chimerical

Many seem to hold off on TAing but it's not uncommon to starting RAing in the first year.

I understand, I'm just taking a wait-and-see approach. I figure there's no use worrying about something if I'm not even sure it'll be an issue. :)

That's a bit of a generalization. I too am wondering how fast I'll be able to complete my PhD and haven't given much thought to the other things you listed.

LOL, the guys around here aren't bad. Try perusing a video game, comics, or automotive forum. :p

figuringout is in a strategy program, it's just one that takes a more disciplinary approach. You'll find that programs can run the spectrum from very discipline-based to those that are more multidisciplinary and focused on management itself.

Whoops, I never posted here did I? Domestic applicant applying to programs in strategy. Undergrad GPA: 3.97 from Top 10 undergrad (summa cum laude) Grad GPA: N/A GMAT/GRE: 760 (48Q, 48V, 6.0 AW) Age: 22 International/US: US Research Experience: Senior honors thesis (with departmental distinction), RA at top strategy department, three conference presentations, one minor journal article Accepts: Stanford, Wharton, Duke, Chicago, UCLA, Michigan, Illinois, Toronto Waitlist: HBS Reject: MIT Anything Else notable: Couple years of work experience in quant/stat-heavy job

I think you may have misunderstood what HBS said. While they do start reviewing and meeting before the application deadline, they don't have rolling admissions in the traditional sense. They didn't even conduct interviews until about one and a half months after their deadline. Now it may still help to get your application in early in that you might have a better chance of standing out before review fatigue sets in for the admissions officers (though that can cut both ways - it might be better to be later and fresh in their minds), but I haven't seen anything to suggest that HBS fills up the class or shortlist before the deadlines. To the contrary, applicants are routinely shuffled between concentrations and then admitted months after the deadline.

From talking to students I've heard it can be a little rough if you are the only person in your class (as is relatively common in smaller programs). Regardless though, it's probably best to not assume you'll be automatic friends with people in your cohort. They may be in different phases of their lives or your personalities might not click. Fortunately, university campuses are usually pretty vibrant places and if you make a little effort to put yourself out there and meet people (which isn't always easy, I know) you should be able to carve out a decent social network. As for being lonely during the dissertation phase, well, take breaks and tap into that social network. :)

R is the most commonly used free option, but if you have access, I think SAS or Stata would be more useful to learn. I prefer SAS as it makes it a bit easier to manipulate large datasets but Stata comes with a better set of "prepackaged" statistical analyses, so it's really a matter of what you want to use it for.

Congrats! In the end fit is what matters most, IMO.

So you've decided on Columbia? Congrats!!

Well, not everything is on SSRN or Google Scholar, and if you don't have institutional access to the top journals it can still be pretty hard to get a hold of things. I've had to conduct tons of lit searches at work and even with our access to databases like JSTOR and EconLit it can be hard to actually find full-text articles. :p

Glad to help. Good luck with your decision!

Thanks! Definitely excited. :D

Some programs require you to make a deposit when you accept their offer, so if that's the case you'd lose that. But other than that there wouldn't be any strict financial or legal consequences. The bigger worry is if you want to apply again in the future, as backing out of an accepted offer may well kill your chances at being re-admitted to that school in the future.

Yup, strategy to be specific.

SSRN is a great resource. In addition, Google Scholar can sometimes turn up PDFs hosted on university websites. It may not be the final published version but it's usually enough to get the general idea.

Naw, we're both going into management. I don't know much about Haas marketing so I can't offer any advice there, but if it's not a good fit for your interests, I wouldn't spend too much time considering it.

Congrats! American was my vote as well but either way I think you were right to trust your instincts.

I think all else equal it's usually better to branch out a bit and go somewhere new for your PhD, unless your home department is exceptionally strong. In this case it seems like Queens is a stronger program. Talk to current students to get a sense of the environment and their relationship with faculty and check faculty research to see if it's strong enough in corporate finance. If you get positive responses to both then I would suggest Queens.

lol, thanks! Took me long enough, I know. :p

I was in a similar position. Try to figure out which one you would regret less, if that makes any sense.

You should definitely be able to get some guidance from the program coordinator. Even programs with very flexible curriculums usually have some strongly recommended theory and methods courses for first-years.

Once I got the hang of it I actually found SAS much easier to use overall, though STATA certainly has a better range of pre-packaged statistical tools.