We repeatedly elicit beliefs about the returns to study effort, in a large university course. A behavioral model of quasi-hyperbolic discounting and malleable beliefs predicts that the dynamics of beliefs mirrors the importance of exerting self-control, such that believed returns increase as the exam approaches, and drop post-exam. Exploiting variation in exam timing to control for common information shocks, we find this prediction confirmed: average believed study returns increase by about 20% over the period before the exam, and drop by about the same amount afterwards. Additional analyses further support the hypothesized mechanism that beliefs serve as a means of self-control.

Optimism is deemed to be a pervasive tendency in belief formation with anticipatory utility as its leading explanation. We provide evidence on whether such anticipatory utility is myopic or also includes utility from future anticipation. In a between-subjects design, we expose participants to the same lottery, and we vary only the delay to uncertainty resolution whilst keeping the payoff delay constant. Thus, we isolate the role of anticipatory utility from that of discounting material payoffs. First, we find greater optimism for longer resolution delay. Second, elicited time preferences suggest that belief formation is not constrained by instrumental costs of biased decision making. Third, we also elicited resolution delay preferences and find that greater optimism comes with greater reluctance to change resolution delay. Indeed, these preferences exhibit a pronounced ‘endowment effect’ and for a given resolution endowment, have a tendency towards dynamic inconsistency. We conclude by discussing implications for theories of optimism.

Algorithms are becoming ubiquitous in decision-making, necessitating a thorough understanding of how decisions involving algorithms are perceived and made.  In this study, we focus on individuals' perceptions of responsibility and investigate whether delegating decisions to algorithms allows them to avoid punishment. Additionally, we explore whether the prospect of punishment constitutes a motive in the delegation decision. Using a controlled online experiment, we observe no difference in punishment patterns between delegated and non-delegated decisions. Moreover, introducing the prospect of punishment reduces the propensity to delegate.  Hence, the ability to use algorithms as a means to shift responsibility is limited, in turn slowing down algorithmic uptake.