Let’s start with the definition of Panel data. Panel data has both cross-sectional and time-series features. Why Cross-sectional? Simply because panel data is created from various cross-sectional units. And why timeseries? because information on those cross-sectional units is collected across different time periods. It can be years, months or days or any other interval.

Types of Panel Data: Panel data can be of two type – balanced and unbalanced panel. We come across a balanced panel when each cross-sectional unit has exactly same number of time series observations. A unbalanced panel occurs when there are different number of time series observations for each of the cross-sectional units. If the number of cross sectional units is higher than the count of time series observations, then we have a short panel. Otherwise it is a long panel.

Advantages of Panel data: Now let’s discuss the advantages of the panel data.

1. Suppose we are trying to build a regression model and we have all the explanatory/independent(X) variables in a cross-sectional data format. However, we do not have the time-series component of the data which means we cannot test the behaviour of cross-sectional units over time. There is no way we can find out if the time variable played any role to influence the behaviour of cross-sectional units. This problem is addressed in panel data. It corrects for this omitted variable issue.
2. Since panel data combines both time series data and cross-sectional data, it enhances both the quantity and quality of data. So, it ensures more degrees of freedom for statistical analysis, less chances of collinearity among the variables. So, the estimation of unknown parameters using panel data will be more efficient.
3. Panel data is more beneficial to study the dynamic behaviour of a sample that cannot be captured either by cross-sectional or time-series data alone. For example, cross-sectional data can give us point estimate of the incidence of a particular illness. However, panel data will be able to show how the proportion of this incidence rate changes over time in the same cross-sectional unit.