Hello,

I am hoping someone might be able to point me to code that would allow me to perform multiple imputation (mi) for Missing At Random (MAR) panel data.

Right now, xtreg takes the number of observations down from ~3,400 to ~100 due to the variance in missing data which is organized by country year. The number of variables in the each regression range from 17-30. Because of the economic and political nature of the data, about half of those variables are missing 10-20% of the total number of observations that should exist.

As far as I can tell, mi would be the best option to account for the missing data, though mi is not inherently suited for panel data. In addition to my general hope to find a relevant code, I have a few other questions.
  1. Are there any issues with or solutions to performing mi to variables in longitudinal data? Wide is typically the standard shape for mi.
  2. Is clustering/grouping an option in mi? vce(robust), which should automatically cluster, is used in the regression commands.
  3. Based on the above information, are these basic commands on the right track? Note: when I performed mi on a second variable with a significantly greater amount of missing data than the first, STATA returned this last "mi estimate" command with "estimation sample varies between m=1 and m=22." It did not return an error with the first variable.
Code:
mi set mlong
mi register imputed var
mi impute mvn var, add(10) rseed(1234)
mi estimate: xtreg vars
Any answers, advice, or feedback you are willing to provide would be appreciated!

Thank you.