Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We estimate a rich model of college major choice using a panel of experimentally-derived data. Our estimation strategy combines two types of data: data on self-reported beliefs about future earnings from potential human capital decisions and survey-based measures of risk and time preferences. We show how to use these data to identify a general life-cycle model, allowing for rich patterns of heterogeneous beliefs and preferences. Our data allow us to separate perceptions about the degree of risk or about the current versus future payoffs for a choice from the individual’s preference for risk and patience. Comparing our estimates of the general model to estimates of models which ignore heterogeneity in risk and time preferences, we find that these restricted models overstate the importance of earnings to major choice. Additionally, we show that while men are less risk averse and patient than women, gender differences in expectations about own-earnings, risk aversion, and patience cannot explain gender gaps in major choice.