Perverse Incentives? How Economics (Mis-)shaped Academic Science

By Ken Chiacchia, Senior Science Writer, Pittsburgh Supercomputing Center

July 12, 2017

The unintended consequences of how we fund academic research—in the U.S. and elsewhere—are strangling innovation, putting universities into debt and creating numerous PhD graduates and postdoctoral fellows who will not be able to get jobs in their chosen fields, according to economist Paula Stephan of Georgia State University.

The good news, Stephan said at the opening plenary session of the PEARC17 conference in New Orleans on July 11, is that researchers probably needn’t go back to the politicians to ask for more money. The bad news: the current system is so ingrained it’s hard to be optimistic.

“I don’t think it would take more funding to [encourage] more risk,” she said, but “unless we change the incentives in the system we’re going to continue to overbuild and over train.”

Stephan identified three major effects of the perverse incentives governing academic research: over-training, risk aversion and over-building of physical infrastructure. All three are problems in their own right but also feed back to make the situation worse.

“Economics is about incentives and cost,” Stephan explained, and both are problematic in most national funding systems. She particularly examined that of the U.S.

The Inaugural Practice and Experience in Advanced Research Computing (PEARC) conference—with the theme Sustainability, Success and Impact—stresses key objectives for those who manage, develop and use advanced research computing throughout the U.S. and the world. Organizations supporting this new HPC conference include the Advancing Research Computing on Campuses: Best Practices Workshop (ARCC), the Extreme Science and Engineering Development Environment (XSEDE), the Science Gateways Community Institute, the Campus Research Computing (CaRC) Consortium, the Advanced CyberInfrastructure Research and Education Facilitators (ACI-REF) consortium, the National Center for Supercomputing Applications’ Blue Waters project, ESnet, Open Science Grid, Compute Canada, the EGI Foundation, the Coalition for Academic Scientific Computation (CASC) and Internet2.

Over-training: A Plague of PhDs

Increasingly, Stephan argued, universities are following a “high-end shopping mall” model in which they “lease” space to researchers—the “stores.” Physical building, particularly during the funding increases of the 1990s, became a priority as universities vied to attract top-performing (read: highly funded) research faculty. One down side to this model, though, is that individual principal investigators took on so much of the risk. With about 95 percent of research faculty paying their own salaries through soft money, funding has become existential and devours increasing amounts of the average lab head’s time: One study estimated that PIs spend 42% of their professional time on grant administration and writing.

“This raises the issue of how you’re going to staff your lab,” Stephan said. While few researchers make a conscious decision to bias hiring toward some types of research workers, the economic pressures often give little choice.

The issue is stark in the decision of whether to employ graduate students, postdoctoral fellows or staff scientists to conduct lab research. Nationally, graduate students average a stipend of about $26,000 annually; in addition, they represent approximately an additional $16,000 or more for tuition and other student costs. Their hourly “pay rate,” then, can be between $19.50 and $27.50.

Postdoctoral fellows are paid more. But they also have no tuition costs and at most universities have few additional benefits. Assuming a university follows the NIH benchmark of $43,692 for a first-year postdoc, their hourly rate comes to around $17 to $18, depending on the field.

Staff scientists start at about $60,000 to $75,000, coming out to an hourly rate of about $30.00. But that doesn’t reflect their full cost, which includes much more extensive benefits than students or postdocs.

Given this incentive structure, Stephan explained, it isn’t hard to understand the relative scarcity of staff scientists. Her own study found that at least 72 percent of academic research papers had postdocs or grad students as their first author. In the NSF’s annual survey, life science PhD graduates with definite job commitments have fallen from a peak of 70% in 1994 to 58% in 2014—and most of those are going to postdoc positions, not permanent jobs.

With the scarcity of permanent positions for these postdocs to go to next, “academe has become the alternate career track” for PhDs, particularly in physics and the physical and life sciences, she said.

“Training [has become] less about the future supply and more about getting research and teaching done now,” Stephan said.

Aversion to Risk

Along with the oversupply of PhDs, the funding structure has created an atmosphere in which risk-taking is discouraged in the funding process. In an influential Proceedings of the National Academy of Science USA paper, biomedical giants Alberts, Kirscher, Tilghman and Varmus criticized biomedical research funding as overly risk averse. Researchers have perceived a similar problem in the physical sciences: Even DARPA, which once self-identified as funding risky projects, has been criticized for being over-cautious.

At the stage of grant application reviews, the common requirement for preliminary data among many reviewers tilts the field against high-risk projects. So does the use of bibliometric measures of author impact. The short-term nature of the funding cycle also discourages novelty: “It’s hard to recover from failure in three years,” Stephan said. And since the success rate for grant continuations is higher than that for new grants, the system encourages researchers to “stay in their lanes.”

“The stress on ‘translational’ outcomes” that provide immediate practical applications “also discourages risk,” she added.

Another study showed that highly novel papers tend to show pronounced payoffs at 13 years after publication but little at three years. Non-novel papers, on the other hand, pay off better at three-year cycles—but don’t improve over time.

If You Build It, They Will Not Necessarily Come

Overbuilding—the construction of unneeded university brick and mortar—came with the NIH budget doubling in the late 1990s. Universities, assuming continued growth, embarked on a “building binge” to attract top grant-attracting faculty. They borrowed to do so, partly because interest payments for debt service can be included in calculating indirect costs charged against those grants—and thus it would, presumably, “pay for itself.”

From 1988 to 2011, biomedical research floor space at the average university increased from 40,000 square feet to 90,000 square feet.

When funding declined in real dollars, unrecoverable debt and even facility mothballing followed. The annual average university debt service grew from $3.5 million in 2003 to $6.9 million in 2008. It created an economic drag on many research universities that will be hard to escape.

“All disciplines will pay for this, not just the biomedical sciences,” Stephan said.

The Way Out?

The irony, of course, is that the primary justification for government-funded research is to take risks that industry can’t.

For economists, the case for academe starts with a concept called “market failure,” Stephan explained. It’s the term used to describe the way most firms avoid overly risky projects; the difficulty of capturing financial benefits from fundamental discovery is a particular disincentive to pursue that which does not pay off in the near term.

“But the risky stuff shifts knowledge frontiers, eventually contributing to economic growth,” she said.

Excellence is not the same thing as risk-taking, Stephan took pains to add. Not all excellent research takes big risk; not all risky research is of high quality.

“I think as a country we need a portfolio,” she said. “It does not mean that there is not a substantial role for what we call ‘normal’ research.” But if we don’t change the incentive structures of our funding process—rewarding outcomes over longer time periods, creating incentives to encourage permanent rather than temporary jobs and make living on “soft money” less precarious, we won’t see the kind of innovation in which academic research was supposed to specialize.

“I’ve been working at this for too long, so I’m not wildly optimistic,” Stephan admitted.

Ken Chiacchia, Senior Science Writer, Pittsburgh Supercomputing Center, is following a non-traditional career path for science PhDs.

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