Table 13
Wage gains for workers that move out of a closed establishment
Job mobility |
Total | |||||||
_______No_______ |
Yes | |||||||
Spatial mobility |
Spatial mobility | |||||||
No |
Yes |
No |
Yes | |||||
Move out of a |
No Yes |
Wage |
(ʌvg) |
0.06 |
0.06 |
0.09 |
0.10 |
0,06 |
Hourly wage |
(Avg) |
0.09 |
0.09 |
0.12 |
0.12 |
0,09 | ||
Wage |
(Avg) |
0.07 |
0.06 |
0.07 |
0.12 |
0,07 | ||
Hourly wage |
(Avg) |
0.09 |
0.08 |
0.11 |
0.15 |
0,10 | ||
Total |
Wage |
(Avg) |
0,06 |
0.06 |
0.08 |
0.10 |
0.06 | |
Hourly wage |
(Avg) |
0,09 |
0.09 |
0.12 |
0.13 |
0.09 |
Source: LMEEM(2000)
When a worker move out of a closed establishment and change employer it has lower
wage gains, but if change location it receives more.
3.3.Multivariate analysis of wage mobility, job mobility and spatial
mobility in the Portuguese economy
In the previous section we analysed patterns of mobility. It is also interesting to measure
the joint effect of all variable on wages, which can be performed by estimating a wage
equation..
The model estimated is derived from a Mincer equation in which two dependent
variables are considered: the wage and the hourly wage both for 1998 and in logarithms.
The model estimated is:
y =X 'β+Z 'σ+ α.mobemp + θ.mobsec +λ1.mob1+λ2.mob2+λ3mob3 Eq.4.1
where y is the logarithm of wage in 1998, X the matrix of individual worker
characteristics (including gender, schooling, tenure, potential experience), Z the matrix
of workplace characteristics (including location, industry, and size). Mobemp stands for
job mobility, mobsec for industry mobility, and mob1, mob2, and mob3 account for the
three levels of spatial mobility.
13