"O Data, Data! Wherefore Art Thou Missing?"

Here is a nice summary of all of the ways to address the missing data problem. All is great if it turns out that all of these techniques suggest that the missing data is missing at random. But which specification should you use as your baseline: The missing dummy trick or just drop missing observations? I usually just drop missing observations because it's simpler, Regardless of what you choose, it is important to discuss your results from the techniques discussed in the article (even if they suggest that the missings are not missing at random).