From the Wall Street Journal, November 6, 2014.
I find this very interesting (full disclosure, I have both attended graduate business school and now I teach at the graduate level for business students). It is also reflective of how some Economics programs (additional disclosure, I also have a graduate degree in Economics) select their PhD candidates: take everybody who did perfectly on the GRE (score of 800) and select admits from that pool. Many programs, having experienced poor results from that selection process, determined that having PhD programs comprised of 90% Asians compromised the program quality. For my PhD applications and admission process I emphasized that I was adept at quantitative analysis as a tool of research but that I was never going to be the next great mathematical economist – instead, I focused on playing to interdisciplinary skills, broad knowledge base, excellent writing and communication abilities, professional background, and a history of successful research at the MSc level. I was successful at gaining admission to a couple top-tier programs, but there was a clear divide in my admissions: schools focused on applied modelling made offers while those focused on theory did not. This is a result of the split in the education of economics, where some schools are heavily focused on particular aspects of the field – and of course a result of the different aptitudes of the practitioners of economics.
To me, this is also the difference between significance in a statistical sense and significance in the sense of “importance” (for an interesting read on this see Donald N. McCloskey, The Loss Function has been Mislaid: the Rhetoric of Significance Tests, AEA Papers and Proceedings, May 1985). More and more schools are realizing that while quantitative skills are the largest predictor of success in the program, it is possible that other factors predict professional success (we can also say that success in the program is probably a predictor of professional success, and thus the tests are indicators of future potential). But those other factors are typically dominated by Western students. [Cheating aside] when we note that Asian students are far more adept at quantitative testing, we should be careful to note their ability to apply it to interesting (important) problems. Japanese and Korean students tend to be much better at this than Chinese students (in my limited experience, Indian students have very mixed outcomes with very high variance in quality).
I can note that different institutions focus on education and training to different ends, and that the professions and advancement of economics and management relies on both great theory and great application – the question is: do the tests tell us which students are which? I think more and more schools across all professions (economics, management, sciences, medicine, etc…) are starting to differentiate between students using many other metrics than test scores and transcripts.