AlSharpton

Several of the grad students at ND don't drive, but I would say it makes life easier having a car. There are several shops/restaurants very close to campus, which you could potentially walk to if you needed to do so, but I wouldn't recommend doing that in the winter. Some of the grad students carpool whenever they go grocery shopping which is probably your best bet if you don't drive. Also, the stipend goes a long way in south bend so you probably could save up enough to buy a car in a relatively short period of time if you needed to.

You should always go to the flyout unless you are absolutely sure you are attending a certain program. Even if you think you are absolutely sure it is still a good idea to go to flyouts. There is no substitute for being at a campus in person and being able to interact with the faculty/grad students one on one. Also, the way the flyouts are setup can reveal a lot of information about the program/department culture that you might not have received otherwise.

There are plenty of on campus housing options for grad students and there usually isn't a problem as far as availability of housing goes. The campus of ND is safe. Some of the areas outside of ND in South Bend might be a different story, but you shouldn't have any problems on or near campus. Feel free to PM if you want more info.

This depends on the lack of math in your profile. If you are lacking the basics like linear algebra or multivariate calculus, then an MA in financial econ or applied math is not going to help you. If you are lacking things like real analysis or differential equations, then financial econ/math is not a bad way to go so long as you have the chance to take those types of courses and you are genuinely interested in finance. Otherwise i say do an MA in econ while taking the math classes you need.

I had a somewhat similar experience as you as my undergrad GPA was low (around 3.2). My two cents. Top 20 schools are likely out of the question, whether you do a masters or not. Most of the schools that I was rejected from rejected me on the basis of my low undergrad GPA, even as the rest of my profile was relatively strong. The issue with top schools is that you are competing with people who have almost no deficiencies in their profile, whereas you have a glaring one. This gives adcoms an excuse to ding you, even if the rest of your profile is still strong. I would apply to lower ranked schools that are relatively strong in the areas you are interested in. Doing a math masters is an option, but only if you are certain that you can improve your math grades and you are willing to spend the time/money. Your math courses are the weakest part of your profile and are the greatest cause for concern given that you have not exhibited an upward trajectory in your math GPA over time. Taking additional math classes and doing well along with getting strong letters will certainly improve your prospects, but I think your target range should be in the Top 30-70 conditional on doing well in your grad level real analysis course. Conditional on doing well in a math masters, I would say your placement is likely better, but top 20 is still unlikely (but not impossible).

First year here. It's interesting to see how many people have lost weight in this thread while I lost 20 lbs my first semester. I guess people deal with stress in different ways.

The more math you have, the easier your first year will be. That being said the jump from an MA program to PhD program is still substantial. In my MA program our macro theory course ended with what my PhD macro theory 1 course will begin with.

This. Also learn a programming language or two in your spare time if you already haven't. Something like R, MATLAB, GAUSS, or even the Mata language within Stata will pay dividends once you start doing your actual research.

A few points.... The people who teach the core theory classes do not necessary write the core exams, especially for a first year AP. Also, your post makes me question the level of commitment you actually have in regards to learning the core theory at a level sufficient enough to pass the comps without an unfair advantage over your classmates. This reflects poorly on you as well as the institution that you are in, which by the way, can be found relatively easily with a few google searches given the information in your post.

I would go with grad analysis + PhD macro + grad math stats personally, but talk it over with some of your professors and people who know better than I do and see what they say.

If you are interested in doing macro, then PhD macro would be the way to go then, as his connections/recommendation would certainly help you out in the admissions process. Letters of recommendation are probably the most important part of your profile in my opinion. At a certain level, there are way more applicants than positions open who have great GRE scores, great GPAs, strong math backgrounds, etc. At this point letters of recommendation often tip the scales so if you think you will do well/impress your macro prof, then I would go with PhD macro.

Only you have the best idea of what you can handle. That being said I would take the most difficult course load I could while still having time available for the application process (which is always much more time consuming than originally planned for). One thing to keep in mind is that grad level probability is usually measure theory based so if you haven't already had grad level real analysis/measure theory you may be at a slight disadvantage. Personally I think option 1 is the best bet with grad math stat instead of grad level probability. These courses will all send strong signals and will balance your profile nicely, and should allow time for the application process as well. Every school/professor approaches analysis differently, but when I took grad level analysis we essentially covered everything we did in undergrad analysis 1 and half of what we did in undergrad analysis 2, except in a more general way and with a higher level of rigor (along with a few other topics). So if your school's approach to analysis is similar, I would definitely go with grad analysis over undergrad analysis 2. Also, PhD micro is much more uniform on how it is taught across programs relative to PhD macro, so I believe PhD micro will send a stronger signal than macro. Since you have had undergrad probability already, I believe a math stats class will be more beneficial to your profile and your future coursework than grad level probability will be. Best of luck.

From personal experience, it is incredibly difficult to focus and stay motivated in classes during the admissions process. I think I spent almost as much time researching schools/faculty than I did on actual coursework this spring. I would take classes that are challenging enough to keep you interested, but not overly difficult. More than anything take classes that will help you out in your PhD such as programming, technical writing, research, etc.

Your profile looks pretty solid for the range you are looking at, although I would apply to several programs outside the top 30 that specialize in your interests.if possible. Also, at this point your letters of recommendation will be the most important part of your profile conditional on you doing well on the GRE. Hopefully you made a very good impression on the professors that you RAed for.

From my experience in TA-ing intro micro/macro courses, I found that most of the students tended to adopt the biases of professor rather than engaging in real economic reasoning, so I'm not really sure how much benefit the current approach of the least math possible is really providing. And like many others have said, the level of math prep and willingness to do math for most econ majors, especially at regional states, is astoundingly bad. I do think having a more mathematically rigorous approach to these courses would have a much greater benefit for the students who would be willing/able to work through it; however, given that the department/faculty has to partially justify their existence by how many students register for their courses, it wouldn't be in the best interest of the department to raise the level of rigor for these courses. So if we keep the undergrad courses as they are we are left with students who often lack clarity of thought and understanding or if we raise the rigor we are left with a department that struggles to justify it's own existence due to lack of enrollment. Of course, this really applies mainly to low/unranked schools in the U.S., which make up the lion's share of econ majors in the U.S. At other institutions I'm sure things are different to some extent.