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We characterize those ex-ante restrictions on the random utility model which lead to identification. We first identify a simple class of perturbations which transfer mass from a suitable pair of preferences to the pair formed by swapping certain comp
Externí odkaz:
http://arxiv.org/abs/2408.06547
This paper uncovers tight bounds on the number of preferences permissible in identified random utility models. We show that as the number of alternatives in a discrete choice model becomes large, the fraction of preferences admissible in an identifie
Externí odkaz:
http://arxiv.org/abs/2403.13773
Autor:
Turansick, Christopher
We readdress the problem of nonparametric statistical testing of random utility models proposed in Kitamura and Stoye (2018). Although their test is elegant, it is subject to computational constraints which leaves execution of the test infeasible in
Externí odkaz:
http://arxiv.org/abs/2303.14249
Autor:
Turansick, Christopher
We study consumption dependence in the context of random utility and repeated choice. We show that, in the presence of consumption dependence, the random utility model is a misspecified model of repeated rational choice. This misspecification leads t
Externí odkaz:
http://arxiv.org/abs/2302.05806
We study random joint choice rules, allowing for interdependence of choice across agents. These capture random choice by multiple agents, or a single agent across goods or time periods. Our interest is in separable choice rules, where each agent can
Externí odkaz:
http://arxiv.org/abs/2103.05084
Autor:
Turansick, Christopher
The random utility model is known to be unidentified, but there are times when the model admits a unique representation. We offer two characterizations for the existence of a unique random utility representation. Our first characterization puts condi
Externí odkaz:
http://arxiv.org/abs/2102.05570
Akademický článek
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Publikováno v:
The RAND Journal of Economics, 2020 Oct 01. 51(3), 868-904.
Externí odkaz:
https://www.jstor.org/stable/45380727
Autor:
Turansick, Christopher
In recent years there has been an influx of papers which use graph theoretic tools to study stochastic choice. Fiorini (2004) serves as a base for this literature by providing a graphical representation of choice probabilities and showing that every
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::501a033e28f005a53dab2b1c9bb39001