Despite the increasing relevance of multiple prior beliefs in various domains of economics and beyond and the significant theoretical work on them, little progress has been made on developing choice-based techniques for eliciting them. This paper proposes a new choice-based, incentive-compatible elicitation method for multiple prior beliefs, and implements it in two experiments on continuous sources of uncertainty to elicit the multiple prior equivalent of subjects’ CDFs. The method is theoretically robust, insofar as it applies under a wide range of multiple prior decision models and with few assumptions about the nature of beliefs. In its implementation, we find a significant majority of subjects have non-degenerate sets of priors, with larger sets for more unpredictable events. Finally, we use our method to provide the first elicitation of the mixture parameter in the Hurwicz alpha-maxmin EU model that fully controls for beliefs.

Scientific models structure our perception of reality. This paper studies how we choose among them under expert advice. Scientific models are formalised as probability distributions over possible scenarios. An expert is assumed to know the most likely model and seeks to communicate it to a decision maker, but cannot prove it. As a result, communication about models is a cheap talk game. The decision maker is in a situation of model-uncertainty and is ambiguity sensitive. I show that information transmission depends on the strategic misalignment of players and, unlike similar models in the literature, a form of consensus among scientific models. When science is divided, there is an asymmetry in information transmission when the receiver has maxmin expected utility preferences. No information can be conveyed about models above a certain threshold. All equilibria of the game are outcome equivalent to a partitional equilibrium and the most informative one is interim Pareto dominant. 

Despite years of scientific reporting regarding climate change, public acceptance of economic regulations is still limited. Why scientific forecasts regarding climate change fail to trigger public willingness for the appropriate mitigation is still a highly debated question. This paper surveys the economic literature on environmental information transmission in search of an explanatory mechanism for this paradox. Combining empirical results with existing theoretical mechanisms, I argue that failure in information transmission naturally arises from the strategic setting in which scientific authorities and citizens find themselves in.

This paper studies communication failure regarding risks in the commons. It argues that strategic issues might explain why years of scientific reporting regarding future risks have failed to trigger sufficient climate awareness. We consider a game of contribution to a public bad, where there is uncertainty regarding the damage generated by externalities. Prior to the game, agents receive non-certifiable information regarding the damage from an informed utilitarian expert. We show that in large-scale public good problems information transmission usually fails. We compare this result with the cases of Rawlsian and anti-Rawlsian experts and discuss the implication for climate expert panels. We also investigate the influence of the value of information in our result, which provides us with some insight on the part played by deontology on scientific communication.

This paper examines whether teachers’ gender biases stem from discrimination, and focuses on two of its potential drivers: gender preferences and beliefs. In an online experiment, 1,840 teachers evaluated fictitious transcripts with randomized gender information. Preferences were measured via dictator games, and beliefs through an Implicit Association Test. While teachers showed no gender preferences, they did hold gender beliefs. Analyzing 19,000 transcript evaluations, we find no evidence of gender-based discrimination. Our findings suggest that simply disclosing a student's gender does not trigger biased evaluations, implying that discrimination is more likely to emerge during direct student-teacher interactions.

Can a hearer be rationally justified to have beliefs based on testimony alone when the source of his information is known to have conflicting epistemic goals? Building on a game-theoretical approach I suggest that, contrary to the existing views, he can. But this justification relies on an equilibrium concept, which is only reached on the long run. In addition, the hearer's justified beliefs will always be more imprecise than the one held by the original source. These results highlight the importance of scientific norms which, in practice, are the embodiment of these equilibrium mechanisms and thus of scientific credibility. 

Many epistemologists have argued against the credal view according to which the traditional doxastic attitudes---belief, disbelief, and suspension---can be represented entirely through credences, or quantified degrees of belief. Approaching the problem from the angle of suspension of judgement, this paper proposes a credal view that can overcome most arguments that have been raised against credalism. This view is built upon four principles: (I) Suspension is a state of inquiry that, in the credal world, leads to consider multiple probabilistic models of the world, or imprecise credence, (II) Suspension is a commitment to the pursuit of an inquiry in the face of an insufficient amount of evidence in favour of belief or disbelief, (III) Bayesianism is the rational attitude towards probabilistic models and (IV) Disagreement across probabilistic models favours suspension of judgement.  While more complex than the theories currently present in the debate, my proposal boils down to a type of traditional Lockean threshold view on beliefs, where information dynamics conform to intuition. 

According to pragmatic encroachment (PE), a subject’s practical stakes partly determines whether the subject is in a position to know, or is justified in believing p. It is typically assumed that it is mainly what is at stake for the subject that is relevant. We take the notion of PE to the social world and argue that, in many important cases, what is at stake for an individual contrasts so drastically with what is at stake at a group level, that believing p may not be justified for a subject, yet justified on a collective level (and vice-versa). Determining what is justified belief through PE thus imposes, on the one hand, to determine what collective stakes and evidence should be, and, on the other hand, what individual evidence and stakes should be for a group member. This task is inherently a moral one. One could see this result as a drawback for PE. We argue the opposite: belief justification in the real world cannot and should not be isolated from moral considerations. It is PE, and its extension to moral encroachment’s merit to successfully do so.

We elaborate a new solution to the problem of competing epistemic norms and specifically to the competition between the Zetetic and Evidentilist norms. We build on a game-theoretical modelling of norm competition to argue that one should not choose between both norms but always try to pursue a middle ground, where cognitive abilities are shared between their respective requirements. 

This paper claims that some of the scientific methods commonly employed by the social tipping point literature are epistemically appropriate on a much more restricted domain of application than the one currently targeted by the literature. This is because these methods are prone to overfitting and neglect too much of the scientific uncertainty present in the social science literature. In addition, we  argue that the role of values in the social tipping point literature is underestimated and needs to be approached with more caution.

This paper discusses the scope of statistical analysis when it comes to beliefs on human behaviour. We show that, because in a social setting individual epistemic rationality does not necessarily lead to unravelling true causal structures, choices on causality have to be made on non-epistemic grounds. Often, these choices are moral decisions on causal models; they are part of the epistemic foundation of statistically-based beliefs. We provide arguments to support why choosing causal models on moral grounds first is not only morally granted but also epistemically justified. We show how they speak in favour of policies such as positive discrimination or for individual judgements based on control-responsive features.  

In secondary education, marking holds a pivotal role in shaping students’ academic trajectories and, ultimately, their labor prospects. Grades serve as a compass guiding students, parents, educators, and institutions in navigating the path toward educational success. Crucially, the fairness and reliability of this process depends on the accuracy of the grades themselves. This study aims at accurately estimate the amount of noise in secondary education professional ratings of students’ profile. We als identify some raters’ characteristics that might affect the level of variations in the evaluations. Finally we propose a simple set of rules to help select two raters for each candidate, in a way that minimize the amount of noise in the ratings.

We consider a two tiered wholesale electricity market made of a day-ahead and a real-time market. In the retail market, consumers can subscribe a contract with a conventional retailer or cooperate through an aggregator who directly participates in the wholesale electricity market by taking forward positions. These latter depend on the consumer aggregated demand as estimated in the day ahead. Consumers are then penalized in real time on the basis of their prediction errors. To plan the aggregator’s pricing strategy, we model the consumers in a behavioral economics framework and take into account their possibility to churn. We characterize analytically the core of the game and give conditions for its non emptiness. Then we propose an algorithm based on Machine Learning methods (SVR, Neural Network, Regret) to optimize the aggregator’s pricing strategy in a competitive framework. Our results are finally evaluated on a case study based on time series of the power consumptions of 370 Portuguese consumers.