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log_table_3_FINAL.txt
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log_table_3_FINAL.txt
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---------------------------------------------------------------------------------------------------
name: <unnamed>
log: XXX/jhr_output/log_table_
> 3.txt
log type: text
opened on: 17 Mar 2021, 20:56:41
. global outsheet XXX/jhr_outp
> ut
.
.
. use $datadir/jhr_samples_created
.
.
.
. **** taking out combat
. local demos_everdissolve female ged hsd asc_smc college_pl afqsc black hispanic o
> ther_race sum_combat age age_sq
. local demos_everkids female ged hsd asc_smc college_pl afqsc black hispanic other
> _race sum_combat age age_sq
. local demos_nbr_kids female ged hsd asc_smc college_pl afqsc black hispanic other
> _race sum_combat age age_sq
. local demos_age_marr female ged hsd asc_smc college_pl afqsc black hispanic other
> _race sum_combat
. local demos_evermarr female ged hsd asc_smc college_pl afqsc black hispanic other
> _race sum_combat age age_sq
. local demos_marr_nm_ent female ged hsd asc_smc college_pl afqsc black hispanic ot
> her_race sum_combat age age_sq
. local demos_married female ged hsd asc_smc college_pl afqsc black hispanic other_
> race sum_combat age age_sq
. local demos_re_enlist female ged hsd asc_smc college_pl afqsc black hispanic othe
> r_race sum_combat age age_sq
.
.
. **** taking out combat
. local demos_everdissolve2 female ged hsd asc_smc college_pl afqsc black hispanic
> other_race age age_sq
. local demos_everkids2 female ged hsd asc_smc college_pl afqsc black hispanic othe
> r_race age age_sq
. local demos_nbr_kids2 female ged hsd asc_smc college_pl afqsc black hispanic othe
> r_race age age_sq
. local demos_age_marr2 female ged hsd asc_smc college_pl afqsc black hispanic othe
> r_race age age_sq
. local demos_evermarr2 female ged hsd asc_smc college_pl afqsc black hispanic othe
> r_race age age_sq
. local demos_married2 female ged hsd asc_smc college_pl afqsc black hispanic other
> _race age age_sq
. local demos_marr_nm_ent2 female ged hsd asc_smc college_pl afqsc black hispanic o
> ther_race age age_sq
. local demos_re_enlist2 female ged hsd asc_smc college_pl afqsc black hispanic oth
> er_race age age_sq
.
. gen pre2002 = mind < td(01oct2001) if initial_year ~= .
(7,501 missing values generated)
. gen post2001 = mind >= td(01oct2001) if initial_year ~= .
(7,501 missing values generated)
.
. ***********************************************************************
. **** TABLE 3 **********************************************************
. **** Randomization Tests **********************************************
. ***********************************************************************
.
. foreach var in totmoves_not {
2. foreach sample in /*everkids evermarr married */ re_enlist {
3.
. areg `var' if sample_`sample'_us == 1, robust absorb(exper_br_year_sex_fe)
4. qui summ `var' if e(sample) == 1
5. local mean = r(mean)
6. outreg2 using $outsheet/table_3.xls, replace label ctitle ("all, `sample'") title("`v
> ar' `sample'") dec(3) addtex(Mean, `mean') keep(`demos')
7.
. areg `var' `demos_`sample'2' if sample_`sample'_us == 1, robust absorb(exper_br_year_sex_
> fe)
8.
. qui summ `var' if e(sample) == 1
9. local mean = r(mean)
10. dis "test `var' all, sample = `sample'"
11. test ged hsd asc_smc college_pl afqsc black hispanic other_race age age_sq
12. local f = r(p)
13. outreg2 using $outsheet/table_3.xls, label ctitle ("demos, `sample'") title("`var'")
> dec(3) addtex(Mean, `mean', F-Test p-value, `f') keep(`demos')
14.
. areg `var' if sample_`sample'_us == 1 & male == 1, robust absorb(exper_br_year_sex_fe)
15. qui summ `var' if e(sample) == 1
16. local mean = r(mean)
17. outreg2 using $outsheet/table_3.xls, label ctitle ("all, `sample', male") title("`var
> ' `sample'") dec(3) addtex(Mean, `mean') keep(`demos')
18.
. areg `var' `demos_`sample'2' if sample_`sample'_us == 1 & male == 1, robust absorb(exper_
> br_year_sex_fe)
19.
. qui summ `var' if e(sample) == 1
20. local mean = r(mean)
21. dis "test `var' all, sample = `sample'"
22. test ged hsd asc_smc college_pl afqsc black hispanic other_race age age_sq
23. local f = r(p)
24. outreg2 using $outsheet/table_3.xls, label ctitle ("demos, `sample', male") title("`v
> ar'") dec(3) addtex(Mean, `mean', F-Test p-value, `f') keep(`demos')
25.
. **** pre 9/11 entrance
.
. areg `var' if sample_`sample'_us == 1 & pre2002 == 1, robust absorb(exper_br_year_sex_fe)
26. qui summ `var' if e(sample) == 1
27. local mean = r(mean)
28. outreg2 using $outsheet/table_3.xls, label ctitle ("all, `sample', <= 2001") title("`
> var' `sample'") dec(3) addtex(Mean, `mean') keep(`demos')
29.
. areg `var' `demos_`sample'2' if sample_`sample'_us == 1 & pre2002 == 1, robust absorb(exp
> er_br_year_sex_fe)
30.
. qui summ `var' if e(sample) == 1
31. local mean = r(mean)
32. dis "test `var' all, sample = `sample'"
33. test ged hsd asc_smc college_pl afqsc black hispanic other_race age age_sq
34. local f = r(p)
35. outreg2 using $outsheet/table_3.xls, label ctitle ("demos, `sample', <= 2001") title(
> "`var'") dec(3) addtex(Mean, `mean', F-Test p-value, `f') keep(`demos')
36.
. **** term 6
.
. areg `var' if sample_`sample'_us == 1 & term6 == 1, robust absorb(exper_br_year_sex_fe)
37. qui summ `var' if e(sample) == 1
38. local mean = r(mean)
39. outreg2 using $outsheet/table_3.xls, label ctitle ("term6") title("`var' `sample'") d
> ec(3) addtex(Mean, `mean') keep(`demos')
40.
. areg `var' `demos_`sample'2' if sample_`sample'_us == 1 & term6 == 1, robust absorb(exper
> _br_year_sex_fe)
41.
. qui summ `var' if e(sample) == 1
42. local mean = r(mean)
43. dis "test `var' all, sample = `sample'"
44. test ged hsd asc_smc college_pl afqsc black hispanic other_race age age_sq
45. local f = r(p)
46. outreg2 using $outsheet/table_3.xls, label ctitle ("term6") title("`var'") dec(3) add
> tex(Mean, `mean', F-Test p-value, `f') keep(`demos')
47. }
48. }
Linear regression, absorbing indicators Number of obs = 182,694
Absorbed variable: exper_br_year_sex_fe No. of categories = 13,335
F( 0, 169359) = .
Prob > F = .
R-squared = 0.1719
Adj R-squared = 0.1067
Root MSE = 0.5828
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons | .5811028 .0013634 426.22 0.000 .5784306 .583775
------------------------------------------------------------------------------
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
note: female omitted because of collinearity
Linear regression, absorbing indicators Number of obs = 182,694
Absorbed variable: exper_br_year_sex_fe No. of categories = 13,335
F( 10, 169349) = 81.50
Prob > F = 0.0000
R-squared = 0.1760
Adj R-squared = 0.1111
Root MSE = 0.5813
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
female | 0 (omitted)
ged | .0475041 .0048522 9.79 0.000 .037994 .0570143
hsd | .0395009 .0164042 2.41 0.016 .007349 .0716528
asc_smc | .0132876 .0054959 2.42 0.016 .0025157 .0240595
college_pl | -.1059988 .0105931 -10.01 0.000 -.1267611 -.0852365
afqsc | -.0020406 .0000916 -22.29 0.000 -.00222 -.0018611
black | -.0054075 .0041789 -1.29 0.196 -.0135981 .0027832
hispanic | -.0118804 .0046857 -2.54 0.011 -.0210643 -.0026964
other_race | -.0006214 .0063002 -0.10 0.921 -.0129697 .011727
age | .0213223 .0037478 5.69 0.000 .0139766 .028668
age_sq | -.0003484 .0000629 -5.54 0.000 -.0004718 -.0002251
_cons | .3883794 .0546176 7.11 0.000 .2813302 .4954286
------------------------------------------------------------------------------
test totmoves_not all, sample = re_enlist
( 1) ged = 0
( 2) hsd = 0
( 3) asc_smc = 0
( 4) college_pl = 0
( 5) afqsc = 0
( 6) black = 0
( 7) hispanic = 0
( 8) other_race = 0
( 9) age = 0
(10) age_sq = 0
F( 10,169349) = 81.50
Prob > F = 0.0000
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
Linear regression, absorbing indicators Number of obs = 158,592
Absorbed variable: exper_br_year_sex_fe No. of categories = 9,082
F( 0, 149510) = .
Prob > F = .
R-squared = 0.1564
Adj R-squared = 0.1051
Root MSE = 0.5824
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons | .575401 .0014624 393.46 0.000 .5725347 .5782673
------------------------------------------------------------------------------
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
note: female omitted because of collinearity
Linear regression, absorbing indicators Number of obs = 158,592
Absorbed variable: exper_br_year_sex_fe No. of categories = 9,082
F( 10, 149500) = 81.28
Prob > F = 0.0000
R-squared = 0.1610
Adj R-squared = 0.1100
Root MSE = 0.5808
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
female | 0 (omitted)
ged | .0459579 .0049608 9.26 0.000 .0362349 .0556809
hsd | .0435865 .0169195 2.58 0.010 .0104247 .0767483
asc_smc | .0095627 .0060141 1.59 0.112 -.0022247 .0213502
college_pl | -.1128707 .0113933 -9.91 0.000 -.1352014 -.0905401
afqsc | -.0021549 .000095 -22.67 0.000 -.0023412 -.0019686
black | -.0147778 .0045549 -3.24 0.001 -.0237053 -.0058502
hispanic | -.0147688 .0049626 -2.98 0.003 -.0244954 -.0050422
other_race | .0027205 .0068085 0.40 0.689 -.010624 .016065
age | .021643 .0040027 5.41 0.000 .0137979 .0294882
age_sq | -.00035 .0000673 -5.20 0.000 -.000482 -.000218
_cons | .3847826 .058281 6.60 0.000 .270553 .4990122
------------------------------------------------------------------------------
test totmoves_not all, sample = re_enlist
( 1) ged = 0
( 2) hsd = 0
( 3) asc_smc = 0
( 4) college_pl = 0
( 5) afqsc = 0
( 6) black = 0
( 7) hispanic = 0
( 8) other_race = 0
( 9) age = 0
(10) age_sq = 0
F( 10,149500) = 81.28
Prob > F = 0.0000
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
Linear regression, absorbing indicators Number of obs = 80,774
Absorbed variable: exper_br_year_sex_fe No. of categories = 8,345
F( 0, 72429) = .
Prob > F = .
R-squared = 0.2180
Adj R-squared = 0.1279
Root MSE = 0.5928
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons | .6693862 .0020859 320.92 0.000 .6652979 .6734745
------------------------------------------------------------------------------
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
note: female omitted because of collinearity
Linear regression, absorbing indicators Number of obs = 80,774
Absorbed variable: exper_br_year_sex_fe No. of categories = 8,345
F( 10, 72419) = 24.14
Prob > F = 0.0000
R-squared = 0.2206
Adj R-squared = 0.1307
Root MSE = 0.5918
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
female | 0 (omitted)
ged | .0768025 .0091429 8.40 0.000 .0588824 .0947226
hsd | .0532338 .0258223 2.06 0.039 .0026222 .1038455
asc_smc | .0062103 .0093763 0.66 0.508 -.0121671 .0245878
college_pl | -.0688375 .0164592 -4.18 0.000 -.1010975 -.0365775
afqsc | -.0015874 .000148 -10.73 0.000 -.0018774 -.0012974
black | -.0094303 .0060461 -1.56 0.119 -.0212807 .0024201
hispanic | -.0165859 .0077232 -2.15 0.032 -.0317234 -.0014484
other_race | .0009594 .0095036 0.10 0.920 -.0176676 .0195864
age | .0327988 .0075982 4.32 0.000 .0179063 .0476913
age_sq | -.0005668 .0001318 -4.30 0.000 -.0008251 -.0003084
_cons | .3027651 .1076416 2.81 0.005 .0917878 .5137423
------------------------------------------------------------------------------
test totmoves_not all, sample = re_enlist
( 1) ged = 0
( 2) hsd = 0
( 3) asc_smc = 0
( 4) college_pl = 0
( 5) afqsc = 0
( 6) black = 0
( 7) hispanic = 0
( 8) other_race = 0
( 9) age = 0
(10) age_sq = 0
F( 10, 72419) = 24.14
Prob > F = 0.0000
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
Linear regression, absorbing indicators Number of obs = 22,267
Absorbed variable: exper_br_year_sex_fe No. of categories = 4,258
F( 0, 18009) = .
Prob > F = .
R-squared = 0.2735
Adj R-squared = 0.1017
Root MSE = 0.5341
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons | .4096645 .0035793 114.45 0.000 .4026488 .4166802
------------------------------------------------------------------------------
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
note: female omitted because of collinearity
Linear regression, absorbing indicators Number of obs = 22,267
Absorbed variable: exper_br_year_sex_fe No. of categories = 4,258
F( 10, 17999) = 1.63
Prob > F = 0.0918
R-squared = 0.2742
Adj R-squared = 0.1021
Root MSE = 0.5340
------------------------------------------------------------------------------
| Robust
totmoves_not | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
female | 0 (omitted)
ged | -.0018781 .0163744 -0.11 0.909 -.0339734 .0302172
hsd | .0504832 .0514502 0.98 0.327 -.0503642 .1513306
asc_smc | -.0099183 .0150715 -0.66 0.510 -.0394598 .0196232
college_pl | .0259419 .0308459 0.84 0.400 -.0345191 .0864028
afqsc | -.000662 .0002909 -2.28 0.023 -.0012322 -.0000918
black | .000841 .0130487 0.06 0.949 -.0247357 .0264178
hispanic | .0052506 .0143918 0.36 0.715 -.0229587 .0334599
other_race | .0197186 .0185774 1.06 0.289 -.0166948 .056132
age | .0238591 .0108953 2.19 0.029 .0025033 .0452148
age_sq | -.0003689 .0001837 -2.01 0.045 -.0007289 -8.82e-06
_cons | .0871566 .1578508 0.55 0.581 -.2222462 .3965593
------------------------------------------------------------------------------
test totmoves_not all, sample = re_enlist
( 1) ged = 0
( 2) hsd = 0
( 3) asc_smc = 0
( 4) college_pl = 0
( 5) afqsc = 0
( 6) black = 0
( 7) hispanic = 0
( 8) other_race = 0
( 9) age = 0
(10) age_sq = 0
F( 10, 17999) = 1.63
Prob > F = 0.0918
C:\Program Files\Stata16\ado\plus/o/outreg2.ado
XXX/jhr_output/table_3.xls
dir : seeout
.
.
end of do-file