Deliberately Stochastic

Cerreia‐Vioglio, Simone; Dillenberger, David; Ortoleva, Pietro; Riella, Gil

doi:10.1257/aer.20180688

Cited by 58 publications

(26 citation statements)

References 74 publications

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“…Numerous random utility or random choice experimental and theoretical papers have emerged in an e¤ort to better understand choice. 4 Some authors examine the role of consideration sets (Masatlioglu, Nakajima, and Ozbay, 2012;Manzini and Mariotti, 2014), private information (Lu, 2016), the preference for randomness (Agranov and Ortoleva, 2017;Cerreia-Vioglio, Dillenberger, Ortoleva, and Riella, 2019), and the preference for ‡exibility (Ahn and Sarver, 2013) in explaining the apparent randomness in choice data. These factors help us understand choice, but it is our view that imperfect perception of one's preferences is fundamental in every choice setting.…”

Section: Related Literature 21 Random Utility and Random Choicementioning

confidence: 99%

An Economist and a Psychologist Form a Line: What Can Imperfect Perception of Length Tell Us About Stochastic Choice?

Duffy¹,

Smith

2020

SSRN Journal

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Standard choice experiments are hampered by the fact that utility is either unknown or imperfectly measured by experimenters. As a consequence, the inferences available to researchers are limited. By contrast, we design a choice experiment where the objects are valued according to only a single attribute with a continuous measure and we can observe the true preferences of subjects. Subjects have an imperfect perception of the choice objects but can improve the precision of their perception with cognitive e¤ort. Subjects are given a choice set involving several lines of various lengths and are told to select one of them. They strive to select the longest line because they are paid an amount that increases with the length of their choice. Our design allows us to observe the search history, the response times, and make unambiguous conclusions about the optimality of choices. We …nd a negative relationship between the demanding nature of the choice problems and the likelihood that subjects select the optimal lines. We also …nd a positive relationship between the demanding nature of the choice problems and the response times. However, we …nd evidence that suboptimal choices are associated with longer response times than are optimal choices. This result appears to be consistent with Fudenberg, Strack, and Strzalecki (2018). Additionally, our experimental design permits a multinomial discrete choice analysis. Our results suggest that the errors in our data are better described as having a Gumbel distribution rather than a normal distribution. We also observe e¤ects consistent with memory decay and attention. Finally, we …nd evidence that choices in our experiment exhibit the independence from irrelevant alternatives (IIA) property.

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Section: Related Literature 21 Random Utility and Random Choicementioning

confidence: 99%

An Economist and a Psychologist Form a Line: What Can Imperfect Perception of Length Tell Us About Stochastic Choice?

Duffy¹,

Smith

2020

SSRN Journal

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“…For other explanations of stochastic choice, see Machina (1985), Manzini and Mariotti (2014), Cerreia-Vioglio et al (2019), andAllen et al (2021).…”

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Correlated Choice

Chambers¹,

Masatlıoĝlu²,

Turansick³

2021

Preprint

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As a means for testing for the presence of influence across individuals, we discuss the concept of a stochastic choice function for a group of agents which allows observation of correlation structure (correlated choice rule). We ask when choice behavior is consistent with an underlying unobserved (latent) variable or signal which jointly governs preferences: this hypothesis represents absence of influence. Key is the property of marginality, which demands the independence of any given agents' budgetary choices from the budgets faced by the remaining agents. Marginality permits the construction of well-defined marginal stochastic choice functions. Marginality and non-negativity of an analogue of the Block-Marshack polynomials are equivalent to joint stochastic rationality for small environments. For larger environments, we offer an example of a correlated choice function establishing that each of the marginal stochastic choice functions may be stochastically rational while the correlated choice function is not. Thus, the detection of influence can be aided by studying correlated choice data.

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“… Recent work includes Cerreia‐Vioglio, Dillenberger, Ortoleva, and Riella (forthcoming) and Agranov and Ortoleva (). …”

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Identification With Additively Separable Heterogeneity

Allen¹,

Rehbeck

2019

ECTA

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This paper provides nonparametric identification results for a class of latent utility models with additively separable unobservable heterogeneity. These results apply to existing models of discrete choice, bundles, decisions under uncertainty, and matching. Under an independence assumption, such models admit a representative agent. As a result, we can identify how regressors alter the desirability of goods using only average demands. Moreover, average indirect utility (“welfare”) is identified without needing to specify or identify the distribution of unobservable heterogeneity.

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Deliberately Stochastic

Cited by 58 publications

References 74 publications

An Economist and a Psychologist Form a Line: What Can Imperfect Perception of Length Tell Us About Stochastic Choice?

An Economist and a Psychologist Form a Line: What Can Imperfect Perception of Length Tell Us About Stochastic Choice?

Correlated Choice

Identification With Additively Separable Heterogeneity

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