To the center of the research interests of an educational economist, any “human capital measurement” that can be quantified can go to the left-hand side of the education production function:
is a bad boy - it is exactly the question of which variables
are the good measurements of human capitals, in academia that is scholarly
outputs, student learning, ranking of institutions, etc. that have been
concerning the researchers on these topics and all of us in the academic
community and beyond. The complexity of
finding the best output measures can be as tricky as the Fisher vs. University of Texas case on Affirmative Actions that
forced the society to reevaluate the real “outputs” students get through a
higher education[1].Traditionally, for simplicity economists have been using the easily available administrative dataset such as test scores, graduation rate, college enrollment rate, etc. to proxy for the output side variable in evaluating students’ learning, institutional efficacies and educational policy effectiveness. However, with well-designed performance tracking tools such as palm devices, online learning platforms to understand individual student’s learning process, and with improved methodologies such as econometric techniques to test the real value-added process, our estimations are still only roughly one quarter in identifying all the factors that is contributing causally.
Granted, with all the progress we have had in measuring academic outputs of either the institution, faculty or students, it is widely recognized that while regression models can bring insights about causal effects, we need to search for innovative “instrument variables” to construct the treatment effect in quasi-natural experiment in social context (vs. non-lab), or even further difference-in-difference strategies for policies changes[2].
However, the shadow of “un-observables” and “missing variables” never stopped haunting us, the
. In Good Will Hunting, the question genius Will threw to a boastful Harvard sophomore is indeed hard to answer even
with all the measurement techniques and data we have: if someone
loves learning, would an ivy education be too different than free library books
and seminars? Even though there are studies seemingly to support the “sheep
skin effect” of diplomas[3], but
more current literatures also identify strong self-selection problem of studies
measuring the effects of certain schools on students, their conclusion
intriguing, “after all, high ability
students will succeed whatever their college decisions are”[4].When MOOCs (massive online open courses) are embraced by strong advocates around the world for the free access to the best educational resources just a-click-away, there are elite institutions exploring the opportunity of such a trend by issuing certificates of completing courses or passing certain tests[5], an indeed hard-to-ignore evolution in education, if nothing yet to be clearly a “revolution”. This trend exposes us to even more uncertainties and new questions about measuring human capital. Would employers buy these? How the labor market will evaluate the “value” of the computer era’s learning, which was distracted, further decentralized, even de-institutionalized? With everyone logging their activities via handhold devices and Apps, would new measurements like the Klout Score and PeerIndex, using algorithms to track one’s online “ID”’s “influence score” in the real network that matters for this person, which in certain scenarios can be translated into employability, marketing value, etc[6], truly giving a new definition to “human capital” in the new “cloud” era?
[2] Angrist,
J.D., and J.S. Pischke. Mostly Harmless
Econometrics: An Empiricist's Companion: Princeton Univ Pr, 2008.
[3]
D.A. Jaeger and M.E. Page, "Degrees Matter: New Evidence on Sheepskin
Effects in the Returns to Education," The
Review of Economics and Statistics (1996).
[4]
D.J. Zimmerman, "Peer Effects in Academic Outcomes: Evidence from a
Natural Experiment," Review of
Economics and Statistics 85, no. 1 (2003).
[5] Caroline Porter, College Degree, No Class Time Required, The Wall Street Journal,
2013-01-24. http://online.wsj.com/article/SB10001424127887323301104578255992379228564.html
[6] McHugh, Molly, Klout
reveals a new scoring algorithm – and the critics are quiet, Digital
Trends, 2012-08-14 http://www.digitaltrends.com/social-media/klout-reveals-new-scoring-algorithm-and-the-critics-are-quiet/
