Example 14.1: Effect of Job Training on Firm Scrap Rates
use http://fmwww.bc.edu/ec-p/data/wooldridge/jtrain
iis fcode
tis year
xtreg lscrap d88 d89 grant grant_1, fe
Fixed-effects (within) regression Number of obs = 162
Group variable (i) : fcode Number of groups = 54
R-sq: within = 0.2010 Obs per group: min = 3
between = 0.0079 avg = 3.0
overall = 0.0068 max = 3
F(4,104) = 6.54
corr(u_i, Xb) = -0.0714 Prob > F = 0.0001
------------------------------------------------------------------------------
lscrap | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
d88 | -.0802157 .1094751 -0.73 0.465 -.2973089 .1368776
d89 | -.2472028 .1332183 -1.86 0.066 -.5113797 .016974
grant | -.2523149 .150629 -1.68 0.097 -.5510178 .046388
grant_1 | -.4215895 .2102 -2.01 0.047 -.8384239 -.0047551
_cons | .597434 .0677344 8.82 0.000 .4631142 .7317539
-------------+----------------------------------------------------------------
sigma_u | 1.438982
sigma_e | .4977442
rho | .89313867 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(53, 104) = 24.66 Prob > F = 0.0000
Change in firm's scrap rate in 1989 if the training grant was received in 1988
display exp(_b[grant_1])-1
-.34399671
xtreg lscrap d88 d89 grant, fe
Fixed-effects (within) regression Number of obs = 162
Group variable (i) : fcode Number of groups = 54
R-sq: within = 0.1701 Obs per group: min = 3
between = 0.0189 avg = 3.0
overall = 0.0130 max = 3
F(3,105) = 7.18
corr(u_i, Xb) = -0.0109 Prob > F = 0.0002
------------------------------------------------------------------------------
lscrap | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
d88 | -.1400659 .106835 -1.31 0.193 -.3518999 .0717681
d89 | -.42704 .0999338 -4.27 0.000 -.6251903 -.2288897
grant | -.0822141 .1262632 -0.65 0.516 -.3325706 .1681424
_cons | .597434 .0687024 8.70 0.000 .4612098 .7336583
-------------+----------------------------------------------------------------
sigma_u | 1.4283441
sigma_e | .50485773
rho | .88894293 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(53, 105) = 23.90 Prob > F = 0.0000
Example 14.2: Has the Return to Education Changed Over Time
use http://fmwww.bc.edu/ec-p/data/wooldridge/wagepan
iis nr
tis year
gen edd81 = educ*d81
gen edd82 = educ*d82
gen edd83 = educ*d83
gen edd84 = educ*d84
gen edd85 = educ*d85
gen edd86 = educ*d86
gen edd87 = educ*d87
xtreg lwage expersq union married d81-d87 edd81-edd87, fe
Fixed-effects (within) regression Number of obs = 4360
Group variable (i) : nr Number of groups = 545
R-sq: within = 0.1814 Obs per group: min = 8
between = 0.0211 avg = 8.0
overall = 0.0784 max = 8
F(17,3798) = 49.49
corr(u_i, Xb) = -0.1732 Prob > F = 0.0000
------------------------------------------------------------------------------
lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
expersq | -.0060437 .0008633 -7.00 0.000 -.0077362 -.0043512
union | .0789759 .0193328 4.09 0.000 .0410722 .1168796
married | .0474337 .0183277 2.59 0.010 .0115006 .0833668
d81 | .09842 .145999 0.67 0.500 -.187824 .384664
d82 | .2472014 .1493785 1.65 0.098 -.0456685 .5400712
d83 | .4088129 .1557146 2.63 0.009 .1035206 .7141052
d84 | .6399246 .1652396 3.87 0.000 .3159577 .9638916
d85 | .7729394 .1779911 4.34 0.000 .423972 1.121907
d86 | .9699322 .1941747 5.00 0.000 .5892354 1.350629
d87 | 1.188776 .2135856 5.57 0.000 .7700229 1.60753
edd81 | .0049906 .012222 0.41 0.683 -.0189718 .028953
edd82 | .001651 .0123304 0.13 0.893 -.0225239 .0258259
edd83 | -.0026621 .0125098 -0.21 0.831 -.0271886 .0218644
edd84 | -.0098257 .0127593 -0.77 0.441 -.0348414 .01519
edd85 | -.0092145 .0130721 -0.70 0.481 -.0348436 .0164146
edd86 | -.0121382 .0134419 -0.90 0.367 -.0384922 .0142159
edd87 | -.0157891 .013868 -1.14 0.255 -.0429785 .0114002
_cons | 1.436283 .0192766 74.51 0.000 1.398489 1.474076
-------------+----------------------------------------------------------------
sigma_u | .39876324
sigma_e | .35114511
rho | .5632436 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(544, 3798) = 8.25 Prob > F = 0.0000
test edd81 edd82 edd83 edd84 edd85 edd86 edd87
( 1) edd81 = 0.0
( 2) edd82 = 0.0
( 3) edd83 = 0.0
( 4) edd84 = 0.0
( 5) edd85 = 0.0
( 6) edd86 = 0.0
( 7) edd87 = 0.0
F( 7, 3798) = 0.52
Prob > F = 0.8202
Example 14.3: Effect of Job Training on Firm Scrap Rates
use http://fmwww.bc.edu/ec-p/data/wooldridge/jtrain
iis fcode
tis year
xtreg lscrap d88 d89 grant grant_1 lsales lemploy, fe
Fixed-effects (within) regression Number of obs = 148
Group variable (i) : fcode Number of groups = 51
R-sq: within = 0.2131 Obs per group: min = 1
between = 0.0341 avg = 2.9
overall = 0.0004 max = 3
F(6,91) = 4.11
corr(u_i, Xb) = -0.2258 Prob > F = 0.0011
------------------------------------------------------------------------------
lscrap | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
d88 | -.0039605 .1195487 -0.03 0.974 -.2414293 .2335083
d89 | -.1321925 .1536863 -0.86 0.392 -.4374715 .1730865
grant | -.2967544 .157086 -1.89 0.062 -.6087866 .0152777
grant_1 | -.5355783 .224206 -2.39 0.019 -.9809359 -.0902207
lsales | -.0868607 .2596993 -0.33 0.739 -.6027214 .4290001
lemploy | -.0763642 .3502912 -0.22 0.828 -.7721747 .6194462
_cons | 2.115513 3.108438 0.68 0.498 -4.059017 8.290043
-------------+----------------------------------------------------------------
sigma_u | 1.4415147
sigma_e | .49149052
rho | .89585684 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(50, 91) = 20.75 Prob > F = 0.0000
Example 14.4: Has the Return to Education Changed Over Time
use http://fmwww.bc.edu/ec-p/data/wooldridge/wagepan
iis nr
tis year
reg lwage educ black hisp exper expersq married union d81-d87
Source | SS df MS Number of obs = 4360
-------------+------------------------------ F( 14, 4345) = 72.46
Model | 234.048277 14 16.7177341 Prob > F = 0.0000
Residual | 1002.48136 4345 .230720682 R-squared = 0.1893
-------------+------------------------------ Adj R-squared = 0.1867
Total | 1236.52964 4359 .283672779 Root MSE = .48033
------------------------------------------------------------------------------
lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .0913498 .0052374 17.44 0.000 .0810819 .1016177
black | -.1392342 .0235796 -5.90 0.000 -.1854622 -.0930062
hisp | .0160195 .0207971 0.77 0.441 -.0247535 .0567925
exper | .0672345 .0136948 4.91 0.000 .0403856 .0940834
expersq | -.0024117 .00082 -2.94 0.003 -.0040192 -.0008042
married | .1082529 .0156894 6.90 0.000 .0774937 .1390122
union | .1824613 .0171568 10.63 0.000 .1488253 .2160973
d81 | .05832 .0303536 1.92 0.055 -.0011886 .1178286
d82 | .0627744 .0332141 1.89 0.059 -.0023421 .1278909
d83 | .0620117 .0366601 1.69 0.091 -.0098608 .1338843
d84 | .0904672 .0400907 2.26 0.024 .011869 .1690654
d85 | .1092463 .0433525 2.52 0.012 .0242533 .1942393
d86 | .1419596 .046423 3.06 0.002 .0509469 .2329723
d87 | .1738334 .049433 3.52 0.000 .0769194 .2707474
_cons | .0920558 .0782701 1.18 0.240 -.0613935 .2455051
------------------------------------------------------------------------------
xtreg lwage educ black hisp exper expersq married union, re
Random-effects GLS regression Number of obs = 4360
Group variable (i) : nr Number of groups = 545
R-sq: within = 0.1799 Obs per group: min = 8
between = 0.1860 avg = 8.0
overall = 0.1830 max = 8
Random effects u_i ~ Gaussian Wald chi2(14) = 957.77
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
lwage | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ | .0918763 .0106597 8.62 0.000 .0709836 .1127689
black | -.1393767 .0477228 -2.92 0.003 -.2329117 -.0458417
hisp | .0217317 .0426063 0.51 0.610 -.0617751 .1052385
exper | .1057545 .0153668 6.88 0.000 .0756361 .1358729
expersq | -.0047239 .0006895 -6.85 0.000 -.0060753 -.0033726
married | .063986 .0167742 3.81 0.000 .0311091 .0968629
union | .1061344 .0178539 5.94 0.000 .0711415 .1411273
d81 | .040462 .0246946 1.64 0.101 -.0079385 .0888626
d82 | .0309212 .0323416 0.96 0.339 -.0324672 .0943096
d83 | .0202806 .041582 0.49 0.626 -.0612186 .1017798
d84 | .0431187 .0513163 0.84 0.401 -.0574595 .1436969
d85 | .0578155 .0612323 0.94 0.345 -.0621977 .1778286
d86 | .0919476 .0712293 1.29 0.197 -.0476592 .2315544
d87 | .1349289 .0813135 1.66 0.097 -.0244427 .2943005
_cons | .0235864 .1506683 0.16 0.876 -.271718 .3188907
-------------+----------------------------------------------------------------
sigma_u | .32460315
sigma_e | .35099001
rho | .46100216 (fraction of variance due to u_i)
------------------------------------------------------------------------------
xtreg lwage expersq married union d81-d87, fe
Fixed-effects (within) regression Number of obs = 4360
Group variable (i) : nr Number of groups = 545
R-sq: within = 0.1806 Obs per group: min = 8
between = 0.0286 avg = 8.0
overall = 0.0888 max = 8
F(10,3805) = 83.85
corr(u_i, Xb) = -0.1222 Prob > F = 0.0000
------------------------------------------------------------------------------
lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
expersq | -.0051855 .0007044 -7.36 0.000 -.0065666 -.0038044
married | .0466804 .0183104 2.55 0.011 .0107811 .0825796
union | .0800019 .0193103 4.14 0.000 .0421423 .1178614
d81 | .1511912 .0219489 6.89 0.000 .1081584 .194224
d82 | .2529709 .0244185 10.36 0.000 .2050963 .3008454
d83 | .3544437 .0292419 12.12 0.000 .2971125 .4117749
d84 | .4901148 .0362266 13.53 0.000 .4190894 .5611402
d85 | .6174823 .0452435 13.65 0.000 .5287784 .7061861
d86 | .7654966 .0561277 13.64 0.000 .6554532 .8755399
d87 | .9250249 .0687731 13.45 0.000 .7901893 1.059861
_cons | 1.426019 .0183415 77.75 0.000 1.390058 1.461979
-------------+----------------------------------------------------------------
sigma_u | .39176195
sigma_e | .35099001
rho | .55472817 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(544, 3805) = 9.16 Prob > F = 0.0000
This page prepared by Oleksandr Talavera (revised 8 Nov 2002)
Send your questions/comments/suggestions to Kit Baum
at baum@bc.edu
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