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Joshua C. Teitelbaum and Kathryn Zeiler

The subfield of behavioral economics, while still quite young, has made important contributions to our understanding of human behavior. Through a cycle of theory development and empirical investigation, work in behavioral economics taps into lessons from psychology with the goal of improving economics’ predictive power. While the focus diverges from that of neoclassical economics, the best work in both subfields has much in common. The most useful insights are produced by faithfully applying the scientific method—the development of explanations of behavior through repeated cycles of data collection and hypothesis testing. Gains in knowledge are incremental, and skepticism is encouraged until assumptions built into theory are able to hold up against data collected in multiple environments. In addition, both subfields strive to integrate relevant concepts—e.g., psychological concepts in the case of behavioral economics—into models that produce well-defined, testable, and falsifiable predictions. While some have characterized the mission of behavioral economics as an attempt to abandon rational choice theory and replace it with more realistic assumptions that reflect human fallibility, many behavioral economics models that find strong support in existing data assume a set of rational but non-standard preferences (Zeiler, forthcoming). In fact, a great many works in behavioral economics contain multiple theories able to explain large swaths of existing data, some of which assume individuals make systematic, predictable mistakes, while others assume the error-free expression of non-standard, rational preferences. The empiricist’s role is to discover ways to separate the theories by developing or observing environments in which the theories lead to divergent predictions. In some literatures models that assume mistake-making are in the lead, and in others models assuming non-standard preferences seem to best explain existing data.