College Selection

Now, you are all done with your exams and college application season is just around the corner. It is time to put in some work into college selection. There are two aspects to it: particularity and breadth.

Make sure you are very specific about the colleges you are choosing to apply, and this specificity should ideally come from research fit (nothing else). For example: if you are interested in behavioral finance, University of Miami is definitely a place you should apply irrespective of its MBA ranking. There could be other idiosyncratic reasons, such as location preference, someone you know at the school, a lesser number of required recommendations. Try not to take these factors into account; however, if you do, make sure not to mention this in your application. It will just dilute your case of research focus.

Now the question is how you find which school works in the field that you want to pursue. Unfortunately, the only way forward is tedious and manual. You have to go to each school’s website and check out past research work by professors, current ongoing work and find at least two (preferably three) professors who work in a similar field. This will also help in your essays as well.

Once you have gone through all the schools/ professor websites, you have a list of colleges with good research fit. Now you need to focus on the second part: breadth. The one basic fact to be kept in mind is doctoral admissions are brutal with admissions rate sub 5% for most of the schools, till hundredth rank. For example, 2014 Wharton data:

Concentrations  Applicants Admitted %
Accounting 71 2 2.8%
Applied Economics 210 4 1.9%
Finance 204 7 3.4%
Health Care Management & Economics 55 4 7.3%
Management 146 4 2.7%
Marketing 124 3 2.4%
Operations, Information Management & Decision Processes 118 7 5.9%
Statistics 184 6 3.3%
 Total 1112 37 3.7%

City University of New York University data:

Year Total Applicants Offers Accepted %
2014 205 10 4.9%
2013 161 13 8.1%
2012 129 14 10.9%

As such, it becomes imperative to apply widely and across rankings. There would be few colleges, that may not take students in a particular area in a year or have selected someone from masters and will take them via admission process. So there is a chance that some of your application will just go to waste. Therefore, anything below eight applications is less; however anything above twenty is too much pressure on you and your recommenders. Ideally, you should plan for somewhere between twelve to fifteen schools.

There is one more problem with doctoral admissions – it does not take place in rounds as MBA application does. So what it means is, since the time you know that you have been rejected or someone else is giving interviews (implicit rejection), the window of application will be closed. This coupled with a limited number of intakes per college makes it a good idea to apply to at least four categories of college (based on rankings). As in, if you are applying to twelve places and reasonably certain that you would get into college ranked around thirty, make sure to have three colleges in 1 -15, 16-30, 31- 50, 51 – 70.
For ranking colleges, you could use UTD/ ASU/ US News rankings and weight them as per your preferences.

Lastly, I would like to stress, choose colleges based on research fit, not rankings. Rankings are good if you want to get placed as an average student at the college and concepts of average work well when you have bigger samples (such as MBA, engineering cohort). However, for PhD (especially in B-Schools) there would be two or three students with you and placement/ success or happiness would totally depend on how much you enjoy the particular field you are working on and how much effort you put in. So reach up or go down in terms of college rankings to get to the college that fits you.

 

2 thoughts on “College Selection

  1. Thank you for sharing your thoughts.
    I am wondering whether I should include European Colleges in the mix; also which ranking should I use to compare them with American Schools.
    Thanks

    Like

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