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A company's profits don't have to be complex to make it useful within economics. I didn't claim that it was used everywhere, I claimed that it was useful in some circumstances particularly within econometrics (more specifically time series econometrics). Here is a very widely cited paper within economics that uses complex numbers (I would claim the majority, if not all, macroeconomists are familiar with this paper): "Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series" by Marianne Baxter and Robert King (link http://sws.bu.edu/mbaxter/papers/mbc.pdf). There are others that use very similar math. Complex Analysis is used very often within filtering frameworks. This is a good case against Abstract Algebra. Unless you enjoy it from a recreational standpoint (or are the next John Nash) it will only provide very marginal benefits. Overall, if you have very little programming experience then I think numerical analysis will still be the best course, but if you are lacking in formal math on your profile then complex analysis might be nice to have mostly for signal purposes. Numerical analysis would probably be more useful for passing first year courses.

I agree that numerical analysis is a good one, and maybe even the best of these choices (although I'm biased because I think computational work is fun). IMHO, people can go a little too far overboard on complex analysis and abstract algebra being completely useless... It may not be particularly useful if you are doing mostly applied work, but many of the breakthroughs in economic theory come because there is a problem that no one can solve until someone finds the right tool (often that tool is found within mathematics). Abstract Algebra may not be terribly useful in first year courses, but it may become useful if someone finds the right problem to solve with it. One example where it was used is proving Brouwer's Fixed Point theorem which is used to show existence of NE. Also, Complex Analysis is useful in econometrics.

I know two first year students; one at NYU and one at Colombia who both came straight from China undergrad, so it might just depend on school and the selection of students. They were both quite highly ranked within their department and were at a very good China undergrad.

Yes, in my opinion, the people who are doing the most interesting research in economics are currently developing mathematically rigorous models and then joining that with some kind of data. I think many if not all of those topics are used within economics (some more than others). Probability theory shows up literally all over the place and is a viable contender for having been the most useful undergraduate class I took in preparation for my first year. One example that could use several of the things is a simple macroeconomic model. You will typically have a measure of heterogeneous agents who are maximizing expected utility of their lifetime. In order to solve the majority of the models that look like this, you will need to use at least a little of each of the following: Measure theory(mostly in the context of probability), Probability theory, Some kind of difference or differential equation, Functional analysis (at least to prove the existence of a value function), etc. If you aren't afraid of the math; Stokey, Lucas, with Prescott's Recursive Methods in Economic Dynamics is an excellent book. It is 20 years old, but I think it gives a good introduction of the use of mathematics in macroeconomics. There are lots of other applications in micro and game theory. If you want to see how it is currently being used then you can probably crack open a volume of Econometrica or the American Economic Review. Those should have some good examples.

Agreed. There is no reason for them to suspect that you have the slightest amount of mathematical preparation to handle a masters. I don't know what most masters require, but I would be surprised if basic differentiation and integration (from the high school level) would be sufficient preparation. From what I understand and have experienced, the economics that is typically taught to the undergrads in business majors is not typically at the same level that it is taught to economics majors. i.e. managerial economics \neq (not equal, in case you aren't familiar with latex) economics. If you are set on pursuing this field (and if you are then you should pursue it), I would highly suggest taking at a bare minimum multivariable calculus, linear algebra, and intermediate micro/macro; without this basic understanding, even if you were to be admitted, you would struggle. That's my 2 cents, but take it as what it is: a suggestion from a random person on the internet.

It doesn't look like it is their intro to econometrics. That is econometrics 468 as opposed to the introductory which is 337 (evidenced by google). As far as being similar to an undergrad course in econometrics, it looks pretty similar to what I took at my undergrad for a 2nd course in econometrics.

I guess I must still be a naive first year, but I haven't found my department to be nearly as bad as EJMR. I wonder if we sampled participants of EJMR how their distribution across schools would be... Unfortunately most of them would lie so it isn't possible to get data unless someone hacks their servers and gets the IP addresses, anyone have connections with the NSA? :eager: Is it always a problem or can you get around it by finding a good set of coauthors that you work with?

Hey guys, I don't know if y'all have heard of the stackexchange websites, but basically they are a series of topic specific websites that allow users to ask/answer questions (example topics: general programming, mathematics, physics... Check some of them out to get a feel of what they are like). There is currently a proposal to open an economics specific stackexchange. It would probably have some overlap with this website, but I also think it will be a good place for some broader discussion. I plan on using both. If you are interested in it, check out this site and "follow" the proposal.

For future applicants, these types of problems can be avoided by waiting till you hear back from all of your schools to accept any offers. Accepting March 28th compared to April 14th or 15th won't have any effect on your future. tsonline, I would suggest following the same advice people gave earlier. Call or email the chair and be honest. I doubt they will have any hard feelings since they have invested much in you yet.

Short answer: You need more math. (you'll hear this from at least 6 other people) Take a chance this summer/next fall to take at a bare minimum Calc 3, Linear Algebra, and Real Analysis. Note that these are simply necessary, not sufficient for many schools. I would prioritize Real Analysis and Linear Algebra over Calc 3 because you have probably done some basic multivariate calculus in your other classes. Also, your GRE quant needs to be at the 164+ish range to shoot for places like BU. The lower ranked schools might not be as concerned with how you did, but I'm not sure how their application process works. There is more to be said, but someone else will follow this up.

I think NYU and Michigan both dominate Duke, but I'm not really caught up on the applied micro people at each dept. Don't know more about between NYU and Michigan

If anyone is interested in learning more about NYU Stern, feel free to pm me. It is a biased opinion, but happy to answer any questions that you might have.

Had a classmate that made a very similar decision between a PhD and a hedgefund(not to mention he was a double physics econ major as well). I would set up your schedule to be the PhD prep route, apply to PhD schools (top 5 or whichever you prefer), and apply to jobs. It can't hurt to see what happens and unless the company is very pushy then I don't imagine that they would have a problem with that. He chose PhD based on where he was accepted even though I think his plan is still to end up in the private sector afterwards, but he'll have better tools and skills to do the things that he was planning on doing. And if you decide to go straight to industry then a worst case scenario is that you have gained a few extra skills that you might enjoy having later on down the line if for nothing more than kicks and giggles.

I kinda agree with this, but I won't comment more on it because maybe you have good reasons and I'm not that concerned about it... It sounds like you are doing good research and if you truly love economics enough to survive grad school then it is worth it, but if possible then I wouldn't suggest constraining yourself to top 5/10 schools. There are a lot of students who deserve to be there that get rejected because there is randomness in the application process. Furthermore, there have been a lot of students who have gone to 20-40 ranked grad schools that have placed very well because of their ability to research and it sounds like you can do good research. So take that into consideration, but comes down to your choice. Also, you should talk to your advisor about this. He probably has a better idea of where he can place you than we do.

Don't want to step on anyone's toes, but I just want to go say that I don't agree with this... Stochastic Calculus, PDE, and SDE are all at least pretty useful (I don't know much about the setting of a mathematical finance MA, but the classes themselves are IMO gold). Especially for Macro. I'm a first year and today our professor said that if we took 1 class outside of the economics department that it should be stochastic calculus, he is extremely well-known within economics and I am planning on taking his advice. I agree with everyone else in general though. You'll want more math if you want to do grad school. Not even just for signaling purposes, just to survive. It is a rough 9 months.