Econometrics With R, Python and MATLAB

What is Econometrics?

Econometrics is a field in economics that applies statistical and mathematical methods to economic theories. It has become more relevant over the years as it helps economists quantify their economic theories and hypotheses. Econometrics helps economists test those theories by using statistical tools with mathematical equations. Therefore, it has become a crucial part of economic policymaking.

Econometrics usually involves establishing relationships between various economic variables. For that, economists use mathematical and statistical methods. Usually, economists must perform multiple calculations using complex models. Some economists use programming languages and other tools to expedite the process. These may include R, Python and MATLAB.

What is “R”?

“R” is a programming language that economists use for statistical computing and graphical representation. It offers an extensive list of statistical and graphical techniques. These include machine learning algorithms, time series, statistical inference, linear regression, etc. Furthermore, these are all tools that are an essential part of econometrics. Apart from econometrics, R is also prevalently used in other fields.

R is one of the most popular languages used by statisticians, researchers, analysts, and economists. Through it, they can extract, filter, analyze, visualize and present the data. It is also free to use and open-source, making it more accessible. It is among the top ten popular programming languages in the world. R has existed since the ‘90s but has gained popularity recently for its extensive features and runtime environment.

Base R contains a lot of functionality useful for econometrics, in particular in the stats package. In addition, there are many other econometrics packages available for free on the Internet.

What is Python?

Python is another powerful and high-level object-oriented programming language. It is the world’s most popular programming language. Like R, Python is also well-known among statisticians, economists, data scientists, and researchers. Similarly, most of the packages in R are available in Python as well, making it an all-in-one option for users. Apart from its usage for data processing, Python also has various other uses.

Python has existed since the ‘80s. However, the language has gained popularity recently due to its extensive list of libraries and ease of use. Most programmers recommend it as the best language for beginners to get started. Like R, Python is also open-source, making it available to the public. Most large companies in the technology industry use Python, including Google, Microsoft, Reddit, Mozilla, etc.

There exist many specialized libraries for performing econometrics studies in Python. Amongst them, Statsmodels is a frequently used package.

What is MATLAB?

MATLAB is a programming platform that focuses specifically on the needs of scientists, engineers, and data analysts. It allows users to make complex calculations, implement algorithms, create user interfaces, plot functions and data, and much more. It includes a vast library of mathematical functions for linear algebra, numerical integration, statistics, and differential equations.

MATLAB has some pre-programmed procedures that can help economists with their research. On top of that, there is a wide variety of open-source code available from other users online that is available to the public. Although it may not be as fast as Python or R, it is still the most famous program among high-level econometricians. Similarly, unlike Python and R, MATLAB is neither free nor open-source.

Econometrics studies can be performed by using the Econometrics Toolbox in Matlab.


Econometrics involves the use of statistical and mathematical methods to test economic theories. There are several tools or programming languages that can help econometricians. Usually, econometricians prefer R, Python, and MATLAB. All of these can help econometricians perform complex computations. Based on the needs and usage, each tool or language has its benefits and drawbacks.

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