Working papers results
Experimental evidence suggests that agents in social dilemmas have belief-dependent, otherregarding preferences. But in experimental games such preferences cannot be common knowledge, because subjects play with anonymous co-players. We address this issue theoretically and experimentally in the context of a trust game, assuming that the trustee's choice may be affected by a combination of guilt aversion and intention-based reciprocity. We recover trustees' belief-dependent preferences from their answers to a structured questionnaire. In the main treatment, the answers are disclosed and made common knowledge within each matched pair, while in the control treatment there is no disclosure. Our main auxiliary assumption is that such disclosure approximately implements a psychological game with complete information. To organize the data, we classify subjects according to their elicited preferences, and test predictions for the two treatments using both rationalizability and equilibrium. We find that guilt aversion is the prevalent psychological motivation, and that behavior and elicited beliefs move in the direction predicted by the theory.
This is particularly true for the investment cost friction and habit persistence: when low
frequencies are present in the estimation, the investment cost friction and habit persistence are estimated to be higher than when low frequencies are absent.
We study a Mean-Risk model derived from a behavioral theory of Disappointment with multiple reference points. One distinguishing feature of the risk measure is that it is based on mutual deviations of outcomes, not deviations from a specific target. We prove necessary and sufficient conditions for strict first and second order stochastic dominance, and show that the model is, in addition, a Convex Risk Measure. The model allows for richer, and behaviorally more plausible, risk preference patterns than competing models with equal degrees of freedom, including Expected Utility (EU), Mean-Variance (MV), Mean-Gini (MG), and models based on non-additive probability weighting, such a Dual Theory (DT). For example, in asset allocation, the decision-maker can abstain from diversifying in a risky asset unless it meets a threshold performance, and gradually invest beyond this threshold, which appears more acceptable than the extreme solutions provided by either EU and MV (always diversify) or DT and MG (always plunge). In asset trading, the model allows no-trade intervals, like DT and MG, in some, but not all, situations. An illustrative application to portfolio selection is presented. The model can provide an improved criterion for Mean-Risk analysis by injecting a new level of behavioral realism and flexibility, while maintaining key normative properties.