Baby Varian

If you already have those two masters (LSE and top 30 for Stat) and have done well in them (ie. distinction), then what kind of UG do you need to break into top 10?

That's why you need to do some groping (tatonnement). :)

You wait for (famous economist's name, date) or footnotes if you prefer the other kind of citation, after hearing a statement about economics on the news. I was just watching CNBC and a senior guy at an investment bank said that "corporate profits is the backbone of economic growth". I couldn't believe him because he didn't have any proof.

What about this? Number Systems (§1): ordered fields rational, real and complex numbers Archimedian property supremum, infimum, completeness Sequences and Series of Real Numbers (§3): limits of sequences, algebra of limits Bolzano-Weierstrass Theorem Cauchy sequences, liminf, limsup limits of series, convergence tests, absolute and conditional convergence power series Metric Spaces (§2): metric spaces convergence, completeness, completion open sets, closed sets, compact sets, Heine Borel Theorem connected sets Continuity (§4): functions, cardinality continuity continuity and compactness, existence of minimizers and maximizers, uniform continuity continuity and connectedness, Intermediate Value Theorem monotone functions and discontinuities Differentiation (§5): differentiation Mean Value Theorem L'Hôpital's Rule Taylor's Theorem Is this real analysis?

While you stated that "there seems to be no clear preference for theoretical or empirical proposals", but if I'm required to write the following: Wouldn't that favour experimentalists the most? The "how you're going to do it" part is very hard to write if one's doing theoretical game theory. How someone would be able to do it depends a lot of whether he gets that spark of intuition that allows him to proof his theorems. But, people usually wouldn't know that before their PhD (or else they wouldn't need a PhD). Also, how can one say that he's the best person to do theoretical game theory? Maybe I can say that I got an A+ in Real Analysis and A+ in grad. micro using MWG. But that doesn't seem very impressive (at least for the adcoms... they'll just think you're a nerd). Experimentalists probably have the easiest route because they've probably done experiments in UG (which shows experience) and can describe a very specific proposal (which sounds better than a vague one). Of course, given two proposals of the same quality, SSHRC might not have a preference, but it seems much harder to write a "good" proposal for theoretical work. It's much easier for empirical proposals to be specific. To OP: Are we competing against other economics students or all SSHRC applicants? Is there a certain % reserved for economics?

Mathematical proofs are much more rigorous than comprehensive explanations of human behaviour. Therefore, it may be hard to judge two distinct solutions to the problems. In addition, a mathematical theory of voting behaviour might be correspond to real life behaviour. Real world contracts are incomplete due to the cost of making complete contracts. In the real world, most small businesses don't even use contracts for most transactions. Even when they do use contracts, they rarely enforce them if the cost of hiring lawyers exceeds the benefits of winning the case. Well, I don't vote because I'm a free-rider. But, some people feel patriotic about voting and therefore for them it's probably an enjoyable activity regardless of which party wins. Those are probably not the answers you're looking for and they may seem trivial but those are just my thoughts.

In our school, we use the Baby Rudin for our 300-level analysis and Folland for our 400 level analysis.

I'm not wondering whether this would help me get admitted. I'm simply wondering if a MS in Statistics is neccessary to publish well in the field of empirical finance. I see a lot of people taking graduate level measure theory or mathematical statistics. I'm wondering if they're doing it because it's a good signal (but not useful for research), or because it's a good signal and it's neccessary for good research. I'm worried because I definitely wouldn't be able to do any graduate mathematics during my UG years. I'll probably get a MS before doing a PhD and I'm satisfied with a top 50 school so I'm not worried about getting in. Most of the other threads on Urch focused on whether or not it's useful for getting in but I'm just wondering if I graduate mathematics is helpful for empirical research.

There seems to be a mistake. OP's post linked to Blanchard's Macroeconomics which is a freshman/intermediate textbook. However, I think graduate students would use his Lectures on Macroeconomics instead. Also, I think OP should include Romer's Advanced Macroeconomics, although it's not as advanced as a true PhD textbook (analogous to Varian's book versus MWG).

Hi, I'm planning to study Mathematics for Economists on my own. I have a decent Calculus III and Linear Algebra background, but I've mostly forgotten about them. Although I'm taking other math courses right now (see my other thread), I want to make sure that I have a very thorough understanding of mathematical economics. I'm hoping to finish the book in 6 months. Are there any particular weaknesses in this book? If so, are there books that can be used mitigate its weakness?

I'm going into my third year and I've registered in the following courses: 1. Diff. Eq. 1 2. Diff Eq. 2 3. Calc III 4. Int. Lin. Algebra 5. Proof 6. Int. Micro 1 (hon. for 6-9) 7. Int. Micro 2 8. Int. Macro 9. Int Macro 2 10. Research Course I've taken one term of basic econometrics and probability. I'm aiming for MA/MSc admissions because I don't think I can get into a Top 10 PhD without PhD courses in economics (won't happen, department never granted anyone that and I don't have the preparation). I'm hoping to take the following either during my 4th year. Real Analysis I&II, Variational Calculus, Econometrics (harder), Game Theory, a few MBA courses (only grad course that I can take), Time-Series statistics, math. computing, linear programming (?), and a stochaistic math course. I have the option of taking the following for my one free space in my 3rd year (doing 11 courses): Linear Programming Stat. Inference Complex Variables Dynamics and Chaos Which one's the best?

Honestly, I wouldn't do it. Getting into a PhD program depends strongly on whether or not you get the distinction in the MSc. Therefore, I would probably put all my effort into get. You can always get the certification during the summer after the MSc or even during your PhD program. I think most people just take informal classes or study on their own, although a certificate might look better. But, if you're getting one if your native ("heritage") language, then no one would doubt that your fluency despite not having a certificate.

Why not just do the "lots of specifications" on the full data set? What's so good about leaving the other half "untouched"?

Academic research for finance is saturated but the demand for finance people is strong due to the private sector and MBA students. DSGE does have its own problems: (Google: Building a Science of Economics for the Real World Congress) so there's potential for change.

Sorry, I wasn't aware that it would be suspicious to create another account. I'm actually making a new account for every forum that I'm currently using because I no longer want my forum accounts to be linked to my main (used professionally for work and school) email. I'm making new accounts on a newly created email solely for forum purposes. Please delete my other account and keep this one. Thanks