In this paper, I provide an overview of how one might teach an advanced undergraduate elective on Behavioral Economics. While I focus on the structure and themes from my own course, I also attempt to highlight ways in which instructors might choose an alternative structure. Throughout, I emphasize how a Behavioral Economics elective is a great vehicle in which to highlight to undergraduates the science of Economics.

While present bias is an old idea, it only took hold in economics following David Laibson's (1994) dissertation. Over the past 20 years, research has led to a much better theoretical understanding of present bias, when and how to apply it, and which ancillary assumptions are appropriate in different contexts. Empirical analyses have demonstrated how present bias can improve our understanding of behavior in various economic field contexts. Nonetheless, there is still much to learn. In this paper, we give our assessment of some lessons learned, and to be learned.

The classical economic approach to policy analysis assumes that people always respond optimally to the costs and benefits of their available choices. A great deal of evidence suggests, however, that in some contexts people make errors that lead them not to behave in their own best interests. Economic policy prescriptions might change once we recognize that humans are humanly rational rather than superhumanly rational, and in particular it may be fruitful for economists to study the possible advantages of paternalistic policies that help people make better choices. We propose an approach for studying optimal paternalism that follows naturally from standard assumptions and methods of economic theory: Write down assumptions about the distribution of rational and irrational types of agents, about the available policy instruments, and about the government’s information about agents, and then investigate which policies achieve the most efficient outcomes. In other words, economists ought to treat the analysis of optimal paternalism as a mechanism-design problem when some agents might be boundedly rational. This approach has many advantages. First and foremost, by explicitly addressing when and how people do and don’t pursue their own best interests, economists will be better able to contribute to policy debates. To contribute to debates over regulating private financial decisions, we must study

We examine self-control problems—modeled as time-inconsistent, present-biased preferences—in a model where a person must do an activity exactly once. We emphasize two distinctions: Do activities involve immediate costs or immediate rewards, and are people sophisticated or naive about future self-control problems? Naive people procrastinate immediate-cost activities and preproperate—do too soon—immediate-reward activities. Sophistication mitigates procrastination, but exacerbates preproperation. Moreover, with immediate costs, a small present bias can severely harm only naive people, whereas with immediate rewards it can severely harm only sophisticated people. Lessons for savings, addiction, and elsewhere are discussed.

This paper discusses the discounted utility (DU) model: its historical development, underlying assumptions, and "anomalies" - the empirical regularities that are inconsistent with its theoretical predictions. We then summarize the alternate theoretical formulations that have been advanced to address these anomalies. We also review three decades of empirical research on intertemporal choice, and discuss reasons for the spectacular variation in implicit discount rates across studies. Throughout the paper, we stress the importance of distinguishing time preference, per se, from many other considerations that also influence intertemporal choices.

Evidence suggests that people understand qualitatively how tastes change over time, but underestimate the magnitudes. This evidence is limited, however, to laboratory evidence or surveys of reported happiness. We test for such projection bias in field data. Using data on catalog orders of cold-weather items, we find evidence of projection bias over the weather—specifically, people's decisions are overinfluenced by the current weather. Our estimates suggest that if the order-date temperature declines by 30°F, the return probability increases by 3.95 percent. We also estimate a structural model to measure the magnitude of the bias.

We outline a strategy for distinguishing rank-dependent probability weighting from systematic risk misperceptions in field data. Our strategy relies on singling out a field environment with two key properties: (i) the objects of choice are money lotteries with more than two outcomes; and (ii) the ranking of outcomes differs across lotteries. We first present an abstract model of risky choice that elucidates the identification problem and our strategy. The model has numerous applications, including insurance choices and gambling. We then consider the application of insurance deductible choices and illustrate our strategy using simulated data.

We use data on insurance deductible choices to estimate a structural model of risky choice that incorporates “standard” risk aversion (diminishing marginal utility for wealth) and probability distortions. We find that probability distortions—characterized by substantial overweighting of small probabilities and only mild insensitivity to probability changes—play an important role in explaining the aversion to risk manifested in deductible choices. This finding is robust to allowing for observed and unobserved heterogeneity in preferences. We demonstrate that neither Kőszegi-Rabin loss aversion alone nor Gul disappointment aversion alone can explain our estimated probability distortions, signifying a key role for probability weighting.

Without strong assumptions about how noise manifests in choices, we can infer little from existing empirical observations of the common ratio effect (CRE) about whether there exists an underlying common ratio preference (CRP). We propose to solve this inferential challenge using paired valuations, which yield valid inference under common assumptions. Using this approach in an online experiment with 900 participants, we find no evidence of a systematic CRP. To reconcile our findings with existing evidence, we present the same participants with paired choice tasks and demonstrate how noise can generate a CRE even for individuals without an associated CRP.