questions regarding Ph.d classes

[jongrud]

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Hi, people. I'm a Korean student in Top 3 university in my country. I just finished my undergrad and will now proceed to grad school of the same institution. I've noticed that in this forum, people say grades in Ph.D micro, and metric courses are strong signals in the admission process. But I wonder, are they the same thing as graduate micro, and metric classes, which are based on Mas-collel, and green textbook? The grad classes are in master programs, so I'm afraid they are not the same thing as the Ph.D micro, and metric that people here are talking about? I'm asking this because I already have A+ in grad micro and metric but I'm not sure they are the ones with strong signaling value.

Thanks in advance

[Zubrus]

In general, grad classes are PhD courses. MA programs in Econ exist in the U.S., but aren't common.

[jongrud]

Thanks for replying! That clarifies some ambiguity. But may I ask one more question? I've also taken a grad mathematical statistics as an undergrad last semester, and I only managed to get B due to overloading myself+ temporary health problem before the exam.

The thing is that I can retake it in my grad school and am pretty sure that then I can get A. Would you recommend doing so? I have A+ in grad micro, metric, and undergrad real analysis sequences(two classes) but I'm afraid that B in such mathematical class can potentially hurt my chances badly. The alternative would be taking a grad real analysis class and get A from it (although it's a grad class, people say it's not that advanced compared to the undergrad ones that I excelled in). So the question simplifies to:

Retake the grad math stats to cover up the flaw vs Get over it and ace grad real analysis instead.

[ahududu]

If those classes are really using MWG and Greene, I can only imagine that those classes are PhD level.

[chateauheart]

Thanks for replying! That clarifies some ambiguity. But may I ask one more question? I've also taken a grad mathematical statistics as an undergrad last semester, and I only managed to get B due to overloading myself+ temporary health problem before the exam.

The thing is that I can retake it in my grad school and am pretty sure that then I can get A. Would you recommend doing so? I have A+ in grad micro, metric, and undergrad real analysis sequences(two classes) but I'm afraid that B in such mathematical class can potentially hurt my chances badly. The alternative would be taking a grad real analysis class and get A from it (although it's a grad class, people say it's not that advanced compared to the undergrad ones that I excelled in). So the question simplifies to:

Retake the grad math stats to cover up the flaw vs Get over it and ace grad real analysis instead.

I don't think either option sounds like the best use of your time. You're already near the very top of the distribution in math preparation/signal, way past the point where diminishing returns sets in. If there's some kind of supervised thesis writing, or research assistance that you can do, you should focus on that instead.

[jongrud]

Really? I've never thought that my math preparation was that sufficient because the most of my senior students who got into decent US Ph.D programs took graduate micro, metric, and real analysis and got A from them. I know that these days having good research experience carries more weight than getting A's in math classes (that's why I've started RAing a prof for about six months), but the past record of my senior students is kind of telling me that I also have to take graduate real analysis and get A. In fact, from what I know, the majority of Korean students in US Ph.D programs have taken graduate real analysis. So I'm not so sure if it's actually fine for me to stop taking math.

Any opinions would be appreciated. My interest lies in Applied Micro/metric, Development and other empirical micro fields, FYI. Would adcoms require higher level of math/rigor for Korean/asian students even though it's pretty much useless past a certain point?