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Thread: Phd in Economics - Fall 2020 Cycle

  1. #21
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    Re: Phd in Economics - Fall 2020 Cycle

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    Quote Originally Posted by Rohanps View Post
    Ithought personal attacks weren't allowed on here; or is it one rule for someand a different rule for others?


    Thanks for standing up for me. I have dedicated rationaland non-attacking responses to him and I do not wish to have more conversation withuncivilized person, which is a waste of time.

    Last edited by leolin; 04-24-2019 at 12:23 AM.

  2. #22
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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 ?
    Python is most similar to R. I recommend python because it is fast, easy to read, and is the best at scraping data. Scraping data is in demand because it is a great way to construct a novel data set.

    Matlab is very niche. I never used it, and most of my colleagues don't use it either.

    Stata is easy. You can pick up the basics in a couple hours, and in most cases that it all you will ever need to do most economic reasearch. However, in some cases stata makes simple tasks complicated and complicated tasks very laborious.

    R is harder to learn than stata, but it has an impressive statistical library. Unfortunately, that library also has many bugs and quality control issues are prevalent. R is also slow and difficult to read. I quit using R because I could not read my old code for past empirical projects.

    Python is harder to learn than stata, but it is still not that hard to learn. It's documentation and online resources are excellent, unlike stata. It's statistical library is good and growing. I like python because it is very easy to read. You can go back to old projects and pick up from where you left off quickly. It is also the best at scraping data, which is important right now. A lot of novel data sets are starting to come from scraping websites or other sources.

    I will note that R is easier when it comes to running any analysis, but python is way easier when it comes to data cleaning. Most projects are 90% data cleaning, which is why I really like python.

  3. #23
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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by Kaysa View Post
    Python is most similar to R. I recommend python because it is fast, easy to read, and is the best at scraping data. Scraping data is in demand because it is a great way to construct a novel data set.

    Matlab is very niche. I never used it, and most of my colleagues don't use it either.

    Stata is easy. You can pick up the basics in a couple hours, and in most cases that it all you will ever need to do most economic reasearch. However, in some cases stata makes simple tasks complicated and complicated tasks very laborious.

    R is harder to learn than stata, but it has an impressive statistical library. Unfortunately, that library also has many bugs and quality control issues are prevalent. R is also slow and difficult to read. I quit using R because I could not read my old code for past empirical projects.

    Python is harder to learn than stata, but it is still not that hard to learn. It's documentation and online resources are excellent, unlike stata. It's statistical library is good and growing. I like python because it is very easy to read. You can go back to old projects and pick up from where you left off quickly. It is also the best at scraping data, which is important right now. A lot of novel data sets are starting to come from scraping websites or other sources.

    I will note that R is easier when it comes to running any analysis, but python is way easier when it comes to data cleaning. Most projects are 90% data cleaning, which is why I really like python.
    I am good with R so Python seems doable.

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    Re: Phd in Economics - Fall 2020 Cycle

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    Last edited by chateauheart; 04-25-2019 at 07:23 PM. Reason: rude

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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by JonSnowLives View Post
    I am good with R so Python seems doable.
    Absolutely. Python is much easier to do then R, and its piping capabilities are really nice once you get them running.

  6. #26
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    Re: Phd in Economics - Fall 2020 Cycle

    Quote Originally Posted by Kaysa View Post

    Stata is easy. You can pick up the basics in a couple hours, and in most cases that it all you will ever need to do most economic reasearch. However, in some cases stata makes simple tasks complicated and complicated tasks very laborious.

    ...

    Python is harder to learn than stata, but it is still not that hard to learn. It's documentation and online resources are excellent, unlike stata. It's statistical library is good and growing. I like python because it is very easy to read. You can go back to old projects and pick up from where you left off quickly. It is also the best at scraping data, which is important right now. A lot of novel data sets are starting to come from scraping websites or other sources.
    I agree with you regarding Python vs R, but feel that you're being rather harsh on Stata. In particular, I've found Stata's online resources (such as Statalist) to be incredibly helpful and comprehensive when trying to resolve an issue with code. Agree that Stata is probably best for data cleaning once one has obtained the raw data (e.g. through web scraping with Python).

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    Re: Phd in Economics - Fall 2020 Cycle

    Thanks everyone for all the replies and I apologize for any discord that may have arisen among the posters. I am sure all of the people in this forum has good intentions in their hearts while posting their thoughts. So I was wondering for some sort of definite advice about applying to US schools : Given my profile, what range of rankings should I be realistically looking at (not being over optimistic as well as not being that pessimistic).My interests are in Macro/Trade.

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