• Media type: E-Book
  • Title: Stochastic Choice in Criterion Space
  • Contributor: Mayskaya, Tatiana [Author]
  • imprint: [S.l.]: SSRN, [2017]
  • Extent: 1 Online-Ressource (41 p)
  • Language: English
  • DOI: 10.2139/ssrn.3038369
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 30, 2014 erstellt
  • Description: Many experiments demonstrate that an individual's choice decisions are inconsistent. Following Luce (1959) and Block, Marschak, et al. (1960), a random choice approach to this problem has become very popular. It posits the existence of a probabilistic choice function that describes the probability of choosing an alternative from a given set of options. This paper contributes to the theoretical literature that narrows the class of random choice functions. Each alternative can be fully characterized by a vector in a n-dimensional space. A decision maker pays attention only to a randomly chosen subset of coordinates (or criteria) each time he faces a set of alternatives to choose from. Given this randomly chosen subset, he is perfectly rational, that is he chooses according to some strict preference ordering. For this procedure to be well-defined, the preference ordering must be separable with respect to criteria. In other words, the preference of the decision maker over any two alternatives should not depend on the characteristics that these alternatives have in common. This paper characterizes all systems of choice probabilities that are induced by this choice procedure
  • Access State: Open Access