College Choice and Subsequent Earnings: Results Using Swedish Sibling Data*

Lindahl, Lena; Regnér, Håkan

doi:10.1111/j.1467-9442.2005.00417.x

Cited by 41 publications

(21 citation statements)

References 21 publications

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“…Recent research also found positive return to college quality in Japan, where college quality is measured as the average college entrance examination scores (Ono 2004), and in Italy, where college quality is measured by a comprehensive performance index (Di Pietro and Cutillo 2006). Lindahl and Regnér (2005), using a similar method as the present paper, found large variation in value-added across all Swedish universities, and older universities enjoy higher value-added. They use sibling data to control for college selection.…”

Section: Resultssupporting

confidence: 51%

A value‐added estimate of higher education quality of US states

Zhang

2008

Education Economics

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States differ substantially in higher education policies. Little is known about the effects of state policies on the performance of public colleges and universities, largely because no clear measures of college quality exist. In this paper, I estimate the average quality of public colleges of US states based on the value-added to individuals' early career earnings. I explicitly deal with the problem of self-selection in both where to go to college and where to work. I find considerable variation in the quality of states' public college systems. Using this quality measure, I then explore how various aspects of state higher education policy are associated with college outcomes. I find that states with better faculty quality and with more diversity among public colleges tend to have higher value-added to student earnings.

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Section: Resultssupporting

confidence: 51%

A value‐added estimate of higher education quality of US states

Zhang

2008

Education Economics

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“…Some studies (see, for example, Black and Smith 2006) have attempted to link the quality premium to particular institutional characteristics (for example, ability scores, faculty/student ratios, rejection rates), though as Brewer, Eide and Ehrenberg (1999, p. 106) note, 'there is little evidence that particular college characteristics are systematically associated with differences in earnings, although the effect of any individual variable is shown to be small'. Various reasons have been advanced for the quality earnings premium, including differences in peer effects, curricular design, quality of teachers and quality of instruction given, which all facilitate the accumulation of human capital at varying rates (Lindahl and Regnér 2005).…”

Section: Institution Attendedmentioning

confidence: 99%

The Influences of Institution Attended and Field of Study on Graduates' Starting Salaries

Birch

Miller

2009

Australian Economic Review

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This paper examines the determinants of Australian university graduates' starting salaries, with an emphasis on the institution attended and field of study. It is shown that there is little difference between the starting salaries of students who attended Group of Eight universities and those who attended other universities. There are modest differences in starting salaries across fields of study. However, these differences are considerably less than those associated with the type of employment obtained. These results suggest it is what you do in the labour market, rather than where or what you have studied, that is the main determinant of labour market outcomes.

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“…Using an instrumental variables strategy, Long (2008) estimated the local average treatment effect of college quality and did not find a consistent relationship between college characteristics and earnings. Lindahl and Regner (2005) use sibling data to illustrate that the effect of college quality might be overstated if family characteristics are not fully adjusted for because cross-sectional estimates are twice as large as within-family estimates. It is important to note that most of the above literature has used a single college characteristic, such as school average SAT score, expenditures per student, the Barron's index, or whether the student attended a flagship state university, as a proxy for college quality.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Effects of College Characteristics over the Career Using Administrative Earnings Data

Dale¹,

Krueger²

2014

Journal of Human Resources

133

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Abstract. We estimate the labor market effect of attending a highly selective college, using the College and Beyond (C&B) Survey linked to Detailed Earnings Records from the Social Security Administration (SSA). This paper extends earlier work by Dale and Krueger (2002) that examined the relationship between the college that students attended in 1976 and the earnings they self-reported in 1995 on the C&B follow-up survey. In this analysis, we use administrative earnings data to estimate the effects of several college characteristics (that are commonly used as proxies for college quality) for a more recent cohort: students who entered college in 1989. We also estimate these effects for the 1976 cohort, but over a longer time horizon (from 1983 through 2007).The effects of college characteristics on earnings are sizeable for both cohorts in regression models that control for variables commonly observed by researchers, such as student SAT scores. However, when we partially adjust for unobserved student ability by controlling for the average SAT score of the colleges that students applied to, our estimates of the effects of college characteristics fall substantially and are generally indistinguishable from zero. There were notable exceptions for certain subgroups. For black and Hispanic students and for students who come from families with less parental education, the effects of college characteristics are large, even in models that adjust for unobserved student characteristics. Finally, contrary to expectations, our results do not suggest the effects of college characteristics increased for students who entered college more recently because estimates are similar for the 1976 and the 1989 cohort.*We thank the Mellon Foundation for financial support; Ed Freeland for obtaining permission of participating colleges; Matthew Jacobus and Licia Gaber Baylis for skilled computer programming support; Mike Risha of SSA for merging the C&B data with SSA data and for tirelessly running our programs; Lawrence Katz, Sarah Turner, and Mark Dynarski for helpful comments on an earlier draft; and Mark Long for providing data on college SAT scores.2

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College Choice and Subsequent Earnings: Results Using Swedish Sibling Data*

Cited by 41 publications

References 21 publications

A value‐added estimate of higher education quality of US states

A value‐added estimate of higher education quality of US states

The Influences of Institution Attended and Field of Study on Graduates' Starting Salaries

Estimating the Effects of College Characteristics over the Career Using Administrative Earnings Data

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