Optimality of the expert rule under partial information

Daniel Berend, Luba Sapir

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We study the uncertain dichotomous choice model. In this model a group of decision makers is required to select one of two alternatives. The applications of this model are relevant to a wide variety of areas, such as medicine, management and banking. The decision rule may be the simple majority rule; however, it is also possible to assign more weight to the opinion of members known to be more qualified. The extreme example of such a rule is the expert decision rule. We are concerned with the probability of the expert rule to be optimal. Our purpose is to investigate the behaviour of this probability as a function of the group size for several rather general types of distributions. One such family of distributions is that where the density function of the correctness probability is a polynomial (on the interval [1/2, 1]). Our main result is an explicit formula for the probability in question. This contains formerly known results as very special cases.

Original languageEnglish
Pages (from-to)141-162
Number of pages22
JournalActa Applicandae Mathematicae
Volume69
Issue number2
DOIs
StatePublished - 1 Nov 2001

Keywords

  • Choice
  • Decision rule
  • Dichotomous
  • Expert rule
  • Expertise
  • Experts
  • Model
  • Optimality
  • Partial information
  • Probability

ASJC Scopus subject areas

  • Applied Mathematics

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