Choosing Fixed-Effects, Random-Effects or Pooled OLS Models in Panel Data Analysis using Stata

That's how you clearly explain the steps. Much appreciated

In hausman test p value came 0 means fixed effect model is appropriate but in xttest0 p value came 1 means pooled is appropriate. So which on is appropriate for this analysis??? Please can you explain

Please reply me, is xttest0 in choosing model and xttest0 in check heteroskedasticity for RE model the same? REM is appropriate model for my data. First I check xttest0 to choose between RE and POLS then I use hausman to choose between RE and FE. Now I want to check heteroskedasticity for RE. What should I do?

thank you for this video

Hi thank you for the video which is very helpful. One comment on the first hausman test result to be sure: wouldn't it be that we "reject" the null hypothesis (H0: random effect is a preferred model) as the p-value is 0.000, and accept the H1: fixed effect is a preferred model? The video says that the hausman test allows us to "accept" the null hypothesis and choose to use fixed effects.

hello, due to heteros I put robust, but my result doesn't show probability value and just a dot. any advice?

Regarding the hausman fixed random test, I get the error that estimation result fixed not found. However, I did a fe and re test beforehand. Someone who can help?

Isn’t it standard OLS and not pooled since you didn’t add pooled at the end of the command?

Excellent explaination 👍

If the Hausman test provides chi2(9) = 7.76 and p = 0.5586, while the LM test xttest0 provided chi-square statistics of 58.46, based on this, is the random effects model more appropriate?

How do we decide between Pooled OLS and and fixed effects? If I fail to reject the null of the Breush-Pagan Lagrange multiplier result

Does storing the estimates change or effect the data if we wanna do other regressions later?

very helpful video. Thanks you so much
Can you please help me explaining these results from stata. I need to explain result for my dissertation

As you know robust model may fix the heteroskedasticity problem and also Pooled OLS fixes the serial correlation problem. Which model is preferable if both (heteroskedasticity and serial correlation) tests are failed?

hey i have a question (please i need very urgently help) i do the same but there comes a note which says: the rank of the differenced variance matrix (9) does not equal the number of
coefficients being tested (10); be sure this is what you expect, or there may
be problems computing the test. Examine the output of your estimators for
anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
, but i dont see any problems, what should i do?

Thanks for your helpful video. Can I ask if xttest0 indicates that POLS is suitable (p_value=1.000) and after running xtserial for POLS model, autocorrelation exists. what could I do to fix it? Thanks.

Hi, Thank you for such a fantastic video, in my case I got a p-value of more than .05 for both the Hausman test and LM. What should I do?

Thank you very much! Could you provide the topic of your published paper ?

If p value of constant in FEM becomes more than 5%, would it be a problem?

Very good explanations! Thank you so much!

this video is so useful, thank you very much!

Thanks. This is the first channel explaining everything clearly and step by step by using a real, published study. Please upload more models, tests, and commands

Good job

the concepts were explained really well. Thank you!

Thanks for the video. Having the snapshot of the dataset and the do file would help understand the content better.

Please can I apply same to my RE model, if my Hausman test results allows me to pick RE model... I wanna eliminate heteroskedasticity

Thanks for the video. Having the snapshot of the dataset and the do file would help understand the content better.

Thanks for the video. Having the snapshot of the dataset and the do file would help understand the content better.

Thank you sir, for the excellent video. I have run the FE and RE for research data.

Thanks for the video. Having the snapshot of the dataset and the do file would help understand the content better.

Thank you for this video. Now my question is that exist any test of endogeneity in the fix effects model. Thank you very much.

Thank you sir, for the excellent video. I have run the FE and RE for research data.

I found your presentation very helpful and explained so clearly thank you :)

That was amazingly explained with interesting examples. Thanks a lot

That was amazingly explained with interesting examples. Thanks a lot

This was a really helpful video that breaks it down clearly! Thanks!

There are a few mistakes, but it is a very helpful video to understand. You are a legend, thank you!

Good explication of this method

pretty Splendid. But I have a request please use command mode and speak slowly to elaborate more in-depth.

Thank you very much sir

Its really very informative. But I am unable to run sigmamore command. Plz explain

Thank you so much for using data from your empirical study to teach how to carry out the analysis. Its been very helpful .

Modern presentation

Can u please provide the link for this excel data. The drive link u provided is not opening

Thanks for your great work!...AT the end, yoo explain the meaning of "rho", and the slide says "97.466% of the variance is due to differences across panels"...Did you want to say "entities" instead of "panels"?...Thanks again!

Great tutorial

This method is hot, thanks !