It has long been recognized that there is considerable heterogeneity in individual risk taking behavior but little is known about the distribution of risk taking types. We present a parsimonious characterization of risk taking behavior by estimating a finite mixture regression model for three different experimental data sets, two Swiss and one Chinese, over a large number of real gains and losses. We find two distinct types of individuals: In all three data sets, the choices of roughly 80% of the subjects exhibit significant deviations from linear probability weighting, consistent with prospect theory. 20% of the subjects weight probabilities near linearly and behave essentially as expected value maximizers. Moreover, individuals are cleanly assigned to one type with probabilities close to unity. The reliability and robustness of our classification suggest using a mix of preference theories in applied economic modeling.

Human altruism shaped our evolutionary history and pervades social and political life. There are, however, enormous individual differences in altruism. Some people are almost completely selfish, while others display strong altruism, and the factors behind this heterogeneity are only poorly understood. We examine the neuroanatomical basis of these differences with voxel-based morphometry and show that gray matter (GM) volume in the right temporoparietal junction (TPJ) is strongly associated with both individuals' altruism and the individual-specific conditions under which this brain region is recruited during altruistic decision making. Thus, individual differences in GM volume in TPJ not only translate into individual differences in the general propensity to behave altruistically, but they also create a link between brain structure and brain function by indicating the conditions under which individuals are likely to recruit this region when they face a conflict between altruistic and selfish acts.

Social and cultural historians have long used legal records to shed light on those otherwise lost to the historical record: the poor, the disenfranchised, youths, and women. This special issue seeks to interrogate what analytical value an explicit engagement with the emerging field of the "History of Emotions" can bring to explorations of law and emotions. In this Introduction, I suggest that working with a more methodologically reflexive understanding of emotions, and how they can be analyzed in concrete historical situations, can deepen our understanding-and complicate chronologies of change-regarding the interrelationship between law and emotions. We need to understand emotions not just as inchoate feelings but as bodily practices that are culturally and historically situated. Moreover, in order to historicize emotions, we also need to historicize the psychological, physical, and material context in which a person experiences her emotions: that is, we need historically contingent notions of the self, body, and the material performance of corporeality. Sabine Gruebler killed her husband and his brother's son with an axe in the night between 26 and 27 March in 1774 in the Electorate of Saxony. She did this "out of love" because "we all have to die" in the end. 1 What followed in this lengthy trial was a heated discussion of Sabine Gruebler's state of mind: was she an unstable woman suffering from melancholy, or was she a coldblooded murderess? Gruebler justified her actions through her-admittedly idiosyncratic-notion of love. Her interrogators as well as expert witnesses called upon from the medical and legal faculties sought to establish whether her rational faculties were impaired and, thus, whether she deserved a mitigated sentence. Gruebler's state of mind, her gender and body, and her emotions were all investigated and assessed in deciding her fate. The presiding magistrates as well as the assembled witnesses presented a variety of emotional reactions-from shock to incredulousness, revulsion to pity. The twenty-firstcentury reader of the trial cannot help but also react emotionally to the events described; yet it is clear that the way that Gruebler's emotions and ultimately her actions were judged was inextricably intertwined with historically specific notions of these categories.

How does risk tolerance vary with stake size? This important question cannot be adequately answered if framing effects, nonlinear probability weighting, and heterogeneity of preference types are neglected. We show that the increase in relative risk aversion over gains cannot be captured by the curvature of the utility function. It is driven predominantly by a change in probability weighting of a majority group of individuals who exhibit more rational probability weighting at high stakes. Contrary to gains, no coherent change in relative risk aversion is observed for losses. These results not only challenge expected utility theory, but also prospect theory.

A large body of experimental research has demonstrated that, on average, people violate the axioms of expected utility theory as well as of discounted utility theory. In particular, aggregate behavior is best characterized by probability distortions and hyperbolic discounting. But is it the same people who are prone to these behaviors? Based on an experiment with salient monetary incentives we demonstrate that there is a strong and significant relationship between greater departures from linear probability weighting and the degree of decreasing discount rates at the level of individual behavior. We argue that this relationship can be rationalized by the uncertainty inherent in any future event, linking discounting behavior directly to risk preferences. Consequently, decreasing discount rates may be generated by people's proneness to probability distortions.

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. There is vast heterogeneity in the human willingness to weigh others' interests in decision making. This heterogeneity raises the question how one can parsimoniously model and characterize heterogeneity across several dimensions of social preferences while still being able to predict behavior over time and across situations. We tackle this task with an experiment and a structural model of preferences that allows us to simultaneously estimate outcome-based and reciprocity-based social preferences. We find that non-selfish preferences are the rule rather than the exception. Neither at the level of the representative agent nor when we allow for several preference types do purely selfish types emerge. Instead, three qualitatively different otherregarding types emerge endogenously, i.e., without pre-specifying assumptions about the characteristics of types. When ahead, all three types value others' payoffs significantly more than when behind. The first type, denoted strongly altruistic type, is characterized by a relatively large weight on others' payoffs and moderate levels of reciprocity. The second type is, moderately altruistic and also puts positive weight on others' payoff, yet at a considerable lower level, and displays no positive reciprocity while the third type is behindness averse, i.e., puts a large negative weight on others' payoffs when behind and behaves selfishly otherwise. We also find that there is an unambiguous and temporally stable assignment of individuals to these types. Moreover, the three-type model substantially improves the predictions of individuals' behavior across additional games while the information contained in subject-specific parameter estimates leads to no or only minor additional predictive power. This suggests that a parsimonious model with three types captures the bulk of the predictive power contained in the preference estimates. Terms of use: Documents inJEL-codes: C490, C910, D030.

The dominant behavior observed in social games such as the ultimatum game, the dictator game, and public good games violates the classical assumption in economics of purely selfish preferences. To account for this behavior, economists have proposed social preference models, which introduce nonselfish motives as additional arguments and parameters in the utility function. Like classical utility models, social preference models focus on behavior at the expense of describing underlying cognitive processes, contenting themselves with being "as-if" models. This approach unnecessarily limits the models' psychological realism and forgoes the empirical benefits of describing the processes that produce behavioral outcomes. As an alternative, the chapter proposes fast and frugal classification trees. Designed to describe deliberations and decisions in the mini-ultimatum game, the trees spell out the possible cognitive processes of four distinct types of