2012
DOI: 10.3386/w17985
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Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and Careers

Abstract: Motivated by the large differences in labor market outcomes across college majors, we survey the literature on the demand for and return to high school and post-secondary education by field of study. We combine elements from several papers to provide a dynamic model of education and occupation choice that stresses the roles of specificity of human capital and uncertainty about preferences, ability, education outcomes, and labor market returns. The model implies an important distinction between the ex ante and … Show more

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Cited by 105 publications
(36 citation statements)
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“…There is some evidence, however, of differentiation in the returns along varied dimensions (e.g. Martins and Pereira 2004;Hoekstra 2009;Green and Zhu 2010;Altonji et al 2012;Figueiredo et al 2013;Lindley and Machin 2014). Differentiation reflects a combination of within-group skill heterogeneity and disequilibrium in the graduate labour market, consistent with a range of labour market theories (McGuinness 2006).…”
Section: Introductionmentioning
confidence: 89%
“…There is some evidence, however, of differentiation in the returns along varied dimensions (e.g. Martins and Pereira 2004;Hoekstra 2009;Green and Zhu 2010;Altonji et al 2012;Figueiredo et al 2013;Lindley and Machin 2014). Differentiation reflects a combination of within-group skill heterogeneity and disequilibrium in the graduate labour market, consistent with a range of labour market theories (McGuinness 2006).…”
Section: Introductionmentioning
confidence: 89%
“…The magnitude of this effect is comparable to estimates from previous studies in the U.S. Hamermesh and Donald (2008) estimate that the earnings of students who majored in engineering and hard business are respectively, 31.6 and 48.9 log points higher than those who majored in education. Altonji et al (2012) suggest a wage premium of 56.1 and 51.8 log points for those who studied electrical engineering and finance relatively to education. Melguzio and Wozniak (2011) estimate a 25% to 40% STEM related premium for high achieving minority students.…”
Section: Introductionmentioning
confidence: 98%
“…Goldin, Katz and Kuziemko (2006) find that better female college preparedness, as measured by grades and test scores as well as completion of advanced math and science courses from high school, is an important factor in the reversal from male-dominated colleges to female-dominated colleges in the US. Paglin and Rufolo (1990), Rose and Betts (2004), Goldin, Katz and Kuziemko (2006) and Altonji, Blom and Meghir (2012) touch upon the link between lack of math qualifications 1 and the gender wage gap, but due to the lack of exogenous variation in the choice of math, causality is still not established. Also in our data set, the gender earnings gap is substantial (34%) and one-fifth of this gap evaporates when accounting for advanced math qualifications.…”
Section: Introductionmentioning
confidence: 99%