97461-6.
  2. ^D'Aspremont, Claude; Gevers, Louis (1977)."Equity and the Informational Basis of Collective Choice".The Review of Economic Studies.44 (2):199–209.doi:10.2307/2297061.ISSN 0034-6527.JSTOR 2297061.
  3. ^Kolm, Serge-Christophe (2002).Justice and Equity. MIT Press.ISBN 978-0-262-61179-4.
  4. ^Moulin, Herve (1991-07-26).Axioms of Cooperative Decision Making. Cambridge University Press.ISBN 978-0-521-42458-5.
  5. ^abHerve Moulin (2004).Fair Division and Collective Welfare. Cambridge, Massachusetts: MIT Press.ISBN 9780262134231.
  6. ^Bouveret, Sylvain; Lemaître, Michel (2009-02-01)."Computing leximin-optimal solutions in constraint networks".Artificial Intelligence.173 (2):343–364.doi:10.1016/j.artint.2008.10.010.ISSN 0004-3702.
  7. ^Nicosia, Gaia; Pacifici, Andrea; Pferschy, Ulrich (2017-03-16)."Price of Fairness for allocating a bounded resource".European Journal of Operational Research.257 (3):933–943.arXiv:1508.05253.doi:10.1016/j.ejor.2016.08.013.ISSN 0377-2217.S2CID 14229329.
  8. ^Imai, Haruo (1983)."Individual Monotonicity and Lexicographic Maxmin Solution".Econometrica.51 (2):389–401.doi:10.2307/1911997.ISSN 0012-9682.JSTOR 1911997.
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