Skip to main content

Stata vs R vs Python -- What Should I Master to Analyze Data?

Panel Discussion
Stata R Python
Tuesday, December 6, 2022, 5:30 pm – 6:45 pm

This is a hybrid event, organized in partnership with the Vienna Data Science Group and the Vienna Applied Micro Economics Network.

This is an in-person event on the CEU campus: 1100 Vienna, Quellenstrasse 51, auditorium and you are invited for a drink after the event to stay for networking in the data community of Vienna and continue discussion.

If you can not attend in-person, you will get a Zoom link to join online.



The core of the event is a discussion between three teams (Stata, python, and R-users) about their choice and experience.

There has been a large discussion on the choice of coding language for data analysis for many years, and it is still very much happening. Open source vs plug and play, industry vs academia, data science versus research, there are several considerations.


This is a public event targeted at students and early career practitioners interested in analyzing data for any purpose such as prediction or policy-making. The focus is data analysis: importing and wrangling datasets (incl. large tabular or text); exploration and visualization, estimating causal relationships (e.g. panel data methods, event studies), and making predictions (incl. cross-validation, ML methods like random forest).


We asked all participants three questions: Tell us about yourself, what are you working on, what coding language do you use?

Gábor Békés, Master of Ceremony

  1. My name is Gábor Békés, I'm an assistant professor at CEU and co-author of the recent textbook Data Analysis for Business, Economics, and Policy.
  2. I'm currently working on understanding how having the same cultural background may help people collaborate more intensively in multinational teams. 
  3. In my research, I use Stata and R to clean and combine data tables and rely on R and Python to scrape and parse data. My textbook has case study code available in R, Python, and Stata. 

Arieda Muço,  Team Python 

  1. My name is Arieda Muço and I am an Assistant Professor of Economics at CEU. 
  2. My research lies in the intersection of Political and Development Economics combining tools from natural language processing, machine learning, and causal inference. 
  3. At CEU  I teach Machine Learning for Natural Language Processing with Python, Introduction to Python, and Causal Inference with Stata (Econometrics 2). 

Gayane Gadyan, Team Python 

  1. My name is Gayane Gadyan, I'm a Data Scientist at BlackRock. I’ve studied MA in Economics at CEU and graduated in 2020. 
  2. In my current position, I’m involved in various projects that assume the use of Python on a daily basis. My projects are concentrated mainly on sales data. 
  3. I am working with large amounts of data and building the end-to-end pipeline: from data retrieval up to deployment. 

Marc Kaufmann, Team R

  1. I am Marc Kaufmann, an Assistant Professor in the Department of Economics and Business at CEU
  2. I study the biases and beliefs that people have via online experiments that I code in congame, an experimental economics software in Racket I develop with Bogdan Popa.
  3. So while I predominantly code in Racket, when the experimental data is collected, I load, clean, and analyze it in R, primarily relying on the tidyverse packages.

Zsuzsa Holler, Team R

  1. My name is Zsuzsa Holler, I graduated from the Master in Economics program in 2012 and returned to CEU to teach seminars in the Business Analytics program. Currently, I work as a data scientist for an IT company called Emarsys (owned by SAP now) where I develop AI solutions in the field of e-marketing.
  2. The research project we have been working on recently is about the improvement of an existing bayesian bandit model which optimizes marketing message send times.
  3. I use R to query data from the data warehouse, prepare descriptive statistics and run statistical models. Also, the performance monitoring dashboard related to the project was developed in shiny.

Miklós Koren, Team Stata

  1. My name is Miklós Koren, I am a Professor of Economics at CEU and the Data Editor of the Review of Economic Studies, a leading academic journal in economics.
  2. In this second capacity, I review a lot of scientific code written by authors and give them suggestions on how to improve them.
  3. Stata is a widely used tool among authors and its scripting language is easy to understand, which is crucial if you share code with others.

Márton Fleck, Team Stata

  1. I am Márton Fleck, an associate at RBB Economics, an economic consultancy, and also a doctoral candidate in Economics at CEU. 
  2. Using highly granular data from football, I am currently working on a project to understand the factors that affect the decision-making of the referees. 
  3. I use Stata to clean, combine, and analyze the datasets, and to prepare tables and graphs for the paper.


We are collecting data to the debate -- both from college education and from real life.

R vs Python vs Stata -- Here you find the survey.

It only takes 2 minutes to fill in.


17.30-17.35    Welcome

17.35-17.50    Intro talk of Gabor Bekes

17.50-18.10    The three teams make their case

18.10-18.30    Debate and discussion

18.30-18.45    Q&A


Listed among the top 100 universities worldwide in the QS World University Rankings in a variety of subjects, CEU is known for excellence in teaching and research.

Based in Vienna CEU brings together students and faculty from over 100 countries to exchange ideas in an open and dynamic community.

CEU is accredited in the United States and Austria, and offers English-language Economics and Business Master's in

  • Business Analytics
  • Economics
  • Finance
  • Economic Policy in Global Markets


  • You may enjoy the live debate in-person (Vienna, 1100 Quellenstrasse 51) or ask for a Zoom link to follow online.
  • You are invited for a drink after the event to stay for networking and continue discussion.
  • Please register here, make your choice and you will learn all details in a return mail.