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The instability of instability of centered distributions

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  • Tovey, Craig A.
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    Abstract

    Democratic simple majority voting is perhaps the most widely used method of group decision making in our time. Standard theory, based on "instability" theorems, predicts that a group employing this method will almost always fail to reach a stable conclusion. But empirical observations do not support the gloomy predictions of the instability theorems. We show that the instability theorems are themselves unstable in the following sense: if the model of voter behavior is altered however slightly to incorporate any of the several plausible characteristics of decision making, then the instability theorems do not hold and in fact the probability of stability converges to 1 as the population increases, when the population is sampled from a centered distribution. The assumptions considered include: a cost of change; bounded rationality; perceptual thresholds; a discrete proposal space, and others. Evidence from a variety of fields justifies these assumptions in all or most circumstances. One consequence of this work is to render precise and rigorous, the solution proposed by Tullock to the impossibility problem. All of the stability results given here hold for an arbitrary dimension. We generalize the results to establish stability with probability converging to 1 subject to trade-offs between the assumptions and the degree of non-centeredness of the population. We also extend the results from Euclidean preferences to the more general class of intermediate preferences.

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    Bibliographic Info

    Article provided by Elsevier in its journal Mathematical Social Sciences.

    Volume (Year): 59 (2010)
    Issue (Month): 1 (January)
    Pages: 53-73

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    Handle: RePEc:eee:matsoc:v:59:y:2010:i:1:p:53-73

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    Web page: http://www.elsevier.com/locate/inca/505565

    Related research

    Keywords: Voting Social choice Spatial model Yolk Intermediate preferences Epsilon-core;

    References

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    Cited by:
    1. Tovey, Craig A., 2010. "A critique of distributional analysis in the spatial model," Mathematical Social Sciences, Elsevier, vol. 59(1), pages 88-101, January.

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