Multiple imputation on unbalanced panel data

[Jess Canazares]

Hi all,

I am currently trying to estimate the impact of climate on the income of fisher folks with a(n) (unbalanced) panel data. the climate variables to be used are rain value and soil moisture. however, i have missing data on both climate variables due to a malfunction of the measuring tool. my question is, would it be advisable to use multiple imputation for the missing data? or should i just settle with the results given by xtreg, fe vce(robust)? also, are there any other test/s which better to use?

i'm looking forward to hearing from you. i would very much like to hear more suggestions on this matter. I really do hope you can help me on this. Thank you.

Best regards,
Jess

[Carlo Lazzaro]

Jess:
welcome to the list.
- I would first investigate whether the missingness in your data is ignorable or not (please, see https://uk.sagepub.com/en-gb/eur/mis...ata/book9419);
- -mi- or -ipolate- may be useful tools for dealing with missing data;
- however, please note that Stata can handle both unbalanced and balanced panel dataset without any problem;
- as a closing out remarks, as per FAQ #12 your chances of getting helpful replies are conditional on posting what you typed and what Stata gave you back. Thanks.