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dc.contributor.authorTovey, Craig A.
dc.date1991-05
dc.date.accessioned2013-02-27T23:36:39Z
dc.date.available2013-02-27T23:36:39Z
dc.date.issued1991-05
dc.identifier.urihttps://hdl.handle.net/10945/29234
dc.description.abstractDistributional analysis is widely used to study social choice in Euclidean models [28, 29, 1, 3, 8, 15, 5, 2, e.g.]. This method assumes a continuum of voters distributed according to a distribution function. Since infinite populations do not exist, the goal of distributional analysis is to give insight into the behavior of large finite populations. However, properties of finite populations do not in general converge to the properties of infinite populations. Thus the method of distributional analysis is flawed. In some cases it will predict that a point is in the core with probability 1, while the true probability converges to 0. On the other hand, it is sometime possible to combine distributional analysis with probabilistic analysis to make correct predictions about the asymptotic behavior of large populations, as in [2, e.g.]. Results on the uniform convergence of empirical measures [18, e.g.] are employed to yield simpler proofs of min-max Simpson-Cramer majority [5,2] and yolk shrinkage [26]. The analysis suggests a rule of thumb as to whether or not a prediction based on distributional analysis will be valid for large finite populations. From the experimental point of view, the discussion helps clarify the mathematical underpinnings of statistical analysis of empirical voting data. A careful reading shows Tullock's original paper [28] to be consistent with the analysis given here.en_US
dc.description.sponsorshipNational Research Council and National Science Foundationen_US
dc.description.urihttp://archive.org/details/critiqueofdistri00tove
dc.format.extentNAen_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.subject.lcshPROBABILITY.en_US
dc.titleA critique of distributional analysis in social choiceen_US
dc.typeTechnical Reporten_US
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentOperations Research
dc.subject.authorSpatial model; social choice; asymptotics; consistency; probability; votingen_US
dc.description.funderOM&N Direct Fundingen_US
dc.description.recognitionNAen_US
dc.identifier.oclcNA
dc.identifier.npsreportNPS-OR-91-16
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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