Scenario-based satisficing in saving: a theoretical and experimental analysis

Contrary to the models of deterministic life cycle saving, we take it for granted that uncertainty of one's future is the essential problem of saving decisions. However, unlike the stochastic life cycle models, we capture this crucial uncertainty by a non-Bayesian scenario-based satisficing approach. Decision makers first form aspirations for a few relevant scenarios, and then search for saving plans satisficing these aspirations. In addition to formally specifying scenario-based satisficing in saving, we explore it experimentally. The results confirm that optimal intertemporal allocations are diffcult to derive, and suggest that satisficing allocations can be reached easily when aspirations are incentivized.