<>
Which additional part of "Results 2" do you want to see in your -outreg2-
file? The return list only gives you
scalars:
r(estatdf) = 1
r(estat) = 9.760027575966824
r(estatp) = .0017834723530583
r(jdf) = 2
r(jp) = .4366703186006444
r(j) = 1.657153576564876
and some of them are already present in your call to -outreg2-...
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Kelvin Tan
Gesendet: Mittwoch, 28. Oktober 2009 09:28
An: [email protected]
Betreff: st: Can I produce a regression output with -outreg2- after
-xtoverid2, noisily- ? and temporary names query.
Dear All,
I would like to know if I can produce a regression output with -outreg2-
in LaTeX after-xtoverid2, noisily cl(id)- command. When I ran the
following commands, I only managed to get the "Results 1" from -
xtivreg, re - but not "Result 2" from -xtoverid, noisily cl(id)-. I
would also like to know if there is a command that I can use to change
the temporary names to my variable label names after xtoverid. Thanks in
advance.
Commands:
net install xtoverid2,
from(http://www-personal.umich.edu/~nicholsa/stata)
webuse abdata, clear
xtivreg ys (k = emp wage cap), re
xtoverid2, noisily cl(id)
outreg2 using myfile, tex bdec(3) tdec(2) alpha(0.001, 0.01, 0.05) label
ctitle(test) adds("Endogeneity Pvalue", `r(estatp)', "FE vs RE",
`r(j)',"FE vs RE pvalue", `r(jp)' )
Results 1:
. xtivreg ys (k = emp wage ) cap rec, re
G2SLS random-effects IV regression Number of obs =
1031
Group variable: id Number of groups =
140
R-sq: within = 0.1177 Obs per group: min =
7
between = 0.0114 avg =
7.4
overall = 0.0116 max =
9
Wald chi2(3) =
1.81
corr(u_i, X) = 0 (assumed) Prob > chi2 =
0.6128
------------------------------------------------------------------------
------
ys | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
k | .0134284 .0131901 1.02 0.309 -.0124237
.0392805
cap | -.0022268 .0023298 -0.96 0.339 -.0067931
.0023395
rec | -2.99e-06 .0000183 -0.16 0.870 -.0000388
.0000328
_cons | 4.651151 .0109388 425.20 0.000 4.629712
4.672591
-------------+----------------------------------------------------------
------
sigma_u | .03081492
sigma_e | .06537777
rho | .18177519 (fraction of variance due to u_i)
------------------------------------------------------------------------
------
Instrumented: k
Instruments: cap rec emp wage
------------------------------------------------------------------------
------
Results 2:
. xtoverid2, noisily cl(id)
Unable to display summary of first-stage estimates; macro e(first) is
missing
IV (2SLS) estimation
--------------------
Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on id
Number of clusters (id) = 140 Number of obs =
1031
F( 4, 139) =
4.8e+05
Prob > F =
0.0000
Total (centered) SS = 15.14467789 Centered R2 =
0.4729
Total (uncentered) SS = 8408.096794 Uncentered R2 =
0.9991
Residual SS = 7.983215092 Root MSE =
.088
------------------------------------------------------------------------
------
| Robust
__00000G | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
__00000I | .0134284 .0153607 0.87 0.382 -.016678
.0435348
__00000R | -.0022268 .0026627 -0.84 0.403 -.0074456
.002992
__00000U | -2.99e-06 .0000158 -0.19 0.851 -.000034
.0000281
__00000E | 4.651151 .0101982 456.08 0.000 4.631163
4.671139
------------------------------------------------------------------------
------
Hansen J statistic (overidentification test of all instruments):
2.457
Chi-sq(1) P-val =
0.1170
-endog- option:
Endogeneity test of endogenous regressors:
0.127
Chi-sq(1) P-val =
0.7217
Regressors tested: __00000I
------------------------------------------------------------------------
------
Instrumented: __00000I
Included instruments: __00000R __00000U __00000E
Excluded instruments: __00000L __00000O
------------------------------------------------------------------------
------
Endogeneity test (like DWH test) of endogenous regressors:
0.127
Chi-sq(1) P-val =
0.7217
Regressors tested: k
Test of overidentifying restrictions:
Cross-section time-series model: xtivreg g2sls robust cluster(id)
Sargan-Hansen statistic 2.457 Chi-sq(1) P-value = 0.1170
Regards,
Kelvin
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