Page 191 - Invited Paper Session (IPS) - Volume 2

IPS 208 Johan S. et al.
in cases S1a, S2 and S3, where non-sampling errors have a big impact on
overall data quality. After the data collections are carried out, multiple
indicators can be calculated for each source of non-sampling errors associated
with the different steps in a statistical process, while a unique synthetic
indicator, such as the mean square error, is not computable. Thus, synthetic
quality indicators cannot be set in a regulation such as the IFS. However,
national authorities are required to describe in quality reports a set of
indicators that are both quantitative and qualitative. Quality assessment for
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multisource data is under continuous development in ESSnet projects such as
the ESSnet on Quality of Multisource Statistics.
The move towards source agnosticism improves subsidiarity, enabling EU
member states to choose the most cost-effective sources for themselves
according to their national conditions and needs. It also increases flexibility,
thanks to greater openness to future data sources such as precision farming
data.
iii. Reduced number of variable breakdowns
The 2010 agricultural census covered a total of 273 variables, collected
from all EU farms. In the 2020 census, the core will comprise 184 variables and
will be supplemented by 30 variables in the module ‘Labour force and other
gainful activities’, 15 in the module ‘Rural development’, and 70 in the module
‘Animal housing and manure management’, totalling 299. These are maximum
numbers, as member states may transmit fewer variables if particular items do
not exist or are not significant in the country concerned.
The above information refers to the absolute numbers of variables in
2020. Burden reduction should be assessed throughout 2020-2026, as the
data for the modules will be collected less frequently in the new decade (R10).
Moreover, much burden reduction will be achieved in 2023 and 2026 by taking
the previous regulation on permanent crops into account as well: in 2023, the
IFS will collect a maximum of 470 variables, including the ‘Orchard’ module,
whose predecessor regulation contains over 650 variables, while in 2026 a
maximum of 350 variables are allowed, including the ‘Vineyard’ module,
whose predecessor regulation contains almost 900 variables (R11). In
addition, the core and module system enables that fewer farms will have to
provide data on all variables in a census or sample year. This reduces the
burden on individual farms (R12).
Furthermore, the same list of variables and definitions, as well as common
quality standards and data transmission deadlines, will be used in all EU
member states, increasing interoperability and reusability so as to reduce the
costs and burdens of data collection (R13).

An ESSnet project is a network of several ESS organisations which aims to provide results that
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will be beneficial to the whole ESS.

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