Coloradoecon and Tutonic make a good point here about problem sets. My recommendation is to try to create a problem set for yourself (involving proofs).
For Metrics: - Wooldridge’s intro to econometrics book has proof practice problems
- Casella & Berger Statistical Inference
For Micro: The obvious choice is MWG and you can find the solutions manual online as a pdf form
For the comps, UCLA posts their preliminaries online for micro and macro. Try to solve those problems too.
Time yourself (without looking at the solutions) how long you take solving problems.
For STATA upgrade your obvious choice is to contact customer service.
Dogbones, I looked through your created threads and I do not think you should pursue a PhD in Econ. Not only do you severely lack any research experience; you are also spinning in wheels with the same questions and naivety. Most of your created threads could be solved by simply searching through the right keywords in urch and finding your answers. For which, is also an essential part of research. In 2018, you stated that you would begin an MA in 2019 whilst taking math classes prior to that. Then, you wanted to prepare even further so you postponed it to fall 2020. From my understanding, you graduated in 2013 and have been out of the game for close to 6 years now and you still are thinking about ‘internships’ or learn how to access econ datasets(which signifies you have not done any RA job & puts doubts on your whatever number of working papers); plus, the word internship should be a sin with 6 years of work experience. The created threads are mostly about hypothetical scenarios and frankly all of this seems like a waste of time and nonsense to me.
I’m sorry if my tone is harsh. But I will be honest where I can.
Fit doesn't, and shouldn't, factor into the decision to pursue a masters. The only metric of any importance, is the placement strength of the masters programme. Fit only enters the picture when you're deciding on which PhD programme to apply to.
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