Hi,
I'm trying to conduct panel data regression.
Among 3 options(pooling, fixed, random),
I'd like to know which one would be best for my analysis.
My input data is unusual. It has a lot of individuals(i) but few periods(t)
Specific input data is as follows:
Periods included : 3
Cross-sections included : 8,194
Total panel (unbalanced) observations: 14,939
After conducting regression, my conclusions are as follows:
1) Pooling regression
- Every coefficient is significant with p-values under 1%.
- But, I think this method is relatively simple and dull...
2) Random effect
- Every coefficient is also significant.
- But fixed effect could be a more suitable model because Hausman test rejects null hypothesis,
3) Fixed effect
- According to the Hausman test, this would be suitable.
- But lots of coefficients are insignificant.
- Moreover, it might cause <incidental parameters problem>, owing to asymmetric input data(large cross-section, short periods).
So, I'd like to choose 2) random effect.
Is there any problem I might be missing if I choose 2) random effect ?
I'm concerned about the input data having a very short period.
I've never seen such panel data regression conducted with extremely short periods.
panel: Pooling vs Random vs Fixed (with large i & few t)
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