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  • Finding Mata code

    I rarely use Mata, so this is my first ever post in this forum.

    heckprobit.ado includes the lines

    `vv' mata: heckprob_init("inits","`seldep'", ///
    "`depvar'","`touse'")

    Assuming it can be done, I would like to see the code for heckprob_init. How do I do that? I assume it would be part of a file with a .mata extension, but there seem to be zillions of those.
    -------------------------------------------
    Richard Williams, Notre Dame Dept of Sociology
    Stata Version: 17.0 MP (2 processor)

    EMAIL: rwilliam@ND.Edu
    WWW: https://www3.nd.edu/~rwilliam

  • #2
    OK, I think I found the command:

    Code:
    . mata: mata which heckprob_init
      heckprob_init():  lmataado
    But, the only file I can find is lmataado.mlib. I take it that means I am out of luck with regards to seeing the source code?
    -------------------------------------------
    Richard Williams, Notre Dame Dept of Sociology
    Stata Version: 17.0 MP (2 processor)

    EMAIL: rwilliam@ND.Edu
    WWW: https://www3.nd.edu/~rwilliam

    Comment


    • #3
      Hi Richard
      You're not the first to get stuck on that: http://www.stata.com/statalist/archi.../msg01054.html
      Kind regards

      nhb

      Comment


      • #4
        The closest I could get was
        Code:
        mata describe using lmataado
        . But that I actually rather useless, sorry
        Kind regards

        nhb

        Comment


        • #5
          The Mata source code that goes into lmataado.mlib is not public. However if Richard is curious about the purpose of
          the Mata function heckprob_init(), it is a subroutine that puts information into a Mata structure that the heckprobit
          likelihood evaluator needs for computing the log-likelihood value and its derivatives. The information is basically identifying
          the selected and not-selected observations in the estimation sample.

          logit, ologit, and mlogit all do similar things with Mata. For example, in logit.ado you will see the line

          Code:
          mata: mopt__pl_init("perfect")
          and the source for mopt__pl_init() can be viewed via

          Code:
          viewsource moptimize_evaluators.mata
          There you will see that mopt__pl_init() creates an external Mata object and returns its name in the local macro
          named perfect. This object is just a 4 column row vector that the logit likelihood evaluator will fill with
          information about completely determined outcomes. The completely determined outcomes information is posted
          by Mata function mopt__pl_post(), which gives you a clue what the elements of the 4 column row vector
          mean.

          Comment


          • #6
            Thanks Jeff. Based on this presentation by Jeffrey Wooldridge,

            http://www.stata.com/meeting/chicago...wooldridge.pdf

            I have written a couple of beta programs that work with fractional variables, i.e. vars that range between 0 and 1. As Wooldridge notes, this basically involved relaxing Stata's insistence that dependent vars be coded 0/1. Somebody asked if this could be done with heckprob too. I suspect it can but the hidden MAta code was causing me grief. I'll see if I can figure it out now.
            -------------------------------------------
            Richard Williams, Notre Dame Dept of Sociology
            Stata Version: 17.0 MP (2 processor)

            EMAIL: rwilliam@ND.Edu
            WWW: https://www3.nd.edu/~rwilliam

            Comment


            • #7
              Hello Dr. Williams, I would like to estimate a model with a fractional dependent variable with sample selection. I have tried tweaking heckprobit by replacing calls to "probit" by calls to "fracreg probit" when applicable, but the edited program crashes after the call to`vv' mata: heckprob_init("inits","`seldep'", "`depvar'","`touse'") or after the call to capture noi ml model lf2 heckprob_lf2() [...].

              From what I read in your post, it seems you have managed to solve the issue of using heckprobit with a fractional dependent variable, and I would be very grateful if you could share the code.
              Sincerely

              Comment


              • #8
                Hi Sophie
                This is not exactly via Mata, but you could use -ml- to program your own heckprobit and heckfracprobit.
                Below an example:

                Code:
                ** This first two programs define the MLE for heckman probit, and heckman fracprobit 
                capture program drop mle_heckprobit
                program mle_heckprobit, 
                    args lnf xb zg arho
                    qui {
                        tempvar rho
                        gen double `rho'=tanh(`arho') 
                        replace `lnf'=log(binormal(`xb',`zg',`rho')) if $ML_y1!=0 & $ML_y2!=0 
                        replace `lnf'=log(binormal(-`xb',`zg',-`rho')) if $ML_y1==0 & $ML_y2!=0
                        replace `lnf'=log(normal(-`zg')) if $ML_y2==0
                    }
                end
                
                capture program drop mle_heckfprobit
                program mle_heckfprobit, 
                    args lnf xb zg arho
                    *arho
                    qui {
                        tempvar rho
                        gen double `rho'=tanh(`arho') 
                        replace `lnf'=$ML_y1*log(binormal(`xb',`zg',`rho'))+(1-$ML_y1)*log(binormal(-`xb',`zg',-`rho')) if $ML_y2!=0 
                        replace `lnf'=log(normal(-`zg')) if $ML_y2==0
                    }
                end
                
                * here an example that compares both procedures
                
                 webuse school, clear
                 ml model lf mle_heckprobit (private:private=years logptax) (vote:vote=years loginc logptax) /arho , missing maximize technique(nr bhhh)  nolog
                 ml display
                 heckprobit private years logptax, sel(vote=years loginc logptax)
                 predict priv_xb, xb
                 predict vote_xb, xbsel
                * and an example using simulated data
                 expand 10
                 drawnorm u1 u2, corr(1 -.6994978 1) cstorage(lower)
                 gen vote_hat = (vote_xb+u2)>0
                 gen private_hat = normal(priv_xb+u1)
                 
                 ml model lf mle_heckfprobit (private:private_hat=years logptax) (vote:vote_hat=years loginc logptax) /arho , missing maximize technique(nr bhhh) 
                 ml display
                HTH

                Comment


                • #9
                  cmp may be able to do what you need. It offers the fractional probit model and lets you mix in selection equations, instrumenting equations, etc.

                  Comment


                  • #10
                    Following what Jeff Pitblado (StataCorp) said in #5 above, I would like to suggest that all classes and methods compiled into a Mata library should be documented in help files. A class should have all its elements, public private and protected, and methods well documented, and the methods clearly which arguments are inputs, which are outputs, its purpose and limitations, and what it returns. Yes, it is a lot of work, but it will be extremely useful for cases where Stata doesn't provide exactly what we need. Particularly with classes that can be extended, for example if you had a fixed parameters Logit class, and you wanted to do fractional response Logit, as Richard Williams is trying to do here. You could simply override the method(s) that limit the dependent variable to be 0/1 and check that all values are between 0 and 1 (inclusive), and set the default variance matrix to be the robust one because it is quasi-maximum likelihood. If the class is well designed you would have the different methods that calculate the different variance matrices programmed, and don't need to do it again.
                    Alfonso Sanchez-Penalver

                    Comment


                    • #11
                      Yes, it is a lot of work, but it will be extremely useful for cases where Stata doesn't provide exactly what we need. Particularly with classes that can be extended, for example if you had a fixed parameters Logit class, and you wanted to do fractional response Logit, as Richard Williams is trying to do here.
                      Yes, for a couple of my programs, I copied Stata's code, found where it was doing a 0/1 check, and changed it to doing a check for being in the range 0 to 1. It was pretty easy. Stata now has fracreg but I'm surprised it doesn't have even more programs that work with proportions rather than 0/1.

                      My most recent handout on this is at

                      https://www3.nd.edu/~rwilliam/stats3...onseModels.pdf
                      -------------------------------------------
                      Richard Williams, Notre Dame Dept of Sociology
                      Stata Version: 17.0 MP (2 processor)

                      EMAIL: rwilliam@ND.Edu
                      WWW: https://www3.nd.edu/~rwilliam

                      Comment

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