We report the results of an experiment on how individual risk taking clusters together when subjects are informed of peers' previous risk taking decisions. Subjects are asked how much of their endowment they wish to allocate in a lottery in which there is a 50% chance the amount they invest will be tripled and a 50% chance their investment will be lost. We use a 2 × 2 factorial design varying: (i) whether the subjects initially observed high or low investment social anchors, (ii) whether information about the investment decisions of other subjects in their social group is provided. We find strong evidence that individuals' risk taking decisions are malleable to that of their peers, which in turn leads to social clustering of risk taking. Social anchors shape initial risk taking, with mean investment then converging to a high level across treatments.

In this paper, we use the risk apportionment technique of Eeckhoudt, Rey and Schlesinger (2007) to study higher order risk preferences for others' health as well as ex-ante and ex-post inequality preferences for social risky distributions, and their interaction. In an experiment on a sample of university students acting as impartial spectators, we observe risk aversion towards social health losses and a dislike of ex-ante inequality. In addition, evidence for ex-post inequality seeking is much weaker than evidence for ex-ante inequality aversion. Because ex-ante inequality aversion is unrelated to risk aversion, we conclude that simple forms of utilitarianism are not relevant for individual judgment of social risk over health. Last, our investigation of precautionary distribution, which would occur when one particular group in the society suffers from background health risk, shows substantial polarization of preferences.

In some situations, a decision is best represented by an incompletely analyzed act: conditionally on a given event , the consequences of the decision on sub-events are perfectly known and uncertainty becomes probabilizable, whereas the plausibility of this event itself remains vague and the decision outcome on the complementary event is imprecisely known. In this framework, we study an axiomatic decision model and prove a representation theorem. Resulting decision criteria aggregate partial evaluations consisting of (i) the conditional expected utility associated with the analyzed part of the decision, and (ii) the best and worst consequences of its non-analyzed part. The representation theorem is consistent with a wide variety of decision criteria, which allows for expressing various degrees of knowledge on () and various types of attitude toward ambiguity and uncertainty. This diversity is taken into account by specific models already existing in the literature. We exploit this fact and propose some particular forms of our model incorporating these models as sub-models and moreover expressing various types of beliefs concerning the relative plausibility of the analyzed and the non-analyzed events ranging from probabilities to complete ignorance that include capacities.

We propose a triple test to evaluate the usefulness of behavioral economics models for public health policy. Test 1 is whether the model provides reasonably new insights. Test 2 is on whether these have been properly applied to policy settings. Test 3 is whether they are corroborated by evidence. We exemplify by considering the cases of social interactions models, self-control models and, in relation to health message framing, prospect theory. Out of these sets of models, only a correctly applied prospect theory fully passes the tests at present. Specifically, in broad agreement with the evidence, a gain frame has positive implications for welfare encourages disease prevention activity, though this does not apply if the perceived probability of the bad health outcome is large enough. We see our tests as being useful to identify how much health policy weight policy makers should assign to specific behavioral economic models; they are also useful to verify what next steps would be most useful in further research.

The standard expected utility (EUT) model of tax evasion predicts that evasion is decreasing in the marginal tax rate (the Yitzhaki puzzle). Recent literature shows cases in which incorporating prospect theory (PT) does and does not overturn the Puzzle. In a general environment that nests both PT and EUT preferences, we provide a detailed study of how the elements of PT affect the Puzzle. PT does not always reverse the Puzzle, hence we give and interpret conditions for when it does and does not. When allowing for stigma and/or variable audit probability, PT reverses the Puzzle in the same way and with the same limitations as does EUT, if equally augmented.

We report an experiment where each subject's ambiguity sensitivity is measured by an ambiguity premium, a concept analogous to and comparable with a risk premium. In our design, some tasks feature known objective risks and others uncertainty about which subjects have imperfect, heterogeneous, information ("ambiguous tasks"). We show how the smooth ambiguity model can be used to calculate ambiguity premia. A distinctive feature of our approach is estimation of each subject's subjective beliefs about the uncertainty in ambiguous tasks. We find considerable heterogeneity among subjects in beliefs and ambiguity premia; and that, on average, ambiguity sensitivity is about as strong as risk sensitivity.

Research suggests that to restore equity, third parties prefer compensation of a victim over the punishment of a perpetrator. It remains unclear, however, whether this preference for compensation is stable or specific to certain situations. In six experimental studies, we find that adjustments in the characteristics of the situation or in the available behavioral options hardly modify the preference of compensation over punishment. This preference for compensation was found even in cases where punishment might refrain a perpetrator from acting unfairly again in the future, and even when punishment has a greater impact in restoring equity than compensation does. Thus, the preference of compensation over punishment appears to be quite robust. Implications and ideas for future research are discussed.

According to the 'Description-Experience gap' (DE gap), when people are provided with the descriptions of risky prospects they make choices as if they overweight the probability of rare events; but when making decisions from experience after exploring the prospects' properties, they behave as if they underweight such probability. This study revisits this discrepancy while focusing on information-search in decisions from experience. We report findings from a lab-experiment with three treatments: a standard version of decisions from description and two versions of decisions from experience: with and without a 'history table' recording previously sampled events. We find that people sample more from lotteries with rarer events. The history table proved influential; in its absence search is more responsive to cues such as a lottery's variance while in its presence the cue that stands out is the table's maximum capacity. Our analysis of risky choices captures a significant DE gap which is mitigated by the presence of the history table. We elicit probability weighting functions at the individual level and report that subjects overweight rare events in experience but less so than in description. Finally, we report a measure that allows us to compare the type of DE gap found in studies using choice patterns with that inferred through valuation and find that the phenomenon is similar but not identical across the two methods.

Friendship is commonly assumed to reduce strategic uncertainty and enhance tacit coordination. However, this assumption has never been tested across two opposite poles of coordination involving either strategic complementarity or substitutability. We had participants interact with friends or strangers in two classic coordination games: the stag-hunt game, which exhibits strategic complementarity and may foster "cooperation", and the entry game, which exhibits strategic substitutability and may foster "competition". Both games capture a frequent trade-off between a potentially high paying but uncertain option and a low paying but safe alternative. We find that, relative to strangers, friends are more likely to choose options involving uncertainty in stag-hunt games, but the opposite is true in entry games. Furthermore, in stag-hunt games, friends "tremble" less between options, coordinate better and earn more, but these advantages are largely decreased or lost in entry games. We further investigate how these effects are modulated by risk attitudes, friendship qualities, and interpersonal similarities.

Distributional justice-measured by the proportionality between effort exerted and rewards obtained-and guilt aversion-triggered by not fulfilling others' expectations-are widely acknowledged fundamental sources of pro-social behavior. We design three experiments to study the relevance of these sources of behavior when considered in interaction. In particular, we investigate whether subjects fulfill others' expectations also when this could produce inequitable allocations that conflict with distributional justice considerations. Our results confirm that both justice considerations and guilt aversion are important drivers of pro-social behavior, with the former having an overall stronger impact than the latter. Expectations of others are less relevant in environments more likely to nurture equitable outcomes.

The note puts forward the idea of , a novel instrument, which like revealed preference is observable from choice and important for individual and social welfare. We provide the axiomatic underlying individual's choice model, preliminary experimental results that support the idea, and an appealing allocation rule that uses the revealed desirability information along with the revealed-preference information.

I reconsider Bleichrodt, Pinto Prades and Wakker's (BPW) 2001 paper about eliciting utility measures from stated preference surveys. That paper pioneers a method that is now widely used in behavioural economics to correct individuals' 'biases' and to recover their 'true preferences'. However, BPW propose this method as way of dealing with inconsistent responses to stated preference surveys, in contrast to more recent applications which aim to help individuals to avoid supposed mistakes in their private choices. I argue that the concepts of true preference and bias are empirically ungrounded, but that BPW's approach can be interpreted as not invoking those concepts. By 'regularising' preferences revealed in actual choice, this approach constructs measures of individual welfare that are broadly aligned with actual preferences and consistent with normative standards of rationality that are appropriate for public decision-making. Public decision-makers' normative judgements are made explicit, rather than being disguised as apparently empirical claims about true preferences.

This paper provides a general framework for analyzing self-confirming policies. We study self-confirming equilibria in recurrent decision problems with incomplete information about the true stochastic model. We characterize stationary monetary policies in a linear-quadratic setting.

We introduce a new class of real-valued monotones in preordered spaces, injective monotones. We show that the class of preorders for which they exist lies in between the class of preorders with strict monotones and preorders with countable multi-utilities, improving upon the known classification of preordered spaces through real-valued monotones. We extend several well-known results for strict monotones (Richter-Peleg functions) to injective monotones, we provide a construction of injective monotones from countable multi-utilities, and relate injective monotones to classic results concerning Debreu denseness and order separability. Along the way, we connect our results to Shannon entropy and the uncertainty preorder, obtaining new insights into how they are related. In particular, we show how injective monotones can be used to generalize some appealing properties of Jaynes' maximum entropy principle, which is considered a basis for statistical inference and serves as a justification for many regularization techniques that appear throughout machine learning and decision theory.

While the paradigm of utility maximisation has formed the basis of the majority of applications in discrete choice modelling for over 40 years, its core assumptions have been questioned by work in both behavioural economics and mathematical psychology as well as more recently by developments in the RUM-oriented choice modelling community. This paper reviews the basic properties with a view to explaining the historical pre-eminence of utility maximisation and addresses the question of what departures from the paradigm may be necessary or wise in order to accommodate richer behavioural patterns. We find that many, though not all, of the behavioural traits discussed in the literature can be approximated sufficiently closely by a random utility framework, allowing analysts to retain the many advantages that such an approach possesses.

We consider a group of receivers who share a common prior on a finite state space and who observe private correlated messages that are contingent on the true state of the world. Our focus lies on the beliefs of receivers induced via the signal chosen by the sender and we provide a comprehensive analysis of the inducible distributions of posterior beliefs. Classifying signals as minimal, individually minimal, and language-independent, we show that any inducible distribution can be induced by a language-independent signal. We investigate the role of the different classes of signals for the amount of higher order information that is revealed to receivers. The least informative signals that induce a fixed distribution over posterior belief profiles lie in the relative interior of the set of all language-independent signals inducing that distribution.