Environmental Engineering Reference
In-Depth Information
Table 8.6
Summary: support for the tested hypotheses
Hypothesis (1)
Hypothesis (2)
Hypothesis (3)
1990
2003
1990
2003
1990
2003
Germany
Ye s
Ye s
Ye s
Ye s
Ye s
No
Greece
No
No
Ye s
Ye s
Ye s
Ye s
Spain
Ye s
Ye s
No
Ye s
Ye s
Ye s
France
No
No
No
Ye s
Ye s
Ye s
Italy
Ye s
Ye s
Ye s
Ye s
Ye s
Ye s
Portugal
Ye s
Ye s
Ye s
Ye s
Ye s
Ye s
Finland
-
-
-
No
-
No
Sweden
-
No
-
No
-
No
UK
Ye s
Ye s
Ye s
Ye s
Ye s
Ye s
(2) and (3) were widely supported, whereas hypothesis (1) was only accepted in
five countries. Finland and Sweden are the two countries where all hypotheses were
rejected. So it seems that there is a tendency that two of our examined regional
characteristics, i.e. the share of agriculture in total employment and the presence of
LFA, affect farming intensity, whereas farming intensity is less affected by an urban or
rural territorial context. It is, however, not unlikely that our hypothesis on the impact
of the degree of rurality on farming intensity shows a better score if a lower level of
regional aggregation would have been considered. The studied regional characteristics
do not affect farming intensity in Finland and Sweden. Obviously, farming intensity
in the Nordic agriculture in these countries is more dependent on other factors,
likely related to a short growing season due to climatological conditions.
Regional Characteristics Included in Integrated Assessments
Our findings suggests that regional characteristics matter in the economic and
environmental performance of farms in Western Europe. In the scope of integrated
assessments of farms' performance and agricultural policy, it could be recommended
to include regional characteristics as well in such assessments. A main issue in such
an inclusion refers to the regional level for measuring regional characteristics.
On the whole, there is not one regional level that fits all purposes. On the contrary,
per single indicator a suitable regional level should be strived at by looking for
territorial units that are rather homogeneous for the specific indicator at stake.
Expert knowledge could be of help in determining a suitable regional level for the
measurement of regional indicators. Nevertheless, in reality often a trade-off has to
be made between what is a theoretically suitable regional level and the regional
level at which data is available. In this chapter, for example, we used the FADN
regions as data on farming intensity were available at this level. However, we
argued that for the analysis of the studied regional characteristics a lower level of
regional aggregation would be more appropriate. Future research on methods for up
