I know that the panel data accounts for both heterogeneity across individuals or groups for dynamic effects that are not visible in cross sections, but should this be the answer to this question?
The main feature would be dealing with some types of heterogeneity/omitted variable problems. Dynamic adjustment is another. There are at least two more:
- Since panel data have variation across units and across time, so more efficient estimation is possible, at least sometimes. There's also more variability, less collinearity, and more degrees of freedom.
- Some problems can only be dealt with in a panel setting. Consider the problem of distinguishing between returns to scale (compare costs of firms of different size) from that of technological change.