. xtset code year
panel variable: code (strongly balanced)
time variable: year, 2010 to 2019
delta: 1 unit
. summarize roa size der inv
Variable |
Obs
Mean Std. Dev.
Min
Max
-------------+--------------------------------------------------------roa |
100
1.8539
7.45655
-19.92
24.29
size |
100
8.6441
.692714
6.2
9.94
der |
100
.727 .4585848
.05
1.9
inv |
100
.0699 .2859522
-.96
.48
. summarize roa size der inv, detail
ROA
------------------------------------------------------------Percentiles
Smallest
1%
-19.845
-19.92
5%
-13.52
-19.77
10%
-6.525
-17.33
Obs
25%
-.645
-17.01
Sum of Wgt.
50%
2.165
Largest
100
100
Mean
1.8539
Std. Dev.
7.45655
Variance
55.60014
75%
4.68
19.05
90%
8.53
20.9
95%
14.28
22.89
Skewness
99%
23.59
24.29
Kurtosis
-.1826973
5.478676
SIZE
------------------------------------------------------------Percentiles
Smallest
1%
6.23
6.2
5%
7.885
6.26
10%
8.045
6.3
25%
8.4
50%
8.57
Obs
6.3
100
Sum of Wgt.
Largest
100
Mean
8.6441
Std. Dev.
.692714
75%
9.13
9.92
90%
9.24
9.92
Variance
.4798527
95%
9.91
9.93
Skewness
-1.14342
99%
9.935
9.94
Kurtosis
6.760273
DER
------------------------------------------------------------Percentiles
Smallest
1%
.05
.05
5%
.16
.05
10%
.2
.14
Obs
25%
.34
.14
Sum of Wgt.
50%
.665
Mean
Largest
Std. Dev.
100
100
.727
.4585848
75%
.98
1.7
90%
1.46
1.71
Variance
.2103
95%
1.63
1.75
Skewness
.6615055
99%
1.825
1.9
Kurtosis
2.566857
INV
------------------------------------------------------------Percentiles
Smallest
1%
-.795
-.96
5%
-.535
-.63
10%
-.345
-.62
Obs
25%
-.085
-.59
Sum of Wgt.
50%
.15
100
Mean
Largest
Std. Dev.
75%
.26
.46
90%
.38
.47
Variance
95%
.435
.48
Skewness
99%
.48
.48
Kurtosis
100
.0699
.2859522
.0817687
-1.024072
3.99098
. correlate roa size der inv
(obs=100)
|
roa
size
der
inv
-------------+-----------------------------------roa | 1.0000
size | 0.2141 1.0000
der | -0.0332 0.1261 1.0000
inv | 0.6302 0.2843 -0.0840 1.0000
. reg roa size der inv
Source |
SS
df
MS
Number of obs =
-------------+----------------------------------
F(3, 96)
=
= 0.0000
Model | 2194.49743
3
731.499144
Prob > F
Residual | 3309.91632
96
34.478295
R-squared
-------------+---------------------------------Total | 5504.41375
99
21.22
= 0.3987
Adj R-squared = 0.3799
55.6001389
Root MSE
= 5.8718
-----------------------------------------------------------------------------roa |
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
-------------+---------------------------------------------------------------size |
.38386
.8997488
0.43
0.671
-1.402127 2.169847
der | .2354828
1.307656
0.18
0.857
-2.360194
inv | 16.2005
2.169896
7.47
0.000
11.89329 20.50771
-0.36
0.719
-17.98532 12.44965
_cons | -2.767835 7.666301
------------------------------------------------------------------------------
. reg roa size der inv, vce(robust)
Linear regression
100
Number of obs
F(3, 96)
Prob > F
=
=
100
15.19
=
0.0000
R-squared
=
0.3987
Root MSE
=
5.8718
2.83116
|
roa |
Robust
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
-------------+---------------------------------------------------------------size |
.38386
.5624701
0.68
0.497
-.7326344 1.500354
der | .2354828
1.022748
0.23
0.818
-1.794656 2.265621
inv | 16.2005
2.489846
6.51
0.000
11.25819 21.14281
_cons | -2.767835 5.057914
-0.55 0.585
-12.80772 7.272046
------------------------------------------------------------------------------
. xtreg roa size der inv, re
Random-effects GLS regression
Group variable: code
Number of obs
=
Number of groups =
R-sq:
100
10
Obs per group:
within = 0.2282
min =
between = 0.7939
10
avg =
overall = 0.3982
10.0
max =
10
Wald chi2(3)
corr(u_i, X) = 0 (assumed)
Prob > chi2
=
=
54.33
0.0000
-----------------------------------------------------------------------------roa |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------size | .5590149
.9467309
der | -.0961712
inv | 16.43593
0.59
0.555
-1.296544 2.414573
1.37717 -0.07
0.944
-2.795375 2.603032
2.38446
0.000
11.76248 21.10939
0.616
-19.93221 11.81774
6.89
_cons | -4.057236 8.099625 -0.50
-------------+---------------------------------------------------------------sigma_u | 1.091722
sigma_e | 5.7056897
rho | .03531768 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xttest0
Breusch and Pagan Lagrangian multiplier test for random effects
roa[code,t] = Xb + u[code] + e[code,t]
Estimated results:
|
Var
sd = sqrt(Var)
---------+----------------------------roa | 55.60014
7.45655
e | 32.55489
5.70569
u | 1.191857
1.091722
Test: Var(u) = 0
chibar2(01) =
0.06
Prob > chibar2 = 0.4037
. reg roa size der inv, vce(robust)
Linear regression
Number of obs
=
100
F(3, 96)
=
15.19
Prob > F
=
0.0000
R-squared
=
0.3987
Root MSE
=
5.8718
|
roa |
Robust
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
-------------+---------------------------------------------------------------size |
.38386
.5624701
0.68
0.497
-.7326344 1.500354
der | .2354828
1.022748
0.23
0.818
-1.794656 2.265621
inv | 16.2005
2.489846
6.51
0.000
11.25819 21.14281
_cons | -2.767835 5.057914
-0.55 0.585
------------------------------------------------------------------------------
. outreg2 using STATA, replace ctitle(POLS)
dir : seeout
. seeout using "STATA.txt"
Hit Enter to continue.
-12.80772 7.272046