A Revealed Preference Ranking of U.S. Colleges and Universities *
Abstract
We present a method of ranking U.S. undergraduate programs based on students’ revealed preferences. When a student chooses a college among those that have admitted him, that college “wins” his “tournament.” Our method efficiently integrates the information from thousands of such tournaments. We implement the method using data from a national sample of high-achieving students. We demonstrate that this ranking method has strong theoretical properties, eliminating incentives for colleges to adopt strategic, inefficient admissions policies to improve their rankings. We also show empirically that our ranking is (1) not vulnerable to strategic manipulation; (2) similar regardless of whether we control for variables, such as net cost, that vary among a college’s admits; (3) similar regardless of whether we account for students selecting where to apply, including Early Decision. We exemplify multiple rankings for different types of students who have preferences that vary systematically.
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Many of the highest mobility rate colleges, such as California State colleges and a number of community colleges, are not highly selective in terms of student observables such as SAT scores or revealed preferences.
“In particular, many of the highest mobility rate colleges -such as the California State colleges and a number of community colleges -are not highly selective institutions in terms of student observables such as SAT scores or based on students' revealed preferences (Avery et al. 2013).”
From Mobility Report Cards: The Role of Colleges in Intergenerational Mobility (2017) · cites this paper as Avery et al. 2013
Section I (p. 4) supports the use of students’ revealed preferences to rank colleges. But the paper says its ranking covers only about a hundred undergraduate programs, and the cited passages do not establish that California State colleges or community colleges have low selectivity by SAT scores or revealed preferences. It also does not address which colleges have the highest mobility rates. (LLM, conf=0.78)
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Research works printed but not linked: 16
- Avery, Christopher, Andrew Fairbanks, and Richard Zeckhauser. The Early Admissions Game: Joining the Elite . Cambridge, MA: Harvard University Press, 2003.
- Avery, Christopher, and Caroline M. Hoxby. The College Admissions Project: Counselor Report . Cambridge, MA: The College Admissions Project, 2000.
- Avery, Christopher, and Caroline M. Hoxby. "Do and Should Financial Aid Packages Affect Students' College Choices?" in Caroline M. Hoxby, ed. College Choice: The Economics of Where to Go, When to Go, and How to Pay for It . Chicago: University of Chicago Press, 2004.
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- Glickman, Mark E. "Paired Comparison Models with Time Varying Parameters," Doctoral thesis, Harvard University Dept of Statistics, 1993.
- Glickman, Mark E. "Parameter Estimation in Large Dynamic Paired Comparison Experiments." Applied Statistics , 48 (1999), pp. 377-394.
- Glickman, Mark E. "Dynamic Paired Comparison Models with Stochastic Variances," Journal of Applied Statistics , 28 (2001), pp. 673-689.
- Good, Irving J. "On the Marking of Chess Players," Mathematical Gazette , 39 (1955), pp. 292-296.
- Luce , R. Duncan. Individual Choice Behavior . Wiley: New York, 1959.
- Thurstone, L.L. "A Law of Comparative Judgment," Psychological Review , 34 (1927), pp. 273-286.
- Manski, Charles F., and David A. Wise. College Choice in America . Cambridge: Harvard University Press, 1983.
- Mosteller, Frederick. "Remarks on the Method of Paired Comparisons. I. The Least Squares Solution Assuming Equal Standard Deviations and Equal Correlations," Psychometrika , 16 (1951), pp. 3-9.
- Spence, Michael. "Education as a Signal," Chapter 2 in Market Signaling . Cambridge: Harvard University Press, 1974.
- Stern, Hal. "Are All Linear Paired Comparison Models Empirically Equivalent?" Mathematical Social Sciences , 23 (1992), pp. 103-117.
- Wall Street Journal. "Glass Floor: How Colleges Reject the Top Applicants and Boost Their Status," Wall Street Journal , May 29, 2001.
- Zermelo, Ernst. "Die Berechnung der Turnier-Ergebnisse als ein Maximumproblem der Wahrscheinlichkeitsrechnung," Math. Zeit. , 29 (1929), pp. 436-460.
Cited by
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Mobility Report Cards: The Role of Colleges in Intergenerational Mobility
Chetty, R., Friedman, J., Saez, E., Turner, N., & Yagan, D. (2017) · National Bureau of Economic Research · doi:10.3386/w23618 · Cited by 632 · see citing works
Why Don’t Elite Colleges Expand Supply?
Blair, P., & Smetters, K. (2021) · doi:10.3386/w29309 · Cited by 16 · see citing works
- Authors
- Avery, C. N., Glickman, M. E., Hoxby, C. M., & Metrick, A.
- Affiliations
- National Bureau of Economic Research (US)
- Venue
- The Quarterly Journal of Economics
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-12-13
- Volume
- 128
- Issue
- 1
- Pages
- 425-467
- ISSN
- 0033-5533 (ISSN-L)
- 1531-4650
- OpenAlex
- W2144427781
- Cited by
- 97
- References
- 0
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 6 · 2023: 9 · 2022: 9 · 2021: 9 · 2020: 9 · 2019: 7 · 2018: 7 · 2017: 2 · 2016: 6 · 2015: 2 · 2013: 2 · 2012: 6
- FWCI
- 7.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Quarterly Journal of Economics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Game Theory and Voting Systems
- Social Sciences › Education › School Choice and Performance
- Social Sciences › Education › Higher Education Research Studies
- Keywords
- university rankings, revealed preference, tournament ranking, university admission, early decision, student preferences, undergraduate programs, high-achieving students, net cost, preference heterogeneity
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