2017
DOI: 10.3982/ecta14230
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Single-Crossing Random Utility Models

Abstract: We propose a novel model of stochastic choice: the single‐crossing random utility model (SCRUM). This is a random utility model in which the collection of preferences satisfies the single‐crossing property. We offer a characterization of SCRUMs based on two easy‐to‐check properties: the classic Monotonicity property and a novel condition, Centrality. The identified collection of preferences and associated probabilities is unique. We show that SCRUMs nest both single‐peaked and single‐dipped random utility mode… Show more

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Cited by 55 publications
(36 citation statements)
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“…11 In a more recent paper, Apesteguia et al (2017) study a case of random parameter models where the parameters can be ordered according to the single-crossing property.…”
Section: Related Literaturementioning
confidence: 99%
“…11 In a more recent paper, Apesteguia et al (2017) study a case of random parameter models where the parameters can be ordered according to the single-crossing property.…”
Section: Related Literaturementioning
confidence: 99%
“…A recent literature expressed concerns in using these models for risk and time preferences (Apesteguia and Ballester ()). If, instead, we use the random parameter model that Apesteguia, Ballester, and Lu () proposed to deal with these concerns, RSTL should always be chosen.…”
mentioning
confidence: 99%
“…All these effects are easy to accommodate in our setup, by supposing that there are two rankings i such that t 1 o 1 d and o 2 t 2 d, and that the introduction of d increases the probability of ranking 1 . The advantage of this way of modelling the phenomenon is that the mechanism holds regardless of the type of decoy that is introduced, whether it is a phantom alternative, or one that induces compromise, or a symmetrically dominated alternative, and so on.…”
Section: Lemma 3 Let P Be a Stochastic Choice Rule That Satisfies Modmentioning
confidence: 99%
“…The states correspond to on-off conditions that are relevant for the decision maker and are hidden to the observer, such as time pressure. 1 For instance, a store manager may wonder whether the variability in buying patterns fits a 'dual' form behaviour due to the presence or absence of time pressure at the time of purchase. Scanner data on the repeated purchases of each consumer are likely to be available to the manager, as well as which products were available at the time of each purchase, so that a stochastic choice function can be constructed.…”
Section: Introductionmentioning
confidence: 99%