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Everything posted by coloradoecon

  1. You may also want to review a mathematical probability & statistics textbook, which will help with metrics. Simon & Blume is a good resource as well. Some of the topics in that book are more geared toward what you'll actually see in your graduate-level courses (e.g. optimization, quadratic forms, basic linear algebra).
  2. I’ve taken the PhD sequence in Micro and Metrics at my unranked university and received A’s. Textbooks were Greene and Wooldridge for Metrics and MWG for Micro. As for math, I’ve taken multivariate calculus, Linear Alg I-II, Diff Eq, Probability, Math Stats, Real Analysis I-II, Set Theory, Topology, and grad lebesgue theory. (A’s in all classes). For research, I've RA'ed for a few years with two professors and did a senior thesis on an empirical topic. I'm graduating with a B.S. in Mathematics and Economics. During my pre-doc RA stint at a Fed bank, I have the opportunity to take some courses at a T40 program. If you could pick two courses from below, what would you advise? My interests are in Micro and Metrics. Grad topology Grad functional analysis Grad complex analysis Measure theoretic probability Abstract Algebra PhD Micro I (again, but this time at a better institution) Other (something else)
  3. I'm 99% sure superballamy is an alt account of dogbones.... I didn't catch on at first, but the writing style, the profile, all point to dogbones. I'm very much of the opinion that you should take math classes in the mathematics department, if possible. From personal experience (I don't claim this for all universities, but perhaps this is true of most universities), they have been much more rigorous, and they have prepared me well for grad econ courses. It's not a bad thing to take math courses and advanced economics courses which use other math course content.
  4. Last year, I received interview requests in mid-December and was extended an offer in late December / early January.
  5. Startz and Prof provide good points. I am not making a general point here or disagreeing with them at all. However, I will note that in a panel discussion on Economics PhD admissions comprised of the graduate admissions chairs of Rochester, UW-Madison, and UND, all three noted that a letter of recommendation from a math professor could be very beneficial, with two actively suggesting two econ professors + one math professor is an excellent combination. There isn't a "consensus" per se among admissions chairs / committees. But, if you do have three strong economics faculty to draw letters from (especially from a professor who taught theory-heavy or advanced class + you RA'ed for or did research under), I would go there first.
  6. I'd highly suggest trying to do a stint as an RA at your university and/or an independent thesis if that's not too late. It is certainly more difficult to get a predoctoral RA position without some research experience (or at least proficiency in a statistical package or programming language like R, Stata, Python, etc.) It's also very important to note - you should be getting an Economics PhD not because you enjoy the coursework, but because you want to be a researcher. It's hard to know you want that without any experience in research. Also note that in PhD programs, your goal is to produce research (coursework is just your toolkit), and you are your own RA. I do expect the upcoming cycle to be more competitive due to some schools having deferrals, and schools having smaller budgets. An RAship or some time to work in economics research is certainly worthwhile. Pre-doctoral RAships at universities, NBER, etc. will typically look more heavily at your research and programming experience as opposed to an RA position at the Fed. Something to keep in mind. Feel free to reach out if you have more questions.
  7. 1. It is very unclear to my why you know you will be writing *GRADUATE LEVEL* topology papers, given that you haven't taken any formal proof-based classes yet. Right now, what is studied and developing at the graduate level (and beyond in terms of research) in topology is algebraic topology, knot theory, and maybe geometric group theory (if you consider that in the "topology field"). Those require decent knowledge in Modern/Abstract Algebra (at the graduate level). I fail to see why getting to that level is valuable at all for economics - taking graduate topology is one thing, but expending the time and effort to have a graduate-level novel paper in the field is another. The opportunity cost there is HUGE. 2. I would shoot for one solid paper, not two mediocre ones. I would certainly not attempt two economics papers plus papers in topology!
  8. Most times when you clean data, there is time for analysis, critique, and suggestions. You produce a certain set of results. Is that what you expected? You know the data better than your economist in some cases, so you should be well-equipped to explain discrepancies or new tests / tasks to be applied, and to engage with them when they do instruct you to carry out certain actions. Professors who write you letters know that you are their RA and don't expect you to do work on par with a co-author (though sometimes that possibility arises - but not always, and that's fine). That's not what you were hired for, and that's not what they expect. But you should intentionally not be a robot that follows instructions (though you should be able to carry out the tasks well) - show creativity, insights, and ask a lot of good questions. It shows you are genuinely interested in the research, are following, and can point your professor towards where to take the research next.
  9. I would highly, highly recommend you do some studying in a Calculus-based probability text this summer on your own before you take that class. I am talking about something like the first part of Casella & Berger (Ch 1-4, 5.5) or Grimmett & Stirzaker's "Probability and Random Processes" (Chapters 1-5, 7). Brush up on your analysis as well, since elements of measure theory may be introduced. Your goal in a graduate-level course is to place as high as possible (ideally in the top quartile). Most of the students in the course likely have taken a yearlong probability & statistics sequence, which places you at a disadvantage. You can make up for that by working hard and getting acquainted with key prerequisite material. Feel free to direct message me if you have questions.
  10. A thesis in your sophomore year is a little early, but you should definitely be thinking about what you are interested in and perhaps read / attend seminars around those topics. Don't also feel the need to corner yourself in on your interests so early. People change all the time after they enter grad school. Usually, people begin seriously researching during their junior year, often for a proposal and to receive funding, which leads to a two or three semester research and writing period for the thesis. It's not a dissertation, and it probably won't be great. But it is a good place to start writing and learning about the entire research process, as your first papers are almost always bad. When it comes to RA positions, look to not only take on short-term projects, but long-term ones as well. Not only will you learn a lot and understand more about the research process, but the professor you have worked long-term with and taken a (preferably advanced) course from will write you the strongest letters.
  11. Bayes, given that the OP has not decided between Applied Mathematics PhD or Economics PhD (and has just finished freshman year, so they have lots of time), I would recommend they keep Abstract Algebra unless they decide to pursue an Economics PhD, as most graduate math programs want to see two semesters of Algebra (as well as two semesters of Analysis). You have a very challenging courseload, good luck! You look like you are driven, which is good. I might consider moving the Abstract Algebra to your junior year, and take an analysis sequence during your sophomore year. This will prepare you well for the graduate micro courses you want to take during junior year. Given your school (T30), if you manage to get excellent grades with this course-load, and have good research experience, you should be competitive basically everywhere. Edit: I'm realizing you are taking the entire first-year PhD sequence in your sophomore and junior years. That probably is not necessary (like Bayes says, drop Macro) and potentially has more risk than reward. The Metrics and Micro sequence is worth taking, but I would ask the professors whether it is okay to take Metrics I without any previous coursework in probability / statistics in a math department. I don't think I would have been able to succeed without my prior training in rigorous probability / stats courses. Additionally, consider taking a lighter load your last year, and doing an independent thesis project. You will also be applying then, which will consume quite a bit of your time. I think you'll learn, the more you RA and work more closely with professors, that an Economics PhD is not about coursework, but about producing research and developing research skills. The coursework is an means to that goal of producing research.
  12. Couple of notes: 1. Dyu just finished *sophomore year* because the application time is Fall 2021. You have more courses than I had when I was entering my junior year, and more RA experience than I had at the time as well. For reference, I had Intermediate Micro & Macro, Calculus III, Statistics (in the econ department), Linear Algebra, Intro to Proofs. That's it. In the summer before my junior year, I did comprehensive study of Real Analysis and RA'ed (as you did). In my junior year, I did take Diff Eq, Real Analysis, Undergrad Metrics, two field courses (game theory & forecasting), Grad Econ Math, Micro I, & Metrics I, Probability, Math Stat. You definitely have time. 2. I would recommend you take a yearlong probability-statistics sequence (in the Math Department), not just probability. Your math preparation route is good though. If you want to add one more course, go ahead and take topology. But Real Analysis will be an important course for you this year - make sure you dedicate enough time and effort to it. I'm not sure what your linear algebra course was like, but a second semester may be helpful, if your first semester didn't use a text on the level of Linear Algebra Done Right (proof-based, infinite-dimensional). 3. In addition to undergraduate metrics, you may wish to take a game theory course as well (in addition to other field type courses, or advanced theory courses). I would try to get more long-term RA opportunities with professors as well. Consider applying out to the NY Fed / Fed Board internships next summer too. 4. If you do well in your advanced math courses, I suggest you take graduate Micro I and possibly graduate Metrics I next fall. It's a bit early for me to say without seeing some more advanced coursework and grades, but if you keep up your grades and especially if you have some strong signalling courses (grad Micro, maybe measure theory), especially coming from a T20 school, you should have a good shot at any school. In that case, applying to a T10 is absolutely a good use of your money. This year will be your hardest year, be ready for it and get to work!
  13. Note that NBER is not the Fed, but that is a good resource. Beefing up your programming skills will be key, as RA positions often require you complete a coding task. Econ_ra on twitter is a good place to look as well - but not everything on there will necessarily be the best - filter through and ask your mentors. I'm biased, but I think the Fed (especially its stronger branches) provides some excellent opportunities and support, and helps students really decide whether or not an Economics PhD is for them. I do think it is probably easier to get an RA position at a Fed Bank / the Board as opposed to top universities. But talk to your mentors to hear their thoughts.
  14. I don't think you'd be competitive for T30 yet; I'd say that you would probably get into T50-60 programs. Especially if your goal is to go into academia, it would be wise to position yourself for a couple of years so you can get into a better-placing program. Some advice, if I was in your shoes (and again - you don't necessarily have to follow what *I* would do): 1. Take on an RA position under a professor during your last year, and opt to apply out to full-time RA positions (at the Fed, at other universities, etc.) There are a couple benefits here, the first of which is simply knowing whether or not you really want to pursue a PhD (which should be because you want to conduct original research), in addition to opportunities for excellent letters, especially coming from an unranked institution. 2. While at university, take a yearlong Probability and Statistics (in the Math Department). Do some studying so that when you RA, you can retake Real Analysis and do well in it. Alternatively (and perhaps more optimally), you could take Real Analysis II (in addition to Prob/Stat) at your university (an A is key), and then try to take a graduate Micro course (and maybe Metrics too) while you are RAing. Fed RA positions will reimburse you quite generously to take courses while you work full-time. If you follow these steps and receive high marks in your academics and in your RA work, I see no reason why you wouldn't have a decent shot at the Top-30.
  15. Admissions committees are using imperfect information to try to select students that will be excellent economic researchers. What admissions directors at T20 programs have mentioned is that this most clearly comes from your (mathematics and graduate econ) coursework and from letters from PhD economists who are proven researchers who have worked directly with you on research and/or have taught you in an advanced class. I see no reason why the letter from a well-known T10 professor who publishes in top journals (and that you've RA'ed for and coauthored with) would be weighted any less than a junior faculty from a lesser institution without the same publication record. And I'm sure that senior faculty member can give you better advice than everyone on here who has not completed (or entered) graduate school or does not have a faculty position.
  16. UCSD is a T15 program and UCI is a T50 program as per USNews. I would say that generally most people would say that UCSD dominates UCI. As a result, UCSD is more competitive to get into, with an annual pool of 800+ applications. I would hazard a guess that UCI's application pool is no more than 300, based on similarly ranked California schools (e.g. UCSB is ranked higher than UCI and has generally had Go ahead and take a look at the placements as well. Realistically speaking, how "boring" an area should not play a role in your decision-making calculus, unless absolutely everything else is equal. Maybe if this was an undergraduate program that would be a valid concern. This is a PhD program. Look at the research output, rankings, faculty, placements, and yes, funding.
  17. UW-Madison has slightly more than 500 applications each year, and in the past three years has admitted between 93 and 146 students to achieve an entering class of 25-30.
  18. I am curious how many applicants there were for the cycle.
  19. Couple of thoughts, which may or may be not what you are looking for. 1. I learned R/RStudio first. There's a lot more open source resources, lectures, exercises for you to develop proficiency, and it is becoming rapidly more popular. Once you know R, Stata is quite easy to learn. I'd argue that R is more powerful than Stata. Perhaps you wish to do that. Regardless, you should learn BOTH, which will increase your competitiveness for many RA positions. But you should start with one. 2. Ask your professors who have published papers on their sites or in journals (ideally that you have taken coursework from) for the code that goes along with their paper. It is a good exercise to get the original data, learn by doing and understanding how the code works, and replicate the paper. Be honest with them, show initiative, and tell them you are trying to learn Stata or R. It may lead you to a potential RAship under them.
  20. I'd disagree with dogbones. I do think, based on past profiles and examples, that you would generally be competitive for programs ranked between 50-100, with programs in the 35-50 range being a reach. I don't think you'd be competitive for T30. Couple points of advice: 1. I would highly consider retaking the GRE to get a higher Quant score. Some (T30) schools will not admit students with 90 percentile (and I assume that the exceptions have some large spike from another area in the application). A 164 places you at 87th percentile. 2. An RAship would improve your portfolio. Especially coming from a lower-ranked LA school, this is a great way to especially improve your letters (and potentially bolster your coursework, both from more classes at your current institution and potentially a few classes during your RAship). There is some room for concern with some of your math grades and low Quant GRE score, especially coming from a lower-ranked institution, so additional coursework may help.
  21. 1. If you haven't taken real analysis, you should take real analysis. Math camp is not meant to be comprehensive; it is generally meant as a review for students and as tutonic mentioned, does not have signalling ability. 2. I am assuming you have taken some undergraduate econometrics course - if you have done so, go ahead and take grad metrics. If not, and you've taken linear algebra, calculus, probability, and statistics, you're definitely ready. I'd read something like Woolridge's Introductory Econometrics beforehand to help build your intuition. Micro I is a good signalling class and generally holds more value than Grad Metrics though.
  22. So I am majoring in both math and economics. A couple of notes, at least from what I think: 1. A math major in itself is not really important; doing well (and learning the material well) in math courses is. If by doing the latter, you happen to get a math degree, great. But realize you can take all of the suggested math coursework without needing to get a major, and the law of diminishing returns does come to play. If you've taken the calculus sequence, linear algebra, probably theory & statistics, differential equations, point-set topology and two semesters of analysis, a semester or two of number theory and abstract algebra potentially required for a math major is not going to give you a whole lot of benefit beyond the courses you have taken. But if you love math and proof courses (which I do), go ahead! Doing well will help you, but doing poorly will hurt you. 2. If you decide to take these classes (which it seems like you are), your grades in Grad Micro really matter and your grades in Real Analysis really matter. These are probably your most important classes. Especially at at T30 school, these classes are challenging - you are taking them with PhD students - the 15-20 students that a committee selected out of hundreds of applicants! If taking a math major causes you to rush your math classes so you overload yourself to complete requirements and prevent you from really concentrating to learn material and get an A in these classes, don't take a math major. If this is not the case, go ahead with a math major. Just be wise with your time. 3. Beyond sufficient math background (Calculus, Linear Algebra, Probability & Statistics, Real Analysis, and maybe Diff Eq and point-set topology - though some of this is not necessary, this is likely the upper bound of sufficient), more time on research / RA work for a professor / a thesis will probably do you more good than an additional math class. So yes - sufficient math background + good grades in grad courses (in addition to research & letters & GRE) are great preparation. A math major is not necessary.
  23. PROFILE: Type of Undergrad: T60 Public University, BS in Math + BS in Economics Undergrad GPA: 4.0 Type of Grad: n/a Grad GPA: n/a GRE: 170/164/5.5 (Q/V/AW) Math Courses: Calc III, Intro to Proofs, Linear Algebra (two semesters), Real Analysis (two semesters), Probability Theory, Mathematical Statistics, Differential Equations, Topology, Abstract Algebra. (all A) Plan to take measure theory in the Fall. UG Econ Courses: Intermediate Micro/Macro, Game Theory, Development, Metrics, etc. Grad Econ Courses: Micro I, Metrics I-II, Math Economics (all either A+ or A). Letters of Recommendation: 1. Professor I took 1 undergrad class & Micro I from and RA with. 2. Professor I took grad Metrics II from + junior-senior capstone advisor. 3. Professor I took an advanced undergraduate course with. Research Experience: 2 years RA for a professor + junior-senior capstone (2 year research project) + NY Fed Intern. Teaching Experience: Experience tutoring but no TA experience. What are my chances at T20-30?
  24. I can't speak to the first two, but for the third - your specific department is what matters. It doesn't matter what the school does for its engineering or history PhD graduate placements; what matters is the placement for your department.
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