The optimality of the expert and majority rules under exponentially distributed competence

Luba Sapir

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We study the uncertain dichotomous choice model. In this model a set of decision makers is required to select one of two alternatives, say 'support' or 'reject' a certain proposal. Applications of this model are relevant to many areas, such as political science, economics, business and management. The purpose of this paper is to estimate and compare the probabilities that different decision rules may be optimal. We consider the expert rule, the majority rule and a few inbetween rules. The information on the decisional skills is incomplete, and these skills arise from an exponential distribution. It turns out that the probability that the expert rule is optimal far exceeds the probability that the majority rule is optimal, especially as the number of the decision makers becomes large.

Original languageEnglish
Pages (from-to)19-36
Number of pages18
JournalTheory and Decision
Volume45
Issue number1
DOIs
StatePublished - 1 Jan 1998

Keywords

  • Decision rule
  • Expert rule
  • Logarithmic expertise
  • Majority rule
  • Optimal rule
  • Partial information

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