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I recently asked a professor if he was planning on hiring a research assistant for next semester. I thought I'd be a pretty good candidate since I have decent experience using STATA, SAS, SPSS, R Studio and Mathematica, but he started asking me about a couple programs I had never heard of before. That led me to wonder what are the most commonly used programs for Economics. A friend of mine suggested I also look into Matlab and Python.

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Also, the professor could be annoying by a graduate/undergraduate student who claims he has decent experience with 6 fairly different and complex programs. –  Soccerman May 29 at 6:25
Could you specify what kind of Economics your professor is teaching? Time Series analysis, General Equilibrium modelling? The kind of program he uses probably depends on what he needs it to do. –  denesp May 29 at 8:09
I agree that the question is somewhat broad. At least you could explicitly state that you're after academic economists, which is somewhat implied in your question already. –  FooBar May 29 at 14:54
This was a Microeconomics professor, who specializes in Environmental Economics. –  Forgot the Jacobian May 29 at 21:40
+ to your friend! –  garej 2 days ago

5 Answers 5

From my experience (buy-side economist role),

  1. Eviews - the GUI is very convenient to deal with the most of the daily tasks e.g. updating econometrics models and forecasts; and its continuously improving interface with external databases make my life much easier
  2. R / Matlab - easy for monte carlo simulation and dealing with financial data and stochastics models

Excel is popular for equity financial modeling and corporate finance, but C++ / R are dominated in financial engineering / quants field

SPSS is more popular in other social science field as it is not really good at dealing with time series (major part of my work) in my opinion

SAS is good for huge set of data due to its unique memory management... but Eviews can handle most of situation in my case (unlike financial data, what we face with economic data is a lack of observation instead of too much data for the memory..)

Python is a fast program but not convenient to implement for daily analysis purpose.. and for the rest you mentioned, they evolve to provide quite similar functions nowadays

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Python is a programming language with extensive interfaces to a very large range of libraries - which makes it the swiss army knife for analysis for people with reasonable programming skills. For those who can't afford/get a Matlab license, the python numeric libraries provide good alternatives. C++ is also a programming language - and requires advanced programming skills. –  Lumi May 29 at 8:59
Some would say Python is a good alternative to Matlab even if you can afford/get a license. –  cc7768 May 29 at 15:23
You may very well think that, I couldn't possibly comment :) –  Lumi May 29 at 16:24

There's three important dimensions for programs/languages:

  • Convention: Having a program that everyone uses helps you to get feedback/help, work with coauthors, use other people's codes
  • Ease of use: Since many uses in economics are routines, having the program doing these for you and making your implementation of the use easier is a big bonus
  • Adaptability: A program that allows you doing covering most of your needs and learning only one syntax versus having to work with different programs at the same time

In terms of frequency of usage among academic economists, here's my ranking:

Top tier

  • For econometrics, by far, STATA. Mostly because of convention and ease of use.
  • For dynamic programming, and to some extent monte carlo, by far, Matlab. Mostly because of convention and ease of use

Second tier

  • For time series econometrics, Eviews (ease of use)
  • For all kinds of econometrics, R (adaptability, somewhat convention)
  • The swiss knife of really anything, Python (adaptability)


  • SAS, for huge data sets

This list is of course my personal opinion, and for academic economists only. I believe that no one will dispute the top tier, but the second tier/specialists can be somewhat debated. And then there's some more who are even more specialist (for example, Octave as a open source Matlab alternative)

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Octave * is the open source Matlab alternative. –  Hessian May 29 at 15:03

This really depends on your school or profession as to what is most prevalent.

Professors at my school seem to use mostly Matlab and Stata. Some subjects even require GAUSS, which I had never heard of before. There is also some python involved.

In my experience (anecdotal), the finance sector uses excel a lot.

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To add to the anecdotal evidence collection, I also have experienced that Stata is the most standard stats software.

EViews is another option.

As for other programs, beside statistical analysis software, LaTeX is a programming language used to format documents for presentation.

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LaTeX is a markup language. –  jmbejara May 29 at 9:52
Actually LaTeX is Turing complete and thereby a programming language. –  Rud Faden May 29 at 18:52
@RudFaden So is Microsoft Excel. –  Michael Greinecker 2 days ago

A whole lot of paid and free stuff exists for almost everything required for economics analysis. I’m not an environmental guy, but you may start your quest to guess what your professor meant by visiting this link (among hundreds alike). For more detailed treatment, see a book.

For a general overview, let’s consider a following list (I will state only programs that I launched at least once in my life, not claiming for profound knowledge =))):

  • For impact analysis: IMPLAN, REMI, to name a few.
  • For DSGE: Dynare backed by GNU Octave
  • For spatial (GIS) analysis: Esri ArcGIS vs MapInfo
  • For Statistical Analysis: Stata, EViews (BTW, used by FED), Statistica (former Statsoft, currently Dell), Statgraphics; + Free: R (R Studio as IDE), GNU Gretl for free-riders
    …Oh, SAS/Stat and IBM SPSS, and plenty of Oracle stuff that I do not like (for thier policy and prices) just for completeness.
    + Excel add-ins, like XLStat.
  • BigData: Hadoop + Haskell as a functional programming language (actively used in finances).
  • Dynamic modelling: Vensim and a whole lot of dynamic modelling software.
  • Algebraic packages: Matlab backed by Simulink vs Mathematica backed by SystemModeler (less so for Economics). Some people indeed use Maple. + Free aforementioned Octave.
  • Must-to-know-the-basics: Excel VBA and a whole lot of Excel add-ins (like NodeXL for networks - may be not that much used but nice).
    BTW, what I know about networks makes me to mention Ucinet.
  • Some general purpose languages: Python, including packages like Pandas, Scipy, Numpy, IPython, Theano etc. (imho, better to use in bundles like Anaconda etc.)
    May be, C++ or Java as object-oriented languages (just to mention).
  • Databases: relational MySQL and recently coming modern NoSQL solutions like MongoDB (nice with Python).
  • Just for snacks...
    • Agent-based modelling: NetLogo.
    • Game theory: Gambit (TTBOMK written in Python).
    • Experimental economics: ZTree.

Thanks for the occasion to reflect the issue. Hope that helps.

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