Recovering Ex Ante Returns and Preferences for Occupations Using Subjective Expectations Data

National Bureau of Economic Research, 2010

Modeling College Major Choices Using Elicited Measures of Expectations and Counterfactuals * 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.

Journal of Political Economy

Using panel data on male undergraduates at Duke University, we make three contributions to the literature on subjective expectations. First, we show elicited data on earnings beliefs and probabilities of working in particular occupations are highly informative regarding actual earnings and occupational choices. Second, we show how subjective expectations data can be used to recover ex ante treatment effects as well as the relationship between these treatment effects and individual choices. We find large differences in expected earnings across occupations, and substantial heterogeneity across individuals in the corresponding ex ante returns. We also find clear evidence of sorting across occupations based on expected earnings; those who report higher probabilities of working in a particular occupation also report higher earnings in that occupation. Finally, while expected earnings influence occupational choice, we show that non-pecuniary factors also play an important role, with a sizable share of individuals expecting to give up substantial amounts of earnings by choosing occupations that are not their highest paying ones.

2014

We show that data on subjective expectations, especially on outcomes from counterfactual choices and choice probabilities, are a powerful tool in recovering ex ante treatment effects as well as preferences for different treatments. In this paper we focus on the choice of occupation, and use elicited beliefs from a sample of male undergraduates at Duke University. By asking individuals about potential earnings associated with counterfactual choices of college majors and occupations, we can recover the distribution of the ex ante monetary returns to particular occupations, and how these returns vary across majors. We then propose a model of occupational choice which allows us to link subjective data on earnings and choice probabilities with the non-pecuniary preferences for each occupation. We find large differences in expected earnings across occupations, and substantial heterogeneity across individuals in the corresponding ex ante returns. However, while sorting across occupations is partly driven by the ex ante monetary returns, non-monetary factors play a key role in this decision. Finally, our results point to the existence of sizable complementarities between college major and occupations, both in terms of earnings and non-monetary benefits.

International Economic Review, 2003

This article uses factor models to identify and estimate the distributions of counterfactuals. We extend LISREL frameworks to a dynamic treatment effect setting, extending matching to account for unobserved conditioning variables. Using these models, we can identify all pairwise and joint treatment effects. We apply these methods to a model of schooling and determine the intrinsic uncertainty facing agents at the time they make their decisions about enrollment in school. We go beyond the "Veil of Ignorance" in evaluating educational policies and determine who benefits and who loses from commonly proposed educational reforms. * Manuscript

De Economist, 1992

2003

This paper uses factor models to identify and estimate distributions of counterfactuals. We extend LISREL frameworks to a dynamic treatment effect setting, extending matching to account for unobserved conditioning variables. Using these models, we can identify all pairwise and joint treatment effects. We apply these methods to a model of schooling and determine the intrinsic uncertainty facing agents at the time they make their decisions about enrollment in school. Reducing uncertainty in returns raises college enrollment. We go beyond the "Veil of Ignorance" in evaluating educational policies and determine who benefits and loses from commonly proposed educational reforms.

Review of Economics and Statistics, 2012

2000

for providing unpublished estimates, comments and other assistance, participants at seminars at Yale University, MIT, and the University of Wisconsin for comments on an earlier draft, Bridget Longridge for research assistance, and the MacArthur Foundation for financial support.

The ANNALS of the American Academy of Political and Social Science, 1998

Understanding the economic payoff to human capital investments is very important from the standpoint both of individuals and of society. Correctly estimating these impacts necessitates having a well-developed idea of the microeconomic determinants of human behavior. Without this, empirical analyses of such topics as career choice, college choice, or wage determination will be flawed. We begin with a discussion of why these choice models are important -using examples of similar attempts that do not capture sufficient information -and illustrate their usefulness in a variety of contexts. We also describe the results of our attempts to examine college choice using microeconomic models.

2009

We utilize the 2000 cohort of university graduates from the National Graduate Survey (NGS) to estimate the extent to which the choice of field of study is influenced by expected returns to those fields of study. The expected returns are based on earnings equations estimated from the earlier 1990 NGS cohort for the years 1992 and 1995 -- years that