Ao Wang

This paper tests reference dependence by examining whether increases in hypothesized reference points are offset by equivalent increases in payoffs, without relying on parametric assumptions about gain–loss value functions. In effort tasks, we find systematic expectation-sensitive behavior, yet reject expectations-based referents and pointwise payoff-based prospect-theoretic referents. In investment games and a re-analysis of cab driver data, we uncover intuitive evidence for various path-dependent prospect-theoretic reference points. Despite added degrees of freedom, these models yield tractable predictions. In lottery choices, canonical two-stage manipulations isolating common consequences induce large reference-dependent effects, underscoring the need for continued theoretical development beyond existing models.

Sequential choices are ubiquitous in daily life, yet making optimal decisions in such settings—where properly accounting for option value is crucial—can be challenging. This paper provides field experimental evidence on the neglect of option value in high-stakes decisions and quantifies the associated welfare consequences. We study a centralized college admissions system where students submit brief preference lists. Although option value should encourage riskier top choices, many students are overly cautious and fail to include safer lower-ranked options. We argue that directed cognition—making myopic decisions while ignoring the value of subsequent options—explains this behavior. An in-field experiment targeting a key framing-based prediction shows that about 50% of applicants exhibit this pattern, especially among disadvantaged students. Counterfactual analysis suggests that de-biasing interventions could significantly reduce outcome gaps and improve overall efficiency.

This paper reports a field experiment that tests the effect of motivated cognition on information acquisition. When the high-stakes College Entrance Exam is held in the month of Ramadan, Chinese Muslim students not only underestimate the cost of fasting when uninformed, but further, misread clear empirical evidence of the cost, which we obtain by analyzing administrative data on past students' exam performance. Inspired by the theory of motivated cognition, we tackle this learning failure by randomly offering a subset of the students reading materials in which well-respected Muslim clerics explain that it is permissible to postpone the fast until after the exam. Students who receive the material are substantially less likely to misread our empirical analysis and more willing to postpone the fast.

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around the square root of x. However, this calculation omits a further benefit of frequent testing: removing infections from the population lowers intra-group transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms, etc.) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

We investigate the causal impact of collegiate economics courses on students’ decision-making. By exploiting a Chinese college-admission system that quasi-randomly assigns students to economics/business majors given students’ preferences and the College Entrance Exam’s cutoff scores for economics/business majors, we are able to isolate the treatment effects of an economics education on students’ responses to a decision-making survey. Specifically, we compare the survey responses of students who narrowly meet the cutoffs for the economics/business majors to those who do not and find that students educated in economics/business courses are more likely to be risk neutral and less prone to common biases in probabilistic beliefs. While students in economics/business majors do not show significant changes in social preferences, they appear more inclined to believe that others behave selfishly.

We present a general approach to experimentally testing candidate reference points. This approach builds from Prospect Theory's prediction that an increase in payoffs is perfectly offset by an equivalent increase in the reference point. Violation of this prediction can be tested with modifications to existing econometric techniques in experiments of a particular design. The resulting approach to testing theories of the reference point is minimally parametric, robust to broad classes of heterogeneity, yet still implementable in comparatively small sample sizes. We demonstrate the application of this approach in an experiment that tests the role of salience in setting reference points.