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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.
Terrence Chorvat and Kevin McCabe
This chapter discusses some ways in which neuroscientific research applied to economics, commonly referred to as neuroeconomics, can inform legal scholarship. Given the limitations on space in this chapter, it was not possible to discuss anything like all of the neuroeconomic research that has been done in the last few years, even all of that which is of relevance to legal scholarship. Therefore, this chapter is a highly selective review of the research that the authors believe is useful to legal scholars. The focus of the chapter is on neuroeconomic research related to financial decisions and its relevance to legal scholarship.
Peter H. Huang
This chapter offers legal scholars a brief introductory survey of modern happiness research. It analyzes how happiness research can inform legal policy, and explains how and why happiness research differs from and is related to behavioral economics. The author develops two conditions under which law and policy should care more about experienced happiness versus remembered happiness. Connections are made between being happy, being ethical, and being mindful, while the chapter illustrates how happiness research applies and relates to negotiations and conflict resolution. Finally, the author considers how happiness research can improve legal education and legal practice.
Claudia M. Landeo
Vertical restraints have been the subject of lively policy and academic discussions. This chapter argues that experimental law and economics might strengthen the contributions of economic theories of vertical restrains to the design and implementation of antitrust institutions. First, experimental law and economics provides empirical evidence of the robustness of economic theories of antitrust. Second, the combination of economic theory and experimental work represents the application of scientific research methods. Third, experimental law and economics studies of antitrust involve the replication of complex and abstract economic theories using simple environments. These settings might facilitate policy-makers’ understanding of economic theories of antitrust. The chapter assesses the validity of claims regarding the contributions of experimental law and economics by investigating the methodological characteristics of seminal experimental work on vertical restraints and the outcomes produced by these studies.
Sumit Agarwal and Brent W. Ambrose
Agarwal and Ambrose examine the effect of direct mail (commonly referred to as junk mail) advertising on individual financial decisions by studying consumer choice in relation to home equity debt contracts. Consistent with the theoretical predictions, the authors find that financial variables underlying the relative pricing of debt contracts are the leading factors explaining consumers’ home equity debt choice. Furthermore, they also find that the intended use of debt proceeds significantly impacts consumer choice. However, when they study consumers who received a direct mail solicitation for a particular debt contract (line versus loan), they find evidence that the relative pricing variables are less relevant in explaining consumer contract choice, even though they were presented with a full menu of debt contracts. Thus, their results are consistent with the view that advertising is persuasive.
Jonathan Baron and Tess Wilkinson-Ryan
Baron and Wilkinson-Ryan outline the conceptual foundations of behavioral law and economics. The authors concentrate on the behavioral concepts imported into the field from psychology and experimental economics, and survey the normative models, descriptive theories, and prescriptive approaches featured in behavioral law and economics research. They endeavor to point out common themes in the research in an effort to tie together various groups of findings and counter the criticism that the field lacks the cohesion of standard law and economics.
Humans have adapted to their uncertain environment by the method of trial and error. This evolutionary process made them reason about uncertain facts the way they do. Behavioral economists censure this mode of reasoning for violating the canons of mathematical probability that a rational person must obey. Based on insights from probability theory and the philosophy of induction, Stein argues that a rational person need not apply mathematical probability in making decisions about individual causes and effects. Instead, she should be free to use common sense reasoning that generally aligns with causative probability. Stein also shows that behavioral experiments miss their target when they ask reasoners to extract probability from information that combines causal evidence with statistical data. Because it is perfectly rational for a person focusing on a specific event to prefer causal evidence to general statistics, Stein argues, those experiments establish no deviations from rational reasoning.