Optimal Fine Reductions for Self-Reporting: The Impact of Loss Aversion

Abstract

Fine reductions for self-reported offenses entail a potential tradeoff. On the one hand, inducing offenders to self-report allows the social planner to save on enforcement costs and reduce harm through early detection. On the other hand, fine reductions may also reduce deterrence: offenders anticipate that if their probability of apprehension turns out to be higher than initially expected, they can exploit the possibility of a more lenient sanction. We analyze how this trade-off is affected by the offender's utility function, contrasting neoclassical standard preferences with loss aversion. For loss aversion, we apply the approach by Kőszegi and Rabin (2006), in which reference points are determined by the ex ante expectations of equilibrium strategies. Assuming that the private benefit from crime is lost in case of detection, we distinguish between loss aversion in the fine dimension and in the benefit dimension. Intuitively, one might assume that loss aversion facilitates law enforcement because losses loom larger than gains, which sets incentives to refrain from crime. This intuition, however, carries over to our model with self-reporting only if loss aversion in the fine dimension is sufficiently large compared to loss aversion in the benefit dimension.