This book is about doing panel data econometrics with the R software. As such, it is aimed at both panel data analysts who want to use R and R users who endeavor in panel data analysis. In this introductory chapter, we will motivate panel data methods through a simple example, performing calculations in base R, to introduce panel data issues to the R user; then we will give an overview of econometric computing in R for the analyst coming from different software packages or environments.
In this section we will introduce the broad subject of panel data econometrics through its features and advantages over pure cross‐sectional or time‐series methods. According to Baltagi (2013), panel data allow to control for individual heterogeneity, exploit greater variability for more efficient estimation, study adjustment dynamics, identify effects one could not detect from cross‐section data, improve measurement accuracy (micro‐data instead of aggregated), use one dimension to infer about the other (as in panel time series).
From a statistical modeling viewpoint, first and foremost, panel data techniques address one broad issue: unobserved heterogeneity, aiming at controlling for unobserved variables possibly biasing estimation.
Consider the regression model
where is an observable regressor and is unobservable. The ...