The Role Of Heterogeneous Risk Preferences Discount Rates And Earnings Expectations In College Major Choice

In this paper, 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 perceptions 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 are likely to 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.

Handbook of Economic Expectations discusses the state-of-the-art in the collection, study and use of expectations data in economics, including the modelling of expectations formation and updating, as well as open questions and directions for future research. The book spans a broad range of fields, approaches and applications using data on subjective expectations that allows us to make progress on fundamental questions around the formation and updating of expectations by economic agents and their information sets. The information included will help us study heterogeneity and potential biases in expectations and analyze impacts on behavior and decision-making under uncertainty. Combines information about the creation of economic expectations and their theories, applications and likely futures Provides a comprehensive summary of economics expectations literature Explores empirical and theoretical dimensions of expectations and their relevance to a wide array of subfields in economics

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The choice of a college major plays a critical role in determining the future earnings of college graduates. Students make their college major decisions in part due to the future earnings streams associated with the different majors. We survey students about what their expected earnings would be both in the major they have chosen and in counterfactual majors. We also elicit students' subjective assessments of their abilities in chosen and counterfactual majors. We estimate a model of college major choice that incorporates these subjective expectations and assessments. We show that both expected earnings and students' abilities in the different majors are important determinants of student's choice of a college major. We also show that students' forecast errors with respect to expected earnings in different majors is potentially important, with our estimates suggesting that 7.5% of students would switch majors if they made no forecast errors.

There is a growing body of research examining the labor market returns to college major, motivated by the large returns to skill in the labor market. Prior research has focused almost exclusively on mean effects and has paid little attention to the role of earnings growth and variability. Using linked administrative data from Texas on public K-12 students followed through college into the labor market, we find that the focus on mean differences mask four important features of the returns to college majors. First, majors are associated with varying earnings growth, which makes the returns sensitive to the experience distribution of the sample analyzed. Second, average earnings effects vary across workers; quantile treatment effect estimates show that mean effects mask considerable effect heterogeneity. Third, major choice affects earnings variability within workers over time. College major effects on earnings and variability are negatively correlated; high return majors also have more stable earnings. Finally, there is substantial variation in returns across specific majors within aggregate major groups and across institutions. This variation suggests that estimate of returns to college major are sensitive to how majors are aggregated and the composition of institutions in the sample.

This 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 upwards 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. The following are appended: (1) Figures A1 and A2; and Tables A1, A2, and A3; (2) Information on Survey Design and Information Treatments; (3) and Estimation Details.