If payoffs are tickets for binary lotteries, which involve only two money prizes, then rationality requires expected value maximization in tickets. This payoff scheme was increasingly used to induce risk neutrality in experiments. The experiment presented here involved lottery choice and evaluation tasks. One subject group was paid in binary lottery tickets, another directly in money. Significantly greater deviations from risk neutral behavior are observed with binary lottery payoffs. This discrepancy increases when subjects have easy access to the alternatives' expected (...) values and mean absolute deviations. Behavioral regularities are observed at least as often as with direct money payoffs. (shrink)

Simon introduced satisficing, but he did not provide a precise definition or analysis. Other researchers have subsequently interpreted satisficing in various ways, but a consensus perspective still has not emerged. This paper interprets satisficing as a class of decision strategies that a person might use when seeking to optimize in a setting where deliberation is costly. Costly deliberation lies at the heart of Simon’s motivation of satisficing, but he did not formalize the idea. I do so here, studying decision making (...) as a problem of minimax-regret planning in which costly deliberation enables a person to reduce ambiguity. I report simple specific findings on how the magnitude of deliberation costs may affect choice of a decision strategy. (shrink)

This paper is about satisficing behaviour. Rather tautologically, this is when decision-makers are satisfied with achieving some objective, rather than in obtaining the best outcome. The term was coined by Simon, and has stimulated many discussions and theories. Prominent amongst these theories are models of incomplete preferences, models of behaviour under ambiguity, theories of rational inattention, and search theories. Most of these, however, seem to lack an answer to at least one of two key questions: when should the decision-maker satisfice; (...) and how should the DM satisfice. In a sense, search models answer the latter question, but not the former; moreover, usually the question as to whether any search at all is justified is left to a footnote. A recent paper by Manski fills the gaps in the literature and answers the questions: when and how to satisfice? He achieves this by setting the decision problem in an ambiguous situation and by using the Minimax Regret criterion as the preference functional. The results are simple and intuitive. This paper reports on an experimental test of his theory. The results show that some of his propositions appear to be empirically valid while others are less so. (shrink)

We implement a risky choice experiment based on one-dimensional choice variables and risk neutrality induced via binary lottery incentives. Each participant confronts many parameter constellations with varying optimal payoffs. We assess optimality, as well as optimal satisficing by eliciting aspirations in addition to choices. Treatments differ in the probability that a binary random event, which are payoff—but not optimal choice—relevant is experimentally induced and whether participants choose portfolios directly or via satisficing, i.e., by forming aspirations and checking for satisficing before (...) making their choice. By incentivizing aspiration formation, we can test satisficing, and in cases of satisficing, determine whether it is optimal. (shrink)