A research-based ranking of public policy schools
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A research‑based ranking of public policy schools Elliott Ash1 · Miguel Urquiola2 Received: 5 February 2020 © The Author(s) 2020
Abstract This paper presents rankings of U.S. public policy schools based on their research publication output. In 2016 we collected the names of about 5000 faculty members at 44 such schools. We use bibliographic databases to gather measures of the quality and quantity of these individuals’ academic publications. These measures include the number of articles and books written, the quality of the journals the articles have appeared in, and the number of citations all have garnered. We aggregate these data to the school level to produce a set of rankings. The results differ significantly from existing rankings, and in addition display substantial across-field variation. Keywords University rankings · Research productivity · Quantity vs quality in research · Public policy schools
Introduction Recent years have seen an increase in the number and variety of university rankings. This growth is likely due, at least partially, to demand for information from participants in educational markets. For instance, prospective students might wish to see measures of university reputation, given that attending different schools has been shown to have a causal impact on individuals’ career outcomes.1 Moreover, universities pursue a diversity of goals: While some individuals may be interested in which schools offer the most financial aid or the smallest classes, others may be interested in which generate the greatest gains for low-income students.2 1 Hoekstra (2009), Saavedra (2009), and Zimmerman (2016) show that college selectivity can affect labor market outcomes. See also MacLeod and Urquiola (2015) and MacLeod et al. (2017) for theoretical and empirical analyses of the impact of school reputation on labor market earnings. 2 For example, Chetty et al. (2017) rank colleges according to different measures of their ability to produce income mobility. Diversity of rankings may also reflect that educational institutions use many inputs to produce multiple outputs.
For useful comments we are grateful to Scott Barrett, Richard Betts, Steven Cohen, Page Fortna, Merit Janow, Wojciech Kopczuk, Bentley MacLeod, Dan McIntyre, Victoria Murillo, Justin Phillips, Cristian Pop-Eleches, Wolfram Schlenker, Joshua Simon, and Eric Verhoogen. For excellent research assistance we thank Kaatje Greenberg, Sanat Kapur, and Vu-Anh Phung. All remaining errors are our own. * Elliott Ash [email protected] Miguel Urquiola [email protected] 1
ETH Zurich, Zurich, Switzerland
2
Columbia University and NBER, New York, US
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Vol.:(0123456789)
Scientometrics
In this environment—and especially given expanding data availability—the best outcome might be for a large amount of information to be available on each school. Using these data, market participants can generate rankings focused on the inputs or outputs of their interest. Consider the case of undergraduate college rankings as exemplifying such a high-inform
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