Question

I have a panel data comprising 30 emerging countries and 22 time periods from 1976 to 2017. How can I choose between panel data methods say Pooled, fixed and Random effects models? I wish to know the difference between these methods in simple terms.........................................

Answer 1

According to Wooldridge (2010), pooled OLS is employed when you select a different sample for each year/month/period of the panel data.

Fixed effects or random effects are employed when you are going to observe the same sample of individuals/countries/states/cities/etc.

These are some questions you need to ask yourself when it comes to panel data methods -

1. Are you observing the same sample along different periods of time?

If you do, that's why pooled OLS is not working. The fixed or random effect models are probably correct. Their R-squared is very low, so you can include variables or dummies of time to correct heteroskedasticity or inertial effects that are at play.

If you don't (which means you are using different samples along each period), include the dummies of time and test for Breusch Pagan and F again. Probably, the significant variables will remain significant and the model with dummies will pass the tests.

2. If you are using the same sample along all periods, use the Hausman test to verify if fixed or random effects are to be used as a model.

Null hypothesis: random effects.

Alternative hypothesis: fixed effects.

For p-value > 0,05: random effects. Test it with and without time dummies and see the results. See if the relevant variables are significant or not.