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  • Fixed Effects Model vs. Pooled OLS when facing contradictory test results

    Hello again!

    Hopefully for the last time in a while I have a general question. I would be very thankful if you can help me...as you always do.
    Although I found multiple discussions about this problem here, I don't feel like there was a direct answer to this in previous topics. At least for me personally, there was not a clear answer.

    I try to make it short: (I can post the actual test outputs if necessary, but I feel the question is not case specific)

    Breusch Pagan Lagrange Multiplier test for random effects (xttest0): p-value > 10% -> Indicates Pooled OLS more appropriate than Random Effects model
    Hausman Test: p-value < 5% -> Indicates Fixed Effects model more appropriate than Random Effects model
    Joint F-test for fixed effects below the Fixed Effects regression table: p-value < 1% -> indicates Fixed Effects model is more appropriate than Pooled OLS

    ...so in this situation I am not sure if the Fixed effects model is the clear "winner", since I remember from a statistics course (not 100% sure if I remember it correctly!), that it was said: When the Breusch Pagan multiplier test couldn“t be rejected one has to run a pooled regression and ignore the panel data structure (So the BP LM test gives a statement for RE vs POLS and FE vs POLS)

    Since I am not very comfortable with the proceeding to just ignore the panel structure, I searched online and found multiple contradictory statements:
    E.g. Park, H.M. (2011) Practical Guides to Panel Data Modeling: A Step-by-Step Analysis Using Stata; p. 50, clearly states, that the given situation indicates the use of a Fixed effects model.

    Nevertheless I also found multiple confirming statements.
    Is there a clear proceeding for the choice between FE and POLS in this situation? Or is there at least a free choice between FE or Pooled OLS at this point?

    Greetings and thank you in advance!




    Last edited by Joan Stein; 27 Aug 2020, 12:59.

  • #2
    Joan:
    as per your description, I would give -xtreg,fe- a try.
    I would also test whether your model suffers for misspecification.
    As an aside, posting what you typed and what Stata gave you back (as per FAQ) is never redundant.
    Kind regards,
    Carlo
    (Stata 19.0)

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    • #3
      @Carlo thank you very much for your response!
      That is actually what I was hoping for...
      I faced this problem several times in previous as well as past studies.

      And thanks for the hint with regard to specification tests. I tested my model via Ramsey RESET and Linktest so I hope the model itself is good.

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