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Learning and Earning: An Approximation to College Value Added in Two Dimensions

Evan Riehl, Juan E. Saavedra and Miguel Urquiola ()

No 22725, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper explores the implications of measuring college productivity in two different dimensions: earning and learning. We compute system-wide measures using administrative data from the country of Colombia that link social security records to students’ performance on a national college graduation exam. In each case we can control for individuals’ college entrance exam scores in an approach akin to teacher value added models. We present three main findings: 1) colleges’ earning and learning productivities are far from perfectly correlated, with private institutions receiving relatively higher rankings under earning measures than under learning measures; 2) earning measures are significantly more correlated with student socioeconomic status than learning measures; and 3) in terms of rankings, earning measures tend to favor colleges with engineering and business majors, while colleges offering programs in the arts and sciences fare better under learning measures.

JEL-codes: I23 J24 J44 (search for similar items in EconPapers)
Date: 2016-10
New Economics Papers: this item is included in nep-lam and nep-lma
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Published as Learning and Earning: An Approximation to College Value Added in Two Dimensions , Evan Riehl, Juan E. Saavedra, Miguel Urquiola. in Productivity in Higher Education , Hoxby and Stange. 2019

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Chapter: Learning and Earning: An Approximation to College Value Added in Two Dimensions (2018) Downloads
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