Course Advice during RAship

[coloradoecon]

I’ve taken the PhD sequence in Micro and Metrics at my unranked university and received A’s. Textbooks were Greene and Wooldridge for Metrics and MWG for Micro.

 

As for math, I’ve taken multivariate calculus, Linear Alg I-II, Diff Eq, Probability, Math Stats, Real Analysis I-II, Set Theory, Topology, and grad lebesgue theory. (A’s in all classes).

 

For research, I've RA'ed for a few years with two professors and did a senior thesis on an empirical topic. I'm graduating with a B.S. in Mathematics and Economics.

 

During my pre-doc RA stint at a Fed bank, I have the opportunity to take some courses at a T40 program.

If you could pick two courses from below, what would you advise? My interests are in Micro and Metrics.

 

1. Grad topology
   
2. Grad functional analysis
   
3. Grad complex analysis
   
4. Measure theoretic probability
   
5. Abstract Algebra
   
6. PhD Micro I (again, but this time at a better institution)
   
7. Other (something else)
   

[econliker]

Are your interests theoretical micro/metrics or are you planning empirical work? I think from your post it seems like you prefer theory, but if you're actually more of an applied person you've already taken sufficient courses and now the most important part will be your letters, in my opinion. On the other hand, for theory, those courses you listed would be more relevant. My sense is that measure theoretic probability would be the most directly relevant to metrics theory. I was also initially going to suggest grad topology, but that seems like it would be a bit overkill given that you've done undergrad topology already.

 

Others should jump in with their two cents since I'm not a theory person, but it seems like you're on a great path towards a strong graduate program!

[rtj]

If you could pick two courses from below, what would you advise? My interests are in Micro and Metrics.

 

1. Grad topology
   
2. Grad functional analysis
   
3. Grad complex analysis
   
4. Measure theoretic probability
   
5. Abstract Algebra
   
6. PhD Micro I (again, but this time at a better institution)
   
7. Other (something else)
   

 

For metrics and micro theory, I’d say probability is useful. Additionally, functional analysis may be useful, but it probably depends on how it’s taught and what the focus is. Another option is to look into an optimization course using a text like Luenberger (1969). I see this referenced frequently in macro, micro, and metrics, and the text covers core aspects of functional analysis in the context of optimization. There you’d probably learn the relevant functional analysis to economics. Grad topology is a very broad subject, as topology is a very active area of mathematical research, but I don’t think it’s necessary - point-set should be enough, and you can pick up more later if necessary. I don’t think complex analysis will be useful, unless (perhaps) you want to do time series. I don’t think algebra will be useful at all. I personally wouldn’t redo PhD micro a second time, as you’d redo it a 3rd time during your PhD. There’s an unnecessary signaling risk there as well.

 

I agree with the above poster - if you want to do empirical work, you don’t need more math. Also, in any case, focus on getting good letters. Don’t forget that once you have a certain level of mathematical maturity and personal discipline, which you seem to have, you can self study math.

 

This is just my take based on what I’ve read and heard from my advisors. I’m applying this cycle and want to do work in macro and metrics. Our math backgrounds seem similar, which is why I replied.