Hello everyone,

I'm dealing with panel data analysis and still confused about few things
I have a type of panel data that i considered as short panel because it consist of large n and small t, which is 74 corporation for period of 2016-2018 in Indonesia. I'm working with causality type of research to test a topic called intellectual capital. So here is my questions:
1. In case of short panel data, is it allowed to do fixed effect model particulary LSDV model as i have many cross-section number? some said that it will decrease degree of freedom and will suffer from biased estimation especially when i only have 3 years of observation. What considered as sufficient and too small degree of freedom in case of LSDV?
2. Is it necessary to do F-test/Chow test to compare between pooled ols and fixed effect model for this type of panel data? because as far as i know, f test is basically testing the dummy variable for unobserved individual effect or time effect that belong to LSDV.
3. I considered there are one way effect model and two way effect model. How to decided which one is more appropriate for my model? and in case of one way effect model, how to decide between individual effect and time effect model, what should be my consideration?
4. for another estimation model as random effect and pooled ols, Does it generate biased parameter estimation if i choose to use my current data? if not, what should i do?
5. Could you suggest a reference or formal way to test outliers for my data in stata? and does it affect my parameter of estimation in panel data analysis?

For now that's everything i really try to figure out,
please considered to reference any book to furthermore reading.
Thank you.