The results of the estimation considering the wage as the dependent variable are
reported in Table 15.
Table 14
Estimation Results for Wage Model
Source | SS df MS
Number of obs = 1236803
F( 61,1236741)=33133.55
Prob > F = 0.0000
R-squared = 0.6204
Adj R-squared = 0.6204
Root MSE = .35032
---------+------------------------------
Model | 248043.914 61 4066.29367
Residual | 151778.2241236741 .122724341
---------+------------------------------
Total | 399822.1371236802 .323270934
|
lsal98 |
| Coef. |
Std. Err. |
t |
-P->-|--t|--- |
[95% Conf. |
Interval] |
|
------------------------- | ||||||
|
sexo |
| -.2082559 |
.0006997 |
-297.65 |
0.000 |
-.2096273 |
-.2068846 |
|
mob1 |
| .0241476 |
.0015536 |
15.54 |
0.000 |
.0211026 |
.0271925 |
|
mob2 |
| .077264 |
.005193 |
14.88 |
0.000 |
.0670859 |
.0874421 |
|
mob3 |
| .0987891 |
.0034433 |
28.69 |
0.000 |
.0920404 |
.1055378 |
|
mobsec |
| -.0252569 |
.0017056 |
-14.81 |
0.000 |
-.0285998 |
-.0219141 |
|
mobemp |
| .0229967 |
.001574 |
14.61 |
0.000 |
.0199116 |
.0260817 |
|
saimor |
| -.015432 |
.0016559 |
-9.32 |
0.000 |
-.0186775 |
-.0121865 |
|
entnov |
| .049663 |
.0016788 |
29.58 |
0.000 |
.0463725 |
.0529535 |
|
antig98 |
| .0098432 |
.0001138 |
86.46 |
0.000 |
.0096201 |
.0100664 |
|
qsup98 |
| .7953185 |
.0023545 |
337.79 |
0.000 |
.7907039 |
.7999332 |
|
qmed98 |
| .5320795 |
.0018837 |
282.47 |
0.000 |
.5283875 |
.5357715 |
|
pqua98 |
| .2175058 |
.0015231 |
142.80 |
0.000 |
.2145205 |
.2204911 |
|
pesp98 |
| .0913745 |
.0016478 |
55.45 |
0.000 |
.0881449 |
.0946042 |
|
pnqua98 |
| .002509 |
.0018047 |
1.39 |
0.164 |
-.0010282 |
.0060461 |
|
school98 |
| .0140561 |
.0004011 |
35.04 |
0.000 |
.0132699 |
.0148423 |
|
pexp98 |
| .0047937 |
.0000358 |
133.78 |
0.000 |
.0047235 |
.0048639 |
|
small98 |
| .1433129 |
.0008993 |
159.37 |
0.000 |
.1415504 |
.1450755 |
|
medium98 |
| .2391344 |
.0009726 |
245.88 |
0.000 |
.2372282 |
.2410406 |
|
big98 |
| .3021693 |
.0011439 |
264.15 |
0.000 |
.2999273 |
.3044114 |
|
ant2 |
| -.0001295 |
3.40e-06 |
-38.08 |
0.000 |
-.0001362 |
-.0001228 |
|
school2 |
| .0017435 |
.0000225 |
77.56 |
0.000 |
.0016994 |
.0017875 |
|
_cons |
| 11.09669 |
149.7557 |
0.07 |
0.941 |
-282.4194 |
304.6128 |
Note: 28 regional dummies and 12 industry dummies were included.
The overall quality of the model seems to be good. The results shown seem to be in line
with what was expected. The results confirm the effect of characteristics such as tenure,
experience, and skills and also the effect of spatial and job mobility on wages.
Female workers earn lower wages. There is a premium for tenure but at diminishing
rates given the signal for ant2 (tenure squared). There is also a premium for schooling,
at increasing rates, and for skills. The size of firms has an effect on wages as workers of
larger firms earn higher wages.
With respect to the effects of the variables that account for mobility, we see that
workers that move out of a closing establishment receive lower wages. Moving into a
new establishment seems to have a positive effect on wages.
With respect to the variables that account for the effects of the different types of
mobility on wages we found that industry mobility (mobsec) has a negative effect on
14
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