Can you run a fixed effect model on unbalanced data?
As Peterson said, you can run standard fixed effects models on your entire unbalanced data and still get estimates. You could also add a time fixed effect or even use a varying coefficient model.
Can a panel variable be used to eliminate fixed effects?
Only the panel variable is used to eliminate the individual (or in this case firm) fixed effects but it does nothing about the time fixed effects. So xtreg will perform the within transformation using the specified panel id but if you want to control for year fixed effects you need to include the dummies as you suggest.
Why are the coefficients of a panel biased?
You could also add a time fixed effect or even use a varying coefficient model. However, if you choose to only use firms that remain all the time, then your coefficients will be biased because of the “Survival” bias (firms that remained may have better overall performance and therefore “survive” easier nomatter the market concentration).
What should I do if I have unbalanced panel data?
Then your sample is not representative of ecuadorian firms anymore. Just be aware of that. Dear David. Ideally, you should exclude the data of all firms that did not remain all time period.
Is there way to correct unbalanced panel data?
Stata takes care of unbalanced panel without further request from the researcher. However, if your question concerns tools such as inverse probability weighting (IPW) to correct for units lost at follow-up, no they are not included in Stata -xt- commands suite.
Which is better, unbalanced data or balanced data?
My question is what data set is the most appropriate to analyze the data. Unbalance or balanced panel data? With unbalanced data, it suffers from attrition due to relegation of football clubs. With balanced data (12 clubs) my data suffers from sample selection bias.