Agricultural Economics in the Context of Portuguese Rural Development - The Agricultural Economics of the 21st Century - page 123

4 Data Description

All the statistical information was obtained via the Statistics of Portugal (INE 2014 )
and is relative to the variables described in the previous section.
The distribution of the values associated with each variable, across Portuguese
municipalities, is shown in the following Figs. 9.1 (relative to the output of
agriculture and other related sectors) and 9.2 (for the employment and the number
of multifunctional farms).
From Fig. 9.1 it is possible to observe that the large part of economic activity,
considered here to be more or less related to the farming sector, is concentrated
within the Portuguese municipalities of the coastal north, center, and around
Lisbon, with some exceptions for the coastal south (Alentejo) in the case of the
agricultural output and for the textile industry that is concentrated mainly around
the Oporto region. There are some exceptions, also, for the accommodation,
restaurants, and consultant services in the municipalities of the extreme south of
Portugal (Algarve).
Figure 9.2 shows that the number of farms with multifunctional activities does
not follow the pattern referred to in Fig. 9.1 . This context is expected considering
that the alternative activities in the farms appear as a complement, plausibly in areas
where agriculture has less productivity.
For example, the greater number of farms with forestry are situated in the
municipalities of the interior of Portugal, namely in the central interior. The
municipalities with a greater number of farms with services provision are located
in the north (inland and coastal). Renewable energy production is verified, namely,
in the regions near Lisbon and in the south interior.
Employment is greater in regions near Oporto, Lisbon, and in the coastal south
(Alentejo). In this case, this pattern is more or less similar to that of the evolution of
the agricultural output across the Portuguese municipalities.
The greatest number of farms with mixed production (crops and livestock) and
with income coming from outside sources are situated in the interior north of
Portugal, namely around the municipality of Bragan¸a. These zones are indeed a
part of Portugal with many difficulties, but with many dynamics.
Figures 9.3 and 9.4 are relative to the global spatial autocorrelation measured
through Moran's I statistics. Moran's I can have values from

1 (perfect negative

spatial autocorrelation) to 1 (perfect positive autocorrelation).
The negative global spatial autocorrelation means, for a variable, that the values
in a municipality negatively influence the values of neighboring municipalities (the
number of neighbors dependent on the distance or contiguity matrix considered), in
the Portuguese context, for the case analyzed here, and vice versa.
These figures were obtained with GeoDa software ( 2014 ), considering a queen
contiguity matrix for one (showing stronger global spatial autocorrelation) and five
(almost without global spatial autocorrelation). When it is intended to analyze, for a
certain variable, the relationships between closer spatial unities (municipalities,
regions, countries, etc.) the considering of distance or contiguity matrix is crucial.