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Thread: Phd in Economics - Fall 2020 Cycle

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    Re: Phd in Economics - Fall 2020 Cycle

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    I disagree strongly with leolin's advice. It's ridiculously off the mark.

    You have a MA from a top Canadian program, and you were top of your cohort. In terms of academic coursework, you are probably in the 98th+ percentile *within* the selective pool of applicants to top 20 programs. Additionally, your research interest and experience seem to be in empirical work. There is very little value, in either the short run or long run, from taking further graduate math. You're set for PhD applications. Any marginal effort should be focused on RA experience and building rapport with your letter-writers - but even that is not necessary for getting into a top Canadian PhD (or a equivalent top 20 program in the USA). Ask your professors what proportion of MA students they admit into their PhD programs per year just based on their master's performance, and chances are you're well within the quota. There's no uncertainty here.

    You've received conflicting advice, so let me explain the difference in our experience here. I personally took grad real analysis as a 19 year old, and another grad probability course at 20. I don't think they helped me a single bit in my graduate econ career. I've never looked back into Billingsley (the reference text) even once after I finished the course. And, judging from my conversation with two top 5 adcom members after my application season, the grad math courses were not key to my application success. They were, on the other hand, a huge expenditure of time.

    Looking back at leo's profile, on the other hand, he's a current applicant in this cycle, and has an unusually lopsided profile himself - little coding and too much math, as other posters had pointed out to him. He also seems to be underperforming his expectations in this cycle. I realize I'm being a jackass by digging up another poster's background, but it's bizarre to me that an underperforming applicant doesn't seem to realize his understanding of the admissions weights is flawed, and is now offering the same wrong approach to other applicants. Flagrantly wrong advice like this - the undue obsession with grad-level math and lack of emphasis on research experience - is frustrating as hell, especially when we've been pointing it out on this forum for 5 consecutive years, and every cycle we have dozens of cases reaffirming the forum's consensus. We've had an applicant with 4.0 in 2 years of grad math at an Ivy league university who got significantly worse admissions results than another applicant from a comparable institution with a 3.7 undergrad GPA, 1 grad micro course, and 1 year of RA experience.

    Conditional on already having rigorous grad econ courses, I advise *every* applicant against taking grad real analysis unless they have a substantiated belief they'd be specializing in micro theory or econometric theory. By substantiated belief, I mean something like 1 year of working in a supervised research project in either of those topics. Chances are you should already be enrolled in a grad econ program by the time you can make that decision.
    Last edited by chateauheart; 04-19-2019 at 09:50 PM.

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by chateauheart View Post
    I disagree strongly with leolin's advice. It's ridiculously off the mark.

    You have a MA from a top Canadian program, and you were top of your cohort. In terms of academic coursework, you are probably in the 98th+ percentile *within* the selective pool of applicants to top 20 programs. Additionally, your research interest and experience seem to be in empirical work. There is very little value, in either the short run or long run, from taking further graduate math. You're set for PhD applications. Any marginal effort should be focused on RA experience and building rapport with your letter-writers - but even that is not necessary for getting into a top Canadian PhD (or a equivalent top 20 program in the USA). Ask your professors what proportion of MA students they admit into their PhD programs per year just based on their master's performance, and chances are you're well within the quota. There's no uncertainty here.

    You've received conflicting advice, so let me explain the difference in our experience here. I personally took grad real analysis as a 19 year old, and another grad probability course at 20. I don't think they helped me a single bit in my graduate econ career. I've never looked back into Billingsley (the reference text) even once after I finished the course. And, judging from my conversation with two top 5 adcom members after my application season, the grad math courses were not key to my application success. They were, on the other hand, a huge expenditure of time.

    Looking back at leo's profile, on the other hand, he's a current applicant in this cycle, and has an unusually lopsided profile himself - little coding and too much math, as other posters had pointed out to him. He also seems to be underperforming his expectations in this cycle. I realize I'm being a jackass by digging up another poster's background, but it's bizarre to me that an underperforming applicant doesn't seem to realize his understanding of the admissions weights is flawed, and is now offering the same wrong approach to other applicants. Flagrantly wrong advice like this - the undue obsession with grad-level math and lack of emphasis on research experience - is frustrating as hell, especially when we've been pointing it out on this forum for 5 consecutive years, and every cycle we have dozens of cases reaffirming the forum's consensus. We've had an applicant with 4.0 in 2 years of grad math at an Ivy league university who got significantly worse admissions results than another applicant from a comparable institution with a 3.7 undergrad GPA, 1 grad micro course, and 1 year of RA experience.

    Conditional on already having rigorous grad econ courses, I advise *every* applicant against taking grad real analysis unless they have a substantiated belief they'd be specializing in micro theory or econometric theory. By substantiated belief, I mean something like 1 year of working in a supervised research project in either of those topics. Chances are you should already be enrolled in a grad econ program by the time you can make that decision.
    I think it's alright to look at my profile. They are published and public and everyone can see it. But you turn an open discussion into attacks and as an economist, I'm not sure if anyone will respect you even though your view might be correct.

    As for my view, I think OP has the ability to do both grad real analysis and RA concurrently and does an excellent job in both, which is why I recommend OP to do both at the same time.

    Of course, you can challenge my view, by arguing that the selection committee don't care about maths as long as it's sufficient, or OP already has a good preparation in maths, etc. I don't know what the selection committee at Top 20 think so what you said might be correct. As for the preparation, there's no precise way to define what constitutes a good preparation. You might think OP is very strong in maths, while I think it could be slightly improved.

    Also are good RA jobs that easy to land on, and those jobs could fill in the gap of 6 months (which I would assume is the time OP has before applying for Fall 2020 entry)? These are the questions that you need to think about when recommending OP to devote all his time into RA jobs, while grad real analysis course is available for him to take.

    How much time does the grad real analysis take up? For me I don't think it is a huge expenditure of time. It's just like any normal courses, which is why I think real analysis is a must (not taking a huge amount of time while credibly signal any maths ability). But if OP finds it otherwise and doing grad real analysis affects the performance on RA, then of course RA should be prioritized. I have never said maths is more important than research and you have wrongly accused me.

    You also mentioned the coding issue, and I did forget to mention that OP could improve coding since he's doing empirical stuff. However, I am dedicated to be a micro theorist so coding is not as important as maths (although I do agree having more coding is not harmful), and it seems to you not having coding is one of the reasons why I'm an underperformer to you.

    We are all trying to help, and I do get a lot of suggestions on Urch. After I am admitted to my dream program I thought I should come out and help others, just like how people used to help me. I respect you in the way that you helped a lot of people over the past years, but what you said is just disgusting and show no respect as an top economist.
    Last edited by leolin; 04-24-2019 at 12:53 AM.

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    Re: Phd in Economics - Fall 2020 Cycle

    The OP is clearly not lacking math rigor. Its probably uncommon to have all those other courses and not analysis, but in this case it will probably help. Furthermore, real analysis is usually seen as desirable because it shows ability to handle the first year: the OP has already taken graduate micro and is getting a (hopefully strong) letter from that prof. Logically nothing points to real analysis as being the weakest link here. Graduate analysis seems like a bad use of time.

    This looks like many profiles posted here in the past where more experienced posters said "get a full time RA job and you are a top 10 shoo in". I would defer to chateau on their estimation that its not strictly necessary for top 20/Canadian top 5, but your admission chances are monotonically increasing in RA experience, and you always want to get accepted to the place you're on the margin for...

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by chateauheart View Post
    I disagree strongly with leolin's advice. It's ridiculously off the mark.

    You have a MA from a top Canadian program, and you were top of your cohort. In terms of academic coursework, you are probably in the 98th+ percentile *within* the selective pool of applicants to top 20 programs. Additionally, your research interest and experience seem to be in empirical work. There is very little value, in either the short run or long run, from taking further graduate math. You're set for PhD applications. Any marginal effort should be focused on RA experience and building rapport with your letter-writers - but even that is not necessary for getting into a top Canadian PhD (or a equivalent top 20 program in the USA). Ask your professors what proportion of MA students they admit into their PhD programs per year just based on their master's performance, and chances are you're well within the quota. There's no uncertainty here.

    You've received conflicting advice, so let me explain the difference in our experience here. I personally took grad real analysis as a 19 year old, and another grad probability course at 20. I don't think they helped me a single bit in my graduate econ career. I've never looked back into Billingsley (the reference text) even once after I finished the course. And, judging from my conversation with two top 5 adcom members after my application season, the grad math courses were not key to my application success. They were, on the other hand, a huge expenditure of time.

    Looking back at leo's profile, on the other hand, he's a current applicant in this cycle, and has an unusually lopsided profile himself - little coding and too much math, as other posters had pointed out to him. He also seems to be underperforming his expectations in this cycle. I realize I'm being a jackass by digging up another poster's background, but it's bizarre to me that an underperforming applicant doesn't seem to realize his understanding of the admissions weights is flawed, and is now offering the same wrong approach to other applicants. Flagrantly wrong advice like this - the undue obsession with grad-level math and lack of emphasis on research experience - is frustrating as hell, especially when we've been pointing it out on this forum for 5 consecutive years, and every cycle we have dozens of cases reaffirming the forum's consensus. We've had an applicant with 4.0 in 2 years of grad math at an Ivy league university who got significantly worse admissions results than another applicant from a comparable institution with a 3.7 undergrad GPA, 1 grad micro course, and 1 year of RA experience.

    Conditional on already having rigorous grad econ courses, I advise *every* applicant against taking grad real analysis unless they have a substantiated belief they'd be specializing in micro theory or econometric theory. By substantiated belief, I mean something like 1 year of working in a supervised research project in either of those topics. Chances are you should already be enrolled in a grad econ program by the time you can make that decision.
    Thanks a lot for shedding new light into the topic ! Students from previous years have been placed at top Canadian programs (Toronto, UBC, Queens) constantly and at top places in the US (Stanford, Princeton, Cornell, Penn, and few others I heard) and in the UK (LSE, UCL, and so on). I am trying to get some RA experience and was mulling over taking the Analysis class because I have time.But RA experience is top on my list. And my LOR's should be good I believed because my proffs know me very well in those grad classes ( I had a really good rapport with them).

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by therealslimkt View Post
    The OP is clearly not lacking math rigor. Its probably uncommon to have all those other courses and not analysis, but in this case it will probably help. Furthermore, real analysis is usually seen as desirable because it shows ability to handle the first year: the OP has already taken graduate micro and is getting a (hopefully strong) letter from that prof. Logically nothing points to real analysis as being the weakest link here. Graduate analysis seems like a bad use of time.

    This looks like many profiles posted here in the past where more experienced posters said "get a full time RA job and you are a top 10 shoo in". I would defer to chateau on their estimation that its not strictly necessary for top 20/Canadian top 5, but your admission chances are monotonically increasing in RA experience, and you always want to get accepted to the place you're on the margin for...
    Thanks so much!

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by chateauheart View Post
    I disagree strongly with leolin's advice. It's ridiculously off the mark.

    ...

    Looking back at leo's profile, on the other hand, he's a current applicant in this cycle, and has an unusually lopsided profile himself - little coding and too much math, as other posters had pointed out to him. He also seems to be underperforming his expectations in this cycle. I realize I'm being a jackass by digging up another poster's background, but it's bizarre to me that an underperforming applicant doesn't seem to realize his understanding of the admissions weights is flawed, and is now offering the same wrong approach to other applicants.
    I thought personal attacks weren't allowed on here; or is it one rule for some and a different rule for others?

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by chateauheart View Post
    I disagree strongly with leolin's advice. It's ridiculously off the mark.

    You have a MA from a top Canadian program, and you were top of your cohort. In terms of academic coursework, you are probably in the 98th+ percentile *within* the selective pool of applicants to top 20 programs. Additionally, your research interest and experience seem to be in empirical work. There is very little value, in either the short run or long run, from taking further graduate math. You're set for PhD applications. Any marginal effort should be focused on RA experience and building rapport with your letter-writers - but even that is not necessary for getting into a top Canadian PhD (or a equivalent top 20 program in the USA). Ask your professors what proportion of MA students they admit into their PhD programs per year just based on their master's performance, and chances are you're well within the quota. There's no uncertainty here.

    You've received conflicting advice, so let me explain the difference in our experience here. I personally took grad real analysis as a 19 year old, and another grad probability course at 20. I don't think they helped me a single bit in my graduate econ career. I've never looked back into Billingsley (the reference text) even once after I finished the course. And, judging from my conversation with two top 5 adcom members after my application season, the grad math courses were not key to my application success. They were, on the other hand, a huge expenditure of time.

    Looking back at leo's profile, on the other hand, he's a current applicant in this cycle, and has an unusually lopsided profile himself - little coding and too much math, as other posters had pointed out to him. He also seems to be underperforming his expectations in this cycle. I realize I'm being a jackass by digging up another poster's background, but it's bizarre to me that an underperforming applicant doesn't seem to realize his understanding of the admissions weights is flawed, and is now offering the same wrong approach to other applicants. Flagrantly wrong advice like this - the undue obsession with grad-level math and lack of emphasis on research experience - is frustrating as hell, especially when we've been pointing it out on this forum for 5 consecutive years, and every cycle we have dozens of cases reaffirming the forum's consensus. We've had an applicant with 4.0 in 2 years of grad math at an Ivy league university who got significantly worse admissions results than another applicant from a comparable institution with a 3.7 undergrad GPA, 1 grad micro course, and 1 year of RA experience.

    Conditional on already having rigorous grad econ courses, I advise *every* applicant against taking grad real analysis unless they have a substantiated belief they'd be specializing in micro theory or econometric theory. By substantiated belief, I mean something like 1 year of working in a supervised research project in either of those topics. Chances are you should already be enrolled in a grad econ program by the time you can make that decision.
    One last thing, I won't tell you the name, but the underperformer did get to a top theory school outside top 20, which is exactly my expectation.
    Last edited by leolin; 04-24-2019 at 12:22 AM.

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    Re: Phd in Economics - Fall 2020 Cycle

    Chateu's advice is spot on. Leolin's intentions might be in the right place but leolin's advice is wrong.

    OP's profile is solid. Landing an RA would be great as long as OP's mentor actually provides good guidance on how to do research, or is able to write OP a solid recommendation letter. Getting such an RA is easier said than done though. Learning python often helps.

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by Kaysa View Post
    Chateu's advice is spot on. Leolin's intentions might be in the right place but leolin's advice is wrong.

    OP's profile is solid. Landing an RA would be great as long as OP's mentor actually provides good guidance on how to do research, or is able to write OP a solid recommendation letter. Getting such an RA is easier said than done though. Learning python often helps.
    Thanks !! Is python significantly different than MATLAB/STATA/R ?

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by JonSnowLives View Post
    Thanks !! Is python significantly different than MATLAB/STATA/R ?
    Matlab and R are general purpose programming languages with a focus on matrix and scientific/statistical applications. Stata is a statistical package with a programming language tacked on.

    Python is a general purpose programming language that is used in a wide variety of arenas. If you can program well in Matlab or R then learning Python is not that hard. Being good at Stata doesn't necessarily get you to the same point.

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