my question involves a panel dataset. I have a number of firms over a period from 2001-2017 for various variables like total assets, net income, liabilities,….
Example of firm dataset which has some missing values:
Firm – date – total assets – net income – liabilities
Apple – 2001 – xyz – xyz – xyz
Apple – 2017 – xyz – missing – xyz
Amazon – 2001 – xyz – xyz – missing
Amazon – 2017 – missing – xyz – xyz
Now I want to calculate some descriptive statistics of the firms in the dataset. For example, I want to calculate the average total assets across all firms (to answer e.g. How big is the average firm? How much liabilities has the average firm?). As the dataset has some missing values, I should not just take the average across total assets (column total assets). Should I rather first calculate the average across each firm (despite some missing values) and then the average across all firm averages (giving all firms the same weight)?
Or are there any better descriptive statistic measures for this kind of dataset with some missing values?