Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the European Social Fund (ESF) regulation : final report.
Date: 2018-10-02
Institutions: Directorate-General for Employment, Social Affairs and Inclusion
Subjects: EU employment policy, European Social Fund, cost analysis, data collection, data processing, employment service, report, vocational training

Developing ‘Off-the-Shelf’ 
Simplified Cost Options (SCOs) 
under Article 14.1 of the 
European Social Fund (ESF) 
regulation 

Final report 

PPMI 
April – 2018 

 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
EUROPEAN COMMISSION 

Directorate-General for Employment, Social Affairs and Inclusion 
Directorate F — Investment 
Unit F.1 — ESF and FEAD: Policy and Legislation 

Contact: Loris di Pietrantonio  

E-mail:  EMPL-F1-UNIT@ec.europa.eu  

European Commission 
B-1049 Brussels 

Directorate-General for Employment, Social Affairs & Inclusion  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Directorate-General for Employment, Social Affairs & Inclusion  

 
 
EUROPEAN COMMISSION 

Developing ‘Off-the-Shelf’ 
Simplified Cost Options 
(SCOs) under Article 14.1 of 
the European Social Fund 
(ESF) regulation  

Final report 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EUROPE DIRECT is a service to help you find answers  
to your questions about the European Union 

Freephone number (*): 
00 800 6 7 8 9 10 11 

(*) The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you) 

LEGAL NOTICE 

This document has been prepared for the European Commission however it reflects the views only of the 
authors, and the Commission cannot be held responsible for any use which may be made of the information 
contained therein. 

More information on the European Union is available on the Internet (http://www.europa.eu). 

Luxembourg: Publications Office of the European Union, 2018 

PDF  

ISBN 978-92-79-86975-4 

doi: 10.2767/787584  

KE-02-18-843-EN-N 

© European Union, 2018 
Reproduction is authorised provided the source is acknowledged. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EUROPEAN COMMISSION 

TABLE OF CONTENTS 

EXECUTIVE SUMMARY ...................................................................................................... 8 

METHODOLOGICAL APPROACH .................................................................................................. 8 
KEY RESULTS OF THE STUDY .................................................................................................... 8 

INTRODUCTION .............................................................................................................. 10 

1.  OVERALL METHODOLOGICAL APPROACH ............................................................... 12 

1.1.  DATA COLLECTION ..................................................................................................... 12 
1.2.  DATA PROCESSING AND ANALYSIS .................................................................................... 17 

2. 

SCO FOR THE UNEMPLOYED ................................................................................... 18 

2.1.  COST OF A SUCCESSFUL EXIT FROM AN INTERVENTION ............................................................. 18 
2.1.1.  Definition of the SCO ..................................................................................... 18 
2.1.2.  Method to determine and update the amounts.................................................. 18 
Insights on application of this SCO .................................................................. 26 
2.1.3. 

3. 

SCO FOR EMPLOYMENT SERVICES ......................................................................... 27 

3.1.  COST PER COUNSELLING HOUR........................................................................................ 27 
3.1.1.  Definition of the SCO ..................................................................................... 27 
3.1.2.  Method to determine and update the amounts.................................................. 27 
Insights on application of this SCO .................................................................. 38 
3.1.3. 

4. 

SCOS FOR PEOPLE IN EMPLOYMENT AND PUBLIC SERVANTS ................................ 39 

4.1.  OPTION 1: COST PER PARTICIPANT TRAINING HOUR ................................................................ 39 
4.1.1.  Definition of the SCO ..................................................................................... 39 
4.1.2.  Method to determine and update the amounts.................................................. 39 
Insights on application of this SCO .................................................................. 47 
4.1.3. 
4.2.  OPTION 2: TRAINEE SALARY COSTS PER TRAINING HOUR .......................................................... 48 
4.2.1.  Definition of the SCO ..................................................................................... 48 
4.2.2.  Method to determine and update the amounts.................................................. 48 
Insights on application of this SCO .................................................................. 54 
4.2.3. 
4.3.  RELEVANCE OF EU-LEVEL SCOS FOR PEOPLE IN EMPLOYMENT TO TRAINING FOR PUBLIC SERVANTS .......... 54 

5 

 
 
 
 
EUROPEAN COMMISSION 

LIST OF FIGURES 

Figure 1. Simplified data collection process: data on training for the unemployed and Employment 
Services ............................................................................................................................ 14 
Figure 2. Simplified data collection process: data on training for people in employment and training 
for public servants .............................................................................................................. 16 
Figure 3. Predictive power of the OLS model for counselling staff costs ..................................... 32 
Figure 4. Predictive power of the model for training cost per participant training hour ................. 43 
Figure 5. Predictive power of the model for trainee salary costs ............................................... 51 
Figure 6. Average trainee salary costs as a median of hourly labour cost per employee (adjusted to 
2015 level) ........................................................................................................................ 53 
Figure 7. Status of data availability on trainings for public servants .......................................... 55 

LIST OF TABLES 

Table 1. LMP data used to inform the development of SCO for the unemployed .......................... 13 
Table 2. Changes in sample size after data cleaning ............................................................... 20 
Table 3. Unit cost rates ....................................................................................................... 23 
Table 4. Summary of the data from PES Business Models study ............................................... 28 
Table 5. Data received from PES .......................................................................................... 30 
Table 6. Unit cost rates for Employment Services (hourly) ....................................................... 33 
Table 7. Extrapolation: the difference between predicted and empirical SCO values .................... 34 
Table 8. CVTS dataset for Option 1 calculations ...................................................................... 40 
Table 9. Categories of costs of CVTS variable ‘c7subhour’ ........................................................ 42 
Table 10. HICP 2010 average indices (2015=100) used for adjustment of training costs ............. 44 
Table 11. Option 1: cost of training per participant training hour .............................................. 45 
Table 12. CVTS dataset for Option 2 calculations .................................................................... 48 
Table 13. CVTS variables for calculation of Option 2 ............................................................... 49 
Table 14. Average trainee salary costs as a median of hourly labour cost per employee .............. 51 
Table  15.  Training  for  public  servants:  availability  of  data  per  member  state  and  per  option/ 
calculation method ............................................................................................................. 55 

6 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

LIST OF ACRONYMS 

CVTS (4) 
DG EMPL 
GDP 
EC 
ESF 
EU 
FTE 
LCS 
LMP 
PES 
SCO 
SES 
TNC 

Continuing Vocational Education Survey (2010) 
Directorate-General for Employment, Social Affairs and Inclusion 
Gross domestic product 
European Commission 
European Social Fund 
European Union 
Full time equivalent 
Labour Cost Survey 
Labour Market Policy (database) 
Public Employment Service 
Simplified cost option 
Structure of Earnings Survey  
Simplification Thematic Network 

7 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

EXECUTIVE SUMMARY 

The purpose of this study is to support the European Commission in its efforts to establish 
EU-level Simplified Cost Options (SCOs) under the Article 14.1 of the European Social Fund 
regulation. Such SCOs would be established for the following policy areas: training of the 
unemployed,  provision  of  employment  services  (counselling  of  the  unemployed),  and 
training for people in employment (including public servants). The study report contains 
the methodological approach used to define SCOs, descriptions of the SCOs as well as unit 
costs estimated for each Member State. The SCOs descriptions elaborate on the definitions, 
sampling techniques, calculation methods, and audit trails for reimbursement of costs.  

Methodological approach 

This  study  is  largely  based  on  analysis  of  statistical  data  extracted  from  Eurostat  or 
provided by the European Commission. Statistical data was complemented by quantitative 
data extracted from other studies, and administrative data collected through an EU-wide 
survey of various relevant data handlers at Member State level. For the calculation of SCO 
for the training of the unemployed we used Labour market policy (LMP) statistics and data 
collected through the EU-wide survey. To establish the SCO for employment services, we 
have extracted qualitative data from the European Network of Public Employment Service’s 
(PES)  business  models  study  and  PES  capacity  assessment  and  PES  Benchlearning 
initiative. Additional data was acquired directly from Public Employment Services in several 
Member States. For the calculation of SCOs for people in employment and public servants 
we used statistical data from CVTS 4, Structure of Earnings Survey (SES) and Labour Cost 
Survey (LCS). We have also collected administrative data on relevant ESF operations form 
several the Member States, but due to data coverage and quality issues it was used for 
verification purposes only. Data processing and analysis phase included a thorough data 
cleaning, exploratory analysis testing methods to calculate the SCOs, calculation of unit 
costs and extrapolation of missing unit costs. To ensure the validity of established unit cost 
rates,  we  have  verified  them  by  employing  multivariate  analysis  of  socioeconomic 
development comparators. 

Key results of the study 

I. 

SCOS FOR THE UNEMPLOYED 

The EU-level SCO for the training of the unemployed was established as an output-based 
SCO.  It is defined as a  unit cost per  one successful exit from an  eligible intervention. A 
‘successful exit’ refers to a participant leaving an intervention and obtaining a certificate, 
accreditation or other national measure providing sufficient assurance that his/her training 
was  successfully  completed  (based  on  a  national  practice  of  a  Member  State).  The 
definition of an intervention was taken from the LMP methodology and is typically a non-
formal VET type training course which has identifiable participants and incurs expenditure.  

The LMP data was used to establish unit cost rates for 23 Member States.  For other five 
Member States unit costs were extrapolated using ordinary least squares regression model 
that  was  constructed  from  various  relevant  socioeconomic  indicators  and  unit  costs 
calculated based on the LMP data. For two Member States, unit costs calculated based on 
the LMP data appeared to lack reliability, thus alternative unit costs were also established 
through  extrapolation.  The  calculated  unit  costs  largely  reflect  the  socioeconomic 
differences between the Member States, but some deviations were observed. These can 
be  justified  by  specific  training  practices  evident  from  the  qualitative  data  in  the  LMP 
database  (e.g.  duration,  target  group,  eligible  expenses  etc.).  In  Member  States  where 
qualitative data was not sufficient to determine the factors behind exceptionally high/low 
unit cost, rigorous data verification process ensured that the calculated unit costs reflect 
specific training practices.  

8 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

II. 

SCO FOR EMPLOYMENT SERVICES 

The  EU-level  SCO  for  the  counselling  of  the  unemployed  was  defined  as  an  input-based 
SCO. It establishes a unit cost per one hour of counselling of an unemployed person. This 
SCO covers only the labour costs (including related labour taxes, social contributions and 
compulsory  health insurance)  of  counselling.  It  reflects  the  average  hourly  costs  of  PES 
staff providing counselling services in a particular Member State. 

Although originally intended, we could not determine an output-based EU-level SCO due 
to  the  limited  data  availability.  National  institutions  do  not  collect  the  data  needed  for 
determining  the  costs  incurred  per  output:  depending  on  the  Member  State,  it  is  not 
possible  to  determine  the  number  of  counselling  recipients,  the  length  of  counselling 
services or the expenditures associated with these services. However, the input-based SCO 
could be replaced by an output-based SCO once the data availability issues are resolved, 
e.g. through the PES Benchlearning initiative (in particular, if data on average duration of 
counselling provided per participant were available). 

This SCO was established using data collected from the PES Business Models study for 24 
countries. We have also contacted the national PES to complement and verify PES Business 
Models  study data. For  the remaining four Member States unit costs  were extrapolated. 
Extrapolation  was  conducted  using  ordinary  least  squares  regression  model  that  is 
constructed  using  socioeconomic  indicators  and  unit  costs  calculated  based  on  the  PES 
Business  Models  study  data.  The  calculated  unit  costs  largely  reflect  the  socioeconomic 
differences between the Member States. 

III. 

SCOS FOR PEOPLE IN EMPLOYMENT AND PUBLIC SERVANTS 

Two options to define the EU-level SCO for the in-formal training for people in employment 
were identified as the most feasible. First option is an input-based SCO, which establishes 
a unit cost per participant training hour. Here ‘training’ refers to any type of  non-formal 
training,  of  any  duration,  that  person  undertakes  with  the  purpose  to  obtain  knowledge 
and/or learn new skills for a current or future job, increase earnings, improve job and/or 
career opportunities in the current or another field and generally improve opportunities for 
advancement and promotion. Second option is also an input-based SCO, which establishes 
a unit cost for trainee salary costs per training hour. It supplements Option 1 and can be 
funded only when compliance with state aid rules is ensured. 

For both SCO options unit costs were established using CVTS4 (2010) data for 21 Member 
States. For the remaining seven Member States unit costs were extrapolated using linear 
regression  (OLS)  models  based  on  Eurostat’s  macroeconomic  indicators.  Subsequently, 
calculated values were adjusted to 2015 level using HICP indices. The calculated unit costs 
largely reflect the socioeconomic differences between Member States and stay within the 
range  or are slightly higher than values  of  relevant national unit cost rates and training 
costs implied by historical administrative data collected.  

The study also revealed that using the same unit cost rates for training for public servants 
as those suggested for training of people in employment could be relevant if one accepts 
that the full costs will not be reimbursed. It could also be feasibly used for certain public 
servants  training  operations,  the  training  costs  of  which  are  close  to  average  costs  of 
training for employed persons.  

The potential unit cost values proposed in this study can be updated using the most recent 
CVTS data, which have 2015 as the reference year and is expected to be published in early 
2018. 

9 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

INTRODUCTION 

PURPOSE AND SCOPE OF THE STUDY 

This  report  is  the  final  outcome  of  the  study  “Developing  ‘Off-the-Shelf’  Simplified  Cost 
Options  (SCOs)  under  Article  14.1  of  the  European  Social  Fund  (ESF)  regulation”.  The 
results presented here are intended to support the European Commission in its efforts to 
move beyond Member State-specific SCOs and instead use the empowerment contained in 
Article  14.1  of  the  ESF  regulation  to  devise  EU-level  SCOs  that  can  be  applied  by  any 
Member  State,  in  particular  in  policy  areas,  such  as  training  for  the  unemployed, 
provision of employment services (counselling of the unemployed) and training 
for people in employment (including public servants).  

To  test  the  feasibility  of  various  approaches  for  determining  SCOs  and  calculating  the 
potential unit costs or lump sums, we explored a multitude of data sources, relying mostly 
upon the following: 

  Labour Market Policy (LMP) statistics on labour market interventions implemented 
by  different  Member  States  obtained  from  DG  Employment,  Social  Affairs  and 
Inclusion of the European Commission; 

  LMP-complementary data provided by Member States upon the request of the study 

team; 

  data extracted from other relevant EU-wide studies focusing on Public Employment 

Services in the EU; 

  microdata  of  the  Continuing  Vocational  Education  Survey  (CVTS  4)  on  costs  of 

continuing vocational training incurred by enterprises in the EU; 

  project-level administrative data provided by Member States on operations funded 

by ESF and targeting people in employment.  

The  potential  unit  cost  rates  were  established  and  proposed  for  all  EU  Member 
States.  In  those  cases  where  it  was  not  possible  to  establish  unit  cost  rates  due  to 
unavailable or insufficient data, extrapolation was applied.  

METHODOLOGICAL APPROACH 

The  study  is  largely  based  on  analysis  of  statistical  data  (LMP,  CVTS 4,  Structure  of 
Earnings  Survey  (SES)  and  Labour  Cost  Survey  (LCS)  data,  etc.)  acquired  either  from 
Eurostat or from the European Commission. We also used quantitative data extracted from 
other  ongoing  or  already  completed  relevant  studies,  such  as  the  European  Network  of 
Public Employment Service’s (PES) Business Models study, PES capacity assessment and 
PES  Benchlearning  initiative.  All  this  data  was  thoroughly  cleaned  and  analysed  using 
STATA – a dedicated data analysis and statistical software.  

To  support  and  complement  our  findings  based  on  analysis  of  the  above-mentioned 
statistical data, we also conducted an EU-wide survey of various data handlers at Member 
State  level  (representatives  of  Managing  Authorities  and  Public  Employment  Services, 
members  of  the  Simplification  thematic  network  under  ESF  Transnational  Cooperation, 
etc.). Depending on policy area and Member State, the information collected through e-
forms  and  brief  interviews  ranged  from  metadata  to  complement  the  LMP  data  to 
administrative project-level data on operations supported by ESF in the area of training for 
people  in  employment.  This  helped  the  study  team  to  better  understand  the  national 
context and, where possible, was utilised to verify the proposed SCOs. 

Based  on  analysis  of  the  data  that  was  made  accessible  to  the  study  team,  the  report 
presents  one  calculation  method  to  establish  unit  costs  for  the  unemployed  and  one 
method to determine unit costs for the Employment Services (counselling). Meanwhile for 
training for people in employment, two alternative/complementary methods are presented. 
The  proposed  methods  were  selected  after  considering,  testing  and  eliminating  a  set  of 

10 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

other calculation methods. A detailed definition of each calculation method, including unit 
cost rates proposed and notes on their reliability are provided in parts 2-4 of the report.  

The  key  challenges  faced  by  the  study  team  for  establishing  EU-level  SCOs  were  all 
associated with either challenges in obtaining the data, or with limitations in the quality of 
this data: 

1)  missing information (data gaps) in time series and contamination of the LMP data; 
2)  limited availability of the LMP-complementary data, and a burdensome and time-

consuming data collection process at the Member State level; 

3)  lengthy process to obtain data (CVTS 4) from Eurostat.  

To mitigate and/or overcome the above-mentioned challenges, the study team maintained 
regular contacts with all data holders at EU and national levels; mobilised its resources and 
advanced  in  parallel  with  several  data  collection  activities  to  compensate  for  any  time 
losses; applied relevant extrapolation techniques for countries where data is unavailable 
or  insufficiently  reliable;  constantly  considered  and  explored  alternative  information 
sources  (such  as  other  ongoing  and/or  already  completed  studies)  to  supplement  and 
validate  the  already  available  data,  and  also  triangulated,  whenever  possible,  the  study 
findings, etc.  

STRUCTURE OF THE REPORT 

Structurally, the report is organised into four parts:  

  The  first  part  briefly  presents  the  overall  methodological  approach  applied  within 
this  study.  Here  we  explain  how  data  collection  and  analysis  processes  were 
organised to obtain the data needed for establishing SCOs in all areas covered by 
the study. 

  The  second  and  third  parts  of  the  report  elaborate  on  methods  proposed  for 
calculation  of  SCOs  for  training  and  counselling  (Employment  Services)  of  the 
unemployed. Among other things, here we provide definitions of both the SCO and 
relevant terms, introduce the calculation method in question, elaborate on sampling 
techniques applied and reliability of potential unit cost rates proposed by the study 
and define the audit trail for reimbursement of costs claimed by Member States. 
  Likewise, the fourth part focuses on methods proposed for establishing SCOs in the 
area of training for people in employment, indicating what unit cost rates could be 
set  per  each  Member  State,  explaining  in  detail  how  the  proposed  figures  were 
established and providing instructions how they should be implemented in practice. 

11 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

1.  OVERALL METHODOLOGICAL APPROACH 

In this part of the report, we describe the overall methodological approach adopted in this 
study, focusing mostly on measures undertaken to acquire data needed for  establishing 
EU-level SCOs, and outlining the outcomes of our efforts. More specifically, the following 
chapters provide a brief description of the survey (via e-forms tailored to collect data from 
data holders at the Member State level) and queries for the LMP, CVTS 4 and other data 
issued by our team to assess which calculation methods are feasible and should be pursued 
in the study. 

Since detailed information on cleaning, sampling and processing of data is provided when 
discussing each SCO, in this part of the report we discuss data analysis only in very broad 
terms, outlining and briefly presenting only the key steps of this process.  

1.1.  Data collection 

The  process  of  data  collection  for  this  study  turned  out  to  be  a  highly  challenging  task. 
Factors, such as collection of data during the summer holiday season, lengthy procedures 
to  obtain  some  of  the  statistical  data  due  to  data  ownership  rules,  differences  in 
organisation and scrutiny of data handling practices in the Member States, etc., impeded 
the  progress.  To  mitigate  the  impact  of  these  risks,  the  study  team  adopted  an  agile 
approach to the data  collection process, pursuing availability and exploring suitability of 
multiple data sources at once. Both, the process and outcomes, of our efforts are briefly 
discussed in the following sections.  

LMP DATA 

Labour market policy (LMP) statistics provide information on labour market interventions 
which  are  defined  as  ‘Public  interventions  in  the  labour  market  aimed  at  reaching  its 
efficient functioning and correcting disequilibria and which can be distinguished from other 
general  employment  policy interventions  in  that  they  act  selectively  to  favour  particular 
groups in the labour market.’1 Data available from this database covers public interventions 
which  explicitly  target  groups  of  persons  with  difficulties  in  the  labour  market:  the 
unemployed, persons employed but at risk of involuntary job loss and inactive persons who 
would like to enter the labour market. 

The time series data for the LMP database was collected using the same methodology for 
all Member States, hence it is easily comparable and, therefore, was prioritised over other 
sources of data for the calculation of EU-level SCOs: 

 

 

Interventions classified as ‘training’ (Category 2 in the LMP methodology) were used 
as reference data for determination of SCO for training for the unemployed. Training 
covers  publicly  financed  measures  that  aim  to  improve  the  employability  of  LMP 
target  groups  through  training.  All  training  measures  include  some  evidence  of 
classroom teaching, or if in the workplace, supervision specifically for the purpose 
of  instruction.  Different  types  of  trainings  are  included,  namely:  institutional 
training, workplace training and alternate training. 
Interventions  classified  as  ‘labour  market  services’  (Category  1  in  the  LMP 
methodology)  were  expected  to  be  used  as  reference  data  for  determination  of 
SCOs  for  the  Employment  Services.  However,  due  to  significant  gaps  and 
contamination of data needed for calculations, this approach was found to be non-
feasible.  

1 Eurostat.  

12 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Although  some  of  the  LMP  statistics  are  available  publicly  from  Eurostat,  more  detailed 
data  was  necessary  to  achieve  the  study  objectives.  Hence,  PPMI  issued  a  query  to  DG 
EMPL (as the body responsible for conducting the LMP data collection) and was provided 
with extracts of anonymised data. Due to data ownership rules DG EMPL could not disclose 
the full data to a third party before consulting and acquiring permission from the Member 
States (the final owner of this data). For more details on the LMP data used for establishing 
SCO for the unemployed see Table 1. 

Table 1. LMP data used to inform the development of SCO for the unemployed 

Publicly available LMP data used to 
inform the development of SCO for 
the unemployed 

type of action; 
total expenditure; 

 
 
  number of participants: stock 

(total), entrants, exits; 

operational 

  detailed 

and 
target groups; 
  planned duration; 
 

intervention  start  and  end 
year; 
receipt of cash and non-cash 
benefits 
as 
unemployment benefits); 
source  of  finance  (central 
government, ESF, etc.); 

(such 

 

 

  data 

from  the  qualitative 
of 
(description 

reports 
interventions). 

Anonymised LMP data used to inform the 
development of SCO for the unemployed 

  metadata on expenditure and participants: 
notes  by  data  providers  describing 
quantitative  data  on  expenditure  (formal 
and free); 

  number  of  participants:  stock  (volume, 

FTE), exits to employment; 

  number  of  participants  per  intervention 
broken  down  by  previous  status,  sex, 
unemployment duration, age; 

  average  duration  of  participation  in  an 

intervention; 

  exchange 

  qualitative data about interventions (items 
5-14 of the LMP qualitative questionnaire); 
convert 
rates 
expenditure  data 
the 
Member States (from national currencies to 
euros). 

used 
received 

from 

to 

Source: compiled by PPMI. 

To ensure that our calculations are comparable with current market prices, only the most 
recent data (i.e. for the period 2013-2015) were used to inform our analysis. Originally, 
the LMP database contains information for the period 1998-2015. 

LMP-COMPLEMENTARY DATA 

In  line  with  the  terms  of  reference,  the  survey  of  relevant  data  holders  at  the  Member 
State  level  was  conducted  using  e-forms  tailored  specifically  for  this  task.  Originally 
intended to serve as an alternative data source, these e-forms were used to validate and 
complement the LMP data: the contact persons identified in each Member State were asked 
to provide (if available) the following additional data and metadata: 

  LMP data for 2016; 
  data  on  volume  (duration  of  training/counselling  received  by  participants  or 

provided to participants) of relevant interventions; 

  data on exits excluding drop-outs; 
  data on expenditure excluding cash and non-cash benefits; 
  method to record expenditure; 
  method to validate the completion of training received by participants. 

The full-scale collection of LMP-complementary data on training for the unemployed and 
Employment Services was launched on 15 September 2017. Invitations to cooperate were 
primarily addressed to liaison persons at PES (identified by the PES Network Secretariat), 
national contact points for LMP data and contacts identified as data providers by members 
of the Simplification Thematic Network (hereinafter referred to as ‘TNC’). Overall, our aim 

13 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

was  to  establish  direct  contact  with  either  data  holders,  or  people  in  national  ministries 
responsible for handling the relevant data.  

A detailed scheme illustrating how the data collection was organised is provided in Figure 
1.  

Figure 1. Simplified data collection process: data on training for the unemployed 
and Employment Services 

Source: compiled by PPMI. 

Our team maintained contacts with the Member States until mid-November, resulting in 
replies with partially completed e-forms from more than a half of Member States – at least 
some additional data on training for the unemployed and Employment Services has been 
received  from  respectively  18  and  16  countries.  However,  in  most  of  the  cases  it  was 
limited to metadata (e.g. method to record expenditure) and LMP data for 2016. Only a 
few Member States actually sent us the data on duration of training/counselling received 
by participants or provided to participants by responsible bodies. As a result, we used this 
information  to  improve  our  understanding  of  the  national  interventions  and  learn  more 
about  the  quality  of  data  reported  in  LMP,  instead  of  utilising  it  to  directly  inform  our 
calculations. 

DATA EXTRACTED FROM OTHER STUDIES 

According to the terms of reference, one of the initial aims of this study was to establish 
an output-based SCO for the Employment Pathway. Employment Pathway can be defined 
as an integrated collection of employment services intended to help the unemployed person 
to find a job. A single SCO for the pathway to work would group these employment services 
under one single unit cost payable on the basis of milestones (intake and orientation, skills 
audit, training, exit, and job placement).  

However,  a  thorough  analysis  of  the  data  available  from  LMP  and  collected  from  the 
Member  States  revealed  that  establishing  an  output  or  even  input-based  SCO  for 
Employment Pathway is not feasible due to data quality issues and conceptual challenges 
faced by the study team in this policy area: 

1)  a common definition for ‘Employment Pathway’ is lacking at EU level; 
2)  the definition of information services and individual case management (two main 
sub-categories of ‘labour market services’ in the LMP database) is relatively broad, 
allowing for a large variation in the content of interventions; 

3)  the importance attributed to the two types of interventions mentioned above vary 
substantially across Member States and, more importantly, interventions within the 
same  sub-category  differ  significantly  in  terms  of  content,  budget,  duration  and 
target groups; 

4)  it is not possible to take account of the full spectrum of services in each Member 
State due to gaps in the time series data available for relevant interventions; 

14 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

5)  some  Member  States  (e.g.  the  Netherlands,  Austria,  Sweden  and  Finland)  have 
informed  the  study  team  that  they  use  ESF  funding  to  finance  non-typical 
interventions or allow great flexibility in their design for regional/local level.  

As there is no  common  definition for ‘Employment Pathway’  in the EU,  it was agreed to 
establish  a  SCO  for  the  main  type  of  employment  services,  namely,  counselling  of  the 
unemployed.  This  SCO  could  be  used  to  cover  costs  related  to  counselling  of  the 
unemployed  until  an  agreement  on  a  common  definition  for  ‘Employment  Pathway’  is 
reached. 

Furthermore, PES websites and a few other ongoing and/or already completed studies were 
explored  as  alternative  sources,  aiming  to  overcome  the  above-outlined  difficulties  and 
establish at least an input-based SCO until relevant data is available for setting an output-
based SCO. 

PES Benchlearning and 
PES capacity assessment 

PES business models study  PES websites 

Per Member State in 
the period 2014-2017: 

Per Member State in the 
period 2009-2014: 

Per Member State in the 
period 2013-2016: 

  total PES staff costs; 
  total number of PES 

staff; 

  total number of PES 

staff (FTE). 

  total PES 

expenditure; 

  PES expenditure on 

benefits; 
  total PES 

expenditure without 
benefits 
(calculated); 

  total number of PES 

staff (in FTE); 

  total number of job-
seeking clients. 

  total PES 

expenditure; 

  total PES staff costs; 
  total number of PES 

staff; 

  number of PES staff 

at head 
office/regional 
offices/local offices; 
  total number of job-
seeking clients. 

Source: compiled by PPMI. 

The possibility of merging the data available from these sources was carefully tested, yet 
in  most  of  the  cases  this  proved  to  be  non-feasible  due  to  mismatches  between  the 
overlapping  figures.  As  a  result,  our  calculations  (and  extrapolation  for  those  Member 
States where data is missing) of the input-based SCO for Employment Services is largely 
based on data extracted from the PES business models study. See part 3 of the report for 
more details. 

CVTS 4 DATA 

The main data source for determining the EU-level SCOs for non-formal training for people 
in  employment  is  the  Continuing  Vocational  Training  Survey  (CVTS 4).  CVTS 4  contains 
statistically  reliable,  comparable  and  regularly  updated  enterprise-level  data  on  costs  of 
continuing vocational training courses in all EU Member States. Importantly for this study, 
information such as the cost of CVT courses per training hour, structure of costs and hours 
in  CVT  courses  per  participant  can  be  extracted  from  CVTS 4.  However,  the  publicly 
available CVTS 4 data was not sufficient to this end, as it informed only on training costs 
in PPS (purchasing power standard) at the level of Member States, NACE Rev.2 or size of 
an enterprise. Furthermore, the data was insufficient for exploring the variation of costs 
across the most relevant types of trainings at country or enterprise levels. 

Hence, PPMI applied to Eurostat to gain access to CVTS 4 microdata. The official approval 
of  our  application  on  20  September  was  followed  by  consultations  with  the  national 
statistical authorities in Member States to gain their agreement on sharing the data. The 

15 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

files  containing  partially  anonymised  data  (scientific-use  files)  reached  our  team  on  7 
November.  

Notably,  CVTS  4  microdata  does  not  cover  the  following  eight  Member  States:  Austria, 
Greece, Hungary, Ireland, Italy, Latvia, the Netherlands and Slovenia. However, standard 
datasets for the remaining 20 countries are sufficient to calculate both input- and output-
oriented SCOs for training for people in employment and to extrapolate unit cost rates for 
the  remaining  Member  States.  For  more  details  on  the  CVTS  data  sample  used  for 
calculations see part 4 of the report.  

ADMINISTRATIVE DATA ON RELEVANT ESF OPERATIONS 

Due to uncertainty over the availability of the CVTS 4 microdata, we conducted a survey 
of data holders at the Member States level via e-forms tailored to collecting administrative 
data on relevant ESF operations in parallel. Both e-forms (one for operations involving non-
formal training for people in employment and another for operations providing training for 
public  servants)  were  piloted  with  authorities  of  Czechia,  Latvia  and  Lithuania,  before 
circulating the survey in all Member States. 

The full-scale collection of data on training for people in employment and public servants 
was launched on 18 September 2017. Invitations to cooperate and provide us with data 
for the development of SCOs were primarily addressed to members of TNC or other contact 
persons identified by the study team. A detailed scheme illustrating how this process of 
data collection was organised is provided in Figure 2.  

Figure  2.  Simplified  data  collection  process:  data  on  training  for  people  in 
employment and training for public servants 

Source: compiled by PPMI. 

Simplified data collection process: data on training for people in employment and training 
for public servants  Overall,  data of  varying volume and quality on training for people in 
employment  was  received  from  12  countries/regions:  Austria,  Belgium  (Flanders), 
Bulgaria,  Cyprus,  Estonia,  Germany  (Bremen  and  Hamburg),  Greece,  Ireland,  Poland, 
Portugal,  and  Slovenia.  Also,  at  least  some  data  on  training  for  public  servants  was 
obtained  from  seven  countries/regions  –  Bulgaria,  Cyprus,  Estonia,  Germany  (Bremen), 
Greece, Poland and Portugal. The remaining countries/regions either did not respond, or 
mentioned the following reasons as to why the requested data could not be provided: 

  data is not available at the detail required for our calculations; 
  data  cannot  be  retrieved  in  an  electronic  format  and  manual  collection  is  not 

feasible; 

  data is not reliable and cannot be used for the development of SCOs. 

Due to the low coverage and significant variation in quality of the administrative data 
provided by Member States, the study team used it only for verification of the SCOs for 
people in employment based on the CVTS 4 microdata.  

16 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

1.2.  Data processing and analysis 

The data processing and analysis phase of this study involved the following key steps: 

  data cleaning to eliminate any irrelevant and bad data (e.g. duplicates, missing 
values),  as  well  as  identify  and  remove  from  the  analysis  the  most  prominent 
outliers; 

  exploratory  analysis  to test the  feasibility of different methods for  establishing 

SCOs; 

  calculation  of  potential  unit  cost  rates  and  extrapolation  of  SCO  values  in 

Member States where data is insufficiently reliable or unavailable; 

  verification of the potential unit cost rates to ascertain if they make sense based 
on the multivariate analysis of various socioeconomic development comparators. 

A detailed description of samples of interventions/operations used for establishing SCOs, 
as well as data cleaning techniques and unit cost rate calculation methods applied in this 
study is provided in parts 2-4 of the report. 

17 

 
 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

2.  SCO FOR THE UNEMPLOYED 

2.1.  Cost of a successful exit from an intervention 

2.1.1.  Definition of the SCO 

This is an output-based SCO, where a  ‘successful exit’ refers to a participant leaving an 
intervention and obtaining a certificate, accreditation or other national measure providing 
sufficient assurance that his/her training was successfully completed (based on a national 
practice of a Member State). Participants may exit an intervention (a non-formal VET type 
training course which has identifiable participants and incurs expenditure) more than once, 
i.e.  a  successful  exit  does  not  have  to  be  unique.  Furthermore,  if  a  participant  receives 
multiple  certificates  for  completing  different  training  course  modules  within  the  same 
intervention, it should be counted as a single successful exit from an intervention. Although 
interventions are typically organised in the framework of the PES, they can also be provided 
on another basis, so long as a proof of training completion is available and is recognised 
by the PES. These interventions typically involve non-formal training, with a duration up 
to 12 months (though not exclusively). 

2.1.2.  Method to determine and update the amounts 

2.1.2.1.  Data sources  

LMP statistics are the key source of data used for establishing this SCO. Developed by DG 
EMPL and disseminated by Eurostat, the LMP database is the most comprehensive source 
of statistically validated data on public interventions in the labour market.  

Based on a thorough analysis of both the LMP database and the methodology applied to 
collect  the  LMP  data,  we  concluded  that  our  calculations  should  be  based  on  data  for 
interventions  classified  as  ‘training  measures’  (Category  2  in  the  LMP  methodology). 
Training measures, by definition, cover all publicly financed measures that aim to improve 
the employability of LMP target groups through training. All training measures include some 
evidence  of  classroom  teaching  (might  be  blended  with  online  training,  but  cannot  be 
delivered completely online), or if in the workplace, supervision specifically for the purpose 
of  instruction.  Different  types  of  trainings  are  included,  namely  institutional  trainings, 
workplace trainings, alternate trainings. The scope of our dataset is limited primarily to the 
interventions that explicitly target groups of persons with difficulties in the labour market – 
the  unemployed  or  the  inactive  (6.1-6.3  operational  target  groups  in  the  LMP 
methodology).  

As  mentioned  in  Chapter  1.1,  only  some  of  the  LMP  data  is  accessible  publicly  from 
Eurostat. Our team has extracted the following data from this source: 

total expenditure per intervention; 
total expenditure per Member State; 

 
 
  number of exits per intervention. 

In addition, we utilised the following data provided by DG EMPL: 

  metadata  on  expenditure  and  participants:  notes  by  data  providers  describing 

quantitative data on expenditure (formal and free); 
  average duration of participation in an intervention; 
  qualitative  data  about  interventions  (items  5-14  of  the  LMP  qualitative 

questionnaire). 

To minimise the impact of short-term socioeconomic fluctuations and mitigate the risk of 
data irregularities (e.g. in countries where expenditure is recorded on a ‘cash basis’ and, 
therefore,  is  not  aligned  with  participant  data),  our  analysis  encompasses  data  from  a 

18 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

three-year period, covering the years 2013-2015. Data for 2016 was not included because 
it was not yet available for most of the Member States, and, even where available, it was 
not yet verified by Eurostat. However, in those cases where data for 2016 was available, 
we used it to verify whether any major changes have occurred, especially in terms of the 
budget size or the number of participants.  

For  countries  where  LMP  data  was  insufficient  or  inaccurate,  unit  cost  rates  were 
extrapolated. The  regression model utilised for this purpose has been constructed using 
statistical indicators extracted from Eurostat’s databases and unit costs calculated for those 
Member States where LMP data was sufficient. The following indicators were used: 

1)  GDP per capita in purchasing power standards (PPS) (2014-2016); 
2)  annual average unemployment rate (2014-2016); 
3)  comparative  price  levels  (of  final  consumption  by  private  households  including 

indirect taxes) (2014-2016); 

4)  EU-SILC Survey median income by household type (2014-2016). 

2.1.2.2. 

Sample and quality of data 

The final data sample was constructed using the LMP data for 26 Member States: for the 
United Kingdom, the LMP data was not available after 2011 and for the Netherlands the 
LMP  data  misrepresent  their  typical  training  practices  (as  pointed  out  by  the  Managing 
Authority). To ensure the quality of data included in the sample, we applied a two-round 
data cleaning process. 

First round of data cleaning. The initial data sample included all interventions available 
in the LMP database for the 2013-2015 period. However, to address certain data availability 
and  reliability  issues  identified  by  the  study  team,  the  following  measures  were 
undertaken: 

1)  elimination of duplicate interventions; 
2)  elimination of interventions with missing data; 
3)  elimination of interventions with insufficient data (data available for 1 year only); 
4)  elimination of interventions classified as type “support for apprenticeships;”2 
5)  analysis  of  notes  from  data  providers  in  Member  States  and  elimination  of  the 

interventions which were found to have unreliable data; 

6)  verification  of  consistency  of  the  accounting  methods  used  in  different  Member 
States.  Some  interventions  had  to  be  eliminated  as  the  methods  used  differed 
significantly from the ones described in the LMP methodology; 
7)  verification of double accounting and fixing of identified issues; 
8)  elimination of outliers based on the 1.5 inter-quartile range rule. 

As a result, our sample decreased from 216 to 135 interventions. These changes, however, 
did  not  have  a  significant  impact  on  the  representativeness  of  our  data  sample  – 
interventions retained in the sample account for more than 60% of the overall budget of 
interventions reported by 22 out of 23 countries for which LMP data is available.  

Notably, some of the data used in the calculations (e.g. expenditure figures and number 
of exits from an intervention) was flagged in the LMP database as ‘estimated.’ According 
to  the  LMP  database  manual,  Member  States  are  required  to  provide  estimates  when 
relevant  factual  data  is  not  available.  Among  others,  data  on  planned  budget  figures 
submitted  instead  of  historical  data  was  flagged  as  estimated.  Some  Member  States 
explained  why  only  estimated  figures  could  be  provided  and  described  the  estimation 
method in the metadata (notes). As indicated in the description of the first round of data 

2 Eliminated to avoid duplication because expenditure on apprenticeships is eligible to be reimbursed on the basis 

of other EU-level standard scales of unit costs. 

19 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

cleaning, we have analysed these notes and excluded any unreliable data from our data 
sample.  The  remaining  estimated  data  was  reliable  enough  to  be  included  in  the 
calculations (e.g. were estimated on data from the last year; estimated on expenditure for 
similar interventions; the budget was divided between interventions based on the number 
of participants, etc.). We have also asked Member States to provide more accurate data if 
possible, but none of them could. 

Second  round of  data  cleaning.  To  verify  the  unit  costs  established  from  the  sample 
obtained  after  the  first  round  of  data  cleaning,  we  checked  how  they  compare  across 
Member  States  that  are  similar  in  terms  of  their  socioeconomic  development.  Member 
States were grouped into clusters using a hierarchical clustering technique. However, since 
we  observed  a  rather  significant  variation  of  unit  costs  calculated  for  Member  States 
belonging  to  the  same  cluster,  qualitative  information  about  interventions  in  ‘outlier’ 
countries was utilised to inform the second round of data cleaning. As a result of cleaning, 
the data sample decreased to 120 interventions, but its coverage remained sufficient to 
ensure  high  representativeness  of  interventions  reported  in  the  LMP  database: 
interventions retained in the data sample account for more than 60% of the overall budget 
of interventions reported by 21 out of 23 countries for which LMP data is available. The 
second round of data cleaning included the following steps: 

1)  elimination of the interventions whose average duration exceeds 12 months;3 
2)  elimination of interventions whose costs were found to be unnaturally high/low due 
to the type of implemented activities (e.g. interventions involving formal education 
or online training activities); 

3)  elimination of interventions whose costs were found to be unnaturally high/low due 
to  the  specific  group  targeted  by  these  interventions  (e.g.  health  specialists, 
engineers). 

Information  on  changes  in  the  overall  size  of  the  data  sample,  number  of  interventions 
included  in  calculations  for  different  Member  States,  and  information  on  coverage/ 
representativeness of these samples are presented in Table 2. Even though the number of 
interventions  per  Member  State  varies  significantly,  this  should  not  be  interpreted  as  a 
limitation of the sample. The variance of sample sizes is determined by differences in the 
national  practices  for  planning  and  administering  of  interventions/  programmes.  Some 
countries differentiate their interventions/programmes on the basis of their target groups 
(and thus typically have a large number of interventions), whereas others have a single 
intervention  that  encompasses  all  target  groups  at  once.  Thus,  to  check  the 
representativeness of the samples, a more suitable method is to compare the share of the 
budget covered by interventions included in the sample. Budget coverage is calculated by 
dividing  the  total  expenditure  for  interventions  included  in  the  sample  by  the  total 
expenditure  for  trainings  (includes  all  interventions  in  category  2)  reported  by  each 
Member State in the LMP database. 

Table 2. Changes in sample size after data cleaning 

Country 

Initial 
sample 

AT 

BE 

BG 

11 

14 

14 

Sample 
after 
cleaning 
7 

1st 

Coverage 
after 
cleaning 
89% 

1st 

10 

10 

67% 

71% 

Sample  after 
2nd cleaning 

Coverage  after 
2nd cleaning 

4 

5 

10 

78% 

49% 

71% 

3  This  step was  skipped  in  the  case  of  Germany because  long  interventions  appear  to  be  a  part  of  the  typical 
training practice in this country and do not distort the calculations of a unit cost. Furthermore, since data on 
duration  was  not  available  in  the  LMP  database  for  some  of  the  interventions  reported  by  other  Member 
States,  there  is  a  small  chance  that  a  small  number  of  interventions  whose  duration  was  longer  than  12 
months were included in the final sample used for calculations.  

20 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country 

Initial 
sample 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

10 

2 

18 

1 

3 

11 

11 

7 

11 

10 

2 

15 

3 

1 

3 

7 

7 

3 

9 

16 

2 

8 

14 

3 

0 

Sample 
after 
cleaning 
7 

1st 

Coverage 
after 
cleaning 
97% 

1st 

1 

12 

1 

2 

0 

8 

4 

8 

10 

1 

11 

0 

1 

2 

5 

0 

0 

6 

9 

1 

8 

8 

3 

0 

100% 

66% 

97% 

100% 

N/A 

77% 

97% 

65% 

99% 

99% 

94% 

N/A 

100% 

81% 

95% 

N/A 

N/A 

94% 

77% 

92% 

100% 

85% 

100% 

N/A 

Sample  after 
2nd cleaning 

Coverage  after 
2nd cleaning 

6 

1 

12 

1 

2 

0 

7 

3 

8 

10 

1 

11 

0 

1 

2 

5 

0 

0 

5 

9 

1 

7 

6 

3 

0 

70% 

100% 

66% 

97% 

100% 

N/A 

77% 

65% 

65% 

99% 

99% 

94% 

 N/A 

100% 

81% 

95% 

N/A 

N/A 

90% 

77% 

92% 

95% 

83% 

100% 

N/A 

TOTAL 

216 

135 

120 

Source: compiled by PPMI based on data extracted from the LMP database and provided by the Member States. 

2.1.2.3.  Analysis 

Two different calculation methods were applied to establish the cost of a successful exit 
from an intervention targeting the unemployed. For Member States where LMP data was 
available, the unit cost was calculated using the formula below:  

SCO1=

∑

∑

2015
𝑦=2013
2015
𝑦=2013

(Expy∗W)
(Party∗W)

, where 

Expy - expenditure per intervention in the reference year Y; 
Party - number of ‘certified/accredited exits’ per intervention in the reference year Y; 
W  -  weight  used  to  equalise  the  differences  in  the  number  of  observations  per 
intervention. 

Expenditure. The LMP database collects data on the public expenditure associated with 
each  intervention.  According  to  the  LMP  methodology,  expenditure  should  cover  all 
transfers  and  foregone  revenue  provided  to  the  direct  recipients  as  a  result  of  the 
intervention. This expenditure may include expenditure in the form of: 

21 

 
 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

 

 

transfers  of  cash  payments  (lump  sums,  periodic  payments  to  individuals, 
employers or service providers) or reimbursements; 
the value of directly provided goods and services. The value of services may relate 
to  the  costs  of  purchasing  services  from  third  party  providers  or  the  costs  of 
internally  provided  services  where  there  is  no  explicit  transfer  (e.g.  costs  of  PES 
staff time and related overheads); 

  amounts of revenue foregone through reductions in obligatory levies (taxes or social 
contributions that governments would have otherwise collected if a person did not 
participate in the intervention.). 

According to the LMP methodology, expenditure should be recorded on an accruals basis, 
i.e. measured at the time that the events creating related claims and liabilities occur. This 
is  important  for  ensuring  the  link  between  the  expenditure  and  participant  data. 
Unfortunately, a significant number of the analysed countries collect information only on a 
cash basis. Therefore, to ensure that participant data relates to the expenditure data, we 
have analysed the total costs that were incurred in a three-year period (2013-2015). This 
approach minimises inconsistencies between the expenditure and participant data. 

Certified/Accredited Exits – Participants. This refers to the number of participants per 
intervention  who  successfully  completed  a  certified,  accredited  or  otherwise  formally 
recognised (by the PES) training course(s) and exited an intervention in the reference year. 
By 'certified' we mean that the institution providing training issues a form of certificate to 
prove the participant has successfully completed his/ her training. By 'accredited,' we mean 
that the success of training has been validated by an independent body responsible for its 
accreditation.  National  practices  of  certification  and  accreditation  may  differ,  but  should 
serve as proof of a successful completion of a training. Exits do not have to be unique i.e. 
a unique participant may exit an intervention more than once.  

Notably, 25 out of 28 Member States contacted by our team did not provide us with data 
on the number of ‘certified/accredited exists.’ Member States could not distinguish between 
successful  (here  the  successful  exit  is  understood  as  an  exit  from  an  intervention  after 
successfully completing one’s training) and an unsuccessful (here the unsuccessful exit is 
understood  as  a  drop-out  from  an  intervention,  i.e.  a  participant  who  has  left  an 
intervention  without  completing  their  training)  exits  (except  for  Lithuania,  Portugal  and 
Slovakia). Therefore, we used LMP data, in particular the number of ‘exits,’ as the closest 
approximation of ‘certified/accredited exists’ to establish the unit costs. ‘Exits’ refer to the 
total number of participants who have left an intervention during the year, i.e. the outflow 
irrespective  of  the  reason  for  leaving.  Persons  who  leave  early  (drop-outs)  are  counted 
equally with participants that complete their training. 

Weight. The number of available observations (i.e. the number of years for which relevant 
data is available) per one intervention differs. A simple arithmetic average would result in 
a unit cost where interventions with more observations would have a larger impact on the 
average. Thus, to eliminate this bias we are using weighted averages. Weights are assigned 
to each intervention based on the number of observations available. 

For countries where LMP data  was not available  or appeared to lack  reliability, we have 
determined  the  unit  cost  using  a  linear  extrapolation  method.  Linear  extrapolation  uses 
the ordinary least squares (OLS) regression model to predict missing values based on the 
available data. OLS regression modelled the relationship between the unit costs calculated 
using the formula presented above and the indicators presented in chapter 2.1.2.1. Linear 
regression may only be used when the relationship between variables in the model is linear. 
Our model had a sufficiently good fit (R2=91%) to yield credible extrapolation results. 

2.1.2.4.  Results 

The  potential  unit  cost  rates  for  training  of  the  unemployed  are  presented  in  Table  3. 
Applying  the  calculation  method  described  above,  unit  costs  were  determined  for  23 

22 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

countries. The calculated unit costs largely reflect the clustering patterns observed when 
comparing  Member  States  based  on  selected  socioeconomic  indicators  mentioned  in 
section 2.1.2.1. However, a few deviations can be observed. For some Member States (e.g. 
Germany,  Hungary  and  Ireland),  it  can  be  explained  by  the  specific  training  practices 
evident  from  the  available  qualitative  data  (e.g.  longer  duration,  specific  target  groups, 
training  method,  etc.).  In  other  countries,  especially  where  a  few  large  interventions 
encompass  all  trainings  organised  for  the  unemployed  in  the  country  (e.g.  Estonia, 
Hungary, and Lithuania), qualitative data is insufficient for determining the factors behind 
exceptionally high/low unit costs. Nevertheless, considering the rigorous data verification 
process  that  the  data  in  the  sample  has  undergone,  we  conclude  that  these  unit  costs 
reflect the specific training practices in those Member States.  

Extrapolated unit cost values were established for seven Member States. It was not feasible 
to determine a unit cost for the United Kingdom because the latest data available from the 
LMP database for this country was for 2011. After two rounds of data cleaning, LMP data 
for  Italy was found to  be insufficient to inform the calculations. Meanwhile LMP data for 
other  three  Member  States  was  not  representative  of  their  typical  training  practices 
(Greece, Malta and the Netherlands) or was under revision by the Member States (Greece 
and Malta). For more information see the footnotes. The study team has also extrapolated 
unit costs for Croatia and Romania even though calculations based on the LMP data were 
feasible.  This  was  done  because  calculated  values  raised  suspicion  as  to  whether  they 
represent the actual costs of typical training practices in Croatia and Romania.  

Although the unit costs calculated for Germany, Hungary and Ireland stand out from unit 
costs  in  other  countries  in  their  clusters,  such  variation  can  be  explained  by  training 
practices specific to these countries:  

 

typical interventions in Germany are characterised by long duration (12 months and 
over).  As  a  result,  if  Germany  adopted  the  EU-level  SCO,  the  requirement  for 
duration of training (up to 12 months spent within an intervention) should not be 
applied to this country; 

  a large share  of training courses in Ireland target specific target groups, such  as 

the socially excluded, LTU, youth, etc.; 

  expenditure on training for the unemployed in Hungary, in addition to training costs, 
includes income compensation and support for employers involved in training of the 
disabled. 

Table 3. Unit cost rates  

Country 

First cleaning, EUR 

Second cleaning 

Extrapolated values, EUR 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL4 

ES 

FI 

1837 

2525 

596 

3339 

521 

6959 

5803 

711 

2774 
6814 

2277 

3351 

596 

2696 

521 

6959 

5803 

711 

2772 

5885 

2064 

4 Data under revision by Member State during the study period. 

23 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country 

First cleaning, EUR 

Second cleaning 

Extrapolated values, EUR 

FR 

HR5 

HU 

IE 

IT6 

LT 

LU 

LV 

MT7 

NL8 

PL 

PT 
RO9 

SE 

SI 

SK 

UK10 

6274 

4299 

1818 
11 119 

1359 

19 302 

756 

608 
994 

53 

7512 

822 
424 

6274 

4299 

1818 

11 119 

1359 

19 302 

756 

594 

994 

53 

7303 

854 

424 

689 

3676 

2256 

5018 

583 

5863 

Source: compiled by PPMI based on data extracted from the LMP database and provided by Member States 

2.1.2.5.  Audit trail 

The audit trail for this EU-level SCO is presented below. 

Audit trail 

Types of 
operations 

Training of the unemployed.  

Training  is  a  non-formal  VET  type  training  course,  which  has 
identifiable  participants  and  incurs  expenditure.  All  training 
measures  have  to  include  some  evidence  of  classroom  teaching 
(might  be  blended  with  online  training,  but  cannot  be  delivered 
completely online), or if in the workplace, supervision specifically 
for the purpose of instruction. 

Indicator name 

Exit from an intervention upon successful completion of a training. 

Exit  from  an  intervention  refers  to  an  exit  after  completing  a 
training. A participant may  exit an intervention more than once, 
i.e.  the  number  of  successful  exits  does  not  have  to  equal  the 
number of unique participants who have exited an intervention. 

5 Expenditure composition of the largest intervention (90% of the budget) has changed in 2013, thus expenditure 

fluctuated significantly in 2013-2015. 

6 LMP data availability is limited to two interventions and both of them fall under the category of apprenticeships. 
7 LMP data are not representative of typical trainings for the unemployed and are under revision by the Member 

State. 

8 LMP data represent only a part of the trainings available for the unemployed and differ significantly from the 

trainings financed by the ESF. 

9 When the rate is compared to administrative data for training used to develop separate unit costs, there is a 

significant divergence, while the extrapolated rate is comparable.  

10 LMP data not available after 2010. 

24 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail 

‘Successfully completed training’ refers to completion of a training 
when  a  certificate,  accreditation  or  other  national  measure 
providing sufficient assurance that the participant has completed 
a training has been obtained (based on the national practice of the 
Member  State).  More  than  one  training  may  be  completed 
successfully when exiting an intervention, but it should be counted 
as one successful exit. 

Category of costs  All  eligible  costs  of  the  training  operation  (direct  and  indirect 
training costs) eligible under ESF regulation. 

Measurement 
unit for the 
indicator 

Number  of  exits  after  successful  completion  of  a  training  with  a 
certificate/an  accreditation  (or  another  equivalent  national 
measure  proving  completion  of  a  training)  during  a  reference 
period. If a participant receives multiple certificates for completing 
different training course modules within the same intervention, it 
should be counted as a single successful exit from an intervention. 

Specific 
requirements for 
the audit trail 
and justification 
of achievement 
of SCOs 

Key risks and 
measures to 
prevent 
‘creaming’ of 
participants and 
perverse 
incentives 

Managing Authorities and intermediary bodies, taking into account 
relevant  national  practices,  must  ensure  the  availability  of  proof 
that an output was delivered.  

The aggregate number of exits reported to the Commission should 
be  traceable  to  separate  trainings  and  participants.  Sufficient 
documentary proof for each participant is necessary for: 

(1)  proof  of  an  exit  from  an  intervention  (e.g.  a  register  of 
participants indicating interventions one has exited, a register of 
interventions indicating participants who have exited, etc.); 

(2)  proof  of  a  successfully  completed  training  (e.g.  a  certificate, 
an  accreditation  or  other  national  measure  providing  sufficient 
assurance that the participant has successfully completed his/her 
training)  

(3)  proof  of  being  registered  or  eligible  for  a  training  based  on 
national eligibility rules (e.g. extracts from PES register). 

Applying an output-based SCO to reimburse the funds to Member 
States  for  training  for  the  unemployed  is  associated  with  the 
following risks: it provides an incentive to increase the number of 
exits by organising shorter training courses/ counselling services 
for  the  same  price;  it  might  encourage  slicing  up  operations 
(generating  more  exits  by  funding  several  smaller  operations 
instead of one bigger operation); it provides an incentive to change 
practices  related to the definition of an exit; it might lock-in the 
existing  practices  (especially  in  Member  States  where  unit-cost 
values are low due to their current focus on short trainings offered 
to large quantities of unemployed persons).  

These risks could be mitigated by reimbursing only successful exits 
that  would  be  proved  by  a  certificate  or  an  accreditation.  The 
preventive  strength  of  this  measure,  however,  depends  on 
national  practices  as  in  some  Member  States  changing  of  the 
certification  or  accreditation  practice  might  be  relatively  easy. 
Another measure to address these risks could be the introduction 

25 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail 

Adjustment of 
amounts 

of  a  result-orientation  requirement.  Achieving  results  might  be 
encouraged either by withholding a certain percentage of the cost 
until a result has been  achieved or by applying a ‘top-up’ to the 
amount  when  a  specific  condition,  such  as  a  change  of  the 
participant’s  status  from  ‘unemployed’  to  ‘employed,’  has  been 
fulfilled  (in  accordance  with  the  proposal  in  Common  Provisions 
Regulation  (CPR)  for  payments  based  on  the  fulfilment  of 
conditions). 

Amounts can be adjusted using the data submitted by the Member 
States to the LMP database. Although LMP statistics are updated 
annually, data analysis has not revealed any significant unit cost 
changes  during  a  period  of  one  year.  Furthermore,  due  to  their 
national accounting practices, some Member States tend to revise 
the  submitted  data  during  the  following  year.  To  minimise  the 
uncertainty for Member States, annual adjustment of the amounts 
should be avoided.  

2.1.3.  Insights on application of this SCO 

Unit cost rates have been calculated or extrapolated for all Member States with a sufficient 
reliability. Hence, it is possible to set an EU-level SCO for training for the unemployed in 
all Member States based on the results presented in section 2.1.2.4.  

The audit trail for this SCO should be feasible without any major administrative changes 
as  analogous  data  (with  an  exception  of  the  indicator  on  success  of  an  exit)  is  already 
being  collected  by  the  Member  States  to  inform  the  LMP  database.  If  certification  or 
accreditation  practices  are  applied  on  a  national  or  regional  level,  such  data  should  be 
easily available for reporting. 

Risks that Member States would be over-compensated using this SCO are minimised by 
the requirement to claim the expenditure only for certified or accredited exits. If combined 
with  a  condition/requirement  to  achieve  concrete  results  (i.e.  exit  from  an  intervention 
should lead to employment), this SCO would become more resistant to perverse effects. 
As described in the previous section, this could be achieved either by withholding a certain 
percentage of the cost until the result has been achieved or by applying a payment based 
on conditions fulfilled (as being currently considered for the new CPR). 

26 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

3.  SCO FOR EMPLOYMENT SERVICES 

3.1. 

 Cost per counselling hour 

3.1.1.  Definition of the SCO 

This is an input-based SCO that reflects the average hourly direct labour costs of PES staff 
providing  counselling  services  in  a  particular  Member  State.  Counselling  services  are 
understood as employment services performed by case handlers that help job-seekers to 
find  employment  (for  example,  intake  and  orientation,  skills  audit,  etc.).  All  counselling 
interventions are organised in the framework of PES. 

3.1.2.  Method to determine and update the amounts 

3.1.2.1.  Data sources 

Country fiches produced by the PES Business Models study are the key source of data used 
for establishing this SCO. Additionally, to verify and collect data that was missing from the 
fiches we contacted 11 PES. In total, we received answers from PES contacted in Bulgaria, 
Cyprus, Estonia, Finland, France, Latvia, Slovakia and the United Kingdom. 

The  PES  Business  Models  study  is  the  most  comprehensive  data  source  that  contains 
information  about  PES  staff  costs  and  number  of  employees  for  the  period  2013-2014. 
Although  originally  intended,  we  did  not  use  the  PES  Benchlearning  and  PES  Capacity 
Questionnaire data in our analysis. Notably, the data obtained from the PES Benchlearning 
and PES Capacity Questionnaire was insufficient to calculate the cost per counselling hour 
(this calculation method is explained in the sub-section below). Furthermore, we could not 
integrate data obtained from the latter sources and country fiches as these data sources 
turned out to be incomparable. 

The purpose of the PES Business  Models study was to examine how  PES are organised, 
their main tasks, the scope of their remit, clients and services and PES Business Models. 
This  study  was  an  update  of  the  previous  study  on  PES  Business  Models  undertaken  in 
2011.11 The study was based on the analysis of information provided by 30 PES through a 
questionnaire completed between February and May 2014. All EU PES submitted completed 
questionnaires.  As  indicated  in  the  study  report,  the  quality  of  responses  was  generally 
high. However, some country fiches were incomplete. 

As  a  result,  we  contacted  PES  to  receive  the  missing  data.  Inquiries  were  circulated  on 
5 January 2018 with a request to provide the following information: 

  PES annual expenditure on PES staff costs in EUR (a total for PES head office and 
regional/local offices) (expenditure includes only direct labour costs: wages, payroll 
taxes, medical and social insurance, etc.); 
total number of PES staff (a total for PES head office and regional/local offices); 
total number of PES staff in full-time equivalent (FTE) (a total for PES head office 
and regional/local offices). 

 
 

The last answers were received on 19 January 2018. Aside from Denmark, Ireland, Italy 
and the Netherlands, the missing data was submitted by all other PES contacted by our 
team.  Thus,  we  applied  extrapolation  to  establish  the  unit  cost  values  for  these  four 
countries.  Our  extrapolation  approach  is  discussed  in  the  following  sub-sections.  It  was 
informed by the following socioeconomic indicators obtained from Eurostat: 

11 The results of the 2011 study are available at: 

http://www.mobilitypartnership.eu/Documents/SS1_PES%20Bussiness%20Models_Final.pdf 

27 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

  GDP per capita in Purchasing Power Standards (PPS) (source: Eurostat12); 
  unemployment  rate  as  a  percentage  of  active  population  (source:  Eurostat, 

 

[une_rt_a]); 
comparative price levels (the ratio between Purchasing power parities (PPPs) and 
market exchange rate for each country) (source: Eurostat, [nama_inc_c]); 

  population size; 
  hourly  labour  costs  in  the  area  of  administrative  services  (source:  Eurostat, 

[lc_lci_lev]). 

In addition, data from country fiches had to be adjusted to better reflect the current labour 
cost levels. For this purpose, we assessed how labour costs changed in the period 2013-
2016. These calculations were informed by data on average hourly labour costs extracted 
from  the  Labour  Cost  Survey  (LCS).13  This  data  is  available  from  Eurostat’s  dataset: 
‘Labour cost levels by NACE Rev. 2 activity [lc_lci_lev].’ 

Finally,  we  explored  a  number  of  methods  for  establishing  an  output-based  SCO  for 
Employment Services. However, our analysis revealed that the currently available data is 
insufficient  for  determining  an  output-based  EU-level  SCO.  Neither  of  the  data  sources 
consulted  contained  all  relevant  data  in  one  piece,  also  significant  mismatches  in 
overlapping  data  were  identified  when  comparing  different  datasets  that  prevented 
merging of data acquired from these sources. The analysis of information provided on PES 
websites and reported in their reports has also revealed that national institutions do not 
collect the data needed for determining the costs incurred per output: depending on the 
Member  State,  it  is  not  possible  to  determine  the  number  of  counselling  recipients,  the 
length of counselling services or the expenditures associated with these services. 

3.1.2.2. 

Sample and quality of data 

The following data for the year 2013 was collected from country fiches: 

total PES expenditure; 

 
  PES expenditure on staff (direct labour costs); 
 

total number of PES staff (5 out of 28 analysed Member States provided this number 
in FTE; others – in number of employees); 
total number of PES staff servicing clients; 
total number of job-seeking clients. 

 
 

The table below demonstrates to what extent each Member State is covered by the data 
collected.  

Table 4. Summary of the data from PES Business Models study14 

Country 

Total PES 
EXP 

EXP on staff 

Total PES 
staff 

AT 

BE_ACTIRIS 

BE_VDAB 

YES 

YES 

YES 

BE_Le FOREM  YES 

BG 

CY 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

NO 

YES 

YES 

Staff 
servicing 
clients 
YES 

YES 

NO 

NO 

YES 

YES 

No. of job-
seekers 

YES 

YES 

YES 

YES 

NO 

NO 

12 Eurostat, 

http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=tec00114&plugin=1 

13 Eurostat, http://ec.europa.eu/eurostat/web/labour-market/labour-costs 
14 YES in italics indicates that data is available only for one year (either 2013 or 2014). 

28 

 
 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country 

Total PES 
EXP 

EXP on staff 

Total PES 
staff 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

NO 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 
YES15 
YES 

NO 

Staff 
servicing 
clients 
YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

NO 

No. of job-
seekers 

YES 

YES 

YES 

NO 

YES 

YES 

NO 

NO 

YES 

YES 

NO 

NO 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

NO 

YES 

YES 

YES 

NO 

Source: prepared by PPMI. 

YES=26  YES=24 

YES=25 

YES=27 

YES=20 

To validate the above-described data extracted from the PES Business Models study, we 
compared it with publicly available data on PES websites. Overall, we managed to collect 
information on the total staff costs and number of PES staff from 11 PES websites (namely, 
Austria,  Belgian  Actiris,  Belgian  Arbeitsamt  der  DG,  Croatia,  Lithuania,  Malta,  Portugal, 
Slovakia, Slovenia, Spain and Sweden). The comparative analysis of data acquired from 
these two sources revealed that significant differences are evident in the following three 
countries: Croatia, Estonia and Slovakia. 

The mismatch of data in Estonia and Croatia could be explained by the fact that staff cost 
figures published on PES websites do not  cover all relevant levels of  PES (such as head 
office,  regional and local offices).  In the case  of Slovakia,  cost figures  from the  website 
matched the data from the country fiche, however, the total number of PES staff was about 
24  times  smaller  (number  of  staff  members  indicated  in  the  country  fiches  was  8992, 
whereas on the website - 372). 

A further comparison of the calculated unit cost values for Croatia with hourly labour cost 
data  from  Eurostat  (see  the  section  below  for  more  information)  did  not  show  any 
discrepancies, and thus, we concluded that the data collected for  Croatia is reliable and 

15 The latter data was retrieved from the SI PES website. 

29 

 
 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

can be used to calculate the SCO. In the case of Estonia, the calculated SCO was somewhat 
higher than the national hourly labour cost levels of administrative staff as indicated by 
Eurostat’s data (respectively, EUR 16.5 and EUR 10.3), whereas in the case of Slovakia – 
it was somewhat lower (respectively, EUR 4 and EUR 7). As a result, we contacted Estonian 
and Slovakian PES to further verify if the data in their country fiches is reliable. 

The close examination of the Latvian fiche revealed that PES staff figures indicated in the 
different  fiche  sections  do  not  match.  Therefore,  Latvian  representatives  were  also 
contacted to determine which figure is correct. 

Data available from country fiches produced by PES Business Models study was insufficient 
for establishing unit cost values for seven countries (namely, Bulgaria, Denmark, Finland, 
Ireland,  Italy,  the  Netherlands  and  the  United  Kingdom).  Thus,  in  addition  to  Estonian, 
Slovakian  and  Latvian  PES,  we  also  contacted  the  latter  six  countries  except  for  the 
Netherlands. A representative of this Member State informed us in advance that required 
data will not be available. Furthermore, we also contacted PES representatives in Cyprus 
and France as  our initial analysis revealed that the  calculated unit cost values for these 
two  Member  States  somewhat  differ  from  the  national  level  of  the  administrative  staff 
hourly labour costs.  As  a result of  our correspondence with PES,  we managed to obtain 
additional  clarifications  from  8  PES  (Bulgaria,  Cyprus,  Estonia,  Finland,  France,  Latvia, 
Slovakia  and  the  United  Kingdom).  The  summary  of  the  data  collected  from  PES  is 
presented in the table below. 

Table 5. Data received from PES 

Country  Reason for Contacting 

Staff costs 

Number of staff  Number of 
staff (FTE) 

2013  2016  2013 

2016 

2013 

2016 

BG 

CY 

DK 

EE 

FI 

FR 

IE 

IT 

LV 

SK 

UK 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

YES 

YES 

YES 

YES 

NO 

NO 

NO 

NO 

NO 

NO 

YES 

YES 

Missing data 

Mismatches  between 
WEB and Eurostat data 
Missing data 

Mismatches  between 
WEB and country fiche 
data 
Missing data 

Mismatches  between 
WEB and Eurostat data 
Missing data 

Missing data 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

NO 

in 

the 

Mismatches 
country fiche 
Mismatches  between 
WEB and country fiche 
data  
Missing data 

YES 

YES 

NO 

YES 

YES 

NO 

NO 

NO 

NO 

YES 

YES 

NO 

YES 

YES 

YES 

NO 

NO 

YES 

YES 

YES 

NO 

YES 

YES 

NO 

NO 

NO 

YES 

YES 

YES 

YES 

YES 

YES 

YES 

NO 

YES 

NO 

NO 

NO 

YES 

Source: prepared by PPMI. 

We  did  not  manage  to  obtain  sufficient  data  to  calculate  unit  cost  values  for  Demark, 
Ireland, Italy and the Netherlands. Therefore, values for these Member States had to be 
extrapolated. As outlined in sub-section 3.1.2.3, we created a statistical model (based on 
OLS regression) to explain the variance of the calculated SCOs and to predict the unknown 
values.  The  model  could  explain  more  than  90%  of  the  unit  cost  variance  (R2  >  90%). 
Extrapolation was carried out at the country level and based on socioeconomic indicators 
obtained from Eurostat (the full list of indicators is presented in section 3.1.2.1). 

30 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

3.1.2.3.  Analysis 

The potential unit cost values were established in two steps. First, we calculated the hourly 
cost of counselling for 2013 by dividing the total PES staff costs in 2013 by the number of 
hours  worked  in  each  Member  State.  Then  we  adjusted  this  rate  based  on  the  average 
increase in labour costs of administrative services in each Member State in the 2013-2016 
period: 

1)  𝑆𝐶𝑂𝑝𝑎𝑡ℎ𝑤2013 =  

𝐶𝑜𝑠𝑡𝑠𝑖
Staff𝑖∗𝑇𝑖∗52,177457

, 

2)  𝑆𝐶𝑂𝑝𝑎𝑡ℎ𝑤2016 =   𝑆𝐶𝑂𝑝𝑎𝑡ℎ𝑤2013 ∗

𝐿𝐶2016
𝐿𝐶2013

, where 

Costsi – PES staff costs in the country I in the year 2013; 
Staffi – the PES staff (head, regional, local offices) number in country  I in the year 
2013; 
Ti - the legal number of hours per week that constitute a full-time equivalent (FTE) 
in country I; 52,177457 – number of weeks per year; 
LC – hourly labour costs as indicated in the Eurostat dataset ‘Labour cost levels by 
NACE Rev. 2 activity [lc_lci_lev].’ 

Expenditure on staff (Costs) refers to the expenditure of Public Employment Services 
to cover the costs of its staff (direct labour costs: wages, payroll taxes, medical and social 
insurance,  etc.).  Ideally,  only  PES  expenditure  on  staff  providing  counselling  services 
should be included in calculations, however, this data is currently not available from some 
Member States. 

Number  of  staff  (Staff)  is  the  number  of  all  staff  working  at  the  Public  Employment 
Services.  Data  for  ten  Member  States  is  based  on  the  national  full-time  equivalents 
(Belgium,  Bulgaria,  Cyprus,  Estonia,  France,  Hungary,  Ireland,  Latvia,  Slovakia  and  the 
United Kingdom). The rest of the data is based on the absolute number of employees (not 
in  FTE).  We  had  to  use  the  latter  indicator  as  a  proxy  for  FTE  where  FTE  data  was  not 
available. After comparing FTE data with the absolute number of employees we concluded 
that these indicators are not significantly different. The FTE number was on average 0.3% 
lower than the absolute number of employees (standard deviation – 1.7 percentage points) 
in 2013 and by 1.7% in 2016 (standard deviation – 3.3 percentage points). Thus, it was 
concluded that using the absolute number of employees instead of FTE in our calculations 
would not significantly affect the final unit cost values. 

Coefficient T is established based on the number of hours per week in full-time equivalents 
(FTE) in each Member State. 

Due to incomplete data available to our team, it was impossible to calculate the potential 
unit cost values for some Member States without applying extrapolation. As such, we had 
to  use  extrapolation  for  four  countries  (Denmark,  Ireland,  Italy  and  the  Netherlands). 
Extrapolation was carried out at the country level with unit costs per country treated as a 
dependent variable and selected socioeconomic indicators as independent variables. The 
full list of socioeconomic indicators is presented in sub-section 3.1.2.1. 

Extrapolation  was  carried  out  using  ordinary  least  squares  (OLS)  regression.  OLS 
regression  is  a  method  for  estimating  the  unknown  parameters  in  a  linear  regression 
model.  Our  OLS  model  is  visualised  in  Figure  3:  the  dashed  line  is  a  reference  line 
representing  a  perfect  correlation  between  predicted  and  empirical  values,  whereas  the 
black  dots  with  country  codes  represent  real  empirical  values.  This  model  helped  us  to 
predict  unit  cost  values  for  Member  States  with  incomplete  data.  Predicted  values  are 
written on the Y-axis and real empirical values – on the X-axis. The full extrapolation results 
are presented in section 3.1.2.4. 

31 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

The model explained more than 90% of the SCO rate variance (R2 > 90%). Therefore, our 
model should be seen as statistically robust and having strong explanatory power. 

Figure 3. Predictive power of the OLS model for counselling staff costs 

Source: prepared by PPMI. 

3.1.2.4.  Results 

The potential unit cost values are presented in  

32 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Table 6. The data sample was sufficient to calculate hourly staff costs for 24 countries. As 
noted  in  the  data  sample  description,  no  data  is  available  for  four  countries  (namely, 
Denmark,  Ireland,  Italy  and  the  Netherlands),  and  thus,  we  had  to  extrapolate  these 
values. In addition to hourly unit cost values, we calculated monthly and yearly values that 
relate to the monthly and yearly labour costs of counselling. This will give more flexibility 
to Member States wishing to use different time units (e.g. use a yearly unit cost value to 
cover the cost of an employee who is working full-time on a project for one year). 

Firstly, we calculated unit cost values based on the data for the year 2013. Secondly, using 
hourly labour cost statistics16 obtained from Eurostat, we adjusted these values to the 2016 
level.  The  results  of  this  exercise  are  presented  in  the  table  below.  On  average,  labour 
costs have increased by 11 % in the period 2013-2016. The highest increase was observed 
in  Romania  (43%),  whereas  in  Italy  labour  costs  shrunk  by  3%.  Adjusted  values  were 
inserted in our OLS regression model as a dependent variable. The OLS model was used 
to  extrapolate  values  for  Denmark,  Ireland,  Italy  and  the  Netherlands.  The  results  of 
extrapolation are presented in  

16 For this purpose, we used the hourly labour costs in the area of administrative and support service activities. 

33 

 
 
 
                               
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Table 6. 

34 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Table 6. Unit cost rates for Employment Services (hourly) 

Country  SCO at 

2013 
level17, 
eur 

SCO 
adjusted 
to 2016 
level 

Predicted 
SCO, 
EUR 

Final 
SCO 
(hourly), 
EUR 

Final SCO 
(monthly), 
EUR 

Final 
SCO 
(yearly), 
EUR 

% change 
in hourly 
labour 
costs18 
(2013-
2016) 

7 % 

1 % 

38 % 

- 

5 % 

7 % 

28 

30 

2* 

21* 

8 

30 

26 

30 

2 

16 

8 

28 

MISSING 

4 % 

MISSING 

8 

15 

14 

30 

34 

6 

6 

26 % 

1 % 

3 % 

5 % 

1 % 

5 % 

20 % 

10* 

15 

14 

32* 

34 

7 

7 

MISSING 

7 % 

MISSING 

-3 % 

MISSING 

MISSING 

5 

23 

5 

8 

27 % 

4 % 

26 % 

10 % 

6 

24 

6* 

9 

MISSING 

1 % 

MISSING 

4 

14 

4 

34 

15 

4 

11 % 

6 % 

43 % 

0 % 

11 % 

18 % 

4 

15 

6 

34 

16 

5* 

MISSING 

14 % 

18* 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

27 

34 

2 

28 

30 

2 

MISSING 

21 

7 

24 

39 

11 

13 

18 

27 

30 

7 

6 

26 

22 

7 

24 

8 

11 

26 

6 

11 

4 

34 

13 

8 

26 

8 

30 

39 

10 

15 

14 

32 

34 

7 

7 

26 

22 

6 

24 

6 

9 

26 

4 

15 

6 

34 

16 

5 

18 

4802 

5007 

388 

3905 

1420 

5416 

6783 

1784 

2632 

2506 

5488 

5212 

1157 

1297 

4579 

3884 

1124 

4220 

989 

1560 

4624 

751 

2606 

1111 

5978 

2868 

798 

3350 

57623 

60080 

4651 

46860 

17046 

64994 

81397 

21406 

31587 

30068 

65860 

62540 

13886 

15564 

54943 

46605 

13484 

50636 

11862 

18723 

55486 

9008 

31274 

13326 

71736 

34418 

9579 

40204 

Source: prepared by PPMI. 
*SCO rates for 2016 are based on the data provided by PES for the following countries: Bulgaria, Cyprus, Estonia, 

Finland, Latvia, Slovakia and the United Kingdom. 

The calculated unit cost rates are relatively similar when compared within country clusters, 
which were created based on the socioeconomic indicators introduced in section 3.1.2.1. 
However, some variation is present. 

17  Hourly  counselling  staff  costs:  unit  cost  rate  for  Employment  Services  at  the  level  of  the  year  2013  labour 

costs. 

18 Eurostat, dataset: ‘Labour cost levels by NACE Rev. 2 activity [lc_lci_lev]’ 

35 

 
 
                               
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Member  States  were  grouped  into  clusters  using  the  hierarchical  clustering  technique. 
Hierarchical  clustering  groups  countries  into  relatively  small  clusters,  which  are 
respectively grouped into larger ones and the exercise is repeated again. The final output 
is a hierarchical tree of clusters. 

The variation of the unit cost values within clusters and between clusters was moderate. 
In most cases, unit cost values did not differ significantly within clusters: the difference 
varied  from  EUR  3  to  EUR  14  at  the  lowest  cluster  level.  The  highest  differences  within 
clusters were observed in the following clusters: 1) Finland and the United Kingdom; 2) 
France  and  Italy.  The  differences  between  clusters  (when  comparing  cluster  averages) 
varied from EUR 5 to EUR 31. The group of countries with the highest average counselling 
staff cost included Sweden and Denmark, with the unit costs above EUR 34 per hour. The 
two groups of Member States with the lowest unit costs (below EUR 7 per hour) included 
Bulgaria, Romania, Latvia, Poland, Hungary and Croatia. 

It can be concluded that our model as well as the collected empirical values are reliable 
and correspond to the actual costs of staff responsible for counselling in Member States. 
To verify the validity of our OLS model as well as the reliability of the collected data, we 
compared the predicted values with the values collected from country fiches (see Table 7). 
The values predicted by our model differed by an average of 19% from the empirical values 
indicated  in  the  country  fiches.  That  is  equal  to  EUR  2.  The  highest  difference  between 
empirical  and  predicted  values  was  observed  in  the  cases  of  Slovakia  (60%  or  EUR  3), 
Poland (50% or EUR 2) and the United Kingdom (44% or EUR 8) (see Table 7). Without 
these  three  outliers,  the  predicted  values  differed  by  an  average  of  15%  from  the  real 
empirical values (that was equal to EUR 2). The OLS model could explain 91% of dependent 
variable’s variance. 

Table  7.  Extrapolation:  the  difference  between  predicted  and  empirical  SCO 
values 

Country  SCO 

empirical19, 
EUR 

Predicted 
SCO, 
EUR 

Eurostat 
labour 
costs20, EUR 

% Diff. between 
predict. and final 
(EUR) 

% Diff. between 
Eurostat and 
final (EUR) 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

28 

30 

2 

21 

8 
30 

MISSING 

10 

15 

14 
32 

34 

7 

7 

MISSING 
MISSING 

27 

34 

2 

25 

32 

3 

-4% (EUR 1) 

-11% (EUR 3) 

13% (EUR 4) 

7 % (EUR 2) 

0% (EUR 0) 

50% (EUR 1) 

MISSING  MISSING 

N/A 

N/A 

7 

24 

39 

11 

13 

18 

27 

30 

7 

6 

26 

22 

6 

20 

35 

10 

10 

15 

23 

26 

6 

6 

22 

18 

-13% (EUR 1) 

-25% (EUR 2) 

-20% (EUR 6) 

-33% (EUR 10) 

N/A 

N/A 

10% (EUR 1) 

0% (EUR 0) 

-13% (EUR 2) 

-33% (EUR 5) 

29% (EUR 4) 

7% (EUR 1) 

-16% (EUR 5) 

-28% (EUR 9) 

-12% (EUR 4) 

-24% (EUR 8) 

0% (EUR 0) 

-14% (EUR 1) 

-14% (EUR 1) 

-14% (EUR 1) 

N/A 

N/A 

N/A 

N/A 

19 Hourly counselling staff cost rate for Employment Services adjusted to the year 2016 level. 
20 Hourly labour costs in the area of administrative services (source: Eurostat, [lc_lci_lev]). 

36 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country  SCO 

empirical19, 
EUR 

Predicted 
SCO, 
EUR 

Eurostat 
labour 
costs20, EUR 

% Diff. between 
predict. and final 
(EUR) 

% Diff. between 
Eurostat and 
final (EUR) 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

6 

24 

6 

9 

MISSING 

4 
15 

6 

34 

16 
5 

18 

7 

24 

8 

11 

26 

6 

11 

4 

34 

13 

8 

26 

Source: prepared by PPMI. 

3.1.2.5.  Audit trail 

6 

21 

7 

10 

22 

6 

8 

4 

31 

11 

7 

20 

17% (EUR 1) 

0% (EUR 0) 

0% (EUR 0) 

-13% (EUR 3) 

33% (EUR 2) 

17% (EUR 1) 

22% (EUR 2) 

11% (EUR 1) 

N/A 

N/A 

50% (EUR 2) 

50% (EUR 2) 

-27% (EUR 4) 

-47% (EUR 7) 

-33% (EUR 2) 

-33% (EUR 2) 

0% (EUR 0) 

-9% (EUR 3) 

-19% (EUR 3) 

-31% (EUR 5) 

60% (EUR 3) 

40% (EUR 2) 

44% (EUR 8) 

11% (EUR 2) 

Audit trail for Employment Services SCO 

Types of 
operations 

Counselling  services  of  unemployed  persons  that  are 
performed  by  case  handlers  and  implemented  by  PES.  This 
type  of  employment  service  helps 
find 
employment  (for  example,  intake  and  orientation,  skills 
audit). 

job-seekers 

Indicator name 

Direct  staff  costs  related  to  one  hour  of  counselling  of  the 
unemployed. 

Definitions: 

One  hour  of  counselling:  normally  means  60  minutes  of 
counselling. Time related to preparation for counselling, travel 
time and any other non-counselling activities are not included 
into counselling time. 

The  unemployed:  an  unemployed  person  or  a  group  of 
unemployed  persons  enrolled  in  a  counselling  intervention 
implemented  by  the  PES.  The  unit  rate  does  not  depend  on 
the number of people in the group. 

Category of costs 

All  direct  labour  costs  of  the  counselling  operation  eligible 
under ESF regulation. 

Measurement unit 
for the indicator 

Number  of  staff  contact  hours  spent  providing  counselling 
services  to  unemployed  people  (one  person  or  a  group  of 
people). The amount paid relates to the number of counselling 
hours;  it  does  not  depend  on  the  number  of  people  in  the 
counselling group.   

Specific 
requirements for 

Managing  Authorities  and  intermediary  bodies,  taking  into 
account  relevant  national  practices,  must  ensure  that  the 

37 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail for Employment Services SCO 

the audit trail and 
justification of 
achievement of 
SCOs 

aggregate  counselling  hours  certified  to  the  Commission  are 
traceable  to  separate  operations,  where  for  each  operation 
there will have to be a sufficient documentary proof on (1) the 
number of staff hours spent providing counselling services, (2) 
the number of participants who received counselling, (3) the 
employment status of the participants. 

Examples  of  supporting  documents  related  to  proof  of  the 
duration of counselling could include: 

staff timesheets; 
counselling schedule/programme; 
register of attendance by the participant; 

 
 
 
  other registers, etc. 

Examples of supporting documents related to the status of a 
participant  (unemployment  person)  could  include  extracts 
from registers, etc. 

Key risks and 
measures to 
prevent ‘creaming’ 
of participants and 
perverse 
incentives 

Applying  an  input-based  SCO  to  reimburse  the  funds  to 
Member  States  for  counselling  of  the  unemployed  is 
associated with the following risks: it provides an incentive to 
increase the duration of counselling or an incentive to organise 
counselling sessions for smaller groups of people. To ensure 
that funding is spent efficiently, we recommend implementing 
one of the following alternative measures: 

1)  To  set  a  maximum  limit  on  the  contact  hours  of 
counselling participants receive on average per whole 
programme nationally21. The national average could be 
calculated annually based on the data of all participants 
who  exited  counselling  interventions  in  the  reference 
year (all national ESF counselling interventions should 
be  included  in  such  calculations).  PES  Benchlearning 
initiative  could  contribute  to  this  end  by  collecting 
(on  average  number  of 
relevant 
counselling hours per FTE) as part of its inquiries in the 
area of ‘allocation of PES resources.’ This information 
could also be used to set up an output-based SCO (by 
multiplying the average number of counselling hours in 
FTE  by  cost  per  counselling  hour  established  by  this 
study).  

information 

2)  To limit the percentage of total working hours per week 
or per year that PES counsellors spend on counselling 
(face-to-face  work  with 
the  unemployed).  The 
maximum  limit  could  be  set  at  the  organisation  level 
rather  than  at  the  individual  level  to  allow  some 
flexibility for counsellors to manage their time. Setting 

21 As the needs of individual participants are very heterogeneous, some unemployed persons might need longer 
counselling than others. Thus it is recommended that maximum limits are set at the programme level and 
not at the intervention or individual level. Averages could be calculated annually based on the total participant 
data. The maximum limits would apply only to these averages. 

38 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail for Employment Services SCO 

the limit on the inputs rather than the outputs would 
not  require  to  collect  additional  information,  as 
opposed  to  the  1st  alternative.  However  the  2nd 
alternative  might  be  less  effective  in  preventing 
perverse  incentives  than  the  1st  one  as  it  only 
indirectly 
counselling. 
Furthermore, it might inhibit the work of counsellors in 
the cases of the sudden increase in the number of the 
unemployed. 

the  duration  of 

limits 

In  addition,  as  an  input-based  indicator,  this  SCO  does  not 
encourage national authorities to look for new, more effective 
methods  of  counselling  and  it  could  lock-in  ineffective 
practices. Achieving results could be encouraged by paying a 
special ‘entitlement’/top-up payment for each result achieved 
during  the  reference  year  (e.g.  change  of  the  participant’s 
status  from  ‘unemployed’  to  ‘employed’)  irrespective  of  the 
number  of  hours  worked.  The  condition  encouraging  result 
orientation could help to make sure that current practices are 
not locked-in. 

As  SCO  relates  to  labour  costs,  which  tend  to  change  over 
time,  it  will  be  important  to  monitor  national  labour  cost 
statistics if there are any significant changes  of the relevant 
indicators. 

Adjustment of 
amounts 

Amounts  can  be  adjusted  using  one  of  the  following 
approaches: 

is  already 

1)  The  number  of  PES  employees  (FTE)  and  associated 
PES  staff  costs,  which  could  be  collected  during  the 
next cycle of the PES Benchlearning initiative. The data 
on  the  number  of  PES  employees  (FTE)  per  Member 
the  PES 
State 
collected 
Benchlearning  exercise  every 
is 
considered to be reliable and could be used to adjust 
the calculated unit cost rates. However, only indicative 
data  is  available  on  the  associated  staff  costs.  Staff 
cost  figures  are  collected  through  the  PES  self-
assessment reports and qualitative questionnaires and 
mostly serves the purpose of qualitative benchmarking 
and self-assessment. Thus, it is not statistically reliable 
or comparable across countries. 

through 
two  years.  It 

2)  Labour  Cost  Index  (LCI)  for  the  economic  activity 
‘Public administration and defence;  compulsory  social 
security’ (NACE Rev. 2, O), which is publicly available 
on  the  Eurostat  website  (dataset  titled:  ‘Labour  cost 
index  by  NACE  Rev.  2  activity  –  nominal  value, 
quarterly data [lc_lci_r2_q]’). The LCI is defined as the 
Laspeyres index of labour costs per hour worked. This 
indicator does not refer directly to the PES labour costs 
but could be used as a proxy indicator. The LCI is the 
only publicly available and internationally comparable 
statistical indicator that reflects the changes of labour 
costs  in  the  area  of  public  administration.  The  LCI  is 

39 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail for Employment Services SCO 

calculated for each quarter and chain-linked annually. 
The  current  reference  year  of  the  index  is  2012.  The 
LCI  does  not  reflect  exchange  rate  movements. 
Therefore,  to  use  the  LCI  for  calculating  monetary 
estimates in euro, exchange rate movements have to 
be  incorporated  in  case  of  certain  non-euro  area 
countries.  As  the  LCI  is  based  on  estimates  provided 
by the Member States, revisions of the LCI are frequent 
and  can  go  back  several  years.  Thus,  annual 
adjustment of rates should be avoided. 

3.1.3.  Insights on application of this SCO 

The proposed SCO for Employment Services relates to inputs, namely, the number of PES 
staff contact hours for counselling. As a result, there are no major risks related to creaming 
of participants. In addition, such input-based indicator effectively eliminates the incentive 
of cutting the length of counselling services offered to the unemployed. 

On the other hand, as an input-based indicator, this SCO does not encourage looking for 
new,  more  effective  methods  of  counselling.  It  could  also  encourage  application  of 
counselling  forms  that  are  less  cost-efficient.  To  address  these  risks,  the  following 
measures could be considered: 

1) setting a limit for the maximum duration of counselling participants on average receives 
per  programme22  or  limiting the  percentage  of  total  working  hours  that  PES  counsellors 
spend on face-to-face counselling. The first alternative might be more effective than the 
second one as it directly relates to outputs. However, controlling the average duration of 
counselling would require MS to collect additional data, which is currently not available. 
Whereas the second option, setting the input-oriented limit, would be less administratively 
burdensome. 

2)  paying  of  a  special  ‘entitlement’/top-up  payment  for  each  result  achieved  during  the 
reference year (e.g. change of the participant’s status from ‘unemployed’ to ‘employed’) 
irrespective of the number of hours worked. 

This input-based SCO could be replaced by an output-based SCO once the data availability 
issues  are  resolved,  e.g.  through  the  PES  Benchlearning  initiative.  In  particular,  the 
average cost of counselling one unemployed person could be established in each Member 
State if data on average duration of counselling provided per participant or per exit from 
an  intervention  was  available.  Unfortunately,  Member  States  do  not  collect  this  data 
systematically.  This  challenge  could  be  addressed  during  the  next  cycle  of  the  PES 
Benchlearning  initiative.  As  indicated  in  the  2015-2016  Benchlearning  report,  the 
Quantitative Benchmarking of PES performance will commence with the collection of more 
comprehensive data on PES performance outcomes and related outputs and inputs such 
as the PES human and financial resources or management of employment services. Hence, 
the  further  progress  of  PES  Benchlearning  initiative  is  likely  to  produce  a  systematic 
evidence-base to be explored for setting an output-based SCO for Employment Services.23 

22 We recommend that maximum limits are set at the programme level and not at the intervention or individual 
level. Averages could be calculated annually based on the total participant data. The maximum limits would 
apply only to these averages and not to individual participants. 

23 European Commission, ‘Annual report: European network of public employment services (PES)’, 2015-2016. 

40 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

4.  SCOS FOR PEOPLE IN EMPLOYMENT AND PUBLIC SERVANTS 

4.1.  Option 1: cost per participant training hour 

4.1.1.  Definition of the SCO 

The unit cost rate for this input-based SCO reflects the average cost of continual vocational 
training (CVT) courses for employees per participant training hour incurred by enterprises 
in a particular Member State. Training costs for this SCO include the following categories 
of costs: 

a)  fees and payments for courses for persons employed; 
b)  travel and subsistence payments; 
c)  labour costs of internal trainers for CVT courses; 
d)  costs  for  training  centre,  training  premises  or  specific  rooms  of  the  enterprise  in 
which CVT courses take place and costs for teaching materials for CVT courses. 

4.1.2.  Method to determine and update the amounts 

4.1.2.1.  Data sources 

The key data source for determining the EU-level SCOs for non-formal training for people 
in employment was the dataset of Continuing Vocational Training Survey (CVTS) 4,24 which 
is  a  part  of  the  EU  statistics  on  lifelong  learning.  CVTS  contains  statistically  reliable, 
comparable  enterprise-level  data  (updated  every  five  years)  on  costs  of  continual 
vocational training (CVT) courses in EU Member States. 

In total 27 EU Member States participated in the CVTS survey in 2010. However, the results 
provided  by  Eurostat  to  the  study  team  covered  only  the  following  21  Member  States: 
Belgium,  Bulgaria,  Cyprus,  Czechia,  Denmark,  Estonia,  Finland,  France,  Germany, 
Hungary, Italy, Lithuania, Luxembourg, Malta, Poland, Portugal, Romania, Slovakia, Spain, 
Sweden and the United Kingdom. 

To determine how training costs vary depending on the type of training, we analysed the 
median  value  of  total  training  costs  per  participant  training  hour  (‘C7subhour’)  for  the 
following target groups: 1) all enterprises in Member States; 2) enterprises which mostly 
invested in external training; 3) enterprises which mostly invested in internal training and 
4) enterprises which received EU (e.g. ESF) subsidies. The CVTS variables used to inform 
our analysis included the following: 

1)  ‘C3iperc’ – paid working time (in hours) for internal CVT courses as a percentage of 

paid working time on all CVT courses; 

2)  ‘C3eperc’– paid working time (in hours) for external CVT courses as a percentage 

of paid working time on all CVT courses; 

3)  ‘B6c,’ indicating if the enterprise has received ES subsidies (e.g. ESF). 

To extrapolate the unit cost values for the seven Member States that were not covered by 
CVTS 4 microdata (Austria, Croatia, Greece, Ireland, Latvia, the Netherlands and Slovenia), 
we additionally used the following indicators from Eurostat: 

1)  total unemployment rate; 
2)  comparative price levels; 
3)  median equalised income. 

24 The reference year of CVTS 4 is 2010. 

41 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

To adjust the calculated unit cost values from the 2010 to the 2015 level, we also used 
Eurostat’s Harmonised Index of Consumer Prices (HICP), in particular the annual average 
index (2015 = 100) for: 

1)  services (overall index excluding goods ‘SERV’); 
2)  catering services (‘CP111’); 
3)  accommodation (‘CP112’). 

Finally, we cross-checked the results of our calculations against the administrative data on 
non-formal  training  of  people  in  employment  collected  from  Member  States  and  the 
available values of relevant national SCOs. 

The potential unit cost values proposed in this study can be easily updated using the most 
recent CVTS data. The next round of CVTS will have 2015 as the reference year and the 
data is expected to be published in early 2018. Variables used for calculations of this SCO 
are defined as the key variables in CVTS, i.e. the variables for which every effort should 
be made to avoid missing values and for which imputation is recommended.25 

4.1.2.2. 

Sample and quality of data 

Our initial dataset covering all CVTS 4 standard datasets for 21 Member States contained 
93 995 rows/entries. However, some of the data was missing, as some enterprises did not 
reply to certain questions. Therefore, we identified instances where the following values 
were included instead of data: 

  9999999998 – N/A; 
  9999999999 – no answer; 
  0 – zero 

and recoded them as ‘missing.’ As a result of this exercise, we were able to disregard the 
missing information, while retaining the other data provided by the same respondent. 

A significant number of outlier cases (i.e. cases larger/smaller than the median value by 
more  than  three  inter-quartile  ranges)  were  detected  in  the  dataset.  Since  medians  (as 
opposed  to  means)  are  not  sensitive  to  outliers,  they  were  opted  as  the  base  for  our 
calculations and the outlier cases were retained in the dataset. 

Table 8 demonstrates the number of observations (both original and valid) available from 
CVTS  microdata  for  calculations  of  cost  of  training  per  participant  training  hour.  For 
Bulgaria,  Hungary,  Lithuania,  Malta,  Poland,  Portugal  and  Romania,  the  number  of 
observations  decreased  substantially  (more  than  50%)  after  recoding  and  cleaning  the 
data. However, this data is still reliable and comparable for all Member States as similar 
statistics on training costs (measured in Purchasing Power Standard) are publicly available 
on Eurostat’s website. 

Table 8. CVTS dataset for Option 1 calculations 

Country 

Initial number of rows 

After cleaning 

BE 

BG 

CY 

CZ 

3434 

3772 

922 

7789 

2227 

707 

474 

5592 

25 Commission Regulation (EU) No 1153/2014 provides the implementation details for the fifth round of CVTS. 

42 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country 

Initial number of rows 

After cleaning 

DE 

DK 

EE 

ES 

FI 

FR 

HU 

IT 

LT 

LU 

MT 

PL 

PT 

RO 

SE 

SK 

TOTAL 

Source: compiled by PPMI. 

3047 

1242 

2185 

6667 

1560 

5411 

5125 

18 424 

4075 

1254 

788 

14027 

3888 

7733 

2014 

2042 

93 995 

2116 

965 

1249 

5249 

1139 

3790 

1686 

9970 

1613 

912 

310 

3936 

1898 

144 

1597 

1244 

34 434 

In  the  CVTS  dataset  continual  vocational  training  refers  to  the  training  measures  or 
activities which have as their primary objectives the acquisition of new competences or the 
development  and  improvement  of  existing  ones.  Also,  these  training  activities  must  be 
financed  at  least  partially  by  the  enterprises  for  employees  who  have  either  a  working 
contract or who benefit directly from their work for the enterprise, such as unpaid family 
workers and casual workers. 

Though non-formal training of employed people targeted by our study is defined as training 
leading  to  qualifications  which  are  not  directly  recognised  as  such  by  relevant  national 
education authorities or not leading to any qualification at all, CVTS data is highly relevant 
for our study. It was agreed that in the scope of our assignment non-formal training refers 
to any type of training, of any duration, that person undertakes with the purpose to obtain 
knowledge and/or learn new skills for a current or future job, increase earnings, improve 
job  and/or  career  opportunities  in  the  current  or  another  field  and  generally  improve 
opportunities  for  advancement  and  promotion.  In  this  way,  the  primary  objectives  of 
training are focused on the development of new or improvement of existing competences 
of employees both in definition of CVT and non-formal training in the scope of our study. 
In both cases random, unplanned or unintentional learning or training undertaken for other 
purposes (personal, social, recreational, etc.) is excluded. 

4.1.2.3.  Analysis 

The unit cost values established for this SCO is a median drawn from the data sample for 
CVTS variable ‘Total training costs per training hour’ (‘C7subhour’).  

43 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Table 9 provides a detailed description of cost categories covered by this variable. 

44 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Table 9. Categories of costs of CVTS variable ‘c7subhour’ 

Cost category 

Description 

Fees and payments for 
courses for persons 
employed 

Travel and subsistence 
payments 

These  are  costs  made  to  external  organisations  for  the 
provision  of  CVT  courses  and  services.  VAT  paid  by  the 
employer  is  excluded  from  all  expenses.  It  refers  to  the 
total amount paid in fees for external courses or for external 
trainers  or  instructors  (including  those  providing  internal 
CVT).  It  should  also  include  payments  made  to  external 
consultants,  assessors  or  examiners  for  course-related 
activities.  Any  payments  made  by  employers  for  courses 
that  have  been  undertaken  in  an  employed  person’s  own 
time  should  be  included.  Fees  for  training  courses 
undertaken by apprentices or trainees should be excluded. 

This refers to actual payments made to cover the travel and 
subsistence costs of employed persons participating in CVT 
courses. VAT paid by the employer should be excluded from 
the  expenses.  It  should  also  include  any  additional 
payments made for time spent travelling to courses. 

Labour costs of internal 
trainers for CVT courses 

These  costs  are  the  labour  costs  of  the  staff  of  an 
enterprise’s own training centre and other staff exclusively 
or  partly  involved  in  providing,  designing  and  managing 
CVT courses within the enterprise. It should include: 

internal trainers and staff of training centres 

 
  directors  and  other  top  managers  concerned  with 

 
 

training policy 
instructors and training managers or officers 
clerical/administrative and other personnel supporting 
these activities 

Anyone  dealing  solely  with  apprenticeship  training  and 
anyone who is not a member of the normal workforce of the 
enterprise should be excluded. For staff engaged full-time 
in course-related activities, the figures quoted should be the 
total  annual  labour  costs  of  all  those  identified.  For  staff 
engaged only partly (for some part of their working hours) 
in CVT course-related activities, it should be a proportion of 
their  labour  costs,  reflecting  the  proportion  of  time  they 
spent in CVT-course related activities. 

These  costs  include  the  costs  of  running  the  rooms  and 
annual depreciation for rooms and equipment. VAT paid by 
the  employer  is  excluded  from  all  expenses.  This  should 
include the cost of running a training centre (excluding staff 
labour costs) or any other premises used for CVT courses. 
If the costs are not available from the enterprise records, 
then  the  costs  may  be  estimated  by  using  data  on  other 
rooms or premises of comparable size and with comparable 
equipment.  Costs  for  teaching  materials  refer  to  costs  of 
materials bought specifically for CVT courses. This can be 
equipment like a beamer, an overhead projector, flipcharts, 
CDROMs, paper, pencils, etc. VAT paid by the employer is 
excluded from all expenses. 

Costs for training 
centre, training 
premises or specific 
training rooms of the 
enterprise, in which CVT 
courses take place and 
costs for teaching 
materials of CVT courses 

Source: Eurostat, CVTS 4 manual – Annexes, Version 6, 26 April 2012. 

45 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Medians  are  calculated  by  ordering  all  relevant  values  within  the  analysed  sample  from 
smallest to largest and picking the value which splits the ordered set into two equal parts. 
Accordingly, 50% of the values in this set are smaller than the median value, while the 
other 50% are larger. 

For  seven  countries,  which  were  not  covered  by  CVTS  microdata,  unit  cost  values  were 
extrapolated  using  the  available  CVTS  data  and  statistical  data  available  from  Eurostat, 
such  as  the  total  unemployment  rate,  comparative  price  levels  and  median  equalised 
income in 28 EU Member States for 2010 (reference year for CVTS data). After carefully 
inspecting  the  data,  we  have  determined  that  two  Member  States  –  Sweden  and 
Luxembourg – are significant outliers. Both countries (and respective data) were removed 
from further calculation of extrapolated values. 

To perform extrapolation, we used the linear regression (OLS) model, where available unit 
cost values were treated as a dependent variable and Eurostat’s macroeconomic indicators 
–  as  independent  variables.  After  rigorous  testing,  we  have  determined  that  the  model 
satisfies the assumptions of a linear regression and meets the standard applied in social 
science research. The performance of the model was more than adequate, its explanatory 
power (R2) exceeding 80%. 

Figure 4. Predictive power of the model for training cost per participant training 
hour 

Source: prepared by PPMI. 

In addition, the model was tested for overfitting by employing cross-validation measures 
and  it  was  determined  that  the  model  performs  reasonably  well  across  all  the  data  and 
that no  sections of the  data contain significant outliers that could negatively impact the 
validity of the  extrapolated indicators. Figure 4 demonstrates performance  of the model 
used  for  extrapolation  of  the  training  costs.  Values  predicted  by  the  model  are  on  the 
vertical axis (Y), while the actual values are on the horizontal axis (X). The continuous line 
shows the actual performance of the model, while the dotted line is for reference – it shows 
hypothetical perfect prediction. The closer these two lines are to each other, the better is 
the predictive power of the model. 

To adjust the calculated unit cost values to the 2015 level, we calculated the mean values 
of annual average indices of HICP for services, catering services and accommodation in 28 
Member  States,  resembling  the  main  categories  of  training  costs  reported  in  the  CVTS 

46 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

dataset. Results of these calculations (see Table 10) show that training costs were higher 
in 2015 (compared to 2010) in all Member States, with the exception of Greece and Cyprus, 
where training costs decreased. 

Table 10. HICP 2010 average indices (2015=100) used for adjustment of training 
costs 

Country 

Services 

Catering services  Accomodation 

Mean value 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

UK 

87.00 

89.69 

95.98 

96.30 

93.6 

93.4 

91.1 

88.12 

103.28 

95.27 

87.67 

93.01 

94.83 

86.84 

90.8 

92.7 

89.74 

88.73 

92.63 

92.63 

89.32 

89.7 

91.35 

85.76 

93.35 

93.75 

89.72 

86.2 

84.98 

87.36 

88.93 

94.58 

89.5 

90.0 

89.1 

77.08 

98.76 

95.84 

85.92 

89.86 

92.47 

85.17 

94.9 

92.1 

85.05 

86.88 

88.55 

88.03 

89.82 

88.8 

90.79 

90.24 

91.57 

93.61 

89.41 

86.7 

88.54 

95.29 

95.85 

123.21 

100.9 

78.8 

99.9 

83.91 

117.11 

95.16 

93.97 

88.63 

102.88 

92.49 

93.9 

96.6 

89.61 

86.31 

91.49 

94.42 

94.47 

87.5 

115.15 

83.09 

93.07 

96.97 

90.50 

87.2 

86.84 

90.78 

93.59 

104.70 

94.67 

87.40 

93.37 

83.04 

106.38 

95.42 

89.19 

90.50 

96.73 

88.17 

93.20 

93.80 

88.13 

87.31 

90.89 

91.69 

91.20 

88.67 

99.10 

86.36 

92.66 

94.78 

89.88 

86.70 

Source: compiled by PPMI base on Eurostat database. 

4.1.2.4.  Results 

The comparison of average training costs for enterprises predominantly financing internal 
and external training showed that the difference in internal and external training costs is 
insignificant in 26 Member States. Only in Denmark and Malta are the costs  of external 
training substantially higher than costs of internal training, respectively by 20% and 66%. 
While  in  most  Member  States  average  training  costs  for  the  sample  of  all  enterprises 
remain  between  the  lower  and  upper  bounds  of  internal  and  external  training  costs,  in 
Finland and the United Kingdom average training costs for the  sample of  all enterprises 
are slightly above, and in France and Italy – slightly below these bounds. 

Table 11 summarises the results of calculated training costs per participant training hour 
based on CVTS 4 (2010) microdata, including values adjusted to the 2015 level. As a result, 

47 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

training costs increased by up to 10% in 12 Member States (Bulgaria, Croatia, Czechia, 
Denmark, Ireland, Italy, Malta, the Netherlands, Portugal, Spain, Slovenia and Sweden), 
and 10-16% in 13 Member States (Austria, Belgium, Germany, Finland, France, Hungary, 
Lithuania,  Luxembourg,  Latvia,  Poland,  Romania,  Slovakia  and  the  United  Kingdom). 
Unlike  in  other  Member  States,  training  costs  in  Cyprus  and  Greece  have  increased. 
Notably, the adjusted values for Estonia are more than 20% higher than average costs of 
CVT  incurred  by  enterprises  in  2010.  Such  increase  was  mainly  caused  by  significant 
inflation  rates  for  catering  services  and  accommodation  in  Estonia  in  the  2010–2015 
period. 

Table 11. Option 1: cost of training per participant training hour 

Country  All 

enterprises, 
2010, EUR 

Internal 
training, 2010, 
EUR 

External 
training, 
2010, EUR 

Adjusted 
values for 
2015, EUR 

Change from 
2010 to 
2015  

AT* 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL* 

ES 

FI 

FR 

HR* 

HU 

IE* 

IT 

LT 

LU 

LV* 

MT 

NL* 

PL 

PT 

RO 

SE 

SI* 

SK 

UK 

29.51 

20.85 

4.81 

19.74 

8.79 

31.49 

37.04 

11.65 

18,85 

16.78 

34.24 

32.57 

10,18 

13.82 

29,63 

25.72 

6.55 

26.08 

7,22 

15.12 

29,19 

9.94 

8.25 

0.23 

53.76 

17,91 

10.00 

31.27 

- 

19.81 

3.38 

18.92 

8.41 

31.06 

34.59 

11.93 

- 

15.93 

33.33 

33.52 

- 

10.67 

- 

26.79 

6.33 

25.00 

- 

11.20 

- 

8.27 

7.55 

0.20 

49.87 

- 

9.81 

31.22 

- 

22.50 

5.11 

19.78 

9.08 

32.43 

41.75 

13.15 

- 

16.79 

33.86 

33.24 

- 

14.33 

- 

28.00 

7.25 

27.62 

- 

18.57 

- 

10.97 

9.72 

0.26 

55.97 

- 

10.64 

31.17 

33.98 

22.97 

5.14 

18.85 

9.29 

36.03 

39.67 

14.03 

17.72 

17.58 

38.39 

35.99 

10.52 

15.67 

31.79 

27.42 

7.43 

29.87 

7.94 

16.49 

32.01 

11.21 

8.33 

0.27 

58.02 

18.90 

11.13 

36.07 

15.15% 

10.16%. 

6.85%. 

-4.49%. 

5.63%. 

14.42%. 

7.10%. 

20.43%. 

-6.00%. 

4.80%. 

12.12%. 

10.50%. 

3.38%. 

13.42%. 

7.30%. 

6.61%. 

13.46%. 

14.54%. 

10.02%. 

9.06%. 

9.65%. 

12.78%. 

0.91%. 

15.79%. 

7.92%. 

5.51%. 

11.26%. 

15.34%. 

Source: compiled by PPMI based on CVTS data and Eurostat’s macroeconomic indicators 
* Member States for which costs of training were extrapolated. 

The determined median values in most Member States are within the range or only slightly 
higher  than  values  of  relevant  national  unit  cost  rates  and  training  costs  implied  by 
historical  administrative  data  collected  by  our  team.  However,  in  some  cases  they  were 
substantially higher than national rates. For example, in Lithuania national unit cost rate 
per participant training hour including participant’s salary is EUR 7.39, i.e. almost the same 

48 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

as adjusted value of our calculations based on CVTS microdata. However, if unit cost values 
from  Option  1  and  Option  2  are  combined,  the  EU-level  unit  cost  rate  per  participant 
training  hour  including  trainee  salary  costs  for  Lithuania  will  be  EUR  11.34,26  i.e.  53% 
higher than the national unit cost rate. 

4.1.2.5.  Audit trail 

Audit trail for Option 1 

Types of 
operations 

Non-formal  training  of  employed  persons.  Random,  unplanned  or 
unintentional  learning  or  training  undertaken  for  other  purposes 
(personal, social, recreational, etc.) is excluded. 

Indicator name 

Participation of an employed person in one hour of training. 

Definitions: 

One  hour  of  training:  normally  means  60  minutes  of  training. 
Time related to preparation for trainings, travel time and any other 
non-training activities are not included in training time. 

Employed person: a  person  engaged in any sort of employment 
(including self-employed) in any sector of the economy. 

Category of costs  All eligible costs of the training operation (direct and indirect training 

costs) eligible under ESF regulation. 

Measurement 
unit for the 
indicator 

Number of completed training hours per participant. 

For example, if all four IT training events (each 10-hours long) were 
attended by 15 participants and the total number of participants of 
all five language training events (each 20-hours long) was 60, the 
total duration of training was 1800 (4*10*15+20*60) hours. 

Specific 
requirements for 
the audit trail 
and justification 
of achievement 
of SCOs 

Managing Authorities and intermediary bodies, taking into account 
relevant national practices, must ensure that the aggregate number 
of  training  hours  certified  to  the  Commission  are  traceable  to 
separate  operations  and  participants,  where  for  each  participant 
there will have to be sufficient documentary proof on (1) the number 
of  training  hours  attended  by  the  participant  and  (2)  the 
employment status of the participant. 

Examples of supporting documents related to proof of participation 
in a training course and duration of participation could include: 

  a  list  of  participants  of  the  training  course/event  with 

signatures for each day of the training/event; 
training programme/ curriculum; 
training schedule; 
register of attendance by the participant; 
register of training completion certificates. 

 
 
 
 

Examples  of  supporting  documents  related  to  the  status  of  a 
participant  (person  in  employment)  could  include  an  employment 

26 EUR 7,43 (Option 1) + EUR 3,71 (Option 2). 

49 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail for Option 1 

Key risks and 
measures to 
prevent 
‘creaming’ of 
participants and 
perverse 
incentives 

contract,  declaration  of  the  beneficiary  or  sending  organisation 
(employer of the participant), extract from registers. 

The relevance of the SCO could be affected by possible changes in 
Member  State  interventions  related  to  training  for  people  in 
employment, such as lower cost/quality of training, larger training 
groups, etc. 

As  this  SCO  is  based  on  CVTS  statistics,  it  will  be  important  to 
monitor  if  there  are  any  significant  changes  of  the  relevant 
indicators. 

This is an input-based SCO. Therefore, there is no significant risk of 
‘creaming’  of  participants  and  perverse  incentives  (‘slicing’  of 
operations, etc.). 

Adjustment of 
amounts 

Regular updates based on the CVTS data. 

4.1.3.  Insights on application of this SCO 

Because the unit cost values for training for people in employment (calculated as a median 
of training costs per participant training hour) relate to inputs, there  are  no major risks 
related to slicing of operations. This measurement effectively eliminates differences due to 
the duration of interventions and helps to avoid pervasive incentive to shorten the training 
courses. 

However, an input-based SCO is less result-oriented, as it does not consider such factors 
as completion of the training course by its participant and is based on the total number of 
working  hours  spent  on  CVT  courses.  To  encourage  application  of  a  more  result-  and 
efficiency-oriented approach, additional requirements could be determined, e.g. to attend 
80% of the training course in order to declare the eligible costs of a participant training 
hour. 

50 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

4.2.  Option 2: trainee salary costs per training hour 

4.2.1.  Definition of the SCO 

This input-based SCO reflects trainee salary costs per training hour. To establish this SCO, 
we calculated the median hourly labour costs per employee incurred by enterprises in 
a particular Member State. Our calculations refer to all employees in private enterprises 
which support training. 

4.2.2.  Method to determine and update the amounts 

4.2.2.1.  Data sources 

Like previously discussed options, this SCO is also based on data extracted from the CVTS 4 
dataset.  The  calculated  values  could  be  updated  every  time  the  new  results  of  a  CVTS 
survey  are  available.  Alternatively,  amounts  could  be  revised  more  frequently  to  reflect 
the socioeconomic developments in EU Member States, in particular changing labour costs. 
For this purpose, Eurostat’s data on average hourly labour costs based on the Labour Cost 
Survey  (LCS)27  and  median  hourly  earnings  based  on  the  Structure  of  Earnings  Survey 
(SES)28 could be used. 

Notably, LCS data is better suited for adjusting the calculated unit cost values, as it reflects 
changes  in  the  average  hourly  labour  costs  (consisting  of  wages  and  salaries  and 
employers’  social  contributions  and  other  labour  costs  paid  by  the  employer)  and, 
therefore, corresponds to the SCO at hand. However, the LCS indicator was not sufficient 
to adjust the calculated unit costs values from the 2010 to the 2015 level, as it covers only 
2008  and  then  the  years  from  2012  to  2016.  Therefore,  our  team  used  median  hourly 
earnings  data  from  SES  to  adjust  the  rates  to  the  2014  level,  and  then  used  the  LCS 
indicator for adjustment to the 2015 level (for more information see Table 14). 

4.2.2.2. 

Sample and quality of data 

CVTS 4 standard datasets obtained by the study team from Eurostat covered 21 Member 
States.  Data  for  Austria,  Croatia,  Greece,  Ireland,  Latvia,  the  Netherlands  and  Slovenia 
were missing. Hence, the unit cost values for these countries were extrapolated. 

As  indicated  in  Table  12,  only  data  for  Belgium  needed  cleaning  –  we  removed  seven 
entries  from  the  dataset,  because  these  seven  enterprises  did  not  provide  any  relevant 
data. No cleaning of the standard dataset was needed for the remaining 20 countries, as 
all respondents provided the data needed for our calculations. 

TABLE 12. CVTS DATASET FOR OPTION 2 CALCULATIONS 

Country 

Original dataset 

Cleaned dataset 

BE 

BG 

CY 

CZ 

DE 

DK 

3434 

3772 

922 

7789 

3047 

1242 

3427 

3772 

922 

7789 

3047 

1242 

27 Measuring the level and structure of labour costs, or total expenditure borne by employers for the purpose of 

employing staff. 

28  Provides  comparable  information  at  EU  level  on  relationships  between  the  level  of  earnings,  individual 
characteristics of employees (sex, age, occupation, length of service, educational level) and their employer 
(economic activity, size of the enterprise, etc.). For reference years 2002, 2006, 2010 and 2014 (next survey 
with reference year 2018). 

51 

 
 
                               
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country 

Original dataset 

Cleaned dataset 

EE 

ES 

FI 

FR 

HU 

IT 

LT 

LU 

MT 

PL 

PT 

RO 

SE 

SK 

UK 

2185 

6667 

1560 

5411 

5125 

18424 

4075 

1254 

788 

14 027 

3888 

7733 

2014 

2042 

3568 

2185 

6667 

1560 

5411 

5125 

18424 

4075 

1254 

788 

14 027 

3888 

7733 

2014 

2042 

3568 

Source: compiled by PPMI. 

A significant number of outlier cases (i.e. cases larger/smaller than the median value by 
more  than  three  inter-quartile  ranges)  were  detected.  However,  since  medians  are  not 
sensitive to outliers, the outlier cases were retained in the dataset. 

4.2.2.3.  Analysis 

The  following  CVTS  variables  were  used  to  calculate  the  median  hourly  labour  cost  per 
employee: 

 

 

total number of hours worked by persons employed in the reference year (variable 
A4); 
total  labour  costs  (direct  +  indirect)  of  persons  employed  in  the  reference  year 
(variable A5). 

Notably,  standard  CVTS 4  datasets  include  only  derivative  indicators  for  the  above-
mentioned variables: 

 

 

‘A4ratio’: total number of hours worked by persons employed in the reference year 
(2010) per person employed; 
‘A5ratio’: total labour costs (direct + indirect) of persons employed in the reference 
year (2010) per person employed. 

Therefore, in our calculations we divided the ratio of total labour costs by the total number 
of hours worked in the reference year and calculated the median value: 

SCO2= median (

𝐴5 𝑟𝑎𝑡𝑖𝑜

𝐴4 𝑟𝑎𝑡𝑖𝑜

), where 

Definitions of main CVTS variables used in our calculations are provided in Table 13. 

Table 13. CVTS variables for calculation of Option 2 

Variable 

Definition 

Total  number  of 
persons 

The total number of persons employed includes all full-time and 
part-time  persons  employed.  Persons  employed:  working 
proprietors; partners working regularly in the enterprise; unpaid 

52 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Variable 

Definition 

employed on 31-
12-2010 (A2tot) 

Total  number  of 
hours  worked  in 
reference 
the 
year  2010  by 
persons 
employed (A4) 

Total 
labour 
costs  (direct  + 
indirect)  of  all 
persons 
employed  in  the 
reference 
year 
2010 (A5) 

family workers; persons from the enterprise and paid by it who 
work  away  from  the  enterprise  (e.g.  sales  representatives, 
delivery  personnel,  repair  and  maintenance  teams);  part-time 
workers and seasonal workers; people absent for a short period 
(e.g. sick leave, paid leave or special leave); those on strike but 
not  absent  for  an  indefinite  period.  It  excludes  anyone  who  is 
working  at  the  enterprise  but  whose  salary  is  paid  by  another 
company,  e.g.  persons  employed  by  firms  under  contract  or 
seconded  staff.  Also,  not  included  are  persons  absent  and  not 
being  paid  during  the  whole  reference  period  (e.g.  for  parental 
leave or long time compulsory military service). 

The total number of hours worked refers to the total number of 
hours  actually  worked  by  all  persons  employed,  excluding 
persons employed holding an apprentice or training contract, in 
2010. It includes time worked during normal periods of work (in 
the  enterprise  or  telecommuting),  time  worked  in  addition  to 
normal  periods  of  work  and  generally  paid  at  a  higher  rate 
(overtime), time spent at the place of work standing by or during 
which no work is done (but for which payment is made) and time 
corresponding  to  short  rest  periods,  including  tea  and  coffee 
breaks. It excludes time spent on paid leave, paid public holidays, 
paid sick leave, paid meal breaks. 

Total  labour  costs  of  persons  employed  (excluding  persons 
employed holding an apprentice or training contract) are defined 
as the sum of the direct and indirect labour costs. The estimate 
of  total  labour  costs  represents  all  expenditure  borne  by 
employers in order to employ workers. It should include: 

direct  labour  costs,  direct  pay,  other  bonuses  and  gratuities, 
payments for days not worked, benefits in kind; 

indirect labour costs,  statutory  social security contributions and 
family  allowances,  non-statutory  payments,  other  social 
expenditure,  vocational  training  costs  (gross),  taxes,  less 
subsidies on labour. 

Source: CVTS 4 manual, version 6. P. 25. 

Amounts  had  to  be  extrapolated  for  Austria,  Croatia,  Greece,  Ireland,  Latvia,  the 
Netherlands and Slovenia, because CVTS 4 data was not available for these countries. For 
extrapolation,  we  used  the  CVTS  data  available  for  other  countries  and  the  following 
statistical data from Eurostat: 

total unemployment rate; 
comparative price levels; 

 
 
  median equalised Income. 

After  carefully  examining  the  data,  we  found  that  two  countries,  namely  Sweden  and 
Luxembourg,  are  significant  outliers.  Therefore,  they  were  removed  from  further 
calculations  of  the  extrapolated  values.  The  extrapolation  itself  is  based  on  a  linear 
regression  (OLS)  model,  where  available  unit  cost  values  were  treated  as  a  dependent 
variable and Eurostat’s macroeconomic indicators – as independent variables. Our model 
satisfies the assumptions of a linear regression. Its explanatory power (R2) exceeds 80%. 

53 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Figure 5 demonstrates the predictive power of the model for extrapolation of trainee salary 
costs. 

FIGURE 5. PREDICTIVE POWER OF THE MODEL FOR TRAINEE SALARY COSTS 

Source: compiled by PPMI. 

4.2.2.4.  Results 

Average  trainee  salary  costs  (as  a  median  of  hourly  labour  cost  per  employee)  were 
calculated for all Member States (for seven countries unit cost values were extrapolated). 
The calculated values for 2010 were further adjusted to the 2015 level using the hourly 
median earnings indicator (from Eurostat’s Structure of Earnings Survey) and the average 
hourly  labour  cost  indicator  (from  Eurostat’s  Labour  Costs  Survey).  The  results  are 
summarised in Table 14, indicating the potential unit costs rates for each Member State 
adjusted to the 2015 level (see the last column). 

TABLE 14. AVERAGE TRAINEE SALARY COSTS AS A MEDIAN OF HOURLY LABOUR COST PER EMPLOYEE 

Country  SCO 2: 
Median 
hourly 
labour cost 
per 
employee 
23.14 
29.52 
1.48 
12.1 
7.16 
21.88 
30.63 
6.52 

AT e 
BE 
BG 
CY 
CZ 
DE 
DK 
EE 

hourly median 
earnings in 
euro: change 
between 2010 
and 2014 (SES) 

SCO 2 
adjusted 
to 2014 
level 

Average hourly 
labour costs: 
difference 
between 2014 
and 2015 (LCS) 

SCO 2 
adjusted 
to 2015 
level 

109% 
105% 
110% 
91% 
99% 
103% 
103% 
120% 

25.22 
31.00 
1.63 
11.01 
7.09 
22.54 
31.55 
7.82 

103% 
100% 
108% 
99% 
104% 
103% 
101% 
105% 

26.03 
31.08 
1.76 
10.94 
7.39 
23.11 
32.02 
8.22 

54 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Country  SCO 2: 
Median 
hourly 
labour cost 
per 
employee 
13.51 
17.51 
25.25 
22.91 
5.72 
4.57 
24.34 
21.29 
3.06 
22.56 
5.68 
7.15 
22.23 
4.03 
10.37 
2.29 
28.09 
6.59 
12.12 
11.66 

EL e 
ES 
FI 
FR 
HR e 
HU 
IE e 
IT 
LT 
LU 
LV e 
MT 
NL e 
PL 
PT 
RO 
SE 
SK 
SL e 
UK 

hourly median 
earnings in 
euro: change 
between 2010 
and 2014 (SES) 

SCO 2 
adjusted 
to 2014 
level 

Average hourly 
labour costs: 
difference 
between 2014 
and 2015 (LCS) 

SCO 2 
adjusted 
to 2015 
level 

88% 
104% 
108% 
109% 
101% 
107% 
111% 
105% 
116% 
103% 
118% 
114% 
104% 
107% 
101% 
105% 
116% 
112% 
102% 
113% 

11.89 
18.21 
27.27 
24.97 
5.78 
4.89 
27.02 
22.35 
3.55 
23.24 
6.70 
8.15 
23.12 
4.31 
10.47 
2.40 
32.58 
7.38 
12.36 
13.17 

97% 
100% 
102% 
101% 
102% 
103% 
101% 
99% 
105% 
100% 
108% 
103% 
101% 
104% 
102% 
107% 
100% 
103% 
101% 
115% 

11.56 
18.30 
27.69 
25.26 
5.90 
5.02 
27.20 
22.20 
3.71 
23.30 
7.21 
8.41 
23.33 
4.47 
10.63 
2.56 
32.67 
7.61 
12.52 
15.16 

Source: compiled by PPMI based on CVTS data and Eurostat’s macroeconomic indicators 
* Member States for which hourly labour were extrapolated. 

The highest average trainee salary costs as a median of hourly labour costs per employee 
are  in  Austria,  Belgium,  Denmark,  Finland,  France,  Ireland  and  Sweden.  The  unit  cost 
values in these countries are above EUR 25 per hour. The lowest unit cost values (below 
EUR 5 per hour) are in Bulgaria, Lithuania, Poland and Romania. The extent to which unit 
cost values vary across different Member States is shown in  

55 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Figure 6. 

56 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

FIGURE 6. AVERAGE TRAINEE SALARY COSTS AS A MEDIAN OF HOURLY LABOUR COST PER EMPLOYEE 
(ADJUSTED TO 2015 LEVEL) 

Source: prepared by PPMI. 

4.2.2.5.  Audit trail 

Audit trail for Option 2 

Types of 
operations 

Non-formal training of employed persons. 

This SCO supplements Option 1 (cost per participant training hour) 
and  can  be  funded  only  when  compliance  with  state  aid  rules  is 
ensured. 

Indicator name 

Labour costs related to participation of an employed person in one 
hour of training. 

Category of 
costs 

Wages for participants of the training operation (in addition to the 
training costs specified in the audit trail description for Option 1). 

Measurement 
unit for the 
indicator 

Number of completed training hours per participant. 

For example, if all four IT training events (each 10-hours long) were 
attended by 15 participants and the total number of participants of 
all five language training events (each 20-hours long) was 60, the 
total duration of training was 1800 (4*10*15+20*60) hours. 

Specific 
requirements 
for the audit 

Managing Authorities and intermediary bodies, taking into account 
relevant national practices, must ensure that the aggregate training 
hours  certified  to  the  Commission  are  traceable  to  separate 

57 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Audit trail for Option 2 

trail and 
justification of 
achievement of 
SCOs 

operations  and  participants,  where  for  each  participant  there  will 
have  to  be  a  sufficient  documentary  proof  on  (1)  the  number  of 
training hours attended by the participant and (2) the employment 
status of the participant. 

Examples of supporting documents related to proof of participation 
in a training course and duration of participation could include: 

  a  list  of  participants  of  the  training  course/event  with 

signatures for each day of the training/event; 
training programme/ curriculum; 
training schedule; 
register of attendance by the participant; 
register of training completion certificates; 

 
 
 
 
  other registers; 
  etc. 

Examples  of  supporting  documents  related  to  the  status  of  a 
participant (person in employment) could include documents, such 
as declaration of the beneficiary or sending organisation (employer 
of  the  participant),  employment  contract,  extract  from  registers, 
etc. 

The relevance of the SCO could be affected by possible changes in 
Member  State  interventions  related  to  training  for  people  in 
employment, such as lower cost/quality of training, larger training 
groups, etc. 

As  this  SCO  is  based  on  CVTS  statistics,  it  will  be  important  to 
monitor  if  there  are  any  significant  changes  of  the  relevant 
indicators. 

This is an input-based SCO. Therefore, there is no significant risk of 
‘creaming’  of  participants  and  perverse  incentives  (‘slicing’  of 
operations, etc.). 

Key risks and 
measures to 
prevent 
‘creaming’ of 
participants and 
perverse 
incentives 

Adjustment of 
amounts 

Regular updates based on the CVTS data. 

4.2.3.  Insights on application of this SCO 

The unit cost values for trainee salary costs calculated as a median of hourly labour costs 
per  employee can be  easily updated using the most recent CVTS data (i.e. 2015). Also, 
the results of calculations could be cross-checked and updated using LCS and SES data. 
This SCO supplements  Option 1, but it can only be applied for  operations which comply 
with state aid rules. 

4.3.  Relevance of EU-level SCOs for people in employment to training for public 

servants 

EU-level  SCOs  for  training  of  public  servants  cannot  be  established  due  to  the  limited 
availability  of  relevant  data.  In  addition,  our  analysis  revealed  that  unit  cost  rates 
calculated  for  those  few  Member  States  where  administrative  data  was  available  do  not 
correspond to amounts established for training for people in employment based on CVTS 
data. Therefore, we conclude that Member States should set/use their own national SCOs 

58 

 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

for  training  of  public  servants.  A  more  detailed  reasoning  is  provided  in  the  following 
sections. 

STATUS OF DATA AVAILABILITY 

To collect the historical administrative data on training for public servants possessed by 
Member States, the study team circulated a tailored e-form to our contact points in each 
country.  As  a  result,  nine  countries/regions  (Bulgaria,  Cyprus,  Estonia,  Germany 
(Bremen), Greece, Lithuania, Malta, Poland and Portugal) sent us at least some of the 
requested data (see Figure 7 for more details on data availability). However, both the 
volume and quality of this data varied significantly. 

Figure  7.  Status  of  data 
availability  on  trainings  for 
public servants 

low 

interest  and  highly 

Such  results  clearly  indicate  that  Member  States 
limited 
have  rather 
capacities to facilitate the development of EU-level 
SCOs  in  this  area.  Furthermore,  SCOs  for  training 
of  public  servants  are  irrelevant  in  many  Member 
States  since  they  do  not  finance  such  kind  of 
training.  Based  on  the  results  of  our  data 
availability survey that was launched in July 2017, 
eight 
(Flanders, 
Wallonia),  Germany  (Hamburg,  Saxony),  Ireland, 
Luxembourg,  the  Netherlands  and  the  United 
Kingdom) indicated that training for public servants 
was  not  supported  either  in  2007-2013,  or  in  the 
2014-2020  period.  During  the  follow-up  data 
collection  phase,  six  more  countries/  regions 
(Austria, Germany (federal level), Denmark, Spain, 
Finland  and  Sweden)  indicated  that  trainings  for 
public servants are irrelevant to them. 

countries/regions 

(Belgium 

EXHAUSTIVENESS AND QUALITY OF THE DATA COLLECTED  

Source: prepared by PPMI. 

As  already  mentioned,  the  data  that  we  managed 
to obtain from nine countries/regions differs considerably, and not only in the number of 
operations covered, but also in the exhaustiveness of the information provided on inputs 
and outputs of supported training activities. As shown in Table 15, for some countries the 
number  of  operations  submitted  is  either  very  small  or  was  provided  to  our  team  in  an 
aggregated form (e.g. Cyprus, Germany (Bremen)). Though such data were sufficient to 
calculate costs per training hour (see Table 15), the reliability of data was not enough to 
establish  national  or  EU  level  SCOs.  In  all  other  cases  (e.g.  Bulgaria,  Estonia,  Greece, 
Lithuania, Poland and Portugal), the data is rather detailed and apparently sufficient for 
setting the national SCOs. 

TABLE 15. TRAINING FOR PUBLIC SERVANTS: AVAILABILITY OF DATA PER MEMBER STATE AND PER OPTION/ 
CALCULATION METHOD 

Number of operations 

Country 

Total  SCO 1  SCO 2 

Description of the data / trainings 

BG 

183 

183 

0 

The data provided covered 183 operations. Data 
received  was  sufficient  to  calculate  cost  per 
participant training hour. From the data received 
two  target  groups  of  training  can  be  clearly 
identified:  public  servants  and  judiciary.  The 
trainings  for  the  judiciary  were  several  times 

59 

 
 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Number of operations 

Country 

Total  SCO 1  SCO 2 

Description of the data / trainings 

CY 

1 

1 

0 

DE (Bremen)  2 

2 

1 

EE 

28 

10 

0 

more  expensive  than  the  general  trainings  for 
public servants. 

The data provided covered one operation, which 
financed  under  2007-2013  OP.  Data 
was 
received  was  sufficient  to  calculate  cost  per 
participant training hour. The main target group 
of  the  trainings  was  civil  servants  in  all 
government departments. 

The  data  provided  covered  two  operations 
financed  under  2007-2013  OP.  Data  received 
was  sufficient  to  calculate  cost  per  participant 
training  hour  and  trainee  salary  costs  per 
training hour (only for one operation). 

The  data  provided  covered  28  operations, 
though, only 10 have information on the training 
costs (as compared to total eligible costs). Data 
received  was  sufficient  to  calculate  cost  per 
participant training hour. The trainings targeted 
both state and local government public servants; 
rural  municipality  and  city  council  members; 
state  and  local  government  shareholding  non-
and 
profit 
companies. The trainings organised also covered 
health  care  and  education  sectors.  The  themes 
covered 
included 
communication;  internal  risk  management  for 
for 
auditors; 
local 
employees; 
government 
development 
members, 
representatives of state shareholding companies 
and foundations. 

trainings 
and 
council 

officials 
of 

organisations, 

foundations 

induction 

trainings 

the 

by 

EL 

15 

15 

1 

LT 

879 

222 

126 

The  data  provided  covered  15  operations 
financed under both 2007-2013 and 2014-2020 
periods. Data received was sufficient to calculate 
cost  per  participant  training  hour  and  trainee 
salary costs per training hour (based only on one 
operation).  The  main  target  groups  of  the 
trainings included the judiciary, public servants, 
employees  of 
local  authorities,  diplomats 
(Ministry  of  Foreign  Affairs).  Some  of  the 
trainings organised included seminars abroad. 

The  data  provided  covered  879  operations 
(project  activities)  financed  under  the  2007-
2013  period.  Data  received  was  sufficient  to 
calculate  all  costs  per  participant  training  hour 
and  trainee  salary  costs  per  training  hour.  A 

60 

 
 
 
Developing ‘Off-the-Shelf’ Simplified Cost Options (SCOs) under Article 14.1 of the 
European Social Fund (ESF) regulation 

Number of operations 

Country 

Total  SCO 1  SCO 2 

Description of the data / trainings 

MT 

7 

0 

0 

PL 

24 

24 

24 

PT 

1954  1954 

1455 

broad  variety  of  trainings  were  financed  for 
different target groups. 

The data provided covered 7 operations financed 
under the 2007-2013 period. Data received was 
insufficient  to  calculate  cost  per  training  hour. 
Attendance  of  trainings/  seminars  abroad  was 
financed. 

The  data  provided  covered  24  operations 
financed  under  the  2007-2013  period.  Data 
received  was  sufficient  to  calculate  cost  per 
participant training hour and trainee salary costs 
per  training  hour.  The  target  group  of  the 
trainings was local government employees. 

The  data  provided  covered  1954  operations 
financed  under  the  2007-2013  period.  Data 
received  was  sufficient  to  calculate  cost  per 
participant training hour and trainee salary costs 
per  training  hour.  Trainings  were  organised  for 
public  servants  in  central  administration,  local 
administration, education and health sectors. 

Source: compiled by PPMI based on the data provided by Member States. 

COMPARISON OF CVTS AND ADMINISTRATIVE DATA 

The  data  available  from  Member  States  clearly  indicates  that  interventions  financed  by 
Member States vary significantly in terms  of type  of training offered (e.g. target group, 
level of skills trained, etc.), duration of training per participant, number of participants per 
training course, etc. It is also evident that costs of training for public servants are much 
higher than amounts proposed in this study for training of people in employment, at least 
in some of the cases where comparison was possible (e.g. in Greece). Therefore, the study 
concludes that using the same unit cost rates as those suggested for training of people in 
employment (based on CVTS data) could be relevant if accepting that the full costs will not 
be  reimbursed  or  for  some  particular  operations  for  which  training  costs  are  close  to 
average costs of training for employed persons. To have a closer proxy to the real costs, 
Member States also have the option of proposing a national level SCO. 

61 

 
 
 
 
 
Getting in touch with the EU

In person

All over the European Union there are hundreds of Europe Direct Information Centres. You can find the address of the 
centre nearest you at: http://europa.eu/contact

On the phone or by e-mail

Europe Direct is a service that answers your questions about the European Union. You can contact this service

– by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls),

– at the following standard number: +32 22999696 or

– by electronic mail via: http://europa.eu/contact

Finding information about the EU

Online

Information about the European Union in all the official languages of the EU is available on the Europa website at: 
http://europa.eu 

EU Publications

You can download or order free and priced EU publications from EU Bookshop at: http://bookshop.europa.eu.  
Multiple copies of free publications may be obtained by contacting Europe Direct or your local information centre 
(see http://europa.eu/contact)

EU law and related documents

For access to legal information from the EU, including all EU law since 1951 in all the official language versions, go 
to EUR-Lex at: http://eur-lex.europa.eu

Open data from the EU

The EU Open Data Portal (http://data.europa.eu/euodp/en/data) provides access to datasets from the EU. Data can be 
downloaded and reused for free, both for commercial and non-commercial purposes.

 
K
E
-
0
2
-
1
8
-
8
4
3
-
E
N
-
N

         doi: 10.2767/787584 

ISBN 978-92-79-86975-4