English
Related papers

Related papers: Revealed Incomplete Preferences

200 papers

We design and implement lab experiments to evaluate the normative appeal of behavior arising from models of ambiguity-averse preferences. We report two main empirical findings. First, we demonstrate that behavior reflects an incomplete…

Theoretical Economics · Economics 2024-07-26 Christoph Kuzmics , Brian W. Rogers , Xiannong Zhang

If uncertainty is modelled by a probability measure, decisions are typically made by choosing the option with the highest expected utility. If an imprecise probability model is used instead, this decision rule can be generalised in several…

Artificial Intelligence · Computer Science 2020-03-27 Jasper De Bock

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved,…

Computer Science and Game Theory · Computer Science 2024-08-21 Aviram Imber , Jonas Israel , Markus Brill , Benny Kimelfeld

Can stated preferences inform counterfactual analyses of actual choice? This research proposes a novel approach to researchers who have access to both stated choices in hypothetical scenarios and actual choices, matched or unmatched. The…

Econometrics · Economics 2025-11-18 Romuald Meango , Marc Henry , Ismael Mourifie

Preferences for mixing can reveal ambiguity perception and attitude on a single event. The validity of the approach is discussed for multiple preference classes including maxmin, maxmax, variational, and smooth second-order preferences. An…

Econometrics · Economics 2024-08-16 Patrick Schmidt

Over time, there have hen refinements in the way that probability distributions are used for representing beliefs. Models which rely on single probability distributions depict a complete ordering among the propositions of interest, yet…

Artificial Intelligence · Computer Science 2013-02-28 Paul Snow

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

We investigate the problem of approximating an incomplete preference relation $\succsim$ on a finite set by a complete preference relation. We aim to obtain this approximation in such a way that the choices on the basis of two preferences,…

Theoretical Economics · Economics 2023-11-14 Hiroki Nishimura , Efe A. Ok

We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying "true" preference. Our conditions are weak, and therefore valid in a wide range of economic environments.…

Theoretical Economics · Economics 2020-11-03 Christopher P. Chambers , Federico Echenique , Nicolas Lambert

We represent preferences that exhibit absolute or relative attitudes towards ambiguity without assuming convexity of preferences. Our analysis is motivated by the recent experimental evidence by Baillon and Placido (2019) indicating that…

Theoretical Economics · Economics 2024-07-02 Francesco Fabbri , Giulio Principi , Lorenzo Stanca

This paper studies lying in a novel context. Previous work has focused on situations in which people are either fully aware of the economic consequences of all available actions (e.g., die-under-cup paradigm), or they are uncertain, but…

Physics and Society · Physics 2019-08-05 Hélène Barcelo , Valerio Capraro

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport

This paper develops a framework to study the statistical power of revealed-preference tests. With randomly sampled budgets and mild smoothness of demand, statistical learning implies that any model consistent with the data must approximate…

Theoretical Economics · Economics 2026-02-12 Charles Gauthier , Raghav Malhotra , Agustin Troccoli Moretti

The consumers' willingness to pay plays an important role in economic theory and in setting policy. For a market, this function can often be estimated from observed behavior -- preferences are revealed. However, economists would like to…

General Economics · Economics 2021-08-02 Edoh Y. Amiran , Joni S. James Charles

Senders of messages prefer to communicate uncertainty verbally (e.g., something is likely to happen) rather than numerically (such as 75%), leaving receivers with imprecise information. While it is well established that receivers translate…

General Economics · Economics 2026-05-21 Robin Bodenberger , Kirsten Thommes

We consider a simple model of imprecise comparisons: there exists some $\delta>0$ such that when a subject is given two elements to compare, if the values of those elements (as perceived by the subject) differ by at least $\delta$, then the…

Data Structures and Algorithms · Computer Science 2015-01-14 Miklos Ajtai , Vitaly Feldman , Avinatan Hassidim , Jelani Nelson

We study elections where voters are faced with the challenge of expressing preferences over an extreme number of issues under consideration. This is largely motivated by emerging blockchain governance systems, which include voters with…

Computer Science and Game Theory · Computer Science 2024-05-15 Georgios Amanatidis , Aris Filos-Ratsikas , Philip Lazos , Evangelos Markakis , Georgios Papasotiropoulos

We extend Berge's Maximum Theorem to allow for incomplete preferences. We first provide a simple version of the Maximum Theorem for convex feasible sets and a fixed preference. Then, we show that if, in addition to the traditional…

Theoretical Economics · Economics 2021-11-17 Leandro Gorno , Alessandro Rivello

Can AI agents predict whether they will succeed at a task? We study agentic uncertainty by eliciting success probability estimates before, during, and after task execution. All results exhibit agentic overconfidence: some agents that…

Artificial Intelligence · Computer Science 2026-02-09 Jean Kaddour , Srijan Patel , Gbètondji Dovonon , Leo Richter , Pasquale Minervini , Matt J. Kusner

Uncertainty may be taken to characterize inferences, their conclusions, their premises or all three. Under some treatments of uncertainty, the inferences itself is never characterized by uncertainty. We explore both the significance of…

Artificial Intelligence · Computer Science 2013-02-18 Henry E. Kyburg