Decisions to trust in strategic situations involve ambiguity (unknown probabilities). Despite many theoretical studies on ambiguity in game theory, empirical studies have lagged behind due to a lack of measurement methods, where separating ambiguity attitudes from beliefs is crucial. Baillon et al. (Econometrica, 2018b) introduced a method that allows for such a separation for individual choice. We extend this method to strategic situations and apply it to the trust game, providing new insights. People’s ambiguity attitudes and beliefs both matter for their trust decisions. People who are more ambiguity averse decide to trust less, and people with more optimistic beliefs about others’ trustworthiness decide to trust more. However, people who are more a-insensitive (insufficient discrimination between different likelihood levels) are less likely to act upon their beliefs. Our measurement of beliefs, free from contamination by ambiguity attitudes, shows that traditional introspective trust survey measures capture trust in the commonly accepted sense of belief in trustworthiness of others. Further, trustworthy people also decide to trust more due to their beliefs that others are similar to themselves. This paper shows that applications of ambiguity theories to game theory can bring useful new empirical insights.

Other-regarding preferences or decision errors are the main explanations put forward to justify contributions exceeding the non-cooperative optimum in VCM games. An alternative rationale relies on ambiguity aversion. Ambiguity aversion increases the perceived marginal benefit of own contributions, which in equilibrium will exceed the Nash level. We present a series of experiments testing this hypothesis. To control for other-regarding preferences, we run a two-player game in which a human player plays with a virtual agent. Players are assigned either to a risky setting (known probabilities of opponent's choices) or to an ambiguity setting (probabilities of opponent's contribution are vague). Results show that ambiguity affects contributions. However, attitude to ambiguity appears to be affected by the location of the aggregate Nash optimum inside the decision space.

Empirical studies of ambiguity aversion mostly use artificial events such as Ellsberg urns to control for unknown probability beliefs. The present study measures ambiguity attitudes using real-world events in a large sample of investors. We elicit ambiguity aversion and perceived ambiguity for a familiar company stock, a local stock index, a foreign stock index, and Bitcoin. Measurement reliability is higher than for artificial sources in previous studies. Ambiguity aversion is highly correlated for different assets, while perceived ambiguity varies more between assets. Further, we show that ambiguity attitudes are related to actual investment choices.

In an experiment with more than 500 participants we study how past experience of uncertainty (imperfect knowledge of the state space) affects risk preferences. Participants in our experiment choose between a sure outcome and a lottery in 32 periods. All treatments are exactly identical in periods 17–32 but differ in periods 1–16. In the early periods of the risk treatment there is perfect information about the lottery; in the ambiguity Treatment participants perfectly know the outcome space but not the associated probabilities; in the unawareness treatment participants have imperfect knowledge about both outcomes and probabilities. We observe strong treatment effects on behavior in periods 17–32. In particular, participants who have been exposed to an environment with very imperfect knowledge of the state space subsequently choose lotteries with high (low) variance less (more) often compared to other participants. Estimating individual risk attitudes from choices in periods 17–32 we find that the distribution of risk attitude parameters across our treatments can be ranked in terms of first order stochastic dominance. Our results show how exposure to environments with different degrees of uncertainty can affect individuals’ subsequent risk-taking behavior.

Healthcare technologies are often appraised under considerable ambiguity over the size of incremental benefits and costs, and thus how decision-makers combine unclear information to make recommendations is of considerable public interest. This paper provides a conceptual foundation for such decision-making under ambiguity, formalizing and differentiating the decision problems of a representative policy-maker reviewing the results from an economic evaluation. A primary result is that presenting information to regulators in an incremental cost-effectiveness ratio or cost-effectiveness analysis (CEA) format instead of a net monetary benefit or cost–benefit analysis (CBA) framework may induce errors in decision-making when there exists ambiguity in incremental benefits and decision-makers use well-known decision rules to combine information. Ambiguity in incremental costs or the value of the cost-effectiveness threshold does not distort decision-making under these rules. In reasonable contexts, I show that the CEA framing may result in the approval of fewer technologies relative to CBA framing. I interpret these results as predictions on how the presentation of information from economic evaluations to regulators may frame and distort recommendations. All the results extend to non-healthcare contexts.

This paper investigates the increasing, but complex, support for reparations among Democratic elected officials—highlighting their tendency to endorse the concept while deferring discussion of policy details. This strategic ambiguity is common in policy discourse and can be embedded within policy design, such as legislative proposals to create commissions tasked with studying and recommending future actions on reparations. The effectiveness of these reparations commissions is uncertain. They could represent productive steps toward genuine reparations or simply serve to alleviate political pressure without any substantial policy changes. We explore these potential outcomes in three inter-related analyses: a compilation and comparison of all bills mentioning slavery reparations introduced at the federal and state level, the first nationally representative public opinion poll asking about support for reparations commissions, and a content analysis of legislative bill texts establishing reparations commissions. Our findings suggest that while reparations commissions offer an effective way for Democratic policymakers to manage conflicting constituency pressures in the short term, their potential to propel forward, rather than stall, the reparations debate hinges on their design and execution.

This work presents a reflection on the meaning and significance of knowledge coproduction in the field of glaciology. We start by invoking the paradigm of Structure–Form–Environment Interplay (SFEI) to formulate a generalised definition of glaciology, which highlights the relevance of knowledge coproduction. The adoption of a relational view of glaciological knowledge leads us to identify five core dimensions of knowledge coproduction: purpose, ethics, ambiguity, inclusion/exclusion, and relationships. Based on those dimensions, we delve into the decisive methodological aspects of the coproduction process, namely the definition of its purpose, the identification of participants, the organisation of the process, the recognition of ambiguity in Ways of Knowing (WoKs), and the consideration of ethical implications. In addition to the already known three stages of knowledge coproduction process (codesign, codevelopment, and codelivery), we propose the inclusion of an additional preparation stage, which entails the acknowledgment of the identity and involvement of all human and nonhuman participants, their positionality, and means to ensure their cultural and ontological safety. We reason that knowledge coproduction does not replace the scientific method, but rather complements it, eliciting the possibility to unveil deeper insights that might be difficult to attain through unilateral means.

Insurers draw on sophisticated models for the probability distributions over losses associated with catastrophic events that are required to price insurance policies. But prevailing pricing methods don’t factor in the ambiguity around model-based projections that derive from the relative paucity of data about extreme events. I argue however that most current theories of decision making under ambiguity only partially support a solution to the challenge that insurance decision makers face and propose an alternative approach that allows for decision making that is responsive to both the evidential situation of the insurance decision maker and their attitude to ambiguity.

Markus nimmt seine Gegenwart als dunkle, düstere Zeit wahr und bearbeitet mit seiner Jesuserzählung die krisenbehaftete Gegenwart. Ein zentraler Baustein in seinem Krisenmanagement ist ein strategischer Einsatz literarisch-theologischer Mehrdeutigkeiten. Die vorliegenden Beobachtungen illustrieren diesen strategischen Einsatz am Beispiel der programmatischen Basileiaaussage in Mk 1,15. Unsere Kernthese lautet: Markus bändigt die Ambiguität der ἤγγικɛν-Aussage in 1,15 durch die ἤγγικɛν-Aussage in 14,42 und beansprucht damit Deutungshoheit inmitten einer existentiellen krisenhaften Zuspitzung in der erzählten Welt. Dieser Gewinn an Deutungshoheit marginalisiert weder die Krisenerfahrung am Vorabend des Todes Jesu noch die Krisenerfahrung in den 70er Jahren, sondern dient dazu, ein wenig festen Boden in all der verbleibenden Unklarheit und Ungewissheit unter die Füße zu bekommen.