Chapter 2

Table 2 – Coefficients of regression on panel data
Italy 1997-2003
Variables Coefficient P>|t|
GDP per capita 0,004 0,068
% population over 65 18,157 0,013
Cost average prescription 3,531 0,001
Prescription per physician 0,011 0,008
Ticket 0,885 0,165
Constant -293,758 0,002
Table 3 – Regression coefficients on panel data
for the north 1997-2003
Variable Coefficient P>|t|
GDP per capita 0,008 0,009
% population over 65 13,638 0,000
Cost average prescription 4,125 0,004
Prescription per physician 0,005 0,428
Ticket0,849 0,257
Constant -295,758 0,000
The model to use for the centre-south is also random effects one, that explains 82,59%
of the overall variability; also in this case both the temporal effect and the territorial ones
are very well explained by the model: the R2 within amounts to 88,15%, while the R2 between
is equal to 66,2%.
The variables which have proven to be significant for the centre-south are: the GDP, the
average cost of the prescriptions, but also the number of prescriptions by physician and
the ticket, the latter surprisingly having a positive sign.
As was expected, total pharmaceutical expenditures seem to be influenced by economic
and demographic factors, but also by factors referable to ineffectiveness.
Regions of the north and Regions of the centre-south substantially represent a homogeneous
whole, as demonstrated by the choice of the random effect model and by the between
variability explained; moreover, a meaningful non-homogeneity is underlined
among the divisions.
The old age effect does not seem to be relevant in the centre-south, whereas the number
of prescriptions per physician is so meaningful that a prescriptive proxy of inefficiency
can be considered.
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CEIS Health Report 2006