Umlaut

Profile: - BSc Econ & BSc Applied Math Top 10 school in Europe/Best in country. Did myself a disfavour by going for difficult and harshly graded courses and other commitments (see later) and ended up with definitely above average but not stellar grades. Somewhere around top 15% of overall GPAs, grades in most exams Top 15% or better, never worse than top 30%. I gather in the US this would be mostly As, where I'm from it certainly isn't. - MSc at Top UK school w Distinction - Started work as Full time RA in US for well known full professor at Top 5 US School. Math courses: A lot with a mixed bunch of grades - all of them above average, but in an exam where the median is a D+ a B- is still a B-. High grades in real analysis though if that's worth anything. Grades in Europe are different from the US is my excuse, I guess. Econ courses: Pretty much the whole lot with a focus on financial economics, more consistently good grades. Letters: Hopefully my current supervisor and some professors from my master's who have agreed to write letters that should be good, I hope. Other: While we don't have collegiate sports like in the US in Europe, I was training and competing at the level of a decent D1 athlete throughout my studies and spending a fair amount of my time on this. Have some top 5 finishes at a national level to show for it. Concerns: Obviously grades are a major concern. Grading in Europe is different from the US where apparently an A is frequently the median grade. Might apply this year, might apply next year - what is the marginal value of working an additional year as RA given that I can't really change anything about my profile? No idea what US schools are realistic to aim for and strongly considering a bunch of schools in Europe closer to home where I know I have strong chances of getting into at least some places.

Is this a converted 4.0 GPA using the WES grade conversion scale or a 4.0 GPA as in 1.0? If it's the latter, I'd apply straight to the Top US departments and LSE EME/Fin&Econ (Research), as well as Bonn/Mannheim, where you presumably would have excellent chances of getting into the exchange programs with US departments and could then ask for LoRs there - Just to keep things simple. Obviously, you would also have excellent chances at any other European department, if you have any other geographic preferences.

No Yurolove?

Bump?

The country and university I'm from are reasonably well known. Atleast prior to the Bologna reforms there were a number of people who went on to pursue PhDs at Top5 departments out of their undergrad here and recently came onto the market, with atleast 2 of them doing quite well and placing at Top 5 depts. However, I suspect their grades would have been better - Nevertheless, a 4.0 GPA is pretty much never achieved and even graduating with distinction (>3.8) is something that doesn't happen every year (I think), especially if you choose to take a Math minor. Furthermore, my university is not a too popular destination for internationals, nor is it a particularly well known or even prestigious name outside of the country. I don't know about sending students to other European departments, but as said before, I am studying at a department ranked similiarly to the ones I'm applying to and have some unofficial feedback that I would probably be able to secure a spot in our MRes. What interests me is how other departments would view my appliation package, which certainly has some (very) rough edges.

PROFILE: Type of Undergrad: Econ Top10 in Europe: Econ Major w Math Minor Undergrad GPA: ~3.4 (Cohort average presumably 2.7) Type of Grad: { } Grad GPA: { } GRE: Remains to be seen, presumably decent Math Courses (held by Math Department): Real Analysis I (Grade B+ | Relative to cohort 10/152), Real Analysis II (A | 1/144), Linear Algebra I (A- | 6/213), Linear Algebra II/Discrete Mathematics (B | 33/148), Introduction to Probability Theory (B | 30/150), Introduction to Statistics (C+ | 4/35), Numerical Analysis (Taking), Metrics (for Mathematicians) (Taking) Econ Courses (grad-level): { } Econ Courses (undergrad-level): Principles (A | 1/1185), Intermediate Macro I (B+ | 53/491), Intermediate Micro I (B | 15/170), Micro II (8 | 15/150) Macro II (A- | 28/190) Investments and Asset Pricing (B+ | 2/168), Several Field Courses (Taking) Other Courses: Introduction to Law (B- | 21/67), Principles Accounting (A- | 4/101), some Business and other courses (8 and Top15% or better) Letters of Recommendation: No idea really. Hoping something materialises. Research Experience: None so far, will write Bachelors Thesis in order to graduate Teaching Experience: Instructor for Financial Mathematics (for non Math students) and Linear Algebra (for non Math students) - Very good teaching evaluations Research Interests: At this point Applied Micro, Finance, Applied Theory, (Development) Policy - I think I'm better at ruling out what I don't want to pursue... Concerns: - Varying performance in Math (and Econ) courses. I think I have hardly ever landed outside the Top 20% in a relevant exam but due to my countries grading policy my profile is far from the 4.0 GPA this would presumably warrant at some US schools. A C+ in Intro to Stats looks a lot worse than being the 4th best student taking an exam. Also, Math courses are so time intensive that despite grades counting towards my GPA roughly 50:50 the necessary time invested is more like 30:70, which puts me at a disadvantage to people without Math minor at my own university. - Lack of Research experience - Wishing you could resit exams Other: - Will spend the next semester at another European university, probably ranked slightly better than my own and will presumably hear some Masters courses there. Suggestions on which provide the biggest benefit for the future are welcome. - I'm a (more or less) nationally competitive athlete in an olympic sport besides all this (more popular than archery...) Applying: Will presumably have to go through a (Research) Masters before applying to a US PhD or continuing, depending on performance during the Masters and the tradeoff between gains from US PhD and two/three added years. Will apply to some of {Oxford MPhil, LSE MRes, Zurich MRes, CEMFI, Bocconi, Bonn, Mannheim, BGSE, TSE, UPF,...} - The typical candidates. I guess overall this profile isn't too exciting, but I figure I'd like to hear where I'm standing at the moment.

Or $$$

Well results are out and I scored (the equivalent of) a D+. The best grade I've heard of so far is a C-. So much for my (anyway ambitious) goal of graduating with distinction. Depending on how things work out, I think I wouldn't do the Math Minor/Major again. Despite the fact that you do learn a lot, the grading and the fact that you're competing with people without the burden of an additional 10-15 hours of work is just too much. Also, I think people aren't too focussed on the lacking Math when comparing European graduates.

I'm a second year European undergrad and have been offered an opportunity to spend the fall semester at TSE. If I were to accept the offer, I'd like to use the possibility to hear some Master's level courses before applying to graduate school/Master's degrees. Since I have a quite large cushion of credit points, I'd want to try and benefit from the semester abroad thing and have atleast some time to explore whilst maintaining or improving my GPA. In order to do this, I was planning to take somewhere between two and four M1 courses, depending on how many credits they each give to arive at a total of about 15 credits or so. However, if I actually want to work on my GPA, I'd have to score 16 or better in these courses. Is this is any kind of way feasible for someone who doesn't have the full courseload of the M1? Having read around a bit, it seems that TSE's grading is notoriously harsh. On the other hand, what I saw in some of the past years exams didn't look too intimidating. But of course, I don't know how strictly those exams were graded... Atleast they didn't look like they were trying to screw you over. Are there any TSE insiders who could give advice on a) courses to take/avoid b) their opinion on whether this is worthwhile I also have my doubts about this because so far I am lacking in research experience and any possible opportunities would proably arise in the semester which I would want to spend abroad.

This was the material covered in 28 lectures held over 14 weeks... (**** me, right?)

For reference, would you consider this to be "overkill" for course with two lectures and one TA session a week? I'm trying to convice myself that it was in order to give myself some kind of excuse, but would really appreciate your honest opinion. For me this was the first time that I really felt I couldn't keep up with the amount of stuff that was being thrown at me. Everything was introduced via theorem-proof with problem sets consisting to 80% of either proofs or tasks in R. Noone of us had had anything to do with statistics since high school. Introduction to probability theory was held in parallel. - Multivariate descriptive statistics and Multivariate Linear Modells/Regression - (Pre-)Hilbert Spaces (Convergence, Cauchy-Schwarz, Projections etc.) - Principal Components Analysis - Cluster Analysis (including introduction of string metrics, i.e. M/S-coefficients, Mahalanobis-norm, etc.) - Factor Analysis via one of the ugliest proofs I've ever seen - Proof of Central Limit Theorem for heteroscedastic variables via Huber (probably the ugliest proof I have seen so far) - Multivariate Normal Distribution (properties and proofs of properties) - Estimators: BLUE, Method of Moments, M-Estimators (Maronna), ML-Estimators including proofs of Bias, MSE and asymptotic convergence - Robust Statistics: Formal definition of Breaking Point/Influence curves - Tests: (two-sample-)t-Test, Chi-Squared, etc. including Behrens-Fischer-Problem - Neyman-Pearson-Lemma/Estimators, predominantly proof of their properties - Unbiased Estimators: Fischer Neyman-factorisation theorem, Rao-Blackwell, Lehmann-Scheffé (including proofs) - Bayesian approach/Bayes-Risk - Jackknife - Parametric and non-parametric Bootstrap - Discriminant function analysis based on Kernel density Estimators Should anyone want the notes to this, I guess I could provide them if you send me a PN - though they wouldn't be in English and are about half as extensive and long as they ought to be if they were to provide enough intuition and explanation behind the proofs.

This is an exam from the last semester. And the entire grade was 100% this exam.

So due to my choice of a Math minor I was forced to hear Intro to Stats at the Math department where the course in this form was held for the first time by a prof who overestimated pretty much everybody in there. The material covered about three Semester of Stats/Metrics as it would be done in an Econ Stats lecture and did it in a much mire rigorous style. Protests that the material covered was too much did not elicit much of a response. I do not know what my final grade will be, but I do know it will not be good (at all), as will most other peoples'. In addition to mistakes that were inevitable, I also added one or two which I really shouldn't have, possibly because the onsetting panic unsettled me sufficiently. You can't resit passed exams where I am from and I am now scared shitless that a probably dismal grade in something falsely called "Intro to Stats" could destroy an otherwise decent profile. Would one terrible grade be overlooked if I now try to remedy it by doing well in i.e. Metrics for Math students?

Yes. .

Bump?Have I already ruled myself out of any specific tier?