Thank you for your email. Here it is the command I am using:
cdsimeq (lnR4rain simpson landdif ProdPblm AgExt) (D_off_female simpson
dependc)
NOW THE FIRST STAGE REGRESSIONS
Source | SS df MS Number of obs =
252
-------------+------------------------------ F( 5, 246) =
0.90
Model | 3.36395721 5 .672791442 Prob > F =
0.4826
Residual | 184.161499 246 .748623978 R-squared =
0.0179
-------------+------------------------------ Adj R-squared =
-0.0020
Total | 187.525456 251 .74711337 Root MSE =
.86523
------------------------------------------------------------------------
------
lnR4rain | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
simpson | .1184274 .1826432 0.65 0.517 -.2413166
.4781714
landdif | .0036154 .0051364 0.70 0.482 -.0065014
.0137323
ProdPblm | -.2105545 .1662512 -1.27 0.207 -.5380119
.1169029
AgExt | .0096537 .0087856 1.10 0.273 -.0076509
.0269584
dependc | .0332848 .0425781 0.78 0.435 -.0505792
.1171489
_cons | 12.42117 .3604348 34.46 0.000 11.71123
13.1311
------------------------------------------------------------------------
------
Iteration 0: log likelihood = -143.86365
Iteration 1: log likelihood = -141.70529
Iteration 2: log likelihood = -141.69626
Iteration 3: log likelihood = -141.69626
Probit regression Number of obs =
252
LR chi2(5) =
4.33
Prob > chi2 =
0.5023
Log likelihood = -141.69626 Pseudo R2 =
0.0151
------------------------------------------------------------------------
------
D_off_female | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
simpson | -.0677971 .3016356 -0.22 0.822 -.6589921
.5233979
landdif | -.0052904 .0084477 -0.63 0.531 -.0218475
.0112667
ProdPblm | .3989428 .2881943 1.38 0.166 -.1659078
.9637933
AgExt | .0071777 .0139787 0.51 0.608 -.02022
.0345754
dependc | -.0779648 .0685734 -1.14 0.256 -.2123662
.0564366
_cons | -.9195571 .5760108 -1.60 0.110 -2.048518
.2094034
------------------------------------------------------------------------
------
NOW THE SECOND STAGE REGRESSIONS WITH INSTRUMENTS
Source | SS df MS Number of obs =
252
-------------+------------------------------ F( 5, 246) =
0.90
Model | 3.36395721 5 .672791442 Prob > F =
0.4826
Residual | 184.161499 246 .748623978 R-squared =
0.0179
-------------+------------------------------ Adj R-squared =
-0.0020
Total | 187.525456 251 .74711337 Root MSE =
.86523
------------------------------------------------------------------------
------
lnR4rain | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
I_D_off_fe~e | -.4269214 .5461192 -0.78 0.435 -1.502587
.6487445
simpson | .0894834 .1890214 0.47 0.636 -.2828234
.4617901
landdif | .0013568 .0058259 0.23 0.816 -.0101181
.0128318
ProdPblm | -.0402373 .2736064 -0.15 0.883 -.5791474
.4986727
AgExt | .012718 .0098561 1.29 0.198 -.006695
.0321311
_cons | 12.02859 .6717123 17.91 0.000 10.70555
13.35163
------------------------------------------------------------------------
------
Iteration 0: log likelihood = -143.86365
Iteration 1: log likelihood = -142.6572
Iteration 2: log likelihood = -142.65558
Iteration 3: log likelihood = -142.65558
Probit regression Number of obs =
252
LR chi2(3) =
2.42
Prob > chi2 =
0.4906
Log likelihood = -142.65558 Pseudo R2 =
0.0084
------------------------------------------------------------------------
------
D_off_female | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
I_lnR4rain | -.8678088 .8453643 -1.03 0.305 -2.524692
.7890749
simpson | .0885422 .3021884 0.29 0.770 -.5037362
.6808205
dependc | -.0535112 .0723519 -0.74 0.460 -.1953184
.0882959
_cons | 10.34456 10.59304 0.98 0.329 -10.41741
31.10653
------------------------------------------------------------------------
------
NOW THE SECOND STAGE REGRESSIONS WITH CORRECTED STANDARD ERRORS
F ambiguous abbreviation
r(111);
end of do-file
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Richard
Williams
Sent: Thursday, August 23, 2007 4:26 PM
To: [email protected]
Subject: Re: st: run "cdsimeq" command and get error message "F
ambiguous abbreviation"
At 02:18 PM 8/23/2007, Sun, Yan (IFPRI) wrote:
>Hi,
>I try to use "cdsimeq" to run simultaneous equations (one continuous
>dependent variables and one dichotomous dependent variables), and got
>error message "F ambiguous abbreviation, r(111)", so I am not able to
>get the second stage regressions with corrected errors. But I do not
>have any variables beginning with "F" in my regression variable lists,
>how could I have F ambiguous abbreviation? Please help. Thanks.
>
>Yan
>IFPRI
It would help to give the exact command you used - and, if possible,
even better if you could provide a reproducible example.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
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