Perspektiv på välfärden 2004 (pdf) - Statistiska centralbyrån

table 4, (denoted with #) and reveal that students,
quite expectedly, do not tend to be employed. It is
also the case that the employed are less prone to
have an unemployment history and that young
people with higher education tend to have children
to a lesser extent. Finally it is revealed that
having children and nest leaving are positively
correlated. Let us now move on to the core of the
analysis.0
Latent variables
In table 5, the relationships between all the manifest
variables related to the two first blocks of
Figure 1 and the latent variables, i.e. income intercept,
deprivation intercept, income slope and
deprivation slope, are displayed. The parameters
represent first the direct standardized regression,
and when appropriate, the correlation coefficient.
However, the direct effects only tell part of the
story, as a substantial component of the impact in
a complex causal model is indirect. Looking only
at the direct effects will therefore erroneously lead
us to believe that a number of variables are unimportant.
Therefore the total effect (indirect + direct)
is also displayed both as standardized and
unstandardized coefficients.
Income intercept
As expected, the income intercept increases with
age. The total effect is, due to an indirect impact,
somewhat higher than the direct effect and the
unstandardized coefficient reveals that income
increases by approximately eight and a half thousand
SEK every year. A more interesting result is
the difference between women and men. There is
a clear gender gap already at this early stage of
the life course, and the total effect shows an annual
income difference of almost 16,000 SEK.
The small indirect effect of gender is attributable
to women’s exposure to unemployment and early
parenthood. The direct impact of class is relatively
small, but reveals that white-collar origin
(middle and high) is associated with a low income
intercept. The total effects are considerably larger
and amplify the differences between those with a
blue-collar origin and those with a white-collar
background. The indirect effect is mainly caused
by the higher probability among those with whitecollar
origin of studying and, hence, of not being
employed. Educational attainment does not affect
income intercept. Being a student does, unsurprisingly,
have a negative effect on income intercept.
The same holds for unemployment, especially
long-term unemployment and parenthood, while
employment naturally increases the income.
Deprivation intercept
In concordance with the result for income intercept,
the intercept for deprivation decreases with
Youth
age. Gender does not directly affect deprivation
intercept, but there is a substantial indirect effect
showing that women are more prone to report
economic difficulties. The indirect effect is mediated
by young women’s higher probability of
leaving the nest at early age, being a parent, being
unemployed and receiving social assistance.
Again it is revealed that the direct impact of class
is minor, but that the indirect effect is substantial,
as class affects almost every one of the manifest
variables that are supposed to be intermediate to
class and the latent variables. The important aspect
to notice is that those with a middle range or
higher white-collar origin not only have the lowest
income intercept, they also have the lowest
deprivation intercept. Hence, their income situation
does not correspond with their experience of
economic difficulties.
The educational effect is somewhat harder to
understand. The level of education, after primary
school, does not seem to be particularly important
even though there are some differences. The main
gap is between those who only have a primary
school education and the rest. A speculative interpretation
would be to suggest that those who only
have a primary school education are a selected
group and that the mechanism leading to early
drop out from the educational system is also connected
to the probability of ending up in an economically
difficult situation.
The fact that st00udents score relatively low on
deprivation intercept should be interpreted in the
light of the negative effect of the interaction term
between age and being a student. The interaction
shows that the longer a person stays in the educational
system, the greater her/his economic problems.
Hence, there is a price to be paid for investment
in human capital. Unemployment, nest
leaving, parenthood and social assistance are all
related to a high deprivation intercept. The last of
these, social assistance, is worth an extra comment.
It is not assumed that social assistance per
se leads to economic difficulties, if anything the
direction of causation should be the opposite.
However, receiving assistance can also be interpreted
as an indicator of an overall difficult situation,
and from that 0perspective is it reasonable to
construe assistance as an indicator of economic
difficulties. It can finally be noted that income
intercept correlates with deprivation intercept in
the expected way, i.e., the higher the income, the
less serious one's problems.
Income slope
The age effect is, as expected, minor and only
indirect. The effect of gender on income slope is
great, direct and important. Compared to men,
women’s income development not only begins at
a lower level (income intercept), it also grows
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