Is There a Better Way to Rank Business Schools?

Patrick Perry and Keith Reigert, NYU Stern School of Business – April 4, 2016


A lot of people at Stern are angry about the data collection error that caused the school's U.S. News and World Report full-time MBA program ranking to drop from #11 last year to #20 this year. Stern failed to report the number of students that submitted GMAT scores to the school, and rather than alert the school to this omission, U.S. News chose to estimate the missing value. Some forensic data analysis, shows that the omission caused U.S. News to effectively replace Stern's average GMAT score (720) with a much lower value (560). We don't definitively know that this is what happened, but the evidence is compelling.

The missing-data debacle got us interested more generally about how business school rankings are determined in the first place. U.S. News describes the process on their website. They measure a set of eight attributes for each school and then reduce these eight values to a single numerical score by taking a weighted combination. Some people have taken issue with the sensitivity of rankings to the specific choices of weights used to combine the individual attributes. These critics certainly have a point, but to us, the more fundamental issue is that many of the measurements that U.S. News uses to rank business schools are themselves problematic.

While attributes like “Mean Starting Salary” and “Mean Undergraduate GPA” are, without a doubt, useful for prospective students deciding whether to apply to a school (and for assessing their chances of being accepted), these attributes may not have much to say about the quality of a school itself. Here is a breakdown of some of the specific measurement issues we see:

It's likely that U.S. News tries to adjust these measurements to fix some of the issues mentioned above, but it is not clear how they are doing this or how effective these adjustments are.

For ranking the “best” business schools, there are three attributes that, while by no means perfect, seem to be more trustworthy:

We don't have much insight into the different psychologies of business school deans and corporate recruiters, but empirically, “Peer Assessment” and “Recruiter Assessment” are strongly correlated with each other (correlation 0.83) and it seems to us like these numbers are two different measurements of the same attribute. To combine both into a single “Combined Assessment Score”, we standardize each to have the same standard deviation and take the average of the two numbers. To make the result more interpretable, we transform back to the original 1-5 scale; this effectively puts a weight of 45% on peer assessment and 55% on recruiter assessment.

Here's a scatter plot of the “Mean GMAT Score” and “Combined Assessment Score” for the ranked U.S. News business schools. Each point represents a school, with the x and y coordinates giving the respective attribute values. (Three schools have average GMAT scores below 600, and they have been excluded from this plot.)

plot of chunk unnamed-chunk-4

If we want to use these two attributes to rank the schools, there is a natural choice, which is to rescale the attributes appropriately and then give each equal weight. (This process has a geometric interpretation, which is that each point in the scatter plot gets mapped to the closest spot on the dashed line, preserving as much of the variability in the data as possible.)

Rescaling is necessary because GMAT scores (ranging from 200-800) are not directly comparable to assessment scores (ranging from 1-5). To make the values comparable, we subtract off the mean of each attribute and divide by its standard deviation. This ensures that each rescaled attribute has mean 0 and standard deviation 1. We then give each rescaled attribute a weight of 50%. To make the values more interpretable, after we compute the scores, we re-center and rescale them to have mean 75 and standard deviation 10, then round the values. The rounding process induces some ties between schools, but otherwise this transformation does not affect the final ranking.

The final formula for determining a school's score is

(Simplified Score) =  -39.14 + 0.125 (Mean GMAT) + 4.26 (Peer Assessment) + 5.28 (Recruiter Assessment)

The following table shows the rank and score for the top 50 schools as determined by this simplified method. We've also included the mean GMAT scores, the assessment scores, and the aggregate scores and rankings as reported by U.S. News.

Rank School Peer
Assessment
Recruiter
Assessment
Mean
GMAT
Simplified
Score
U.S. News
Score
U.S. News
Rank
1 Stanford University 4.8 4.5 733 96.6 98 2
2 Harvard University 4.8 4.6 725 96.2 100 1
3 University of Pennsylvania (Wharton) 4.7 4.5 732 96.1 97 4
4 University of Chicago (Booth) 4.7 4.5 726 95.3 98 2
5 Northwestern University (Kellogg) 4.6 4.5 724 94.7 96 5
6 Massachusetts Institute of Technology (Sloan) 4.7 4.5 716 94.1 96 5
7 University of California - Berkeley (Haas) 4.6 4.3 725 93.7 94 7
8 Yale University 4.3 4.3 721 91.9 90 8
9 Dartmouth College (Tuck) 4.3 4.3 717 91.4 90 8
10 Columbia University 4.4 4.1 715 90.6 89 10
11 New York University (Stern) 4.2 4.0 720 89.8 72 20
12 University of Michigan - Ann Arbor (Ross) 4.4 4.1 708 89.7 86 12
13 University of California - Los Angeles (Anderson) 4.1 3.9 713 88.0 79 15
14 Duke University (Fuqua) 4.3 4.1 696 87.8 86 12
15 University of Virginia (Darden) 4.1 4.0 706 87.6 87 11
16 Cornell University (Johnson) 4.1 4.1 697 87.0 80 14
17 University of Texas - Austin (McCombs) 3.9 4.1 694 85.8 76 16
18 University of North Carolina - Chapel Hill (Kenan-Flagler) 3.9 3.7 701 84.6 76 16
19 Carnegie Mellon University (Tepper) 4.0 3.8 690 84.2 75 18
20 Georgetown University (McDonough) 3.6 3.8 692 82.7 69 22
21 Washington University in St. Louis (Olin) 3.6 3.6 695 82.0 71 21
22 Emory University (Goizueta) 3.7 3.8 678 81.4 73 19
23 Vanderbilt University (Owen) 3.5 3.6 690 81.0 69 22
24 University of Southern California (Marshall) 3.8 3.6 679 80.9 64 31
25 University of Texas - Dallas 2.9 4.2 678 80.1 61 37
26 Indiana University (Kelley) 3.8 3.6 668 79.5 69 22
27 University of Notre Dame (Mendoza) 3.5 3.5 682 79.4 66 25
28 University of Minnesota - Twin Cities (Carlson) 3.5 3.4 680 78.7 65 27
29 Rice University (Jones) 3.4 3.5 676 78.3 66 25
30 University of Washington (Foster) 3.4 3.2 688 78.2 65 27
30 Georgia Institute of Technology (Scheller) 3.2 3.6 678 78.2 63 34
32 University of Wisconsin - Madison 3.6 3.4 669 77.7 65 27
33 Arizona State University (Carey) 3.4 3.4 672 77.2 62 35
34 Ohio State University (Fisher) 3.5 3.4 664 76.7 65 27
34 University of California - Davis 3.2 3.2 683 76.7 56 45
36 Brigham Young University (Marriott) 3.0 3.5 674 76.3 64 31
37 Michigan State University (Broad) 3.3 3.4 664 75.8 62 35
38 University of Maryland - College Park (Smith) 3.4 3.4 658 75.5 57 41
39 Texas A&M University - College Station (Mays) 3.3 3.5 654 75.1 64 31
39 Boston University (Questrom) 3.1 3.0 682 75.1 57 41
39 University of Alabama (Manderson) 2.7 3.4 679 75.1 50 53
42 University of Illinois - Urbana-Champaign 3.4 3.3 654 74.5 60 39
43 Boston College (Carroll) 3.2 3.2 664 74.3 53 50
44 University of Florida (Hough) 3.3 2.7 681 74.2 61 37
45 University of California - Irvine (Merage) 3.1 3.4 656 74.0 54 48
46 University of Rochester (Simon) 3.2 3.0 667 73.6 60 39
46 University of Iowa (Tippie) 3.1 3.0 670 73.6 56 45
48 Southern Methodist University (Cox) 3.1 3.2 656 72.9 54 48
49 Purdue University - West Lafayette (Krannert) 3.4 3.4 635 72.6 55 47
50 Pennsylvania State University - University Park (Smeal) 3.2 3.5 636 72.4 57 41

The simplified GMAT/assessment ranking method gives reasonable results, comparable to U.S. News in most cases. The U.S. News ranking method is much more complicated. Which ranking is better? We're obviously biased, but in this situation, like in most other situations, we prefer the simpler method. With the U.S. News system, we have concerns about many of the inputs, and we don't have much confidence in the weights used to compute the final scores. With the simplified method based on GMAT and assessment, we have confidence in all of the inputs and we can understand how they relate to the final score.


Patrick Perry (@ptrckprry) is an Assistant Professor of Information, Operations, and Management Sciences at NYU Stern.

Keith Reigert (@KeithRiegert) is an MBA candidate at NYU Stern and an editor at the Stern Opportunity.

The raw data used to compute the rankings, was originally collected and reported by U.S. News. The plot and the table in this article were produced using the R software envionment. The data and source code are available for download.


Appendix

Quality measures

To validate our intuition that many of the factors used in the U.S. News ranking are poor proxies for school quality, we looked at scatter plots of all seven attributes versus the schools' mean GMAT scores. In these plots, each point represents a school.

plot of chunk unnamed-chunk-8

From these plots, it is clear that “Employment Rate at Graduation”, “Employment Rate Three Months After Graduation”, “Mean Undergraduate GPA”, and “Acceptance Rate” are poor measures of school quality in that they appear only slightly related to “Mean GMAT Score” (arguably the most reliable measure of school quality).

Despite its strong relationship with “Mean GMAT Score”, we still feel uncomfortable including “Mean Starting Salary” as a ranking factor due to its strong dependence on geography (the highest quality schools tend to be located in cities with high-paying jobs).