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This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, low-achieving students are harmed by high-achieving peers. Analyzing students’ course evaluations suggests that peer effects are driven by improved group interaction rather than adjustments in teachers’ behavior or students’ effort. Building on Angrist’s research, we further show that classical measurement error in a setting where group assignment is systematic can lead to a substantial overestimation of peer effects. However, when group assignment is random—like in our setting—peer effect estimates are biased toward zero.

The discrimination literature treats outcomes as relative. But does a differential arise because agents discriminate against others – exophobia – or because they favour their own kind - endophilia? Using a field experiment that assigned graders randomly to students' examinations that did/did not contain names, we find favouritism but no discrimination by nationality nor by gender. We are able to identify these preferences under a wide range of behavioural scenarios regarding the graders. That endophilia dominates exophobia alters how we should measure discriminatory wage differentials and should inform the formulation of anti-discrimination policy.

We conduct a natural field experiment to test whether offering financial incentives encourages more female job seekers to complete their applications for a tech job. All eligible applicants for the job were invited to perform an online skill assessment. We randomized whether or not they were offered an incentive of up to $10 for completing the assessment. We find no significant effect of the incentive for female applicants (or male applicants).

We extend Becker’s model of discrimination by allowing firms to have discriminatory and favoring preferences simultaneously. We draw the two-preference parallel for the marginal firm, illustrate the implications for wage differentials, and consider the implied long-run equilibrium. In the short-run, wage differentials depend on relative preferences. However, in the long-run, market forces drive out discriminatory but not favoring firms.

This paper investigates how exposure to higher-achieving male and female peers in university affects students’ major choices and labor market outcomes. For identification of causal effects, we exploit the random assignment of students to university sections in first-year compulsory courses. We present two main results. First, studying with higher-achieving peers has no statistically significant or economically meaningful effects on educational choices. Second, we find suggestive evidence that women who have been exposed to higher achieving male peers end up in jobs in which they are more satisfied.

Business degrees are popular and lead to high earnings. Female business graduates, however, earn less than their male counterparts. These gender differences can be traced back to university, where women shy away from majors like finance that lead to high earnings. In this paper, we investigate how the gender composition of peers in business school affects women's and men's major choices and labor market outcomes. We find that women who are randomly assigned to teaching sections with more female peers become less likely to choose male-dominated majors like finance and more likely to choose female-dominated majors like marketing. After graduation, these women end up in jobs where their earnings grow more slowly. Men, on the other hand, become more likely to choose male-dominated majors and less likely to choose female-dominated majors when they had more female peers in business school. However, men's labor market outcomes are not significantly affected. Taken together, our results show that studying with more female peers in business school increases gender segregation in educational choice and affects labor market outcomes.

Save More Tomorrow is a retirement savings plan developed by Richard Thaler and Shlomo Benartzi that incorporates insights from Behavioural Economics. In this paper, we describe how the plan works and discuss how it can be used to increase retirement savings in New Zealand.

Does growing up with a sister rather than a brother affect personality? In this paper, we provide a comprehensive analysis of the effects of siblings' gender on adults' personality, using data from 85,887 people from 12 large representative surveys covering 9 countries (the United States, the United Kingdom, the Netherlands, Germany, Switzerland, Australia, Mexico, China, and Indonesia). We investigated the personality traits risk tolerance, trust, patience, locus of control, and the Big Five. We found no meaningful causal effects of the gender of the next younger sibling, and no associations with the gender of the next older sibling. Based on high statistical power and consistent results in the overall sample and relevant subsamples, our results suggest that siblings' gender does not systematically affect personality.

Does growing up with a sister rather than a brother affect personality? In this paper, we provide a comprehensive analysis of the effects of siblings’ gender on adults’ personality, using data from 85,887 people from 12 large representative surveys covering 9 countries (the United States, the United Kingdom, the Netherlands, Germany, Switzerland, Australia, Mexico, China, and Indonesia). We investigated the personality traits risk tolerance, trust, patience, locus of control, and the Big Five. We found no meaningful causal effects of the gender of the next younger sibling, and no associations with the gender of the next older sibling. Based on high statistical power and consistent results in the overall sample and relevant subsamples, our results suggest that siblings’ gender does not systematically affect personality.

Women are significantly underrepresented in the technology sector. We design a field experiment to identify statistical discrimination in job applicant assessments and test treatments to help improve hiring of the best applicants. In our experiment, we measure the programming skills of job applicants for a programming job. Then, we recruit a sample of employers consisting of human resource and tech professionals and incentivize them to assess the performance of these applicants based on their resumes. We find evidence consistent with inaccurate statistical discrimination: while there are no significant gender differences in performance, employers believe that female programmers perform worse than male programmers. This belief is strongest among female employers, who are more prone to selection neglect than male employers. We also find experimental evidence that statistical discrimination can be mitigated. In two treatments, in which we provide assessors with additional information on the applicants' aptitude or personality, we find no gender differences in the perceived applicant performance. Together, these findings show the malleability of statistical discrimination and provide levers to improve hiring and reduce gender imbalance.