The Palestinian Economy. Theoretical and Practical Challenges

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Abu-Zaineh – Mataria
in behaviour across SES groups (called I B ) – i.e., the variation in the parameter estimates
across income groups. The findings on the heterogeneity in behaviour for a given need are
also decomposed by parts of the demand process; i.e. for the probability of participation
(called I PP ) and the conditional number of usage (called I CC ).
As shown in Table 4.1, with the exception of primary-level, the estimated values of
the concentration index (C y ) of the overall income related-inequality in the utilisation of
each level of health care in the two regions are significantly positive [C y > 0 at p < 0.05].
This indicates that the utilisation of primary-care is generally concentrated among the
poor [C y = –0.0527 and –0.0415 for the WB and GS, respectively], whereas the utilisation
of secondary-level – both outpatient and inpatient services – and tertiary-level are
concentrated amongst the better-off, with the C y index being more pro-rich in the case of
secondary-inpatient [C y = 0.0617 and 0.0313 for the WB and GS, respectively] compared
to secondary-outpatient case [C y = 0.0511 and 0.0247 for the WB and GS respectively],
while they appear to be even a lot more pronounced in the case of tertiary-care [C y =
0.1311 and 0.1204] compared with both types of secondary-care.
The estimated values of Need index (the I N ) – i.e., the aggregation or the combined
effects of all morbidity and demographic variables included in the model – emerge, on the
other hand, invariably significantly negative [I N < 0 at p < 0.05] for all levels of care. This
clearly means that need for health care are always concentrated in the lowest-part of
income distribution, and that the poor are, in general, in a poorer health status than the
rich. Indeed, the (partial) contribution of heterogeneity in need (by income) to the
measured degree of inequality in utilisation is captured, as in the previous research (e.g.,
van Doorslaer, Koolman et al. 2004), by adjusting the distribution of utilisation for a set
of morbidity and demographic variables (age and sex).
However, as shown in Table 4.2, the values of Need Index (I N ) not due to
demographics –i.e., the degree of “need-expected” inequality estimated by allowing for
morbidity differences, while keeping the distribution standardised for demographic
differences– account for the bulk of the I N value [circa 90% of the I N index value]. The
partial contributions of age-sex differences to the I N , although push the distribution of
need further in a pro-poor direction, remain comparatively small and account for only
10% of the I N index value. This indicates that, although demographic differences play
some role in shaping need for health care, the overall value of our I N is mainly accounted
for by the distribution of morbidity across income, which is significantly more prevalent
amongst the poor.