treblekicker

i'm assuming you took abstract algebra if you are a math major. in which case, you either already know most of the linear algebra that you need or could easily fill in the gaps through self study. and to be honest, if you do well in measure theory, you can always learn higher level linear algebra concepts through functional analysis. but it also depends on your goals. if you want to be a reg monkey, then by all means take linear algebra. but if you have other aspirations, more abstract math will do you good.

You're drastically overthinking the depth of thought that goes into this process. The committee takes this process very seriously, but at the end of the day, time is limited, and faculty aren't going to take a deep dive into every aspect of your transcript. That said, if you are taking Functional Analysis, and you are demonstrating an interest in fields that would actually use Functional, someone will likely take note of this. If you are just looking to do something outside of Theory, I wouldn't recommend taking Functional Analysis. Some of the first year content will be slightly easier if you understand basic Functional Analysis results (kind of like knowing some Topology), but even certain branches of theory don't see huge returns beyond basic Measure Theory. Metrics will use a good amount of Functional, but Micro Theory just regurgitates standard arguments.

Don't use Repec, it's not very informative. A lot of faculty do not keep their Ideas profile up to date, so often you'll see faculty affiliated with the wrong department.

This is a bad idea. The median placement at a top 20 school is very similar to a fringe top 10 school. So I would only consider transferring if your current program is a bad fit for your research interests (or for personal reasons, of course). There isn't a lot of upside to transferring, and the downside is huge. Unless you are far into your current program, transferring often requires that you redo some of your progress -- either starting over, or at least retaking qualifying exams. On top of this, even if you successfully get into a higher ranked program, you are going to piss off the faculty at your current school. And even if you transition into a Business program, the profession is very cliquey, and people talk.

yeah i definitely misspoke on the necessity of a JD/PhD. i was mainly just trying emphasize the difficulty of making partner when starting with just a bachelors. and yes, lit consulting also has the lawyer interactions, but relative to most other industry options, it closest resembles academic work (this also depends on which firm you are with).

If you're looking up people with the title 'Economist', then you're looking at the wrong position. This is a very senior position at the big banks. These banks will often hire PhDs into the position of 'Quantitative Analysts' (the title varies from bank to bank). You're basically a backroom employee working on stress tests and the like. This has become huge after Dodd-Frank. They also hire MBAs and graduate students from other quantitative disciplines (Stats, Math, Physics, etc.) into this position. At the end of the day, they're largely looking for people who are strong in the programming language that they use (mostly SAS and some MATLAB), and those who can be commercial (i.e., they can communicate their work to non-technical staff). As far as consulting goes, there are two man branches: management and litigation. You can work in both with only an undergrad degree, though there's a limit to how far you can go with only a bachelors or masters in lit consulting. With management (think McKinsey, Boston Consulting, etc.), your degree doesn't matter at all, and anyone with the right skill set (strong communication skills, good presentation skills, willingness to travel constantly) can go far. But this is also a hellish job (80 hour weeks, living in a hotel five days a week). With lit consulting (think Cornerstone, CRA, NERA, etc.), you really need a JD or a PhD to max out, though again you need to soft skill to progress in this career. Most PhDs find lit consulting to resemble their PhD work, but it's also a real world job with deadlines and bosses. Lit consulting generally targets Finance and I/O students, but some also hire Labor, Health, and Theory. There's also Transfer Pricing, which sort of resembles consulting. You work for the big tax advisory companies (KPMG, Deloitte, EY, and PWC), and again it is a job that an undergrad can do. Like all of these other jobs, you are compensated for your degree, but be ready to work with people with just a bachelors or an MBA. They're looking for a similar skill set as management consulting, though the hours are a lot better (pay is worse). Tech companies have been targeting Econ PhDs the last several years (Amazon, Microsoft, Uber, Facebook, etc.). The role of these jobs vary, but essentially you're a data analyst, so they're looking for candidates who are strong with Python, SQL, Hadoop, etc. For instance, the Amazon interview consists of putting you in front a computer with several programs loaded on and a data set. They give you a fixed amount of time, and ask you to analyze the data as best you can in the time limit. Exactly what you study doesn't really matter, but empirical I/O is generally going to give you the best training for these jobs, as a lot of them want people who are comfortable with auctions. There are other private sector options, like non-profit research organizations (RAND, RTI, CNA, etc.). These jobs are similar to working for the federal government. If you do finance, there are more options available to you, like working on Wall Street.

yes they do... most of the major commercial banks were interviewing at aea, and often hire phds into quant positions. that said, you do not need a phd to succeed at this job (or get hired, for that matter). and management consulting just hires any phd.

all of the rankings are heavily flawed. Penn is a top 10 program, definitely worse than Harvard, MIT, Princeton, Stanford, and Berkeley. Penn is more or less on par with Chicago, Yale, Columbia, Northwestern, and NYU, though toward the bottom of that group.

echoing chateuheart, if you're into something as niche as decision theory, you shouldn't be picking schools, you should be picking advisors. as i mentioned earlier in this thread, decision theory is super narrow -- very few schools outside of the top 50 have any decision theorists, and it is the least employable subfield outside of academia. if you don't already know who you want to work with, i would suggest applying to schools in general for theory. to that end, sloan and booth are fine choices. though as far as i know, neither are great for decision theory. they do have behavioral science groups, if that's what you're interested in.

I agree that topology pops up very often, but a lot of the intuition you need for this sort of stuff comes naturally through a real analysis sequence. (If you want to work with someone like Chris Shannon, sure, this approach won't cut it.) On the other hand, not all first analysis courses cover measure theory, and basic measure theoretic ideas are relatively common, especially if the OP wants to do GT/Mechanism Design.

both would be helpful for theory, but you can read 80% of theory papers with a strong footing in basic analysis and a shallow understanding of measure theory (it's almost always a very standard argument). a course like stochastic processes would help in filling in that final 20% (specifically w/in dynamic games and dynamic mechanism design), but any worthwhile stochastic processes course should require measure theoretic probability. convex optimization is definitely helpful, but it's also material that you can easily just pick up along the way, either through self-study or through a class like functional analysis. so i would recommend the 'focus on measure theory' option.

For someone with your profile, there is little value added to PhD Micro. I would focus on your honors thesis.

Warwick (Stovall and Safra, Segal in the business school) is the best one I can think of. LSE (Ellis) is a good choice if you are open minded, as they have a large group of PoliSci and Phil faculty that study decision theory, though obviously from a different angle.

BU, Duke, and Caltech are probably toward the top end of where you should target. PSU (not a lot of decision theory here, though Chatterjee has done some DT) and Rochester (Kochov, though he's still just an AP) would be good fits as well. Schools like UCLA (Lu) and WUSTL (Natenzon, still an AP, but he works with Gul and Pesendorfer) are worth considering because of their overall strengths in theory.

Probably missing a lot, but this is what I could think of off of the top of my head: Northwestern (Dekel, Siniscalchi, Klibanoff, Olszeski, etc.), Princeton (Gul, Pesendorfer), BU (Epstein, Lipman), Bocconi (Maccheroni, Mariccani, etc.), Berkeley (Ahn, Ergin), Caltech (Border), Duke (Sarver, Sadowski), Penn (Dillenberger), NYU (Ok), Harvard (Strzalecki), Tel Aviv (Gilboa) Theory is already the toughest field, and Decision Theory is the most difficult w/in Theory, so tread carefully when deciding to study DT. I would generally suggest NW and Princeton, as they're both fantastic for Decision Theory and Theory in general (in case you change your mind). Stanford and MIT, despite being the other two best schools for Theory in general, don't really have much in the way of Decision Theorists. Outside of the top 10, BU is the best for Decision Theory.

If a faculty member at a top10 university (assuming he/she isn't a total deadwood) recommends that you take the Math Boot Camp and PhD Micro, then that is a strong signal that he/she thinks you are ready. That said, if you're especially risk averse, there's not a lot of downside to waiting until your Senior year.

Definitely Duke. If there are faculty at the higher ranked school who are aligned with your interests, (almost) always take the higher ranked program.

Disregard this post.

BU's placements are far from top 10. It's a strong school, but like UMD, definitely MRM. Both have fine academic placements. The major difference is that UMD is far better at placing people into gov't, whereas BU has very strong industry placements.

Most of this I don't feel very comfortable answering, but I'll cover what I can. Yes, theory is generally a terrible choice outside of a few programs, but plenty of MRM/LRM students fall into theory for various reasons. This was definitely the case at UNC. As for why all four UNC theory students have the same advisor, I think you can figure this out if you do some research on UNC faculty. And as for why some of the candidates also have empirical papers. Well, if you're doing any sort of theory outside of a handful of schools, you really need to do applied theory. And it can be difficult to sell this if you don't make efforts to appeal to empirical faculty. So many theory students end up producing some empirical work before they go on the job market. This helps a lot with lower ranked programs and non-academic jobs, as you can credibly say that you've done data work. But if you read this work carefully, it's clearly not the main focus of most theory students.

Since you're interested in Applied Micro, I would go with UNC. Almost all of UNC's best placements are in Applied Micro. And there is a good mix between senior and junior faculty in most fields, though mostly Health, Labor, and I/O. Unless you want to specifically work with Ghysels or Hill, I would opt for UT Austin. But yes, there is collaboration across the Triangle, and UNC students take classes at Duke. It is not uncommon for Duke faculty to sit on UNC dissertation committees. For econometrics, it is more common for UNC students to work with Kenan-Flagler faculty, as most of the Metrics students go down the Financial Econometrics path.

There are plenty of fine schools outside of the top 15, but once you get out of the top ~30, the value of the PhD drops at a faster rate. Having just gone through the job market process, as well as several years of anecdotal evidence, my feeling is that you need a fairly good reason to attend a program outside of the top 30. By this I mean you have a well defined research agenda and there is a good match at a LRM school, or you have severe location constraints, or your outside option is terrible, or you want to work at an UVLRM directional school, etc. A lot of people can be very happy at these lower ranked schools, but you need to recognize the issues going in. Often these departments are dysfunctional (especially the ones that perpetually sit in the 30-50 range), have very few faculty that are actually good advisors, and placements are bleak. Everyone eventually gets a job, but just know that underemployment is rampant outside of HRM/MRM. As well, the outside options are considerably weaker the further you go down the rankings. Gov't, policy, and industry all care about rankings, sometimes even more than US academic positions. Same goes for many international universities. The key for those considering schools right now is to look at placements. Ask yourself if you would be happy with the department's median placement from the past few years. Do not focus on the department's best placement. You may end up being the star, but so much changes between now and when you eventually go on the job market.

Texas is the clear choice here.

Duke >>> UVA

Because they want to work with Acemoglu or Fudenberg.