Commission staff working document - Accompanying document to the communication from the Commission to the European Parliament, the Council and the European Court of Auditors - Towards a common understanding of the concept of tolerable risk of error {COM(2008) 866 final}
Date: 2008-12-16
Institutions: European Commission
Subjects: EU expenditure, European Court of Auditors, audit, budgetary control, cost analysis, financial management, general budget (EU), impact study

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EN 

EN 

 
 
COMMISSION OF THE EUROPEAN COMMUNITIES 

Brussels, 16.12.2008 
SEC(2008) 3054 

COMMISSION STAFF WORKING DOCUMENT 

Accompanying document to the 

COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN 
PARLIAMENT, THE COUNCIL AND THE EUROPEAN COURT OF AUDITORS 

Towards a common understanding of the concept of tolerable risk of error 

{COM(2008) 866 final} 

EN 

EN 

 
 
 
  
 
 
 
 
 
COMMISSION STAFF WORKING DOCUMENT 

Towards a common understanding of the concept of tolerable risk of error 

1. SCOPE ............................................................................................................................................................... 3 

2. APPROACH AND ASSUMPTIONS............................................................................................................... 3 

2.1 THE LINK BETWEEN RESIDUAL RISK AND COST OF CONTROLS............................................... 3 

2.2 MODELLING THE RELATIONSHIP BETWEEN THE COST AND THE RATE OF 
UNDETECTED ERRORS ................................................................................................................................... 4 

2.2.1 Linear model......................................................................................................................................... 4 
2.2.2 Extending the linear model................................................................................................................... 5 
2.2.3 Testing the model.................................................................................................................................. 7 

2.3 GENERAL ASSUMPTIONS AND CALCULATION METHODS............................................................ 8 

2.3.1 General assumptions: ........................................................................................................................... 8 
2.3.2 Calculations and methods..................................................................................................................... 9 

2.4 ILLUSTRATIVE CASES............................................................................................................................. 11 

2.4.1 European Regional Development Fund (ERDF)................................................................................ 11 
2.4.2 European Agricultural Fund for Rural Development (EAFRD)......................................................... 15 

3. THE COST OF CONTROLS EXERCISE ................................................................................................... 17 

3.1 METHODOLOGY........................................................................................................................................ 17 

3.2 RESULTS FOR THE COMMISSION SERVICES................................................................................... 18 

3.2.1 European Agricultural Guidance and Guarantee Fund (EAGGF) .................................................... 18 
3.2.2 European Regional Development Fund (ERDF)................................................................................ 19 
3.2.3 DG Employment and Social Affairs.................................................................................................... 20 
3.2.4 DG EuropeAid .................................................................................................................................... 21 
3.2.5 DG Environment................................................................................................................................. 21 
3.2.6 DG Research ...................................................................................................................................... 22 
3.2.7 DG Information Society...................................................................................................................... 22 
3.2.8 Other Services .................................................................................................................................... 23 

GLOSSARY: ....................................................................................................................................................... 24 

2

 
 
 
1.  SCOPE 

The aim of this document is to present the technical elements supporting the conclusions and 
the  analysis  set  out  in  the  accompanying  Communication  COM(2008)  866.  The  document 
presents  the  approaches  taken  in  respect  of  selected  policies  of  the  Commission  for  the 
illustrative examples in the main communication, together with a first estimation of the costs 
of controls for selected policies (results of Action 10 of the Action Plan towards an Integrated 
Internal Control Framework) in both direct centralised mode and shared management mode.  

2.  APPROACH AND ASSUMPTIONS 

2.1. The link between residual risk and cost of controls 

Controls  cost  money  and  a  cost-effective  balance  has  to  be  sought  between  the  number  of 
controls and the amounts of error detected and recovered. The more controls that are carried 
out, the lower the rate of undetected error will be. This intuitive relationship between the level 
of  errors  undetected  by  Commission  and  Member  States'  controls  and  cost  of  controls  is 
shown in the following chart: 

Rate of errors undetected by 

Commission and Member States 

Graph 1 

Zone 1 

Zone 2 

      DAS rate  

Current 
(improved) 
error rate 

Zone 3

Zone 4

Zone 5 

Cost of 
controls

Current costs 

Increase of the rate of on-the-spot controls

 The following components of the curve can be distinguished, each with its own elasticity: 

• 

Zone 1: In the absence of any control: a theoretical level of "errors" would remain 
undetected,  the  nature  and  value  of  which  depend  on  the  complexity  of  the 
regulatory framework, the propensity to error, the inherent risk etc. 

3

 
 
 
 
 
 
 
 
 
 
 
 
 
• 

• 

• 

• 

Zone  2:  (Quasi)  Fixed  costs:  or  the  cost  of  setting  up  the  control  system  before 
controls are carried out (in terms of strategy chosen, risk analysis, definition of tools 
and procedures).  

Zone  3:  Reverse  economies  of  scale:  gradual  reduction  of  the  error  rate  while 
increasing  the  costs  of  control  (due  to  great  level  of  elasticity  at  this  point  of  the 
curve); at a critical threshold (which we call the "tolerable risk point"), the marginal 
benefit  of  an  additional  control  equals  the  marginal  cost  of  an  additional  control. 
Beyond this point the marginal cost of a control exceeds the marginal benefit to be 
expected (in terms of a reduction in the error rate or the amount of error likely to be 
detected and recovered).  

Zone  4:  “One-off”  errors:  once  the  most  important  and/or  systemic  errors  have 
been eliminated, only “one-off” errors will exist. Because of their nature, such errors 
require significant resources in order to be detected. 

Zone 5: Tangent to the 0% error rate: the last remaining errors will require more 
resources to detect them due to the low level of elasticity at this point of the curve 
(ultimately all activities will need to be checked completely to identify these errors). 

While this is a sound theoretical presentation of the issues, it would be very difficult to draw 
the “real” curve reflecting the reality of each policy area. In order to identify the coordinates 
of  the  points  of  the  curve  extensive  data  would  be  needed  to  model  the  impact  of  different 
levels of control - something that is not feasible in practice. It is for example not possible to 
model the impact of the removal of all controls to define a rate of undetected errors in zone 1. 

The process of estimating accurately the cost of control and obtaining reliable data to estimate 
potential  error  rates  would  also  imply  an  extensive  data  collection  exercise,  in  particular  at 
Member State and implementing body level since detailed statistics are currently not available 
(for example the number and value of ongoing projects). However, on the basis of available 
2006  data  complemented  by  data  collected  by  the  Commission  on  the  costs  of  control,  this 
document sets out some illustrative examples of tolerable risk using a variety of assumptions 
which are set out in section 2.3 below. 

2.2. Modelling the relationship between the cost and the rate of undetected errors 

2.2.1.  Linear model 

The basis for the illustrative examples of tolerable risk presented in this document is a simple 
linear model in which the rate of undetected error decreases as more controls are carried out. 
The model presents how one variable (error rate) is related to other variables (principally the 
cost of control and the numbers of projects/beneficiaries to be controlled).  

The model presents the situation where one Y variable (the error rate) is related by a straight 
line to just one X variable (cost of controls). A trend line is then drawn between two known 
points using a Cartesian equation of the type Y = cX + b where 'c' is the (negative) slope and 
'b' the intercept resulting in a distribution (or population) of Y values, appropriately called the 
probability distribution of Y1 given X1, and similarly a distribution of Y2 at X2, and so forth. 
The  population  parameters  b  and  c  specify  the  straight  line,  known  as  the  true  population 
regression  line  and  are  estimated  from  the  available  information  on  control  costs  and  error 

4

 
 
 
 
 
 
 
 
 
rates. Once the line is drawn between two given points the whole set of Y populations can be 
inferred and the level of Y (error) can be predicted at a given level of X (control costs).  
Technically, only 2 coordinates are necessary to prepare the model:  

• 

• 

Point A: the current error rate at the current cost of control  

Point B: the point where all the open projects are audited on-the-spot (if we assume that 
the Y-axis (error rate) is zero once all projects are audited) –  that is that controls will 
detect and correct all errors. 

The line is the following:  

Rate of undetected errors 
(Y) 

Graph 2 

  (A) 

Current rate  

0% 

Current cost 
of controls 

2.2.2.  Extending the linear model 

 (B) 

Cost of 
control for all 
open projects 

Cost of controls 
(X) 

Of  all  the  regression  principles,  the  straight  line  is  the  most  simple.  It  leads  to  a  relatively 
simple formula for calculating the intercept and the slope of the line and is easy to understand. 
However, even if two points can be located, as proposed by the model, defining the shape of 
the connecting line/curve that depicts the relationship between the "undetected error rate" and 
the "cost of controls" is the key issue (essentially defining the slope 'c'). In practice one can 
connect  two  points  with  an  infinite  number  of  different  curves.  Therefore  it  is  important  to 
recognise that a mathematical model is a simplification of a complex reality and can only be 
of  useful  approximation.  In  particular  we  cannot  take  seriously  the  assumption  that  the 
population means are strung out exactly in a straight line (see assumptions in 2.3 below). If 
we  consider  the  intuitive  relationship  between  the  level  of  errors  undetected  by  the  internal 
control  system and the  costs of control, it is likely that the level  of errors decreases rapidly 
initially  (as  the  “easiest”  errors  are  detected)  but  then  becomes  more  flat  eventually  as  the 
"tolerable  risk  point"  is  approached  and  the marginal  cost  of  control  becomes  exceptionally 
high compared to the marginal benefits (as illustrated by graph 1 above). In such cases a non-
linear model is likely to be more representative of the population.  

5

 
 
 
 
 
 
 
 
Since  the  fundamental  problem  of  the  model  comes  down  to  defining  slope  'c',  the  linear 
model  was  extended  by  adding  a  trend  line  to  the  straight  line  to  reflect  a  line  sloping 
downward,  representing  decreased  error  rates  over  increasing  costs  of  control.  Since  the 
population  used  for  this  exercise  does  not  meet  the  assumption  of  homogeneity  (because 
different  projects  present  different  types  and  levels  of  risk),  a  "logarithmic  trend  line"  is 
appropriate, as a logarithmic scale shows variable growth changes percentage-wise (whereas a 
linear  trend  line  is  used  for  constant  rates).  Therefore  a  logarithmic  trend  line is  a  best-fit 
curved line that is most appropriate when the rate of change in the data increases or decreases 
quickly and then levels out. 

The logarithmic equation for calculating trend lines calculates the "best line" through points 
by  using  an  equation  of  the  type  y  =  c  ln  x  +  b  where  c  and  b  are  constants,  and  ln  is  the 
natural logarithm1 function.  

A graphic representation of this trend line is shown in graph 3: 

Graph 3 

Rate of undetected 
errors (Y) 

Current rate 

  (A) 

Rate at 
Tolerable 
Risk Point 

Tolerable Risk 
Point 

0% 

Current 
cost of 
control 

Cost of 
control at 
Tolerable 
Risk Point 

  (B) 

Cost of 
control for 
all open 
projects 

Cost of 
control (X) 

Once the curve is drawn, the level of Y (error) can be predicted at a given level of X (control 
costs). This means the coordinates of an optimal level of control or the cost of control for a 
given  error  rate  (for  example  the  cost  of  achieving  the  2%  materiality  criterion  used  by  the 
European Court of Auditors) can be estimated.  

1 In mathematics, the logarithm of a number to a given base is the power or exponent to which the base must be 
raised in order to produce the number. For example, the logarithm of 1000 to the base 10 is 3, because 10 raised 
to the power of 3 is 1000. In the logarithmic trend line, ln(x) stands for the natural logarithm of . To compute a 
logarithmic  trend  line  one  must  plot  x  against  “log  y”  (for  example  x1,log  y1)  and  (x2,  log  y2),  then  draw  a 
straight line between these points on a graph and calculate the equation of the gradient using Y = cX + b 

6

 
 
 
 
 
 
 
 
 
                                                 
2.2.3.  Testing the model  

It  is  essential  to  acknowledge  that  the  shape  of  the  curve  can  have  a  material  difference  in 
setting the optimal level of controls. Therefore the model was tested using more sophisticated 
mathematical approaches. 

The following modifications of the model were introduced:  

• 

• 

• 

• 

introduction of  "control scope" (% of projects) (A) 

introduction of a more realistic parabolic equation for the cost of control function, 
taking account of fixed and variable costs (B) 

introduction of the concept of "opportunity cost" (C) and a "combined cost curve" 
(D), combining the cost of controls and the opportunity cost 

introduction of a "benefit curve" (consisting of recovery order), current benefit 
being equal to zero (E) 

• 

introduction of "proceeds curve" (benefit– control costs) (F) 

•  making use of "optimisation" problem solving (maximising proceeds/minimising 

costs) 

Graphically this would lead to five curves: 

Graph 4 

t
s
o
C

l

o
r
t
n
o
c
/
y
t
i
n
u
t
r
o
p
p
O

(C)

(E)

(D)

(F)

Control costs  (modified)

Opportunity c ost

(B)

Combined cost

Benefit (rec overed errors)

proc eeds (benefit - c ontrol
cos t)

Con tro l scop e (%  o f pro jects)

(A)

When  tested  within  the  limits  of  the  available  data,  the  tests  were  found  to  produce 
comparable results (see below). The simplified model is therefore believed to be reasonably 
reliable  and  to  provide  a  sound  basis  for  a  first  indication  of  where  the  tolerable  risk  point 
may lie. 

7

 
 
 
 
 
 
 
 
 
 
 
 
2.3. General assumptions and calculation methods 

The  use  of  regression  relies  heavily  on  the  underlying  assumptions  being  satisfied.  In  this 
model, the following hypotheses were made: 

2.3.1.  General assumptions: 

The  following  assumptions  could  potentially  cause  the  tolerable  risk  point  to  be 
overestimated:  

• 

• 

• 

• 

• 

Absence  of  "lurking"  variables:  in  observational  studies,  it  is  essential  to  eliminate 
bias.  For  this  reason  some  existing  models  make  use  of  confounding  variables  called 
"lurking" variables to take into account more than one independent variable and reduce 
bias.  This  is  not  the  case  in  the  model  used  as  many  benefits  are  difficult  to  quantify 
(such as the additional reduction of errors through the deterrent effect of controls over 
and  above  any  specific  error  detected,  the  benefits  beyond  spending,  the  reputational 
risk of the Commission due to fraud, etc). Analysis at this stage was therefore limited to 
cost and benefits of controls in purely quantifiable financial terms. 

All  projects  need  to  be  controlled  to  secure  0%  error:  even  if  theoretically  the 
control chain should  be  designed  to provide "assurance" to final beneficiary level, the 
only  way  to  really  ensure  100%  regularity  and  legality  of  underlying  transactions  is 
through  on-the-spot  controls  of  all  projects  at  a  moment  when  all  costs  can  be  fully 
verified.  

Extrapolation  of  errors:  the  model  excludes  extrapolation  of  errors  (application  of 
corrections  of  systemic  errors  to  non-audited  projects)  and  therefore  requires  100% 
audit coverage since all projects need to be controlled to eliminate all errors. 
The cost of controls axis is project-based2, meaning that each control is assumed to cost 
the  same  amount  and  there  are  no  economies  of  scale  from  simultaneous  auditing  of 
several projects for the same beneficiary. 

Homogeneity of the population: when a straight line is used, the population of projects 
is  assumed  to  be  homogeneous  in  size  and  in  terms  of  risk  of  error.  Technically  this 
means all the Y distributions have the same spread. This is not likely to be the case in 
reality  since  certain  types  of  projects  may  for  example  have  higher  error  rates  than 
others. An optimal approach would allow stratification of the projects according to risk, 
taking  account  of  policy  area,  size  and  nature  of  the  activity,  management  mode  or 
beneficiary where controls would be directed towards higher risk areas thereby reducing 
risk of undetected error at a lower cost. 

Two  further  assumptions  in  the  model  could  potentially  cause  the  tolerable  risk  point  to  be 
underestimated: 

• 

improving  existing  controls  to  reduce  the  error  rate,  for  example  through  better 
guidance and training, is assumed to have zero cost. 

2 While 'project' is a word which has many different meanings within the Commission, it is used in this exercise 
in the context of the Structural Funds and CAP policy areas. 

8

 
 
 
 
 
 
 
 
 
                                                 
• 

Audit  risk:  the  model  excludes  the  audit  risk  (the  risk  of  a  control  not  detecting  an 
existing error) as it assumes that an error rate of 0% would be obtained if all projects 
were controlled. By excluding the "false negatives" and assuming that controls carried 
out identify and correct all errors in a project, we distance ourselves from the standard 
control  frameworks  that  rely  on  the  concept  of  "reasonable  assurance"  used  to 
acknowledge that even the best control system cannot avoid all errors and an increased 
number of controls could never produce a zero level error. 

Furthermore three general assumptions are made: 

• 

• 

• 

The control strategy is annual: eliminating all errors on an annual basis would require 
each project to be audited at the end of each year (to match with the annual opinion of 
the Court of Auditors required by the Treaty), although this is not likely to be feasible in 
reality. 

The  economic  trade-off  between  costs  and  benefits  is  only  valid  as  a  hypothesis 
insofar  as  the  amount  of  error  detected  and  recovered  resulting  from  an  additional 
control is consequently re-allocated for additional controls. 

The  examples  provided  are  based  on  a  single  year  and  it  is  assumed  that  this  year  is 
representative. 

2.3.2.  Calculations and methods: 

2.3.2.1. Current rate (point A): 

To  fully  understand  the  methodology  presented  in  this  working  document,  it  is 
essential to distinguish the errors detected by the ex ante internal control chain of the 
Commission  and  its  implementation  partners  (therefore  proving  the  efficiency  of  its 
controls  put  in  place)  from  those  discovered  by  the  European  Court  of  Auditors, 
whose findings are outside this control chain. Since many of the projects audited in the 
Court's annual sample will not have been subject to the full set of controls required by 
legislation over the lifespan of programmes, the multiannual corrective mechanisms in 
place  (e.g.  for  cohesion  policy)  impact  the  longer-term  error  rate.  The  (annually-
based) tolerable risk point in this illustrative example is therefore totally distinct from 
the error level at the closure of each individual (multi-annual) programme. 

The  methodology  used  only  focuses  on  the  errors  that  the  internal  control  chain  had 
not prevented or detected at the time of the Court's audit. The current rate of error in 
the  calculations  in  this  document  is  therefore  based  on  the  findings  of  the  Court  of 
Auditors  in  their  annual  reports  where  possible.  This  estimation  constitutes  the  first 
point for the construction of the whole model.  

It  is  important  to  bear  in  mind  the  underlying  EU  control  concept  where  ex-ante 
controls  are  of  utmost  importance  as  a  preventive  tool  and  ex-post  controls  fulfil  a 
monitoring  function  as  well  as  acting  as  corrective  controls.  In  order  not  to  focus 
disproportionately  on  the  corrective  ex-post  controls  only,  the  estimated  benefits  of 
improving the existing ex ante controls at limited or no significant additional cost were 
also brought into the equation (using the DAS 2006 "substantive findings" i.e. findings 
with financial impact according to the Court methodology). 

9

 
 
 
 
 
 
 
 
2.3.2.2.Cost of control for all open projects (point B): 

While it could be worthwhile to invest additional resources in desk-based and on-the-
spot ex-ante controls, these controls cannot detect and correct all types of errors. It is 
also  necessary  to  go  on-the-spot  to  fully  control  an  activity  ex-post.  Controls  on  the 
spot  by  the  audit  bodies  are  therefore  necessary  to  check  in  detail  the  legality  and 
regularity of underlying transactions. 

Point  B  (situated  on  the  X-axis)  is  calculated  by  multiplying  the  number  of  open 
projects not controlled (the total population to be controlled) by the average cost of an 
on-the-spot control for each policy and adding the product to the current control cost. 
The  fact  that  the  cost  of  controlling  every  project  on-the-spot  is  estimated  does  not 
mean  that  every  cost  claim  has  been  audited  but  rather  that  each  open  project  is 
assumed  to  be  controlled  once  annually.  Other  methods  were  considered  for  this 
modelling but the available data were insufficient to support these.  

2.3.2.3.The tolerable risk point:  

The optimal trade-off between costs and benefits is based on the concept of marginal 
benefit,  being  the  decrease  in  error  (defined  as  the  amount  of  error  likely  to  be 
detected and corrected by a control) resulting from a unit increase in terms of control 
cost. In this logic, it is worth carrying out additional controls as long as an additional 
Euro spent on controls leads to a reduction of the error of more then one Euro3. The 
tolerable risk point (represented by a star on graph 5) corresponds to the point where 
the  marginal  benefit  of  an  extra  control  becomes  equal  to  its  marginal  cost.  Beyond 
this point an extra euro spent on controls would exceed the benefits obtained from this 
additional euro. This means that from a purely economic viewpoint the tolerable risk 
of error would not be set lower than this "tolerable risk point". 

Graphically  this  point  is  represented  by  the  slope  of  the  tangent  of  the  curve  that 
depicts the cost-benefit relationship. The point where the tangent and the curve touch 
is the point at which the angle of the curve is 45°/135°, which means that an additional 
euro  spent  on  control  at  this  exact  point  would  result  in  an  error  of  one  euro  being 
detected and corrected. Mathematically, at this shared point, the first derivative of the 
curve is equal to the slope of the line (45° tangent gradient)4. 

3 In technical terms a positive net benefit corresponds to the ratio "benefit derived from marginal increase of cost 
of controls/ marginal increase in terms of cost of control" being greater than one. 
4 Mathematically the slope, or derivative, of f(x) at point x is the limit, as h approaches zero, of [f(x+h)-f(x)]/h. 
Note that the tangent for an 45° radian angle (arithmetically equal to '1') is the inverse tangent of an 135° radian 
angle (arithmetically equal to '-1'). 

10

 
 
 
 
 
 
 
 
                                                 
For a negative slope we get the following graphical representation: 

Graph 5 

Rate of undetected 
errors (Y) 

Current 
rate 

  (A) 

      45° 

Tolerable Risk 
Point 

Rate at 
Tolerable 
Risk Point 

      45° 

135° 

0% 

Current 
cost of 
controls 

Cost of 
controls at 
Tolerable 
Risk Point 

  (B) 

Cost of 
controls for 
all open 
projects 

Cost of 
controls (X) 

In  theory  it  could  be  that  for  certain  areas  there  would  be  no  tolerable  risk  point 
because it would be cost-effective to control all projects. Mathematically this is linked 
with the notion of elasticity of a curve. In cases where a chart line is steeper than 45° 
on every point this means it is cost efficient to audit 100% of the projects. In cases of 
very flat chart lines never reaching 45°, this means that controls could be effected as a 
deterrent but could not be justified by pure cost-benefit considerations. Therefore the 
model presented uses a tacit assumption where we assume the degree of elasticity as 
being  sufficiently  high  to  obtain  a  meaningful  trade-off  between  costs  and  benefits.5 
This  approach  implies  that  the  size  and  relative  risk  of  the  different  projects  is  not 
taken  into  account.  However,  this  may  be  disconnected  from  the  true  distribution  of 
the population. Ideally the "tolerable risk point" would be analysed at project level if 
such data were available. 

2.4. Illustrative cases 

2.4.1.  European Regional Development Fund (ERDF) 

The specific nature of the shared management mode required the approach to take 
account of the following characteristics: 

5 'Elasticity' must not be confused with 'slope' as elasticity is the slope of a curve on a log/log graph only and not on a regular graph. 

11

 
 
 
 
 
 
 
 
 
 
 
                                                 
 
2.4.1.1.Specificities of the work done  

•  The estimation of the error rate after improvement of ex ante controls involved the 
analysis of all DAS 2006 errors for the Structural Funds family, classifying each error 
according  to  whether  improved  ex  ante  controls  (resulting,  for  example,  from  the 
provision  of  additional  guidance  and  training  by  the  Commission  and  the  Member 
States) could have prevented it at limited additional cost. The impact of the improved 
ex ante controls on the level of error quoted by the Court of Auditors for the Structural 
Funds  in  its  Annual  Report  2006  (at  least  12%)  was  then  estimated,  resulting  in  a 
revised error rate of 9%. 

•  The  Y-axis  indicates  the  total  error  rate  in  relative  terms.  The  corresponding 
monetary amounts of errors are calculated on the basis of the total public expenditure 
for ERDF in 2006 (including national co-financing).  

•  For the cost of control exercise, the approach developed took account of the fact that 
controls occur at two different levels, namely at Member State level and Commission 
level. Due to the fact that assurance is gained mainly at Member State level, the model 
focuses on that part of the control chain.  

•  The cost of control for all open projects was calculated on the basis of the product of 
the  "number  of  open  projects"  and  the  "average  cost  of  an  ex-post  control"  (both 
estimated  for  2006  exercise).  This  result  was  added  to  the  current  estimated  cost  of 
controls to determine a theoretical cost of controlling all projects on-the-spot annually. 

•  To determine the tolerable risk point the first derivative of the curve was calculated 
and a tangent was drawn at 135° from the X-axis to touch the curve in order to find the 
shared point where the first derivative of the curve is equal to the slope of the tangent. 

2.4.1.2.Assumptions used: 

•  The estimation of the impact of improved ex ante control was done at Commission 
level  and  was  based  on  Commission  assumptions  estimating  the  impact  of  better 
Member State controls, essentially following the issue of further guidance and training 
by the Commission and Member States to all the actors concerned and at all levels. No 
consultation of the Member States took place at this stage.  

• 

It  should  be  noted  that  the  European  Court  of  Auditors'  error  rate,  on  which  the 
extrapolation to take account of the improved ex ante controls was based, relates to the 
entire  Structural  Funds  family  whereas  the  Commission's  detailed  analysis  of  costs 
and benefits covered only the ERDF. 

•  The co-financing rate used to calculate the total public expenditure was estimated at 
50% (meaning that for every euro paid by the Commission an additional euro is paid 
by the Member State). In the absence of detailed data, this rate is based on the Court's 
sample  (using  a  weighted  average  of  the  co-financing  rates  stated  in  its  DAS  2006 
errors).  While  indicative,  the  Commission  considers  this  a  reasonable  approximation 
of the actual figures.  

•  The cost of control figures provided by the Member States were used without any 
revision  or  adaptation  at  Commission  level.  The  figure  obtained  is  therefore  an 
arithmetic sum. However a few Member States did not provide complete information. 

12

 
 
 
 
 
 
 
Despite  this  the  information  obtained  was  deemed  to  provide  a  reasonable  basis  for 
this  exercise.  Better  data  would  require  an  extensive  data  collection  exercise  at 
Member  State  and  implementing  body  level  with  a  commitment  from  all  to  provide 
accurate  and  complete  information.  To  cater  for  the  possible  underestimation  of 
control  costs  by  the  Member  States,  the  effect  of  a  50%  increase  in  costs  of  control 
was estimated by the Commission services and is presented below. 

•  Number of open projects: the number used in the calculations is an estimate as the 
Member States are not required to communicate this information to the Commission. 
However, the estimate was deemed to be sufficiently robust to be used for the purpose 
of  this  exercise.  In  addition,  it  was  assumed  that  the  number  of  projects  is  the  cost 
driver of an Article 10 audit in the Structural Funds. The model therefore disregarded 
the fact that the Article 10 audit is driven primarily by operational programmes, which 
in turn include system audits and audit planning at this level, which are procedures not 
driven primarily by the number of projects. 

•  Average cost of an on-the-spot control: the average cost of controlling a project on-
the-spot was used and not the average cost of performing a control assignment (which 
normally  means  checking  a  payment  claim  attributed  to  an  operational  programme). 
All on-the-spot controls were assumed to cost the same. 

•  The  following  sensitivity  analysis  was  carried  out  to  cater  for  possible  under-  or 
overestimation  of  two  of  the  most  essential  parameters  used  in  the  illustrative 
example,  namely    the  control  costs  by  the  Member  States  and  the  number  of  open 
projects for ERDF: 

Error Rate 
simulations 

Number 
of open 
projects 

250,000
350,000
450,000

Cost of Controls  

€215 Million 
(current cost*) 
2%
4%
5%

+50%  
( MS level) 
4%
5%
6%

+100%  
(MS level) 
5% 
6% 
7% 

*including cost of Commission controls 

If  the  cost  of  controls  by  Member  States  were  50%  higher  than  estimated  by  the 
Member  States6  or  the  number  of  open  projects  100,000  higher  than  the  350,000 
currently estimated by Commission’ services, the tolerable risk point would increase 
by 1 percentage point (to 5%). 

2.4.1.3.Enhanced model: 

Given the broad assumptions made, the product of the simplified model could be subject to 
some uncertainty, one aspect being the value of the results possibly being tainted due to the 
fact  that  important  variables  are  assumed  to  be  stable  (simplification,  preventive  effect  of 
controls).  To  identify  the  possible  impact  of  this,  the  model  was  enhanced,  making  use  of 
parabolic and logarithmic functions.  

6 Number of art 10 controls being constant and at current cost of Commission controls. 

13

 
 
 
 
 
 
                                                 
The following elements were  introduced: 

•  a  more  realistic  parabolic  cost  of  control  function,  making  use  of  a  "fixed  costs" 
constant (being equal to €215 million) and a "variable cost" variable, the second term 
of  the  equation  varying  with  a  calculated  exponent7.  The  basic  idea  behind  the 
parabolic slope is that following a risk analysis, riskier projects would be subject to an 
on-the-spot control first. This means that in order to cover the initial part of the control 
scope,  less  cost  for  control  is  incurred  in  relative  terms,  i.e.  increasing  the  control 
scope becomes relatively more expensive the further one goes along the curve. 

•  a  logarithmic  opportunity  cost  function  (therefore  showing  a  decreasing  marginal 
opportunity  cost),  being  the  cost  incurred,  in  terms  of  unrecovered  amounts,  at  the 
given  cost  of  control  level.8    The  mirror  image  of  this  opportunity  cost  function 
corresponds  to  the  benefit  function  (also  logarithmic),  being  the  benefit  obtained  in 
terms of recovered amounts, at the given cost of control level.9 

From these equations two further equations are derived. 

•  The  sum  of  the cost  of control equation and the opportunity cost equation make 

the  combined cost function (of parabolic type).  

•  The  difference between the benefit equation and the control cost equation make 

the proceeds function (of logarithmic type). 

From  these  functions  the  slopes  were  defined  and  the  derivative  cost  function  and 
derivative profit function calculated. This produced some possible "optimal risk points" as 
illustrated in Graph 6: 

7 f(x) = A + s*x2, with A = current (fixed) cost of €214.19 million and s = factor which corresponds to A and the 
coordinate corresponding to ("100 % control scope"; "€2,250 million euro"). Note that the graph of a degree 2 
polynomial of the form f(x) = a0 + a1x + a2x², where a2 ≠ 0 is always a parabola. 
8 For example, at current cost of control of €215 million there is an implied level  €2,550 million recoveries (this 
being the error rate of 8.6% multiplied with the total public expenditure of €29.65 billion). The opportunity cost 
if everything is controlled would amounts to €350 million. 
9 For example when the control scope (% of projects controlled) amounts to 100%, the recovered amount would 
be €2,550 million. 

14

 
 
 
                                                 
Control costs

(A)

Opportunity cost

(B)

Combined cost

(C)

Benefit (recovered errors)

(D)

proceeds (benefit - control
cost)

(E)

Graph 6 

c ur rent opport unity cos t: 2,550 mio euro
c ur rent error: er ror rate 8,6%

2.500,00

2.250,00

2.000,00

1.750,00

1.500,00

1.250,00

1.000,00

750,00

500,00

250,00

0,00

t
s
o
C

l

o
r
t
n
o
c
/
y
t
ni
u
t
r
o
p
p
O

(B)

(C)

cost min

(D)

(A)

current c ontrol cost: 
215 mio eur o

proceeds max

(E)

0

11

22

33

44

56

67

78

89

100

Control scope (% of projects)

Introduced  on  current  data  basis,  these  equations  yielded  a  comparable  result,  being  a 
tolerable  risk  point  which  ranges  between  3.4%  and  5%.    However,  this  does  not 
guarantee the outcome of the results being bias-free, since the underlying data used are the 
same  and  present  the  same  uncertainties  explained  above.  It  is  rather  the  incomplete 
nature of the data (e.g. Member States figures) instead of the methodology used, that limit 
the scope of the conclusions drawn. 

Since  the  Court  took  only  one  sample  for  the  Structural  Funds  in  the  DAS  exercise,  no 
distinction  can  be  made  between  the  ERDF  and  the  other  structural  funds  measures. 
However,  it  is  assumed  that  the  results  obtained  for  ERDF  can  be,  mutatis  mutandis, 
extrapolated  to  the  other  measures  and  that  the  conclusions  are  therefore  valid  for  the 
whole structural funds family. 

2.4.2.  European Agricultural Fund for Rural Development (EAFRD)  

2.4.2.1.Specificities of the work done: 

•  The  estimation  of  the  error  rate  for  EAFRD  expenditure  is  based  on  statistics 
received  from  Member  States  on  control  results  regarding  agro-environmental 
measures (AEM) concerning expenditure in financial year 2007 since the sample taken 
by the Court on rural development for the DAS 2006 was considered too small to be 
analysed  in  the  same  way  as  for  the  illustrative  example  on  regional  development10. 
The error rate in terms of reductions to cost claims amounts to around 4%.   

•  The  estimation  of  the  costs  of  controlling  AEM  is  based  on  an  estimation  and 
analysis  of  the  costs  of  controls  for  the  European  Agricultural  Guarantee  Fund 
(EAGF) which was carried out by all Member States in the first half of 2007 using a 

10 The Court draws a sample which covers the whole of the Agriculture policy area. 

15

 
 
 
 
 
 
 
 
 
                                                 
methodology  developed  by  the  Commission.  Data  collected  related  to  the  Guarantee 
section of the EAGGF fund (financial year 2005) and takes into account expenditure 
effected by Member State entities concerned (e. g. accredited paying agencies). 

•  The  costs  of  controls  were  calculated  based  on  a  pro-rata  basis  taking  into 
consideration  the  number  of  agents  working  in  full  time  equivalent  (FTE)  in  the 
relevant  entity  in  relation  to  the  number  of  agents  dedicated  to  the  corresponding 
control functions or activities.  

•  The optimal level of control was calculated using the first derivative of the curve that 
was created using three points, starting from the current cost of controls and the 4% 
residual error rate.  

•  Annex 2 contains an overview of the coverage and the benefits of agro-environmental 
measures,  an  explanation  for  the  high  incidence  of  errors  in  this  area,  the  related 
control framework and further information on the preliminary results at Member State 
level of the first rough estimation of the cost of controls. 

2.4.2.2. Assumptions used: 

• 

It  should  be  noted  that  the  information  provided  by  Member  States  is  not  always 
complete  and  properly  verified  and,  therefore,  only  gives  an  indication  of  the 
magnitude  of  the  control  costs.  This  estimation  is  expressed  as  an  average  of  the 
control  costs,  not  including  any  indication  of  the  marginal  costs  of  any  additional 
controls.  

•  A  sensitivity  analysis  reveals  however  that,  even  if  a  margin  of  error  of  50%  was 
applied  for  the  calculation  of  the  control  costs,  the  conclusions  set  out  in  the 
communication would still be valid. 

16

 
 
 
 
 
 
3.  THE COST OF CONTROLS EXERCISE 

In  addition  to  explanations  of  the  methodology  used  for  providing  a  first  indication  of 
tolerable risk in two policy areas, this annex also provides information on the results of a first 
estimation of costs of control launched as Action 10 of the Action plan towards an Integrated 
Internal  Control  Framework11,  a  pilot  exercise  was  launched  to  assess  the  costs  of  control. 
The methodology chosen for this exercise was simple, not time consuming and valid both in 
shared management (Action 10a) and in direct centralised management (Action 10b). 

3.1. Methodology 

The whole methodology for estimating the cost of controls is based on the following three key 
notions:  

• 

• 

• 

Definition  of  control:  "every  function  whose  objective  is  to  verify  the  rights  of  a 
beneficiary". 

All  controlling  entities  were  to  be  covered,  including  the  controlling  entities  in  the 
Member States. 

The  cost  of  control  was  calculated  on  the  basis  of  the  number  of  staff  undertaking 
control activities. 

For the shared management this implied the formula: CC = NF / TF * BE  

Where   CC = Cost of Controls 

NF = Number of FTE involved in control activities 

TF = Total FTE working in the organisation 

BE = Budget of the Entity 

Specificities in direct centralised management : 

−  The cost related to Commission staff was assessed by multiplying the full-time equivalent 
staff  undertaking  control  activities  by  a  standard  staff  cost  established  each  year  for 
budgetary needs. This cost integrates overhead costs such as infrastructure. 

−  The cost of controls related to external contractors was calculated as the amount invoiced 
plus the estimated Commission overhead costs for managing these external contracts. 

Specificities in shared management: 

−  The same methodology as direct centralised management was used for the calculation of 

the costs of direct (Commission) controls under shared management.  

−  The  cost  at  Member  State  level  was  included  to  provide  a  comprehensive  picture  and 
involved data gathering at local level. This involved all relevant Member State authorities 
being  asked  to  estimate  the  proportion  of  their  workforce  involved  in  control  activities 
related  to  EAGGF  and  ERDF  activities  and  applying  this  proportion  to  their  total 
administrative budget to provide a first estimation of the cost of controls. 

11 'Commission Action Plan towards an integrated internal control framework', COM(2006)9 

17

 
 
 
 
 
 
 
 
 
 
 
 
                                                 
3.2. Results for the Commission services 

This section presents some results mainly in line with the cost of controls and therefore in line 
with the methodology described above. All of the services used the year 2006 as the reference 
year except as noted. 

These  figures  are  first  estimates  and  must  be  seen  in  the  light  of  the  tolerable  risk  of  error 
exercise. Therefore they do not constitute officially-validated figures of the Commission and 
must be handled with care, in particular the figures that are based on information relating to 
the Member States. 

It  is  also  important  to  understand  that  the  data  cannot  be  compared  between  DGs  without 
additional information, even if some services may use a similar control strategy and/or budget 
implementation procedures. 

3.2.1.  European Agricultural Guidance and Guarantee Fund (EAGGF 

Agricultural expenditure 2005 
(€ Million) 

Costs of controls 2005 
(€ Million EUR) 

EU-25 
EU-15 
EU-10 

48,670 
44,701 
3,969 

100% 
92% 
8% 

2,018 
1,799 
218 

100% 
89% 
11% 

Percentage 
breakdown 
4.1% 
4.0% 
5.5% 

3.2.1.1.Specificities of the work done: 

• 

• 

• 

• 

• 

The estimation of control costs in agriculture was established as a pilot exercise 
for the costs in shared management and helped to fine-tune the methodology.  

For this reason, the data were collected for the exercise in 2005 instead of 2006.  

The exercise was limited to the EAGGF-Guarantee fund. 

3.2.1.2.Key figures (in light of the above table):  

The total cost of controls amounted €2,018 million (for EU 25). 

The cost of controls represents globally 4.1% of the funds paid (for EU 25). 

18

 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
3.2.2.  European Regional Development Fund (ERDF) 

Cost of 
controls 
Article 4 
(2006) 

 Cost of 
controls 
Article 9 
(2006) 

 Cost of 
controls 
Article 10 
(2006) 

 Cost of 
controls 
Article 15 
(2006) 

 Total Cost of 
MS level 
controls  

 Cost of 
Commission 
controls 
(2006)  

 Total 
Cost of 
Control  

158    

  10 

31 

3 

202 

13 

     215 

(€ Million) 

3.2.2.1.Specificities of the work done: 

• 

• 

• 

• 

• 

• 

• 

The direct control costs were calculated for DG REGIO taking into account the 
statutory and external staff for the following type of services: audit, outsourced 
controls, and operational and financial staff. The figures reflect the situation for 
2006. 

Specific  cost  data  gathering  by  Member  States  took  place  at  local  level.  The 
costs  of  control  figures  provided  by  the  Member  States  relate  to  the  2006 
exercise. They were used without any treatment at Commission level, although 
limited  checking  indicates  that  for  some  Member  States  the  data  provided  was 
incomplete. The figure obtained is therefore the arithmetic sum (cfr supra). 

The cost of controls of the Member States takes account of the Article 4 checks 
(management and control systems compliance by Managing Authorities), Article 
9 checks (certification of expenditure by Paying Authorities), Article 10 checks 
(sample  checks  on  operations  of  at  least  5%  by  Implementing  Bodies)  and 
Article 15 checks (signing-off of the assistance by "winding-up" Bodies) for the 
EU-25.12 

3.2.2.2.Key figures (in the light of the table above):  

The total cost of direct controls for DG REGIO amount to €13 million. 

The ERDF cost of controls of the Member States' (art 4, art 9, art 10 and art 15) 
are estimated at €202 million. 

The total cost of controls is therefore €215 million. 

This  total  cost  represents  0.7%  of  the  total  public  contribution  made  for  that 
year13. 

12  See Commission Regulation (EC) No 438/2001 of 2 March 2001 laying down detailed rules for the 
implementation of Council Regulation (EC) No 1260/1999 as regards the management and control systems for 
assistance granted under the Structural Funds. 
13 ERDF payments by the Commission for 2006 were €14,825.09 million and the co-financing rate is estimated 
at 50%. 

19

 
 
 
 
 
 
   
   
  
  
  
  
   
 
 
 
 
                                                 
3.2.3.  DG Employment and Social Affairs 

Cost of 
controls 
Article 4 
(2006) 
99 

Cost of 
controls 
Article 9 
(2006) 
6 

Cost of 
controls 
Article 10 
(2006) 
20 

Cost of 
controls 
Article 15 
(2006) 
2 

(€ Million) 

Total Cost 
of MS level 
controls 
(2006) 
127 

Cost of direct 
controls for 
ESF 

Outsourced 
audit costs 
(2008) 

Total Cost of 
Control 

13 

2 

142 

3.2.3.1.Specificities of the work done: 

The  staff  costs  were  calculated  for  the  European  Social  Fund,  using  the  staff 
situation  as  at  01/08/2006.  At  this  stage  (in  contrast  to  2008)  there  was  no 
contract to outsource some ex-post controls. A fixed percentage of the costs of 
geographical desk officers was taken into account (30% of their working time). 

The outsourced control costs (also considered a central cost) were based on an 
estimate for the 2008 exercise. 

No specific data gathering took place at local level. Instead, the cost of controls 
at Member State level was estimated in order to provide a comprehensive picture 
of the situation. The figures for DG REGIO were used to calculate a pro rata rate 
using  the  total  payments  for  DG  EMPL  as  numerator  and  the  sum  of  the 
payments for DG EMPL and ERDF payments as denominator of the fraction. 

3.2.3.2.Key figures (in the light of the table above):  

The total central cost of control for ESF is €13 million for staff and €2 million 
for the audits that are outsourced. 

The  Member  State  costs  (art  4,  art  9,  art  10  and  art  15)  are  estimated  at  €127 
million. 

The total cost of control is therefore estimated at €142 million. 
This cost represents 0.8% of the total public contribution for 200614. 

• 

• 

• 

• 

• 

• 

• 

14 DG EMPL payments by the Commission for 2006 were estimated at €9,335.59 million with a co-financing 
rate of 50%. 

20

 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
                                                 
3.2.4.  DG EuropeAid 

Ex-ante staff 
costs (2006)  

Cost of  
control audits 
(2007) 

 Cost of audit 
certificates 
(2006)  

 Total cost of control  

           49    

            15     

             9    

                73   

(€Million) 

3.2.4.1.Specificities of the work done: 

The current cost of control includes staff at headquarters and delegations, the on-
the-spot  controls  contracted  by 
the  expenditure 
verifications via audits contracted by the beneficiaries. 

the  Commission  and 

The  figures  correspond  to  the  cost  of  controls  for  DG  EuropeAid  only,  for 
actions financed by the General Budget. This means the cost of controls related 
to the European Development Fund or DG ECHO, DG RELEX, DG ENLARG, 
and DG DEV activities were excluded. 

3.2.4.2.Key figures (in the light of the table above):  

The total central cost of control is €73 million. 

This cost represents 2% of the payments made. 

• 

• 

• 

• 

3.2.5.  DG Environment 

Current ex-post 
control cost  

 Total ex-ante 
cost (2006)  

 Cost of audit 
certificates 
(2006)  

 Total cost of control  

           0.4    

            2.6    

            0.6    

                 3.6    

(€ Million) 

3.2.5.1.Specificities of the work done: 

• 

• 

• 

The current ex-post control cost takes account of the staff and mission costs.  

The ex-ante costs for 2006 were calculated based on 25.45 FTE.  

The  external  audits  co-financed  by  the  Commission  as  contracted  by  the 
beneficiaries (audit certificates) were calculated and included. 

3.2.5.2.Key figures (in the light of the table above):  

• 

The total central cost of control is €3.6 million. 

21

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
• 

This cost represents 1.6% of the payments made for the year 2006.   

3.2.6.  DG Research 

Current ex-post 
control cost 
(2007) 

 Total ex-ante 
cost (2007)  

 Cost of audit 
certificates 
(2006)  

 Total cost of control  

            6    

            17   

            7  

                30 

(€ Million) 

3.2.6.1.Specificities of the work done:  

The current ex-post control cost were calculated, resulting from the total number 
of audits closed (either performed by an external company or by the DG's own 
resources) and the personnel costs. 

The  ex-ante  costs  were  calculated  for  2007,  resulting  from  the  number  of 
statutory agents and external staff working as FTE controllers. 

The  external  audits  co-financed  by  the  Commission  as  contracted  by  the 
beneficiaries (audit certificates) were calculated for 2006. 

3.2.6.2.Key figures (at the light of the table above):  

The total cost of control is €30 million. 

This cost represents 0.9% of the payments made.  

• 

• 

• 

• 

• 

3.2.7.  DG Information Society 

Current ex-post 
control cost  

 Total ex-ante 
cost (2007)  

 Cost of audit 
certificates 
(2006)  

 Total cost of control  

2 

32 

(€ Million) 

6 

40 

3.2.7.1.Specificities of the work done: 

The numbers for the staff in 2006 were used. 

The  costs  for  on-the-spot  controls  refer  to  those  launched  in  2006  under  the 
Audit Framework Contract. 

The number of on-the-spot controls carried out in 2006 (about 200) was used. 

• 

• 

• 

22

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
• 

• 

• 

• 

Institutional assessments (joint management) and audits carried out as a result of 
OLAF investigations have been excluded. 

The average cost of expenditure verification as foreseen by the beneficiaries in 
the planned budgets was calculated on the basis of a sample of 24 grant budgets 
using the estimated costs for an audit. 

3.2.7.2.Key figures (in the light of the table above):  

The total cost of control is €40 million. 

This cost represents 3.2% of the payments.  

3.2.8.  Other Services 

Against  the  background  of  Action  10  of  the  Action  plan  of  the  Commission,  an 
extension of the cost of control exercise was launched late in 2007 to assess the cost of 
controls of DG ECHO, DG JRC, DG SANCO and DG TREN. 

The costs of control can be summarised in the following table: 

 Total cost of 
control (2007) 
 % of the total 
budget  (2007) 

 DG ECHO  

 DG JRC 

 DG SANCO  

 DG TREN  

25 

3.4% 

4 

1% 

(€Million) 

1.1  

0.3% 

11.2 

1.4% 

3.2.8.1.Specificities of the work done: 

• 

• 

• 

The data collection was done using 2007 as reference year for all services. 

DG  ECHO  takes  into  account  two  management  modes  (joint  management  and 
central direct management). 

DG TREN focuses on centralised direct management only. 

23

 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
Glossary: 

Audit  risk:  represents  the  risk  of  the  auditor  providing  an  inappropriate  opinion  on  the 
financial statements. In other words, it is the risk of the auditor stating the financial statements 
present fairly the financial position of the entity, when in fact they do not. 

Article  4  checks:  the  first  level  checks  carried  out  by  the  Managing  Authorities  of  the 
Member States, as laid down in the rules for implementation of Council Regulation (EC) No 
1260/1999  as  regards  the  management  and  control  systems  for  assistance  granted  under  the 
Structural Funds.  

Article 9 checks: the certification of the expenditure carried out by the Paying Authorities as 
laid  down  in  the  rules  for  implementation  of  Council  Regulation  (EC)  No  1260/1999  as 
regards  the  management  and  control  systems  for  assistance  granted  under  the  Structural 
Funds. 

Article  10  checks:  the  sample  checks  on  operations  of  at  least  5%  of  the  total  of  eligible 
expenditure that need to be carried out by the audit bodies of the Member States, as laid down 
in  the  rules  for  implementation  of  Council  Regulation  (EC)  No  1260/1999  as  regards  the 
management and control systems for assistance granted under the Structural Funds.  

Article 15 checks: the declaration of winding-up of the assistance by the winding-up body, as 
laid  down  in  the  rules  for  implementation  of  Council  Regulation  (EC)  No  1260/1999  as 
regards  the  management  and  control  systems  for  assistance  granted  under  the  Structural 
Funds.  

Break-even point (BEP): the point where the cost of controls equals the benefits (defined as 
the value of error likely to be detected by a control). Beyond this point an extra euro spent on 
controls would exceed the benefits (reduction in error rate in %) obtained from it. 

Control risk: represents the risk that errors or irregularities in the underlying transactions will 
not be prevented, detected and corrected by internal control systems (either at the desk or on 
the spot). 

Elasticity:  In  economics,  elasticity  is  the  ratio  of  the  percent  change  in  one  variable  to  the 
percent change in another variable. It is a tool for measuring the responsiveness of a function 
to  changes  in  parameters  in  a  relative  way.  Elasticity  is  a  popular  tool  among  empiricists 
because  it  is  independent  of  units  and  thus  simplifies  data  analysis.  In  mathematical  terms 
elasticity can be defined as the ratio of the incremental change of the logarithm of a function 
with respect to an incremental change of the logarithm of the argument. 

Ex-ante control: Ex ante verification of an operation represents all the ex ante checks put in 
place  by  the  authorising  officer  responsible  in  order  to  verify  its  operational  and  financial 
aspects. According to the Financial Regulation, each operation shall be subject at least to an 
ex ante verification. The initiation and the ex ante and ex post verification of an operation are 
separate functions. 

24

 
 
 
 
 
 
 
 
 
 
 
 
Ex-post control: the ex post verifications on documents and, where appropriate, on the spot 
check  that  operations  financed  by  the  General  Budget  are  correctly  implemented  and  in 
particular the expenditure and revenue are in order and comply with the provisions applicable 
(in particular those of the budget and the relevant Regulations) and with the principle of sound 
financial  management.  These  verifications  may  be  organised  on  a  sample  basis  using  risk 
analysis.  

Inherent  risk:  represents  the  risk  linked  to  the  activity  itself  and  therefore  related  to  the 
nature of the activities. 

Regression analysis: a curve fitting technique, used in statistics and econometrics, which can 
be broken into two categories: linear regression and nonlinear regression. Of all the regression 
principles the straight line is the simple. 

Linear trend line: an optimized straight line that is suitable for linear datasets. A dataset is 
linear  if  the  pattern  of  data  points  resembles  a  line.  A  linear  trend  line  normally  displays  a 
constant increase or decrease in values. 

Logarithm:  in  mathematics,  the  logarithm  of  a  number  to  a  given  base  is  the  power  or 
exponent to which the base must be raised in order to produce the number. For example, the 
logarithm of 1000 to the base 10 is 3, because 10 raised to the power of 3 is 1000. 

Logarithmic trend line: an optimized curve that is ideal if the rate of changes to the data first 
increases or decreases sharply and then stays nearly the same.  

Residual  risk:  could  be  defined  as  the  risk  linked  to  the  activity  less  the  amount  of  error 
detected  by  controls.  Put  another  way,  residual  risk  is  the  amount  of  error  likely  to  remain 
undetected. 

Trend  line:  A  graphic  representation  of  trends  in  data  series.  Trend  lines  are  used  for  the 
study of problems of prediction, also called regression analysis. 

25

 
 
 
 
 
 
 
 
 
 
Annex 2 

Agro-environmental measures (AEM) in rural development and their control 

1. 

Basic principles and description of agro-environmental measures 

Agro-environment  measures  aim  to  encourage  farming  practices  and  maintenance  activities 
by farmers in view of preserving and enhancing the rural environment and the environmental 
functions of cultivated landscapes.  

The  most  common  AEM  address  in  particular  the  following  environmental  objectives: 
Preservation or enhancement of biodiversity, preservation of endangered species, maintenance 
of high nature value habitats, preservation of water quality and water resources, soil quality 
and  prevention  of  soil  erosion,  preservation  and  enhancement  of  landscapes  and  other 
environmental objectives (e.g. mitigation of climate change, prevention of fires). 

In  the  current  programming  period  2007-2013  agro-environmental  measures  are  obligatory. 
Around  €20.3  billion  have  been  programmed  for  these  measures,  making  them  the  biggest 
group of measures within rural development..  

2. 

Added value of agro-environmental measures 

In  2005,  an  evaluation  of  agro-environmental  measures  was  carried  out  by  an  external 
contractor on behalf of DG AGRI15.  

As regards the added value and benefits of AEM, the evaluators concluded that the measures 
generally  achieved  their  objectives  of  preserving  and  enhancing  the  environment.  This  was 
confirmed with respect to a whole range of issues addressed by AEM: biodiversity, habitats, 
rare animal breeds and endangered species, water quality, water quantity, soil and landscape. 

Some  of  the  results  were  of  a  preliminary  nature,  as  the  impacts  of  AEM  on  biodiversity, 
habitats, landscapes, water and soil can take a long time to emerge and often depend on site-
specific circumstances. However, for a number of measures, robust findings confirming their 
positive environmental effects were presented. These include: 

•  Measures with positive effects concerning the preservation of biodiversity and habitats: 
Reduction  of  inputs,  diversification  of  rotations,  maintenance  of  grasslands,  arable 
reversion  to  grassland  and  extensification,  grass  strips,  maintenance  of  extensive 
grasslands  and  grazing,  ecological  infrastructures  (hedges  and  small  plots),  fallow, 
appropriate mowing dates and methods, reduced tillage, and organic farming. 

15  
http://ec.europa.eu/agriculture/eval/reports/measures/fulltext.pdf. 

The full evaluation report can be found at:  

26

 
 
 
 
 
 
 
 
 
                                                 
•  Measures  with  positive  effects  on  water  quality:  Fallow,  diversification  of  rotations, 
maintenance of grasslands, buffer strips, conversion of arable land to grassland, winter 
soil cover, organic farming, and reduction of agricultural inputs. 

•  Measures  with  positive  effects  on  soil  protection:  Conversion  of  arable  land  to 
grassland,  set-aside  (with  green  cover),  grass  strips,  green  cover  of  the  soil  during 
critical  periods,  terraces  in  the  areas  concerned  by  steep  slopes,  reduced  tillage,  sown 
fallow and ecological infrastructures (hedges and small plots). 

3.  

Control  framework  for  rural  development  measures  in  general  and  agri-
environmental measures in particular 

On a proposal of the Commission, the Council decided for the-post 2007 period to align the 
management  and  control  system  for  the  expenditure  under  the  newly  created  European 
Agricultural  Fund  for  Rural  Development  (EAFRD)  with  the  EAGGF  guarantee  system 
(Council  Regulation  1290/2005).  Thus,  in  the  future,  the  "atouts"  of  the  EAGF  Guarantee 
system,  that  are  largely  recognized,  will  also  cover  the  rural  development  expenditure.  Key 
element  is  that  the  annual  accounts  of  the  accredited  paying  agencies  will  have  to  be 
accompanied  by  an  audit  opinion  and  report  of  an  independent  audit  service  (Certification 
Body), and a statement of assurance signed by the heads of the paying agencies.  

As  regards  more  particularly  the  control  of  agro-environmental  measures,  during  the 
programming period 2000-2006, controllability of agro-environmental measures proved to be 
problematic. The European Court of Auditors, in their special report 3/2005, concluded that 
the verification of the agro-environmental measures poses particular problems and is far more 
resource-intensive  than  verification  of  the  first  pillar  measures  and  other  rural  development 
measures. 

In  order  to  meet  the  recommendations  of  the  Court  several  improvements  have  been 
introduced  to  the  control  framework  for  agro-environmental  measures  regarding  the 
programming period 2007-2013. 

Regarding  the  regulatory  framework  the  applicable  legislation  now  requires  that  all  agri-
environmental commitments and eligibility conditions can be controlled according to a set of 
verifiable indicators to be established by Member States. In order to guide Member States in 
the  application  of  this  provision,  the  Commission  provided  detailed  guidance  to  Member 
States  regarding  the  controllability  of  agro-environmental  measures  (WD  RD  10/07/2006 
final). 

As regards the specific control rules for agro-environmental measures the following should be 
noted:  All  applications  for  agro-environmental  aid  measures  must  be  subject  to  detailed 
administrative  controls  (100%  administrative  controls).  These  checks  include  cross-checks 
within the IACS for all parcels and livestock covered by a support measure, in order to detect 
over  declaration,  double  payments,  etc.  The  administrative  checks  further  aim  at  verifying 
whether the eligibility conditions for the specific measure are met.  

Moreover,  the  applicable  legislation  provides  that  each  year  at  least  5%  of  all  beneficiaries 
subject  to  agro-environmental  commitments  must  be  subject  to  on-the-spot  controls. 
According to the control statistics submitted by the Member States concerning financial year 
2007, 9% (77 490) beneficiaries of agro-environmental measures have been controlled.  

27

 
 
 
4. 

Error rate for expenditure related to agro-environmental measures 

4.1.   Level of error rate 

In its Annual Report 2006, the European Court of Auditors noted in point 5.72 that in rural 
development, the agro-environmental measures are prone to a high incidence of errors. In the 
Annual Report 2007, the Court again reported that rural development is particularly prone to 
errors because of the often complex rules and eligibility conditions. 

The  controls  carried  out  by  Member  States  regarding  the  respect  of  agro-environmental 
commitments by farmers also confirm that these measures are prone to a higher incidence of 
errors  than  other.  According  to  statistics  received  from  Member  States  on  control  results 
regarding  agro-environmental  measures  concerning  expenditure  in  financial  year  2007,  the 
error  rate  in  terms  of  financial  reductions  amounts  to  around  4%.  These  data  were  not 
verified and validated by the certification bodies – and in some cases were also incomplete. 
They  nevertheless  confirmed  that  error  rates  for  agro-environmental  measures  were  higher 
than for other measures in rural development and also significantly higher than the error rate 
for area aids covered by IACS, where the error rate is around 1%. 

4.2.  Reasons for higher inherent risk of error  

The reasons why agro-environmental measures are prone to a higher incidence of errors than 
for example purely decoupled area aid measures are multiple.  

It is crucial in this respect to keep in mind that measures pursuing environmental objectives, 
including agro-environment measures, are based on a number of technical requirements, that 
must be implemented in a spatially differentiated manner, and complied with on a continuous 
basis or at different points in time. It is not possible to reap these considerable environmental 
benefits associated with these measures in a simpler way.  

One source of error common to all these measures is  the over declaration of  either areas or 
animals concerned. In practical terms this means, that for AEM the count starts at 1%. 

However, for the following reasons, these measures may be subject to additional errors: 

•  Measures consist often of multiple obligations for farmers, such as:  

–  Limitations on use of fertilisers and pesticides 
–  Specific timing of certain maintenance activities 
–  Requirements as regards the methods used 
–  Rotation plans 
–  Constraints regarding irrigation 

This inevitably increases the likelihood of multiple errors, which by nature will tend to 
be higher.  

•  Compliance  must  be  continuous  or  at  different  points  in  time  in  relation  to  different 

commitments  

•  It  may  be  difficult  to  establish  in  all  cases  unambiguous  causality  between  the 
commitment  and  the  result  obtained.  As  an  example  may  serve  the  input  reduction  of 
nitrate, the result of which not only depends on the actual behavior of the beneficiary, 
but also on weather conditions, soil structure, etc. 

28

 
 
 
Costs  of  control  of  agro-environmental measures (AEM): preliminary results at 

5. 
Member State level 

In  order  to  calculate  the  costs  of  controlling  of  agro-environmental  measures  the  overall 
control  costs  were  allocated  according  to  the  Full  Time  Equivalent  assigned  to  "other  than 
AEM"  controls  and  "AEM"  controls  at  Member  State's  level.  Comparing  the  agricultural 
expenditure  spent  for  "other  than  AEM"  with  the  costs  of  controls  related  to  "other  than 
AEM",  the  average  costs  of  controls  amount  to  3.3 %.  As  regards  agricultural  expenditure 
spent  for  AEM  in  relation  to  the  costs  of  controls  assigned  to  AEM,  the  average  costs  of 
controls  add  up  to  21.5 %.  Expressed  as  a  percentage  of  total  public  funding  for  AEM, 
including a 58.8% co-financing part by Member States for the period 2000-2006, the control 
costs for AEM amount up to 13%. 

The average costs16 of an administrative control17 for a non-AEM is calculated to add up to 
about €90, while for an AEM the average costs are about €235 , i.e. almost 2.5 times higher. 
The costs for an on-the-spot check of a non-AEM amount to about €520 , while the costs for 
an on-the-spot check of an AEM add up to around €1,100 , i.e. almost twice the amount as for 
a non-AEM. 

These average figures are based on information provided by the Member States. 
For the purpose of this document, the term includes administrative checks as well as other controls such 

16  
17  
as ex-post checks and controls carried out by other bodies such as the paying agencies' internal control 
department. 

29