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  • xtprobit - using lags of the dependent variable

    Hello there,

    I am working with a panel dataset with lots of dummys, and want to run a probit to work out the probability in a given period of taking out insurance. As my independent variables I have dummies such as has there been a fire before, was the income in the last period above a certain value etc. What I would also like to do is have lags of the insurance dummy, so whether insurance was taken out last period, and the period before that.

    Edit: Solved that.
    My issue now is after running the probit, I want to work out the marginal effects, but when I do
    margins, dydx(*) atmeans
    I get the error
    default prediction is a function of possibly stochastic quantities other than e(b),
    what does this mean?
    Last edited by Alex Jeffries; 20 Jun 2015, 15:56.

  • #2
    Alex:
    I would take a look at: http://www.ats.ucla.edu/stat/stata/f...logit_prob.htm
    Kind regards,
    Carlo
    (Stata 19.0)

    Comment


    • #3
      Originally posted by Carlo Lazzaro View Post

      Hi Carlo, thanks for replying. I had come across that resource yesterday and tried to follow the steps there already, but I am still having issues. I've read through the stata help files and remarks but I am making little progress.

      From that link they use
      margins female, at(read=(30(10)70)) predict(mu fixedonly) vsquish
      If I try margins firedummy, predict(mu fixedonly) vsquish, I get that option mu is not allowed. I can't seem to figure out what the mu is, as there is no mention of it in that page, (and I also don't see vsquish in the help files either). I have never seen binary choice models before so I am very confused.
      Last edited by Alex Jeffries; 21 Jun 2015, 06:45.

      Comment


      • #4
        Alex:
        mu is the predicted mean of the fixed part of the model (as explained in the web page);
        -vsquish- is described in -estimation options-.
        Kind regards,
        Carlo
        (Stata 19.0)

        Comment

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