experiencing early retirement, as these may help to change the probability of becoming
poor given that different industries and civil servants have different social protection
regimes (see section 2).
For gender a dummy signalling male is included. For activity status the year previous to
retirement, 5 dummies signalling being employed, part time employed, self employed, in
unpaid activity or unemployed are considered. For industry we consider two dummies
signalling working in manufacturing and in services. We consider four dummies to classify
the type of family, considering the situations of retired alone with children, retired couple
with no children, retired couple with children and others. We included regional dummies
and dummies for being a civil servant and retiring before the legal age.
The reference individual is a female, not a civil servant, not early retired, living in north
region, working in agriculture, that lives alone, and who is a tenant in her home.
Results of the estimated models are presented in Table 6-1: . This includes also some
diagnostic tests on the overall quality of estimation.
Employment status, industry, region, type of family and being civil servant are the
determinants that seem to be important in explaining entry into poverty when retirement
occurs.
Regarding employment status, being self employed, having unpaid activity and, less
significantly, unemployed increases the probability of becoming poor. This is different
from what Bardasi, Jenkins, and Rigg (2002) found. In their paper the self-employed are
not significantly more prone to become poor on retirement than inactive people, and if
anything the effect would be the opposite, since the corresponding parameter is negative.
Working in Manufacturing and in the Services industries seems to decrease the probability
of becoming poor in a significant way, comparing to working in Agriculture.
By region, living in Alentejo increases the probability of becoming poor whereas living in
Lisbon area reduces this probability.
The type of family seems also to play a role, being retired couples with children less prone
to become poor.
16
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