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Re: st: Problem with margins after logit on a person period data


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu, statalist@hsphsun2.harvard.edu
Subject   Re: st: Problem with margins after logit on a person period data
Date   Wed, 08 Jun 2011 19:17:37 -0500

I don't think margins likes it when you use the noconstant option. Is it really necessary for your model?

At 05:08 PM 6/8/2011, Urmi Bhattacharya wrote:
Dear Statalisters,

I am running the following logit on a person-period data

logit school_left childage i.childfemale i.urban i.scstobc
i.casteother i.dadp i.dadm i.momp i.momm wagep wage5 wage8 w
> age9 distp distm disth percapcons durat1 durat2 durat3 durat4 durat5 durat6 durat7 durat8 durat9 durat10 durat11, nocon
> s nolog

Logistic regression                               Number of obs   =      47569
Wald chi2(28) = 14601.42
Log likelihood = -14502.393                       Prob > chi2     =     0.0000

------------------------------------------------------------------------------
school_left | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
childage | -.1413654 .006069 -23.29 0.000 -.1532605 -.1294703
1.childfem~e |   .0212387   .0306462     0.69   0.488    -.0388266    .0813041
1.urban | .0124911 .0368072 0.34 0.734 -.0596497 .0846319 1.scstobc | 1.972676 .1234074 15.99 0.000 1.730802 2.21455
1.casteother |   1.883233    .125722    14.98   0.000     1.636822    2.129643
1.dadp | .680585 .044327 15.35 0.000 .5937057 .7674643 1.dadm | .3872552 .0506982 7.64 0.000 .2878886 .4866217 1.momp | 1.351053 .0835161 16.18 0.000 1.187364 1.514741 1.momm | .9494066 .0918146 10.34 0.000 .7694532 1.12936 wagep | -.0281962 .0061845 -4.56 0.000 -.0403176 -.0160748 wage5 | -.0040992 .0045604 -0.90 0.369 -.0130373 .004839 wage8 | .021027 .0043869 4.79 0.000 .0124289 .0296251 wage9 | .0159427 .0022335 7.14 0.000 .0115652 .0203203 distp | -.0355589 .0162329 -2.19 0.028 -.0673748 -.0037431 distm | -.0024083 .0112658 -0.21 0.831 -.0244888 .0196722 disth | .0186932 .0039384 4.75 0.000 .010974 .0264124 percapcons | -.0001459 .0000278 -5.26 0.000 -.0002003 -.0000915 durat1 | -5.771466 .1406919 -41.02 0.000 -6.047217 -5.495715 durat2 | -4.947835 .1222363 -40.48 0.000 -5.187414 -4.708256 durat3 | -4.690019 .1193602 -39.29 0.000 -4.923961 -4.456078 durat4 | -4.054464 .1132586 -35.80 0.000 -4.276447 -3.832481 durat5 | -3.055883 .1082449 -28.23 0.000 -3.268039 -2.843727 durat6 | -3.560284 .1130896 -31.48 0.000 -3.781936 -3.338633 durat7 | -2.825943 .1099477 -25.70 0.000 -3.041436 -2.610449 durat8 | -2.238741 .1094063 -20.46 0.000 -2.453173 -2.024308 durat9 | -1.427979 .1099217 -12.99 0.000 -1.643421 -1.212536 durat10 | -.3967904 .1152271 -3.44 0.001 -.6226313 -.1709495 durat11 | -2.168164 .1486318 -14.59 0.000 -2.459477 -1.876851
------------------------------------------------------------------------------

.
end of do-file

Since I am interested in the marginal effects of the variables on the
probability of hazard,

I do

margins,dydx(*)

But this gives me the following output

 margins,dydx(*)

Average marginal effects                          Number of obs   =      47569
Model VCE    : OIM

Expression   : Pr(school_left), predict()
dy/dx w.r.t. : childage 1.childfemale 1.urban 1.scstobc 1.casteother
1.dadp 1.dadm 1.momp 1.momm wagep wage5 wage8
               wage9 distp distm disth percapcons durat1 durat2 durat3
durat4 durat5 durat6 durat7 durat8 durat9
               durat10 durat11

------------------------------------------------------------------------------
             |            Delta-method
| dy/dx Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
    childage |  (not estimable)
1.childfem~e |  (not estimable)
     1.urban |  (not estimable)
   1.scstobc |  (not estimable)
1.casteother |  (not estimable)
      1.dadp |  (not estimable)
      1.dadm |  (not estimable)
      1.momp |  (not estimable)
      1.momm |  (not estimable)
       wagep |  (not estimable)
       wage5 |  (not estimable)
       wage8 |  (not estimable)
       wage9 |  (not estimable)
       distp |  (not estimable)
       distm |  (not estimable)
       disth |  (not estimable)
  percapcons |  (not estimable)
      durat1 |  (not estimable)
      durat2 |  (not estimable)
      durat3 |  (not estimable)
      durat4 |  (not estimable)
      durat5 |  (not estimable)
      durat6 |  (not estimable)
      durat7 |  (not estimable)
      durat8 |  (not estimable)
      durat9 |  (not estimable)
     durat10 |  (not estimable)
     durat11 |  (not estimable)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Can someone explain what am I doing wrong? How do I get the marginal
effects after running the logit?

Best

Urmi
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

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