Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThis paper studies the determinants of college major choice using a unique "information" experiment embedded in a survey. We first ask respondents their self-beliefs-beliefs about their own expected earnings and other major-specific outcomes conditional on various majors, their population beliefs-beliefs about the population distribution of these characteristics, as well as their subjective beliefs that they will graduate with each major. After eliciting these baseline beliefs, we provide students with information on the true population distribution of these characteristics, and observe how this new information causes respondents to update their beliefs. Our experimental design creates unique panel data. We first show that respondents make substantial errors in population beliefs, and logically revise their self-beliefs in response to the information. Subjective beliefs about future major choice are positively and strongly associated with beliefs about self-earnings, ability, and spouse's earnings. However, cross-sectional estimates are severely biased upward because of the positive correlation of tastes with earnings and ability. The experimental variation in beliefs allows us to identify a rich model of college major choice, with which we estimate the relative importance of earnings and earnings uncertainty on the choice of college major versus other factors, such as ability to complete coursework, spouse's characteristics, and tastes for majors. While earnings are a significant determinant of major choice, tastes are the dominant factor in the choice of field of study. We also investigate why males and females choose different college majors.

We use a hypothetical choice methodology to estimate preferences for workplace attributes from a sample of high-ability undergraduates attending a highly selective university. We estimate that women on average have a higher willingness to pay (WTP) for jobs with greater work flexibility and job stability, and men have a higher WTP for jobs with higher earnings growth. These job preferences relate to college major choices and to actual job choices reported in a follow-up survey four years after graduation. The gender differences in preferences explain at least a quarter of the early career gender wage gap.

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Using an experiment to measure overconfidence and preferences for competitiveness and risk, this paper investigates whether these measures explain gender differences in college major choices and expected future earnings. We find that individuals who are overconfident and overly competitive expect to earn significantly more. In addition, gender differences in overconfidence and competitiveness explain 18% of the gender gap in earnings expectations. These experimental measures explain as much of the gender gap in earnings expectations as a rich set of control variables. While expected earnings are related to college major choices, the experimental measures are not related with college major choice.While considerable progress has been made to explain gender differences in occupations and labour market trajectories, residual differences remain unaccounted for by standard variables, such as labour market experience, amount and quality of education, family background, as well as customary demographic characteristics (

We assess the implications of nonlinearity for IV and FE estimation when the estimated model is inappropriately assumed to be linear. Our application is the causal link between family income and child outcomes. Our nonlinear IV and FE estimates show an increasing, concave relationship between family income and children's outcomes. We find that the linear estimators miss the significant effects of family income because they assign little weight to the large marginal effects in the lower part of the income distribution. We also show that the linear IV and FE estimates differ primarily because of different weighting of marginal effects. (JEL C26, D14, J12, J13)

We use the workplace experiences of transsexuals -individuals who change their gender typically with hormone therapy and surgery -to provide new insights into the longstanding question of what role gender places in shaping workplace outcomes. Using an original survey of a sample of male-to-female and female-to-male transsexuals, we document their earnings and employment experiences of transsexuals before and after their gender transitions. We find that while transsexuals have the same human capital after their transitions, their workplace experiences often change radically. For many male-to-female transsexuals, becoming a woman brings a loss of authority and pay, and often harassment and termination. On the other hand, for many female-to-male transsexuals, becoming a man brings increases in workplace respect, authority, and, in some cases, earnings. These findings challenge the omitted variables explanations for the gender pay gap and illustrate the often hidden and subtle processes that produce gender inequality in workplace outcomes.

This paper investigates how college students update their future earnings beliefs using a unique "information" experiment: We provide college students true information about the population distribution of earnings, and observe how this information causes them to update their future earnings beliefs. We show that college students are substantially misinformed about population earnings, logically revise their self-earnings beliefs, and have larger revisions when the information is more specifi c and is "good" news. We classify the updating behaviors observed and fi nd that the majority of students are non-Bayesian updaters. While the average welfare gains from our information provision are positive, we show that counterfactually imposing Bayesian processing of information vastly overestimates the gains from the intervention. Finally, we present evidence that our intervention has long-lasting effects on students' earnings beliefs.