Dichotomous preferences

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In economics, dichotomous preferences (DP) are preference relations that divide the set of alternatives to two subsets: "Good" versus "Bad".

Contents

From ordinal utility perspective, DP means that for every two alternatives : [1] :292

From cardinal utility perspective, DP means that for each agent, there are two utility levels: low and high, and for every alternative :

A common way to let people express dichotomous preferences is using approval ballots, in which each voter can either "approve" or "reject" each alternative.

In fair item assignment

In the context of fair item assignment, DP can be represented by a mathematical logic formula: [1] :292 for every agent, there is a formula that describes his desired bundles. An agent is satisfied if-and-only-if he receives a bundle that satisfies the formula.

A special case of DP is single-mindedness. A single-minded agent wants a very specific bundle; he is happy if-and-only-if he receives this bundle, or any bundle that contains it. Such preferences appear in real-life, for example, in the problem of allocating classrooms to schools: each school i needs a number di of classes; the school has utility 1 if it gets all di classes in the same place and 0 otherwise. [2] [3] [4]

Collective choice under DP

Without money

Suppose a mechanism selects a lottery over outcomes. The utility of each agent, under this mechanism, is the probability that one of his Good outcomes is selected.

The utilitarian mechanism averages over outcomes with largest “approval”. It is Pareto efficient, strategyproof, anonymous and neutral.

It is impossible to attain these properties in addition to proportionality - giving each agent a utility of at least 1/n; or at least the fraction of good to feasible outcomes. [5] conjecture that no ex ante efficient and strategyproof mechanism guarantees a strictly positive utility to all agents, and prove a weaker statement.

With money

Suppose all agents have DP cardinal utility, where each agent is characterized by a single number - (so that ).

[6] identify a new condition, generation monotonicity, that is necessary and sufficient for implementation by a truthful mechanisms in any dichotomous domain (see Monotonicity (mechanism design)).

If such a domain satisfies a richness condition, then a weaker version of generation monotonicity, 2-generation monotonicity (equivalent to 3-cycle monotonicity), is necessary and sufficient for implementation.

This result can be used to derive the optimal mechanism in a one-sided matching problem with agents who have dichotomous types

Related Research Articles

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<span class="mw-page-title-main">Indifference curve</span> Concept in economics

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Arrow's impossibility theorem, the general possibility theorem or Arrow's paradox is an impossibility theorem in social choice theory that states that when voters have three or more distinct alternatives (options), no ranked voting electoral system can convert the ranked preferences of individuals into a community-wide ranking while also meeting the specified set of criteria: unrestricted domain, non-dictatorship, Pareto efficiency, and independence of irrelevant alternatives. The theorem is often cited in discussions of voting theory as it is further interpreted by the Gibbard–Satterthwaite theorem. The theorem is named after economist and Nobel laureate Kenneth Arrow, who demonstrated the theorem in his doctoral thesis and popularized it in his 1951 book Social Choice and Individual Values. The original paper was titled "A Difficulty in the Concept of Social Welfare".

<span class="mw-page-title-main">Mechanism design</span> Field in game theory

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Fractional social choice is a branch of social choice theory in which the collective decision is not a single alternative, but rather a weighted sum of two or more alternatives. For example, if society has to choose between three candidates: A B or C, then in standard social choice, exactly one of these candidates is chosen, while in fractional social choice, it is possible to choose "2/3 of A and 1/3 of B". A common interpretation of the weighted sum is as a lottery, in which candidate A is chosen with probability 2/3 and candidate B is chosen with probability 1/3. Due to this interpretation, fractional social choice is also called random social choice, probabilistic social choice, or stochastic social choice. But it can also be interpreted as a recipe for sharing, for example:

Fractional approval voting is an electoral system using approval ballots, in which the outcome is fractional: for each alternative j there is a fraction pj between 0 and 1, such that the sum of pj is 1. It can be seen as a generalization of approval voting: in the latter, one candidate wins and the other candidates lose. The fractions pj can be interpreted in various ways, depending on the setting. Examples are:

Donor coordination is a problem in social choice. There are several donors, each of whom wants to donate some money. Each donor supports a different set of targets. The goal is to distribute the total donated amount among the various targets in a way that respects the donors' preferences.

References

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