Panel data regression is a powerful way to control dependencies of unobserved, independent variables on a dependent variable, which can lead to biased estimators in traditional linear regression models. In this article, I want to share the most important theoretics behind this topic and how to build a panel data regression model with Python in a step-by-step manner.

My intention to write this post is twofold: First, in my opinion, it is hard to find an easy and comprehensible explanation of an integrated panel data regression model. Second, performing panel data regression in Python is not as straightforward as in R for example, which doesn´t mean that it is less effective. So, I decided to share my knowledge gained during a recent project in order to make future panel data analysis maybe a bit easier ;-)

Enough talk! Let´s dive into the topic by describing what panel data is and why it is so powerful!

#python

10.65 GEEK