Data Sources and Quality
Improvements for Statistics on
Agricultural Household Income
in 27 EU Countries
Berkeley Hill
Emeritus Professor of Policy Analysis
University of London (Imperial College)
Introduction



Rising awareness of multiple incomes
1985 Commission ‘Green Paper’ + Annex
Eurostat IAHS statistics 1988-2002






Based in system of national accounts
Harmonised methodology (Definitions)
Sector-level results
Declining EU and national priority
Some political and institutional hostility
Some MS used micro data as source of results
IAHS hiatus of early 2000s




IAHS results increasingly out-of-date
Importance of distributional information
EU enlargement – new types of agricultural
household and business
Court of Auditors 2003 review of IAHS



Met central objective of CAP but
Statistics of poor quality (NL evidence)
Recommended a feasibility study of a uniform
micro-approach across all MS – endorsed by
Council
Interim research work



Gradual accumulation of information on data
sources – Eurostat, OECD etc
ISTAT 2002 TAPAS Initiative reviewed
income data sources and alternative
calculations in Italy
Statistics Sweden 2006 study on feasibility of
adding questions to the FADN farm form

No significant technical barriers
The 2007 feasibility study - AgraCEAS

Template of uniform key definitions (income,
household etc.) developed from






2005 UNECE Handbook
Survey of users
Visits to MS and surveys to find data sources
Feasibility of using template assessed
Method of filling data gaps proposed and
costed
Recommendation made to Eurostat
Key definitions


Household – single budget unit
Household classification



‘narrow’ – agriculture main income source of
reference person
‘broad’ – range of possibilities (any farm income,
holding characteristics - FSS, SFP)
Net disposable income – as in Handbook

Detailed breakdown Imputed items shown
separately
Inventory of data sources (25 MS)

Farm accounts surveys



EU-SILC




Household income not part of EU-FADN
Only some MS collect household data
Generally few agricultural cases
Income data often of poor quality
Household budget surveys (as above)
Taxation records and registers


In many MS farmers not taxed on actual income
Tax income definitions pose problems / disclosure
Example – Austria




Farm accounts - sample of 2,500 holdings
which also covers household income
EU-SILC - 271 cases in 2005.
HBS - carried out once every 5 years.
Tax records - For a large proportion of
farmers tax payment is not based on
accounting income (farmers pay 'lump sum'
taxes)
Example – Poland




Farm accounts - data on five types of nonagricultural income collected from about
10,000 farmers in 2005.
EU-SILC - agricultural cases not known; they
are combined with other self-employed.
HBS - Some 2,000 agricultural households in
2005; problems with income data quality.
Tax records - assessment (mainly) uses a
standard rate based on land and forest area,
land quality and distance to market.
Example - Spain




Farm accounts survey – no household data
EU-SILC - only 253 agricultural cases in 2004
(similar number in 2005).
HBS - only about 120 agricultural cases, but
there are difficulties with incomes from selfemployment.
Tax data - some farmers do not pay tax
based on actual incomes, and incomes may
be estimated.
Example - Luxembourg





Farm accounts survey - questions covering
household income were used for 1989 only.
EU-SILC - only 78 agricultural cases in 2004 .
HBS - few agricultural cases.
Tax records - most farmer incomes are not
on an accounts basis.
Other - There is a poverty survey of
households (CEPS).
Feasibility testing of definitions

Each aspect of the template (household,
agric household narrow and broad, income
definition, comparison with others) was
assessed as:




Currently in use
Not in use but technically possible
Requires development of existing data sources
Requires a new data source
Example – ‘narrow’ agric household
based on the reference person




Currently used – 3 MS
Technically possible – 16 MS
Required data source development – 4 MS
Requires new data source – 3 MS
Example – Can comparisons be drawn
with other socio-professional groups?




Currently made – 7 MS
Technically possible – 10 MS
Requires data source development – 4 MS
Requires new data source – 5 MS
Example – use of Net Disposable
Income?


With existing data source – 19 MS
New data source needed – 5 MS



UK – main data source does not collect tax paid
Germany – questionable reliability of existing
sources
(others were Slovakia, Hungary and Luxembourg)
Filling the data gaps
MS fall into three broad groups
 Special survey needed to cover both ‘narrow’
and ‘broad’ definitions of an agricultural
household – hybrid of FADN and EU-SILC
questions, collected by EU-SILC method
 ‘Narrow’ covered, but special survey for
‘broad’, typically below FADN size threshold
 No new data collection needed – only
extraction
Costing – MS costed individually





Transparent calculations allow alternative
figures to be used
Survey costs based on existing national EUSILC data costs, and commercial rates
Case numbers
‘narrow’ – as for existing FADN samples
‘broad’ – below FADN threshold same
sample rate as above, and at a 1% rate
Examples



Denmark – data extracted from existing
registers (no additional survey)
Germany – additional special period survey
for both the ‘narrow’ and ‘broad’ definitions
Poland – use of existing farm accounts
survey for ‘narrow; additional survey below
FADN threshold to cover the ‘broad’. Other
work needed to faciliate comparisons with
other spg.
Results

Aggregate cost of collecting data to enable
comparable and robust statistics (one-off
surveys)




€11.5 million survey costs + €1 central costs for
the ‘narrow’ definition of an agricultural household
Additional costs of extending coverage to the
‘broad definition’ €9.1 – 13.3 (totalling €22-26m)
In comparison EU-SILC costs c.€27m p.a.
If the cost led to a 1% efficiency gain in Pillar
1 spending, this would be 19 times greater
In conclusion





Good quality data are essential to quality
A useful inventory of data sources on
incomes of farm households is now to hand
A technical assessment of the feasibility of
producing robust EU-wide IAHS statistics has
been made and costed.
Eurostat has not taken up the proposed
actions; some MS do not seem to be keen
The Court of Auditors has expressed interest
in why progress has not been made