<p>If you are only looking for &quot;A department where <strong>at least few</strong> researchers use R?
&quot;, I believe you should be able to find plenty. In my department (Vanderbilt University), I can count <em>at least</em> 3 grad students using R instead of Stata (oh and I guess with myself it makes 4 ;)).</p>
<p>If you are looking for more heavily R-oriented econ department, you might have a harder time. Not necessarily because they do not exist, but because it is not all that easy to figure out (I suspect you don't want to personally ask every graduate students/professors of the departments you are interested in).</p>
<p>Some informative signals might be publicly available however, such as :</p>
<ul>
<li><p>Do people at the department use R in their publications?</p>
<ul>
<li>as suggested by Jan Hoffler, you may want to use the Replication Wiki to figure this out.</li>
<li>You can also look at people's website in case they provide data and replication files for published papers.</li>
</ul>
</li>
<li><p>Is the use of R encouraged in classes given by faculty members at the department?</p>
</li>
<li><p>Does the department offer R tutorials?</p>
</li>
<li><p>Are some of the professors/grad student openly R enthusiasts (again look at personal websites)?</p>
<p>For instance :</p>
</li>
<li><p>This looks like a bad signal : <a href="http://www.bbk.ac.uk/ems/for_students/it/free" rel="nofollow noreferrer">http://www.bbk.ac.uk/ems/for_students/it/free</a></p>
</li>
<li><p>This looks like a good signal : <a href="http://www.clemson.edu/economics/faculty/wilson/Software/FEAR/fear.html" rel="nofollow noreferrer">http://www.clemson.edu/economics/faculty/wilson/Software/FEAR/fear.html</a></p>
</li>
</ul>

CC BY-SA 3.0
2015-04-26T20:56:40.987Z
2016-02-14T14:38:12.530Z
2020-06-17T09:40:54.643Z
Martin Van der Linden
<p>Basically it's better to use the software your PI uses! First (s)he will be able to correct your code. Second, if you're a TA for a class using one software, it's better to handle it...
To find the faculty using R, either have a look at the papers/books published by one department. <strong>Or look at the R-packages published</strong> in your field and find the authors.</p>

<p>I wouldn't look at the cost of a software, because the university often provided it for free or can reimburse you. (Of course you can prefer free softwares for other aspects but then it's not a budget constraint).</p>

CC BY-SA 4.0
2019-04-25T18:34:33.870Z
What does PI stand for?
ahorn
CC BY-SA 4.0
2019-05-10T15:25:51.453Z
https://en.wikipedia.org/wiki/Principal_investigator
Yann
CC BY-SA 3.0
2015-04-26T21:54:00.360Z
2015-04-26T21:54:00.360Z
Yann
<p>In my university the choice of
program is considered generally irrelevant. We focus on results, and it is up to each student to determine which program is best suited for the task and user preference.</p>

<p>You will find that using one language translates very well to another. With resources like stackoverflow, I would not be too concerned about which.</p>

<p>I would very carefully consider the statement "two equal universities". My experience has suggested to me such a thing does not exist, granting personal ambitions, career goals, and topic preference. I think programming choices are perhaps only a proxy for technical rigor and budget, little more.  Given you are only accepted to a finite number of schools, take time to evaluate this criteria closely.</p>

CC BY-SA 3.0
2015-04-27T13:37:31.817Z
While I agree that the choice of program should be irrelevant in theory, in practice, programming something in R to match the result in Stata can add a day or two, which quickly adds up. Plus, there's always the worry that you have some hidden logic errors. What I often do is clean the data in R and do the econometrics in Stata.
Heisenberg
CC BY-SA 3.0
2015-04-27T15:21:48.813Z
@Heisenberg While I agree with you, I think this posts main point is: There are many other criteria which are first-order, and programming choice is second-order. Given the small set of acceptances, it is unlikely that a student has been accepted to two schools that are exactly equal on all the first-order issues and hence "gets to decide" using this second-order criterion.
FooBar
CC BY-SA 3.0
2015-04-26T21:23:40.397Z
2015-04-27T15:07:04.530Z
2015-04-27T15:07:04.530Z
RegressForward
<p>As an economics researcher or a finance oriented professional, it is never enough to know only one language. Here is why : </p>

<p>1) Researchers or experts of different generation ( think about your colleague or the professor or the people working in the high level of position in financial institution) have different habit of using the language. If you would like to partner with them or learn from them, learn their communication language is the only way. For example, Attilio Meucci, an expert in asset allocation, only published his work on Matlab forum. And most of the professors will only use Stata. </p>

<p>2) R is not perfect even it is a hit among the data scientist or statistician for the reason that it's free. Yes, open source and being free is both its good and bad side, the bad point is you need to check very carefully the source code with respect to a complex algorithm, e.g Panel GMM in econometrics. However, the Stata is more user-friendly as it is maintained by a company and can efficiently fix the problem from users' feedback, most of which are professors. As far as I have known, economist such as Barro and Wooldrige all use Stata. I don't see the reason why you cannot learn both.  </p>

<p>3) Expert of R could have a more efficient leaning curve than others who are not. I learn R first, and catched on learning Stata easily in the econometrics course when I was an undergraduate student. The programming essence is similar. Some might say that Stata is easier to learn than R. </p>

<p>So my advice is, go for languages you need. I see lately Professor Sargent starting to learn Python as an old man of around 70 years old. I think you can too being way younger as a graduate student. Good luck.  </p>

CC BY-SA 3.0
2018-02-09T15:27:34.427Z
2018-02-09T15:46:49.840Z
2018-02-09T15:46:49.840Z
exteral
<p>According to my personal observation the majority of (prominent) economists <s>prefer</s> use Stata for their statistical analysis and Matlab for other mathematical work. SAS and Excel are also used (especially in finance). </p>

<p>In my opinion R is a much better software for data cleaning, manipulation and analysis than Stata (not to mention that Stata costs) it is also seems on par with Matlab in what it does best. But I guess (as a graduate student) it will not make cooperation very smooth using a different statistical program than the rest. Use Stata like everyone else or suffer?</p>

<p>Thus a student who is an 'R expert' should, if having to choose between two equal departments, choose the one that uses R. But does such a department exist? A department where at least few researchers use R?</p>

CC BY-SA 3.0
2016-02-12T16:57:52.817Z
[You can use the ReplicationWiki (that I work on) to find out about some authors who have used r for their publications](http://tinyurl.com/R-in-ReplicationWiki).
Jan Höffler
CC BY-SA 4.0
2019-04-25T18:37:49.150Z
I don't think the question is good enough. Your question is essentially, "Does a department that uses R exist?"
ahorn
CC BY-SA 4.0
2019-04-25T21:05:45.643Z
@ahorn sure, do you suggest some improvements or deletion? It's not a question I am interested in at this point in time.
snoram
CC BY-SA 3.0
2015-04-27T12:11:56.610Z
During your career your probably going to learn several languages. It is really not a big deal. If you already good a R, switching is going to be much less of a hassle then learning R was - if that was your first program.
Thorst
CC BY-SA 3.0
2015-04-27T22:53:59.210Z
In my experience, most economists program badly in each language they use— they use loops in R when they should use vectorized operations, they use Stata macros for all sorts of things, and so on. If you're a good programmer, switching should be easy because you understand programming paradigms. If you're a bad programmer, switching should be easy because you're just going to learn slightly different syntax with which to write bad code. Never choose an econ grad program based on a programming language, that's like buying a home because you like the color the master bedroom is painted.
dismalscience
CC BY-SA 3.0
2015-05-07T19:50:56.540Z
I just came across a smiliar discussion on 'Stack Overflow': http://stats.stackexchange.com/questions/25811/is-the-r-language-reliable-for-the-field-of-economics
snoram
<software><r><stata>
R in econ departments?
snoram
# R in econ departments?

(Asked by: username_0 on 2015-04-26)

According to my personal observation the majority of (prominent) economists ~~prefer~~ use Stata for their statistical analysis and Matlab for other mathematical work. SAS and Excel are also used (especially in finance).

In my opinion R is a much better software for data cleaning, manipulation and analysis than Stata (not to mention that Stata costs) it is also seems on par with Matlab in what it does best. But I guess (as a graduate student) it will not make cooperation very smooth using a different statistical program than the rest. Use Stata like everyone else or suffer?

Thus a student who is an 'R expert' should, if having to choose between two equal departments, choose the one that uses R. But does such a department exist? A department where at least few researchers use R?

**Tags:** software, r, stata

> **Comments:**
> **username_3**: During your career your probably going to learn several languages. It is really not a big deal. If you already good a R, switching is going to be much less of a hassle then learning R was - if that was your first program.  
> **username_4**: In my experience, most economists program badly in each language they use— they use loops in R when they should use vectorized operations, they use Stata macros for all sorts of things, and so on. If you're a good programmer, switching should be easy because you understand programming paradigms. If you're a bad programmer, switching should be easy because you're just going to learn slightly different syntax with which to write bad code. Never choose an econ grad program based on a programming language, that's like buying a home because you like the color the master bedroom is painted.  
> **username_0**: I just came across a smiliar discussion on 'Stack Overflow': http://stats.stackexchange.com/questions/25811/is-the-r-language-reliable-for-the-field-of-economics  
> **username_1**: [You can use the ReplicationWiki (that I work on) to find out about some authors who have used r for their publications](http://tinyurl.com/R-in-ReplicationWiki).  
> **username_2**: I don't think the question is good enough. Your question is essentially, "Does a department that uses R exist?"  
> **username_0**: @username_2 sure, do you suggest some improvements or deletion? It's not a question I am interested in at this point in time.  

---

## 4 answers

### Answer by username_7 on 2015-04-26. Score: 15

In my university the choice of
program is considered generally irrelevant. We focus on results, and it is up to each student to determine which program is best suited for the task and user preference.

You will find that using one language translates very well to another. With resources like stackoverflow, I would not be too concerned about which.

I would very carefully consider the statement "two equal universities". My experience has suggested to me such a thing does not exist, granting personal ambitions, career goals, and topic preference. I think programming choices are perhaps only a proxy for technical rigor and budget, little more. Given you are only accepted to a finite number of schools, take time to evaluate this criteria closely.

> **Comments:**
> **username_8**: While I agree that the choice of program should be irrelevant in theory, in practice, programming something in R to match the result in Stata can add a day or two, which quickly adds up. Plus, there's always the worry that you have some hidden logic errors. What I often do is clean the data in R and do the econometrics in Stata.  
> **username_9**: @username_8 While I agree with you, I think this posts main point is: There are many other criteria which are first-order, and programming choice is second-order. Given the small set of acceptances, it is unlikely that a student has been accepted to two schools that are exactly equal on all the first-order issues and hence "gets to decide" using this second-order criterion.  

---

### Answer by username_5 on 2015-04-26. Score: 8

If you are only looking for "A department where **at least few** researchers use R?
", I believe you should be able to find plenty. In my department (Vanderbilt University), I can count *at least* 3 grad students using R instead of Stata (oh and I guess with myself it makes 4 ;)).

If you are looking for more heavily R-oriented econ department, you might have a harder time. Not necessarily because they do not exist, but because it is not all that easy to figure out (I suspect you don't want to personally ask every graduate students/professors of the departments you are interested in).

Some informative signals might be publicly available however, such as :

* Do people at the department use R in their publications?

  + as suggested by Jan Hoffler, you may want to use the Replication Wiki to figure this out.
  + You can also look at people's website in case they provide data and replication files for published papers.
* Is the use of R encouraged in classes given by faculty members at the department?
* Does the department offer R tutorials?
* Are some of the professors/grad student openly R enthusiasts (again look at personal websites)?

  For instance :
* This looks like a bad signal : <http://www.bbk.ac.uk/ems/for_students/it/free>
* This looks like a good signal : <http://www.clemson.edu/economics/faculty/wilson/Software/FEAR/fear.html>


---

### Answer by username_6 on 2015-04-26. Score: 7

Basically it's better to use the software your PI uses! First (s)he will be able to correct your code. Second, if you're a TA for a class using one software, it's better to handle it...
To find the faculty using R, either have a look at the papers/books published by one department. **Or look at the R-packages published** in your field and find the authors.

I wouldn't look at the cost of a software, because the university often provided it for free or can reimburse you. (Of course you can prefer free softwares for other aspects but then it's not a budget constraint).

> **Comments:**
> **username_2**: What does PI stand for?  
> **username_6**: https://en.wikipedia.org/wiki/Principal_investigator  

---

### Answer by username_10 on 2018-02-09. Score: 1

As an economics researcher or a finance oriented professional, it is never enough to know only one language. Here is why :

1) Researchers or experts of different generation ( think about your colleague or the professor or the people working in the high level of position in financial institution) have different habit of using the language. If you would like to partner with them or learn from them, learn their communication language is the only way. For example, Attilio Meucci, an expert in asset allocation, only published his work on Matlab forum. And most of the professors will only use Stata.

2) R is not perfect even it is a hit among the data scientist or statistician for the reason that it's free. Yes, open source and being free is both its good and bad side, the bad point is you need to check very carefully the source code with respect to a complex algorithm, e.g Panel GMM in econometrics. However, the Stata is more user-friendly as it is maintained by a company and can efficiently fix the problem from users' feedback, most of which are professors. As far as I have known, economist such as Barro and Wooldrige all use Stata. I don't see the reason why you cannot learn both.

3) Expert of R could have a more efficient leaning curve than others who are not. I learn R first, and catched on learning Stata easily in the econometrics course when I was an undergraduate student. The programming essence is similar. Some might say that Stata is easier to learn than R.

So my advice is, go for languages you need. I see lately Professor Sargent starting to learn Python as an old man of around 70 years old. I think you can too being way younger as a graduate student. Good luck.


---

