Unbalanced data or Balanced data Unbalanced panels are more common in economic fields, if I want to know the behaviour of firms, what will be the differences using unbalanced data panel. Are there advantages? Does it depend on analysis's period? Or it will be better use balanced panel?
Thanks!
 A: The differences are usually more of a historic nature which is related to the matrix algebra involved. However, this was only a concern when econometrics had to be done by pen and paper way back in the days and today these technicalities barely matter. A discussion of this was provided in an earlier answer by StasK which you can find here.
The main concern with unbalanced panel data is the question why the data is unbalanced. If observations are missing at random then this is not a problem - for a good explanation of what "missing at random" means, have a look at this answer by Peter Flom. If the attrition of firms in your data over time is not random, i.e. it is related to the idiosyncratic errors $u_{it}$, then this sample selection may bias your estimates. For an example of such a case see here (the introductory textbook by Wooldridge, the example is also about panel data for firms as in your case).
A simple test for such sample selection was proposed by Nijman and Verbeek (1992) for fixed and random effects models. Generate a selection indicator $s_{it}$ which equals one if a firm is observed in a given year and zero otherwise. Add the the lagged selection indicator $s_{i,t-1}$ to your model and estimate it via fixed effects using the whole data. Then you test whether $s_{i,t-1}$ is significant. The hypothesis is that the error $u_{it}$ is uncorrelated with the lagged selection indicator, so $s_{i,t-1}$ should be insignificant in order to conclude that attrition is random.
If you want to learn more about this topic, Wooldridge (2010) "Econometric Analysis of Cross-Section and Panel Data" devotes an entire chapter (ch. 19) to sample selection and attrition.
A: It's better to use all available data. If your data is unbalanced, then it's not cool to remove the data to make the panel balanced. Instead, you apply methods which handle unbalanced panels.
