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different p-values in mfx after xtprobit

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different p-values in mfx after xtprobit

ramesh
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Hi, I am using xtprobit model for my research. I want to find the marginal effect after the xtprobit model. I used the "mfx compute, predict(pu0)" command and got the results but my p-value is totally different and it turns out 0.99 for almost all variable. I have attached the xt probit result and its corresponding mfx herewith. Is there any suggest to get consistent p-value in calculating the marginal effect?

Regards,
Ramesh Ghimire,
The University of Georgia
Athens, GA

------------------------------------------------------------------------------
       flood |       Coef.         Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    lnforest |  -.2013822   .0991885    -2.03    0.042     -.395788   -.0069763
    lnpopden |   .8405052   .4208142     2.00   0.046     .0157245    1.665286
      lnarea |   1.242506   .4060901     3.06     0.002     .4465838    2.038428
     lnrain1 |   1.166008   .3712284     3.14     0.002     .4384142    1.893603
 lnelevation |   .1471247    .553111     0.27    0.790    -.9369529    1.231202
  lnlatitude |   .3573529   .4758066     0.75    0.453     -.575211    1.289917
    lnrugged |  -.0959711   .4163809    -0.23   0.818    -.9120627    .7201205
      dlandp |  -.0030963   .0064364    -0.48    0.630    -.0157114    .0095187
lndist_coast |   .0012429   .2458026     0.01   0.996    -.4805214    .4830072
    subhumid |  -6.134987   17518.11    -0.00   1.000       -34341    34328.73
        arid |     .3217398   .4151698     0.77    0.438     -.491978    1.135458
 corruptionl |  -.2832393   .1430083    -1.98   0.048    -.5635303   -.0029482
  lngdp2000l |   -.352413   .3048828    -1.16   0.248    -.9499723    .2451463
        year |   .0412328   .0348107     1.18     0.236    -.0269949    .1094604
       _cons |  -97.51084   69.47674    -1.40   0.160    -233.6828    38.66108
-------------+----------------------------------------------------------------
    /lnsig2u |  -2.869749   1.663904                      -6.13094    .3914423
-------------+----------------------------------------------------------------
     sigma_u |   .2381453   .1981254                      .0466319    1.216188
         rho |   .0536694    .084508                      .0021698    .5966298
------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     0.51 Prob >= chibar2 = 0.238

. mfx compute, predict(pu0)

Marginal effects after xtprobit
      y  = Pr(flood=1 assuming u_i=0) (predict, pu0)
         =  .17457315
------------------------------------------------------------------------------
variable |      dy/dx         Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------
lnforest |  -.0518309      34.252   -0.00     0.999  -67.1854  67.0817   9.86395
lnpopden |   .2163258      142.96    0.00    0.999  -279.978   280.41   4.36014
  lnarea |   .3197912      211.33    0.00     0.999  -413.887  414.526   11.8466
 lnrain1 |   .3001026      198.32    0.00     0.999  -388.405  389.005   5.51255
lnelev~n |   .0378664      25.024    0.00    0.999   -49.009  49.0847   5.77592
lnlati~e |   .0919741      60.781    0.00     0.999  -119.037  119.221    3.5787
lnrugged |  -.0247007      16.324   -0.00   0.999  -32.0187  31.9693    .02399
  dlandp |  -.0007969      .52665   -0.00    0.999  -1.03301  1.03142   41.3952
l~_coast |   .0003199      .22067    0.00    0.999  -.432186  .432826  -2.36574
subhumid*|  -.2453962     .03779   -6.49   0.000  -.319465 -.171328   .040293
    arid*|   .0874895      53.534    0.00      0.999  -104.836  105.011   .307692
corrup~l |   -.072899      48.175   -0.00     0.999  -94.4946  94.3488   4.48657
ln~2000l |  -.0907026      59.941   -0.00    0.999  -117.573  117.391   25.7931
    year |   .0106123     7.01315    0.00     0.999  -13.7349  13.7561   1995.08
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1

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