Hello everyone,
I am trying to generate a regression table for 3 models below and my ultimate goal is to display just the coefficients for each variable, as well as their significance levels. However, when I do this through "estout" command, Stata does not break down "high_qual" into 'A-levels, GCSE" and also does not break down other variables by their categories too (e.g. region into "London, East Midlands" and etc). I was wondering if there is any other way to display regression results using another code? Thank you!
I am trying to generate a regression table for 3 models below and my ultimate goal is to display just the coefficients for each variable, as well as their significance levels. However, when I do this through "estout" command, Stata does not break down "high_qual" into 'A-levels, GCSE" and also does not break down other variables by their categories too (e.g. region into "London, East Midlands" and etc). I was wondering if there is any other way to display regression results using another code? Thank you!
Code:
xtreg wages i.high_qual training_hrs
Random-effects GLS regression Number of obs = 338,294
Group variable: id Number of groups = 89,165
R-squared: Obs per group:
Within = 0.0083 min = 1
Between = 0.1505 avg = 3.8
Overall = 0.1267 max = 10
Wald chi2(6) = 19322.35
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
--------------------------------------------------------------------------------------
wages | Coefficient Std. err. z P>|z| [95% conf. interval]
---------------------+----------------------------------------------------------------
high_qual |
Other higher degree | -3.765343 .081937 -45.95 0.000 -3.925936 -3.604749
A-level etc | -5.305169 .0642317 -82.59 0.000 -5.431061 -5.179277
GCSE etc | -6.618824 .0681372 -97.14 0.000 -6.75237 -6.485278
Other qualification | -7.83586 .0919578 -85.21 0.000 -8.016094 -7.655627
No qualification | -9.896498 .0817473 -121.06 0.000 -10.05672 -9.736277
|
training_hrs | .0016344 .0001601 10.21 0.000 .0013206 .0019482
_cons | 11.37303 .0478542 237.66 0.000 11.27924 11.46682
---------------------+----------------------------------------------------------------
sigma_u | 6.1382893
sigma_e | 6.1667793
rho | .4976847 (fraction of variance due to u_i)
--------------------------------------------------------------------------------------
. estimate store m1, title (Model 1)
. xtreg wages i.high_qual training_hrs i.sex i.region i.age i.sector
Random-effects GLS regression Number of obs = 205,213
Group variable: id Number of groups = 57,917
R-squared: Obs per group:
Within = 0.0225 min = 1
Between = 0.2012 avg = 3.5
Overall = 0.1814 max = 10
Wald chi2(35) = 19472.24
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
----------------------------------------------------------------------------------------------------
wages | Coefficient Std. err. z P>|z| [95% conf. interval]
-----------------------------------+----------------------------------------------------------------
high_qual |
Other higher degree | -2.329431 .1003168 -23.22 0.000 -2.526048 -2.132814
A-level etc | -3.072894 .084336 -36.44 0.000 -3.238189 -2.907598
GCSE etc | -4.229586 .0917349 -46.11 0.000 -4.409383 -4.049789
Other qualification | -5.041695 .1325833 -38.03 0.000 -5.301553 -4.781836
No qualification | -6.210511 .1554506 -39.95 0.000 -6.515189 -5.905834
|
training_hrs | .0009451 .0001978 4.78 0.000 .0005575 .0013326
|
sex |
female | -.9664091 .0647862 -14.92 0.000 -1.093388 -.8394306
|
region |
North West | .162787 .1937713 0.84 0.401 -.2169978 .5425718
Yorkshire and the Humber | -.2455217 .1988844 -1.23 0.217 -.635328 .1442847
East Midlands | .0129424 .2012868 0.06 0.949 -.3815724 .4074572
West Midlands | .4283902 .1990318 2.15 0.031 .0382951 .8184853
East of England | .7615273 .1964324 3.88 0.000 .3765268 1.146528
London | 1.135278 .1869629 6.07 0.000 .7688377 1.501719
South East | 1.15785 .1883632 6.15 0.000 .7886648 1.527035
South West | -.1031834 .1994909 -0.52 0.605 -.4941785 .2878116
Wales | -.1906424 .2052822 -0.93 0.353 -.5929882 .2117034
Scotland | .6628312 .1976266 3.35 0.001 .2754901 1.050172
Northern Ireland | .100596 .2094684 0.48 0.631 -.3099544 .5111465
|
age |
16-17 years old | 2.093445 9.039835 0.23 0.817 -15.62431 19.8112
18-19 years old | 2.170951 9.03903 0.24 0.810 -15.54522 19.88712
20-24 years old | 2.546136 9.038605 0.28 0.778 -15.1692 20.26148
25-29 years old | 3.76751 9.038619 0.42 0.677 -13.94786 21.48288
30-34 years old | 5.268297 9.038609 0.58 0.560 -12.44705 22.98365
35-39 years old | 6.393266 9.03859 0.71 0.479 -11.32205 24.10858
40-44 years old | 6.746084 9.038567 0.75 0.455 -10.96918 24.46135
45-49 years old | 7.130368 9.03856 0.79 0.430 -10.58488 24.84562
50-54 years old | 7.257753 9.038572 0.80 0.422 -10.45752 24.97303
55-59 years old | 7.265843 9.038618 0.80 0.421 -10.44952 24.98121
60-64 years old | 6.758737 9.038757 0.75 0.455 -10.9569 24.47438
65 years or older | 4.785265 9.039245 0.53 0.597 -12.93133 22.50186
|
sector |
managerial & technical occupation | -.0488293 .1115175 -0.44 0.661 -.2673997 .169741
skilled non-manual | -1.901182 .1207305 -15.75 0.000 -2.137809 -1.664554
skilled manual | -5.896793 .123706 -47.67 0.000 -6.139252 -5.654333
partly skilled occupation | -3.051848 .1269658 -24.04 0.000 -3.300696 -2.803
unskilled occupation | -3.380385 .1702209 -19.86 0.000 -3.714012 -3.046758
|
_cons | 9.866818 9.040629 1.09 0.275 -7.852489 27.58612
-----------------------------------+----------------------------------------------------------------
sigma_u | 6.0796049
sigma_e | 6.5503506
rho | .46277955 (fraction of variance due to u_i)
----------------------------------------------------------------------------------------------------
. estimate store m2, title (Model 2)
. xtreg wages i.high_qual training_hrs i.illness_disability i.sex i.children i.general_health i.region i.age i.sector
Random-effects GLS regression Number of obs = 81,014
Group variable: id Number of groups = 45,174
R-squared: Obs per group:
Within = 0.0093 min = 1
Between = 0.2259 avg = 1.8
Overall = 0.2153 max = 4
Wald chi2(43) = 13494.78
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
----------------------------------------------------------------------------------------------------
wages | Coefficient Std. err. z P>|z| [95% conf. interval]
-----------------------------------+----------------------------------------------------------------
high_qual |
Other higher degree | -2.226562 .1213105 -18.35 0.000 -2.464326 -1.988797
A-level etc | -2.750473 .1055585 -26.06 0.000 -2.957363 -2.543582
GCSE etc | -3.690913 .1114786 -33.11 0.000 -3.909407 -3.472419
Other qualification | -4.429453 .1577683 -28.08 0.000 -4.738673 -4.120232
No qualification | -5.281472 .1854816 -28.47 0.000 -5.64501 -4.917935
|
training_hrs | .0006149 .0003174 1.94 0.053 -7.30e-06 .0012371
|
illness_disability |
no | .1494179 .0684527 2.18 0.029 .0152532 .2835826
|
sex |
female | -1.712939 .0848684 -20.18 0.000 -1.879278 -1.5466
|
children |
1 | -.3398704 .1087729 -3.12 0.002 -.5530613 -.1266795
2 | -.2720838 .1282247 -2.12 0.034 -.5233996 -.0207681
3 | -1.174362 .2151139 -5.46 0.000 -1.595978 -.7527469
4 | -1.975734 .4807552 -4.11 0.000 -2.917997 -1.033471
5 | -2.071639 1.181146 -1.75 0.079 -4.386643 .2433645
6 | -4.674262 2.33589 -2.00 0.045 -9.252522 -.0960014
|
general_health |
very good | -.378106 .0689673 -5.48 0.000 -.5132795 -.2429325
or Poor? | -.9154749 .2117265 -4.32 0.000 -1.330451 -.5004986
|
region |
North West | .2585602 .2247362 1.15 0.250 -.1819145 .699035
Yorkshire and the Humber | -.2284908 .2328341 -0.98 0.326 -.6848373 .2278557
East Midlands | .0518488 .2331266 0.22 0.824 -.4050709 .5087686
West Midlands | .5359982 .2331594 2.30 0.022 .0790141 .9929822
East of England | .9415514 .2282001 4.13 0.000 .4942875 1.388815
London | 1.394893 .2199591 6.34 0.000 .9637811 1.826005
South East | 1.466192 .2183471 6.71 0.000 1.038239 1.894144
South West | -.0282937 .2312368 -0.12 0.903 -.4815096 .4249222
Wales | -.2318236 .2358603 -0.98 0.326 -.6941013 .230454
Scotland | .5588212 .2261004 2.47 0.013 .1156726 1.00197
Northern Ireland | -.1259098 .2391234 -0.53 0.599 -.5945829 .3427634
|
age |
18-19 years old | .3611545 .2740854 1.32 0.188 -.1760431 .898352
20-24 years old | .9872718 .2612305 3.78 0.000 .4752694 1.499274
25-29 years old | 2.151108 .2647774 8.12 0.000 1.632154 2.670062
30-34 years old | 3.617456 .2642491 13.69 0.000 3.099537 4.135375
35-39 years old | 4.557396 .2642927 17.24 0.000 4.039391 5.0754
40-44 years old | 4.976156 .2619728 18.99 0.000 4.462698 5.489613
45-49 years old | 5.086969 .2606707 19.51 0.000 4.576063 5.597874
50-54 years old | 4.821479 .261474 18.44 0.000 4.308999 5.333959
55-59 years old | 4.646858 .2659043 17.48 0.000 4.125695 5.168021
60-64 years old | 3.821465 .2773119 13.78 0.000 3.277944 4.364986
65 years or older | 1.444498 .3071334 4.70 0.000 .8425278 2.046468
|
sector |
managerial & technical occupation | -.3820282 .149493 -2.56 0.011 -.675029 -.0890273
skilled non-manual | -2.93446 .1628875 -18.02 0.000 -3.253714 -2.615206
skilled manual | -6.914072 .1672881 -41.33 0.000 -7.241951 -6.586194
partly skilled occupation | -4.267661 .17175 -24.85 0.000 -4.604285 -3.931038
unskilled occupation | -4.637669 .2287794 -20.27 0.000 -5.086069 -4.18927
|
_cons | 13.46299 .3555006 37.87 0.000 12.76622 14.15976
-----------------------------------+----------------------------------------------------------------
sigma_u | 6.4843857
sigma_e | 5.1619774
rho | .61210157 (fraction of variance due to u_i)
----------------------------------------------------------------------------------------------------
. estimate store m3, title (Model 3)
estout m1 m2 m3, cells(b(star fmt(3)) se(par fmt(2)))
------------------------------------------------------------
m1 m2 m3
b/se b/se b/se
------------------------------------------------------------
1.high_qual 0.000 0.000 0.000
(.) (.) (.)
2.high_qual -3.765*** -2.329*** -2.227***
(0.08) (0.10) (0.12)
3.high_qual -5.305*** -3.073*** -2.750***
(0.06) (0.08) (0.11)
4.high_qual -6.619*** -4.230*** -3.691***
(0.07) (0.09) (0.11)
5.high_qual -7.836*** -5.042*** -4.429***
(0.09) (0.13) (0.16)
9.high_qual -9.896*** -6.211*** -5.281***
(0.08) (0.16) (0.19)
training_hrs 0.002*** 0.001*** 0.001
(0.00) (0.00) (0.00)
1.sex 0.000 0.000
(.) (.)
2.sex -0.966*** -1.713***
(0.06) (0.08)
1.region 0.000 0.000
(.) (.)
2.region 0.163 0.259
(0.19) (0.22)
3.region -0.246 -0.228
(0.20) (0.23)
4.region 0.013 0.052
(0.20) (0.23)
5.region 0.428* 0.536*
(0.20) (0.23)
6.region 0.762*** 0.942***
(0.20) (0.23)
7.region 1.135*** 1.395***
(0.19) (0.22)
8.region 1.158*** 1.466***
(0.19) (0.22)
9.region -0.103 -0.028
(0.20) (0.23)
10.region -0.191 -0.232
(0.21) (0.24)
11.region 0.663*** 0.559*
(0.20) (0.23)
12.region 0.101 -0.126
(0.21) (0.24)
1.age 0.000
(.)
2.age 2.093 0.000
(9.04) (.)
3.age 2.171 0.361
(9.04) (0.27)
4.age 2.546 0.987***
(9.04) (0.26)
5.age 3.768 2.151***
(9.04) (0.26)
6.age 5.268 3.617***
(9.04) (0.26)
7.age 6.393 4.557***
(9.04) (0.26)
8.age 6.746 4.976***
(9.04) (0.26)
9.age 7.130 5.087***
(9.04) (0.26)
10.age 7.258 4.821***
(9.04) (0.26)
11.age 7.266 4.647***
(9.04) (0.27)
12.age 6.759 3.821***
(9.04) (0.28)
13.age 4.785 1.444***
(9.04) (0.31)
1.sector 0.000 0.000
(.) (.)
2.sector -0.049 -0.382*
(0.11) (0.15)
3.sector -1.901*** -2.934***
(0.12) (0.16)
4.sector -5.897*** -6.914***
(0.12) (0.17)
5.sector -3.052*** -4.268***
(0.13) (0.17)
6.sector -3.380*** -4.638***
(0.17) (0.23)
1.illness_~y 0.000
(.)
2.illness_~y 0.149*
(0.07)
0.children 0.000
(.)
1.children -0.340**
(0.11)
2.children -0.272*
(0.13)
3.children -1.174***
(0.22)
4.children -1.976***
(0.48)
5.children -2.072
(1.18)
6.children -4.674*
(2.34)
1.general_~h 0.000
(.)
2.general_~h -0.378***
(0.07)
5.general_~h -0.915***
(0.21)
_cons 11.373*** 9.867 13.463***
(0.05) (9.04) (0.36)
------------------------------------------------------------
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