Abstract
We demonstrate the pitfalls when extrapolating behavioral findings across different contexts and decision environments. We study regret theory and the use of "regret lotteries" for motivating behavior change. Here, findings from one-shot settings have been used to promote regret as a tool to boost incentives in recurrent decisions across many settings. Using theory and lab experiments, we find weak evidence for regret as the superior one-shot incentive; critically, for repeated decisions the comparative static is entirely reversed. Moreover, all effects are extremely sensitive to details of regret implementation. Our results imply caution when designing incentive schemes that exploit regret.