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use http://www.ats.ucla.edu/stat/stata/examples/greene/table14_1, clear generate logc = log(c) generate logq = log(q) generate logf = log(pf) save table14-1
Table 14.1, page 566, No effects.
regress logc logq logf lf
Source | SS df MS Number of obs = 90
-------------+------------------------------ F( 3, 86) = 2419.34
Model | 112.705452 3 37.5684839 Prob > F = 0.0000
Residual | 1.33544153 86 .01552839 R-squared = 0.9883
-------------+------------------------------ Adj R-squared = 0.9879
Total | 114.040893 89 1.28135835 Root MSE = .12461
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .8827385 .0132545 66.60 0.000 .8563895 .9090876
logf | .453977 .0203042 22.36 0.000 .4136136 .4943404
lf | -1.62751 .345302 -4.71 0.000 -2.313948 -.9410727
_cons | 9.516923 .2292445 41.51 0.000 9.0612 9.972645
------------------------------------------------------------------------------
Table 14.1, Group Means.
egen mq = mean(logq), by(i)
egen mf = mean(logf), by(i)
egen mlf = mean(lf), by(i)
regress logc mq mf mlf
Source | SS df MS Number of obs = 90
-------------+------------------------------ F( 3, 86) = 53.40
Model | 74.2047466 3 24.7349155 Prob > F = 0.0000
Residual | 39.8361466 86 .463211006 R-squared = 0.6507
-------------+------------------------------ Adj R-squared = 0.6385
Total | 114.040893 89 1.28135835 Root MSE = .6806
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
mq | .7824569 .1518735 5.15 0.000 .4805424 1.084371
mf | -5.523905 6.253856 -0.88 0.380 -17.95616 6.908349
mlf | -1.751066 3.83042 -0.46 0.649 -9.365689 5.863557
_cons | 85.80811 78.8686 1.09 0.280 -70.97747 242.5937
------------------------------------------------------------------------------
Table 14.1, Firm effects.
xtreg logc logq logf lf, i(i) fe
Fixed-effects (within) regression Number of obs = 90
Group variable (i) : i Number of groups = 6
R-sq: within = 0.9926 Obs per group: min = 15
between = 0.9856 avg = 15.0
overall = 0.9873 max = 15
F(3,81) = 3604.80
corr(u_i, Xb) = -0.3475 Prob > F = 0.0000
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .9192846 .0298901 30.76 0.000 .8598126 .9787565
logf | .4174918 .0151991 27.47 0.000 .3872503 .4477333
lf | -1.070396 .20169 -5.31 0.000 -1.471696 -.6690963
_cons | 9.713528 .229641 42.30 0.000 9.256614 10.17044
-------------+----------------------------------------------------------------
sigma_u | .1320775
sigma_e | .06010514
rho | .82843653 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(5, 81) = 57.73 Prob > F = 0.0000
Table 14.1, a1 ... a6, Method 1.
tabulate i, gen(i)
(output omitted)
regress logc logq logf lf i2-i6
Source | SS df MS Number of obs = 90
-------------+------------------------------ F( 8, 81) = 3935.79
Model | 113.74827 8 14.2185338 Prob > F = 0.0000
Residual | .292622872 81 .003612628 R-squared = 0.9974
-------------+------------------------------ Adj R-squared = 0.9972
Total | 114.040893 89 1.28135835 Root MSE = .06011
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .9192846 .0298901 30.76 0.000 .8598126 .9787565
logf | .4174918 .0151991 27.47 0.000 .3872503 .4477333
lf | -1.070396 .20169 -5.31 0.000 -1.471696 -.6690963
i2 | -.0412359 .0251839 -1.64 0.105 -.0913441 .0088722
i3 | -.2089211 .0427986 -4.88 0.000 -.2940769 -.1237652
i4 | .1845557 .0607527 3.04 0.003 .0636769 .3054345
i5 | .0240547 .0799041 0.30 0.764 -.1349293 .1830387
i6 | .0870617 .0841995 1.03 0.304 -.080469 .2545924
_cons | 9.705942 .193124 50.26 0.000 9.321686 10.0902
------------------------------------------------------------------------------
lincom _cons
( 1) _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.705942 .193124 50.26 0.000 9.321686 10.0902
------------------------------------------------------------------------------
lincom _cons + i2
( 1) i2 + _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.664706 .198982 48.57 0.000 9.268794 10.06062
------------------------------------------------------------------------------
lincom _cons + i3
( 1) i3 + _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.497021 .2249584 42.22 0.000 9.049424 9.944618
------------------------------------------------------------------------------
lincom _cons + i4
( 1) i4 + _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.890498 .2417635 40.91 0.000 9.409464 10.37153
------------------------------------------------------------------------------
lincom _cons + i5
( 1) i5 + _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.729997 .2609421 37.29 0.000 9.210804 10.24919
------------------------------------------------------------------------------
lincom _cons + i6
( 1) i6 + _cons = 0.0
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 9.793004 .2636622 37.14 0.000 9.268399 10.31761
------------------------------------------------------------------------------
Table 14.1, a1 ... a6, Method 2.
regress logc logq logf lf i1-i6, noconst
Source | SS df MS Number of obs = 90
-------------+------------------------------ F( 9, 81) = .
Model | 16191.3043 9 1799.03381 Prob > F = 0.0000
Residual | .292622872 81 .003612628 R-squared = 1.0000
-------------+------------------------------ Adj R-squared = 1.0000
Total | 16191.5969 90 179.906633 Root MSE = .06011
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .9192846 .0298901 30.76 0.000 .8598126 .9787565
logf | .4174918 .0151991 27.47 0.000 .3872503 .4477333
lf | -1.070396 .20169 -5.31 0.000 -1.471696 -.6690963
i1 | 9.705942 .193124 50.26 0.000 9.321686 10.0902
i2 | 9.664706 .198982 48.57 0.000 9.268794 10.06062
i3 | 9.497021 .2249584 42.22 0.000 9.049424 9.944618
i4 | 9.890498 .2417635 40.91 0.000 9.409464 10.37153
i5 | 9.729997 .2609421 37.29 0.000 9.210804 10.24919
i6 | 9.793004 .2636622 37.14 0.000 9.268399 10.31761
------------------------------------------------------------------------------
Table 14.1, Time effects.
xtreg logc logq logf lf, i(t) fe
Fixed-effects (within) regression Number of obs = 90
Group variable (i) : t Number of groups = 15
R-sq: within = 0.9858 Obs per group: min = 6
between = 0.4812 avg = 6.0
overall = 0.5265 max = 6
F(3,72) = 1668.37
corr(u_i, Xb) = -0.1503 Prob > F = 0.0000
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .8677268 .0154082 56.32 0.000 .8370111 .8984424
logf | -.4844835 .3641085 -1.33 0.188 -1.210321 .2413535
lf | -1.954404 .4423777 -4.42 0.000 -2.836268 -1.07254
_cons | 21.66698 4.624053 4.69 0.000 12.4491 30.88486
-------------+----------------------------------------------------------------
sigma_u | .8027907
sigma_e | .12293801
rho | .97708602 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(14, 72) = 1.17 Prob > F = 0.3178
Table 14.1, c1 ... c15, Method 2.
tabulate t, gen(t)
(output omitted)
regress logc logq logf lf t1-t15, noconst
Source | SS df MS Number of obs = 90
-------------+------------------------------ F( 18, 72) =59513.52
Model | 16190.5087 18 899.472708 Prob > F = 0.0000
Residual | 1.08819022 72 .015113753 R-squared = 0.9999
-------------+------------------------------ Adj R-squared = 0.9999
Total | 16191.5969 90 179.906633 Root MSE = .12294
------------------------------------------------------------------------------
logc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .8677268 .0154082 56.32 0.000 .8370111 .8984424
logf | -.4844835 .3641085 -1.33 0.188 -1.210321 .2413535
lf | -1.954404 .4423777 -4.42 0.000 -2.836268 -1.07254
t1 | 20.4958 4.209528 4.87 0.000 12.10426 28.88735
t2 | 20.57804 4.221526 4.87 0.000 12.16258 28.9935
t3 | 20.65573 4.224177 4.89 0.000 12.23499 29.07647
t4 | 20.74076 4.24575 4.89 0.000 12.27701 29.20451
t5 | 21.19983 4.440331 4.77 0.000 12.34819 30.05147
t6 | 21.41162 4.538621 4.72 0.000 12.36404 30.4592
t7 | 21.50335 4.571397 4.70 0.000 12.39044 30.61626
t8 | 21.65403 4.622886 4.68 0.000 12.43847 30.86958
t9 | 21.82957 4.656906 4.69 0.000 12.5462 31.11294
t10 | 22.1138 4.792648 4.61 0.000 12.55983 31.66777
t11 | 22.46533 4.949909 4.54 0.000 12.59786 32.33279
t12 | 22.65134 5.008592 4.52 0.000 12.66689 32.63578
t13 | 22.61656 4.986139 4.54 0.000 12.67687 32.55624
t14 | 22.55223 4.955942 4.55 0.000 12.67274 32.43172
t15 | 22.53677 4.940532 4.56 0.000 12.688 32.38554
------------------------------------------------------------------------------
Table 14.2, Random effects, Firm effects.
xtreg logc logq logf lf, i(i) re
Random-effects GLS regression Number of obs = 90
Group variable (i) : i Number of groups = 6
R-sq: within = 0.9925 Obs per group: min = 15
between = 0.9856 avg = 15.0
overall = 0.9876 max = 15
Random effects u_i ~ Gaussian Wald chi2(3) = 11091.33
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
logc | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .9066805 .025625 35.38 0.000 .8564565 .9569045
logf | .4227784 .0140248 30.15 0.000 .3952904 .4502665
lf | -1.064499 .2000703 -5.32 0.000 -1.456629 -.672368
_cons | 9.627909 .210164 45.81 0.000 9.215995 10.03982
-------------+----------------------------------------------------------------
sigma_u | .12488859
sigma_e | .06010514
rho | .81193816 (fraction of variance due to u_i)
------------------------------------------------------------------------------
Table 14.2, Random effects with autocorrelation. Using xtregar we obtain slightly different values for the autocorrelation, coefficients and standard errors. It should be noted that the latest version of Greene's Limdep program also computes different values from those found in the book.
tsset i t
panel variable: i, 1 to 6
time variable: t, 1 to 15
xtregar logc logq logf lf, re
Random-effects GLS regression Number of obs = 90
Group variable (i) : i Number of groups = 6
R-sq: within = 0.9925 Obs per group: min = 15
between = 0.9854 avg = 15.0
overall = 0.9866 max = 15
Wald chi2(4) = 3735.11
corr(u_i, Xb) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
logc | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
logq | .9276293 .0287051 32.32 0.000 .8713683 .9838904
logf | .3997841 .017633 22.67 0.000 .3652241 .4343442
lf | -.9870458 .198669 -4.97 0.000 -1.37643 -.5976618
_cons | 9.902918 .2626146 37.71 0.000 9.388203 10.41763
-------------+----------------------------------------------------------------
rho_ar | .69576607 (estimated autocorrelation coefficient)
sigma_u | .10060015
sigma_e | .04720363
rho_fov | .81955952 (fraction of variance due to u_i)
theta | .67082541
------------------------------------------------------------------------------
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