Testing a mixture model of single-peaked preferences

Smeulders, Bart

doi:10.1016/j.mathsocsci.2018.02.002

Cited by 2 publications

(1 citation statement)

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“…Matzkin (2007) and Hoderlein and Stoye (2014) provided conditions for a probabilistic version of the so-called “weak axiom of revealed preference.” Davis-Stober (2012) described a set of linear inequalities that are necessary and sufficient conditions for probabilistic choice induced by certain heuristic preferences. Smeulders (2018) provided necessary and sufficient conditions for a probabilistic model induced by single-peaked linear orders. Guo and Regenwetter (2014); Regenwetter et al (2014); Regenwetter and Robinson (2017) evaluated various sets of necessary and sufficient conditions for binary choice probabilities.…”

Section: Introductionmentioning

confidence: 99%

Testing probabilistic models of choice using column generation

Smeulders

Davis‐Stober

Regenwetter

et al. 2018

Computers & Operations Research

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In so-called random preference models of probabilistic choice, a decision maker chooses according to an unspecified probability distribution over preference states. The most prominent case arises when preference states are linear orders or weak orders of the choice alternatives. The literature has documented that actually evaluating whether decision makers’ observed choices are consistent with such a probabilistic model of choice poses computational difficulties. This severely limits the possible scale of empirical work in behavioral economics and related disciplines. We propose a family of column generation based algorithms for performing such tests. We evaluate our algorithms on various sets of instances. We observe substantial improvements in computation time and conclude that we can efficiently test substantially larger data sets than previously possible.

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