Appendix A.2: Wagea Dispersion and Experience - March CPS 1993 and 1996
In this appendix I analyze whether the lack of control for managers and production workers’ average experience
modifies the cross-establishment variations in wage differentials. To do so, I used the March CPS for the year
1993 and 1996 in which there is information on workers’ education and age to construct potential experience and
information on the company size. To characterize variations in managers-production workers wage differentials,
I used information on firm size and industry of the workers. In the March CPS, firm size is a discrete variable
that takes 6 values from firms with less than 10 employees to firms with more than 1000 employees. I classified
industries according to the same method as in the NES, with 20 different industries. I next selected individuals
reporting managerial occupations and defined as production or front-line workers anyone reporting a profession
directly linked to the firm’s production. I estimated the wage differentials by regressing the log of hourly wages
on a dummy for managerial occupations. The cross-establishment variations in wage differentials are defined by
interacting the manager dummy to dummies defining the interaction of size and industry.
The table below presents the results of the estimations. Four series of regressions have been performed: an
estimation of the raw wage differentials (column (1)), a regression with the inclusion of workers controls such
as gender, race and union status (column (2)), a regression where education is added as an additional control
(column (3)), a regression where experience and experience squared are added as additional controls (column(4)).
|
Manager/Prod. Wage Diff.als |
(1) No Controls |
(2) + Fem, Mino, Union |
(3) (2) + Educ. |
(4) (2) + Exp. |
|
1993 | ||||
|
Manuf*Large |
0.709 |
0.773 |
0.635 |
0.718 |
|
(0.046) |
(0.045) |
(0.043) |
(0.043) | |
|
Manuf*Medium |
0.811 |
0.849 |
0.670 |
0.766 |
|
(0.081) |
(0.077) |
(0.074) |
(0.075) | |
|
Manuf*Small |
0.760 |
0.760 |
0.600 |
0.693 |
|
(0.070) |
(0.067) |
(0.064) |
(0.064) | |
|
Non Manuf*Large |
0.377 |
0.419 |
0.349 |
0.391 |
|
(0.033) |
(0.032) |
(0.030) |
(0.030) | |
|
Non Manuf*Medium |
0.411 |
0.415 |
0.347 |
0.377 |
|
(0.053) |
(0.051) |
(0.049) |
(0.049) | |
|
Non Manuf*Small |
0.399 |
0.456 |
0.365 |
0.403 |
|
F-Testb (p-value) |
(0.034) |
(0.033) |
(0.032) |
(0.032) |
|
128.6 (0.000) |
157.2 (0.000) |
107.2 (0.000) |
139.1 (0.000) | |
|
1996 | ||||
|
Manuf*Large |
0.729 |
0.800 |
0.640 |
0.737 |
|
(0.055) |
(0.054) |
(0.052) |
(0.052) | |
|
Manuf*Medium |
0.692 |
0.720 |
0.567 |
0.699 |
|
(0.093) |
(0.090) |
(0.086) |
(0.086) | |
|
Manuf*Small |
0.725 |
0.796 |
0.629 |
0.748 |
|
(0.089) |
(0.085) |
(0.082) |
(0.082) | |
|
Non Manuf*Large |
0.480 |
0.512 |
0.425 |
0.477 |
|
(0.037) |
(0.036) |
(0.035) |
(0.035) | |
|
Non Manuf*Medium |
0.508 |
0.519 |
0.413 |
0.509 |
|
(0.064) |
(0.061) |
(0.059) |
(0.059) | |
|
Non Manuf*Small |
0.410 |
0.437 |
0.335 |
0.399 |
|
F-Testb (-p-value) |
(0.041) |
(0.040) |
(0.039) |
(0.038) |
|
102.0 (0.000) |
124.3 (0.000) |
80.2 (0.000) |
115.2 (0.000) | |
|
Detailed Variables Industry*size | ||||
|
1993 F-Testb (p-value) 1996 F-Testb (p-value) |
16.4 (0.000) 12.5 (0.000) |
15.7 (0.000) 11.9 (0.000) |
11.2 (0.000) 8.3 (0.000) |
14.5 (0.000) 11.3 (0.000) |
32
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