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  • Message: "note: multiple positive outcomes within groups encountered" and different coefficients

    Dear all,

    I ran into the message "note: multiple positive outcomes within groups encountered" when running a xtprobit model. I estemate multiple models with each time more independent variables included. So the first model is defined as follows:
    Code:
    xtlogit Initialreturndummy lnofferprice lnDealsize Greenshoepercentage OffertoOpendummy DistanceIPOandfilingdatein Bookrunnerdummy Rankingdummy Segmentdummy, fe
    .

    If I run the second model I get the aforementioned message and the coefficients change to very large values, e.g. from 0.0744 to -4.33490. The second model is defined as:
    Code:
    xtlogit Initialreturndummy lnofferprice lnDealsize Greenshoepercentage OffertoOpendummy DistanceIPOandfilingdatein Bookrunnerdummy Rankingdummy Segmentdummy lnTotalAssets PEVCdummy Phoneticdummy lnSharesoffered Techdummy CompanyAge, fe
    A few observations (4/5) have been omitted as well. Does anyone have an idea how I can fix this?


  • #2
    Damian:
    my guess is that there's no enough outcome variation within panels to make the MLE estimator converge.
    Kind regards,
    Carlo
    (Stata 19.0)

    Comment


    • #3
      Hi Carlo Lazzaro ,

      Thanks for your reply. Could there be something wrong with my data?
      What is now the best thing to do? I have to estimate a binary model with fixed effects per country and if I'm not mistaken a probit model does not allow fixed effects. Therefore, if have to use a logit model since a LPM has some downsides.

      Comment


      • #4
        Damian:
        I thought that -xtprobit- read -xtlogit-.
        That said:
        1) -xtlogit- allows conditional fixed effect, because of incidental parameters bias (https://www.sciencedirect.com/scienc...04407699000445);
        2) I'd take a look at your model and double-check whether its specification is correct.
        Kind regards,
        Carlo
        (Stata 19.0)

        Comment


        • #5
          Hi Carlo,

          Thanks for your help! I think I figured it out now.

          Comment

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