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Higher Education in the Digital Age
By William G. Bowen, Kelly A. Lack PRINCETON UNIVERSITY PRESS
Copyright © 2013 Princeton University Press
All rights reserved.
ISBN: 978-1-4008-6613-7
CHAPTER 1
Costs and Productivity in Higher Education
AS MY WIFE keeps reminding me, I have a Don Quixote–like tendency to flail away at windmills—to take on topics such as race in America and affirmative action; the insidious problems with college sports at all levels, including Division III and the Ivy League (which cause me to cringe whenever the NCAA refers to its legions of "student-athletes"); and, yes, the un forgiving economics of labor-intensive industries, such as the performing arts and higher education. But, my DNA is what it is, and so I am now adding to this list the potential implications of online learning for college costs.
Context matters, and I will begin by outlining as succinctly as I can aspects of the economics of higher education that are relevant to my topic:
• trends in costs, the "cost disease," and how to think about changes in productivity;
• other forces, some deeply ingrained in the fabric of higher education, that also push up costs; and
• growing worries about affordability, especially in the public sector, where reductions in public support have been coupled with significant increases in tuition.
Then, in the second part of the book, I will discuss what I think—or, better said, what I suspect—about the potential impact of the variety of approaches to online learning that are everywhere present, including, of course, at Stanford University and at Stanford spin-offs such as Coursera and Udacity. Is there, as President Hennessy has suggested, a tsunami of some still ill-defined kind coming? Is it realistic to imagine that online learning is a "fix" (at least in part) for the cost disease? Throughout, I will maintain a system-wide perspective, since it will not do to think about these large questions solely from the perspective of individual institutions.
Cost Trends, the "Cost Disease," and Productivity in Higher Education
It is fitting that I gave these Tanner Lectures in close proximity to Clark Kerr's neighborhood, since it was President Kerr, in his capacity as chairman of the Carnegie Commission on the Future of Higher Education, who commissioned a study of mine in the mid-1960s that became The Economics of the Major Private Universities. In that study I documented the seemingly inexorable tendency for institutional cost per student (which is, of course, different from tuition charges) to rise faster than costs in general over the long term. Kerr christened this finding Bowen's Law, although he was, he said, "originally skeptical about it."
What is important today is not the exact numbers contained in that study (which were based largely on a detailed examination of the experiences of the University of Chicago, Princeton University, and Vanderbilt University between 1905 and 1966) but the underlying pattern, which has been found to hold for public as well as private universities, and for colleges too. I reproduce here, as something of a historical relic, a figure from my 1960s Carnegie study (figure 1). The figure shows that, excepting war periods and the Great Depression, which require separate analysis, cost per student rose appreciably faster than an economy-wide index of costs in general. The consistency of this pattern suggested to me then, as it does today, that we are observing the effects of relationships that are deeply embedded in the economic order.
Running through all the factors at play (and there are many, as I will indicate shortly) is a key proposition that my teacher and lifelong friend, William J. Baumol, and I first articulated in our study of the performing arts, which also dates from the mid-1960s. The proposition is known to this day in the literature as the "cost disease." The basic idea is simple: in labor-intensive industries such as the performing arts and education, there is less opportunity than in other sectors to increase productivity by, for example, substituting capital for labor. Yet markets dictate that, over time, wages for comparably qualified individuals have to increase at roughly the same rate in all industries. As a result, unit labor costs must be expected to rise faster in the performing arts and education than in the economy overall.
Robert Frank of Cornell University provided this succinct explanation of the cost disease as recently as March 2012: "While productivity gains have made it possible to assemble cars with only a tiny fraction of the labor that was once required, it still takes four musicians nine minutes to perform Beethoven's String Quartet No. 4 in C minor, just as it did in the 19th century." In short, productivity gains are unlikely to offset wage increases to anything like the same extent in the arts or education as in manufacturing; hence, differential rates of increase in costs are to be expected—a finding Baumol and I reported for major orchestras at about the same time that my Carnegie study of higher education was under way.
About a decade after the Carnegie study, I reported a similar pattern in my 1976 President's Report at Princeton: "While prices in general have risen about 50% [over the previous 10 years alone], the most widely used price index for higher education has risen about 70%." And in 2012, three and a half decades later, Sandy Baum, Charles Kurose, and Michael S. McPherson reported basically the same pattern. In their paper "An Overview of Higher Education," presented at Prince ton University, they cite a careful study using data from the Delta Cost Project that shows that "educational expenditures per FTE student increased at an average annual rate of about 1% beyond inflation at all types of public institutions from 2002 to 2008." There is no need to burden this argument with more data about trends in institutional costs, which are notoriously hard to interpret, in part because they often involve aggregations of various kinds. It is easy to get mired in the underbrush, and we do well to remember the admonition of the architect Robert Venturi: "Don't let de-tails wag the dog."
There is, however, a final big point to note about trends—namely, the reversal that has occurred in the last decade or so in the respective positions of private and public institutions. When I wrote my 1976 report, from the perspective of the president of a private university, there was widespread concern about the widening gap in charges between the privates and the publics (with the privates becoming ever more expensive relative to the publics). In those years, the privates were hit especially hard by the stagflation of the time, with its dampening effect on stock market values that, in turn, affected both returns on endowments and private giving. Today, it is the publics that have suffered more than most of the privates (and certainly more than the most selective privates), largely as a result of sharp cutbacks in state appropriations.
During a discussion session the day after I originally made these remarks at Stanford, President Hennessy contrasted trends in tuition and student aid in the public sector with the recent experience at Stanford. He observed that while Stanford's "sticker price" has continued to increase, as it has throughout almost all of higher education, Stanford has had the financial wherewithal to increase its outlays on student aid by even more than the increases in its tuition and has chosen to spend some part of its resources in this highly commendable way. Only a small number of other wealthy private institutions have been able to do the same thing, and the fortunate circumstances of these relatively well-off "outlier" institutions should not be allowed to obscure the general pattern pertinent to the public colleges and universities that educate three-quarters of this country's college students—or, for that matter, the trends pertinent to the large number of private colleges and universities that have also been compelled to raise tuition faster than they have been able to raise student aid. I will return in due course to the broad subject of increasing stratification in higher education and its implications.
I am aware that thus far I have been using an important word—productivity—without defining it. Put simply, productivity is the ratio of outputs to the inputs used to produce them. But this formulation conceals at least as much as it reveals, since it is maddeningly difficult in the field of education to measure both outputs and inputs—even within a single institution, never mind across institutions serving different missions. If only we produced standardized widgets or harvested blueberries!
As one illustration of how treacherous this terrain is, the National Academy of Sciences released, in 2012, a massive report of over two hundred pages devoted to the measurement of productivity in higher education. A major virtue of the report, which in turn cites a voluminous literature, is that it debunks the idea that productivity in higher education is uni-dimensional. It warns against a multiplicity of dangers that lurk behind the use and misuse of (inevitably) simplified measures. The report insists that "quality should always be a core part of productivity conversations, even when it cannot be fully captured by the metrics." It also emphasizes the complications stemming from joint production of outputs such as teaching and research, and the need to recognize a complex mix of inputs, including capital and student time.
In thinking about the implications of these myriad complications for the ways in which technology might impact the cost disease, I have been helped greatly by the authors of an article in the New England Journal of Medicine (NEJM), who have captured quite skillfully factors that explain what is known as the IT productivity paradox—the apparent tendency, noted by Robert Solow of MIT in 1987, for computerization to fail to improve standard measures of productivity. Solow noted famously, "You can see the computer age everywhere but in the productivity statistics," an observation said to have launched more than two decades of research into the sources of the paradox.
The authors of the NEJM article argue that explanations for the IT productivity paradox fall into various categories. Under the heading of "mismeasurement," they note that "important dimensions of service output such as accessibility and convenience—factors that are greatly improved by IT—are difficult to quantify and are rarely captured by productivity metrics." For example, ATMs increased consumer convenience in banking, but this increase in convenience, and all the time saved by customers, was not captured by traditional measures of productivity.
The authors go on to point out: "In terms of 'mismanagement,' the introduction of new technologies usually forces reexamination of the assumptions that underpin less productive processes." They give a telling example concerning the introduction of electricity in manufacturing: early on, "factories simply swapped large electronic motors for waterwheels and steam engines but retained inefficient belt-and-pulley systems to transmit power from the central power source. Real productivity gains came only after manufacturers realized that many small motors distributed throughout a factory could generate power where and when it was needed."
This discussion in the NEJM, aimed at implications for the health industry, resonates with the uses of IT in education. It is easy to think of examples, including the tendency in the early days of online teaching simply to mimic typical classroom teaching methods, often by videotaping lectures, rather than re-engineering the teaching process as a whole.
From the standpoint of our interest in the cost disease, it is critical to keep in mind that the productivity ratio has both a numerator and a denominator. Productivity improvements can be either output-enhancing (raising the numerator) or input-conserving (lowering the denominator). It seems evident that information technology has been extremely consequential in higher education over the last twenty-five years, but principally in output-enhancing ways that do not show up in the usual measures of either productivity or cost per student. It is important to distinguish between at least two broad types of educational "output": research findings and student learning outcomes. We should also recognize that there is a consumption component in the output numerator. The veritable revolution in information technology has had an especially large impact on research output. Data management systems and powerful number-crunching capacities have permitted research that would have been simply impossible otherwise. Work in particle physics and studies of the human genome are but two examples from the physical and life sciences. To cite a much more mundane example from the social sciences, the work that Derek Bok and I did on the effects of race-sensitive admissions would have been impossible without the construction of the large College and Beyond database. More generally, advances in communications, and the development of networks and systems for managing text and exchanging perspectives with colleagues at a distance, have revolutionized the way papers are prepared and revised—again and again! Yet these innovations do not show up at all in the usual measures of output.
Technology has also led to dramatic improvements in the scholarly infrastructure. If I may again cite activities that I know well, the creation of JSTOR (a highly searchable electronic database of scholarly literature) has changed fundamentally the way scholars use the back issues of journals and has had profound effects on libraries. Similarly, ARTstor (a digital repository of high-quality images) now permits art historians to study, for example, images of a Bodhisattva on the wall of a cave in Dunhuang, an oasis town on the Silk Road, alongside images of the same Bodhisattva on a silk painting at the Guimet Museum in Paris. It is worth emphasizing that these benefits generally do not accrue to the institutions that made the invest ments necessary to realize them. For example, the extra ordinary time savings for scholars made possible by both JSTOR and ARTstor do not prompt the institutions that employ the scholars to harvest these savings by, for example, increasing teaching loads (unimaginable!).
Although faculty and students have certainly benefited in many ways from easy Internet access, relatively little has happened with respect to classroom teaching—until quite recently. In the second part of this book, I will suggest that we are only at the beginning of the kind of re-engineering that could in time transform important parts—but only parts—of how we teach and how students learn. Most fundamentally, I will argue that we need to improve productivity in two ways: (1) through determined efforts to reduce costs—that is, we need to focus more energy on lowering the denominator of the productivity ratio; and (2) through new ways of increasing the student-learning component of the numerator of the ratio, principally by raising completion rates and lowering time-to-degree.
Factors Other Than the Cost Disease Pushing Up Educational Costs
As important as I believe the cost disease to have been (and to be) in putting upward pressure on instructional costs, I certainly do not think that it is the sole villain. Let me now mention ever so briefly three other forces behind the rise in costs. I recognize, of course, that this list is by no means comprehensive.
Inefficiencies
I am not one of those who looks with disdain at how poorly managed colleges and universities are often alleged to be. (I have seen too much of other organizations in all sectors of the economy, including the for-profit sector.) It is at least mildly annoying when, with no attempt to provide evidence, a business publication such as Forbes blithely asserts on its cover (of November 19, 2012) that "no field operates more inefficiently than education." I wonder if that is really true. Perhaps the time has come—if it is not past—when we should cease making such sweeping pronouncements (recognizing that colleges and universities in general have had much greater staying power than many for-profit businesses, which have been seen to fall by the wayside in surprisingly large numbers).
Still, it is hardly surprising that the severe financial pressures of our time have led to renewed calls for more business-like approaches. One consulting firm, Bain & Company, has found that universities such as the University of California, Berkeley, the University of North Carolina, Chapel Hill, and Cornell University are complex, decentralized institutions that could save money by simplifying oversight structures and centralizing functions such as human resources, information technology, and purchasing. In my view, just as it is wrong for business-oriented writers to assert that inefficiency is rampant, it is also unwise for academics to dismiss studies such as these out of hand as contributing to a "corporate mindset" in higher education. Universities do have to become more business-like in relevant respects at the same time that they have to retain their basic commitments to academic values.
(Continues...)
Excerpted from Higher Education in the Digital Age by William G. Bowen, Kelly A. Lack. Copyright © 2013 Princeton University Press. Excerpted by permission of PRINCETON UNIVERSITY PRESS.
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