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st: different p-values in mfx after xtprobit
From
ramesh <[email protected]>
To
[email protected]
Subject
st: different p-values in mfx after xtprobit
Date
Thu, 12 May 2011 09:51:38 -0700 (PDT)
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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