When I construct panel data from large household surveys (say, World Bank's Living Standard Measurement Surveys), I try to construct data set with as many potentially usable variables as possible. This creates a large unbalanced dataset and I don't know how many balanced data left until I run a regression.
I personally have not encountered any problems with this, but I wonder what other people think when they have to use dataset I construct. I have not worked with others so far, but I wonder how I should construct a good dataset to work on if I need to work with professors. Should I construct balanced dataset? Or unbalanced dataset with many variables with many missing values?