COMMISSION STAFF WORKING DOCUMENT EVALUATION of the 2007-2013 rural development programmes - synthesis [Art 87 of Reg. (EU) 1698/2005]
Date: 2022-06-30
Institutions: Directorate-General for Agriculture and Rural Development, European Commission
Subjects: EAFRD, EU aid, EU programme, aid to agriculture, common agricultural policy, competitiveness, operational programme, rural development, rural region, sustainable development

EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 30.6.2022  SWD(2022) 182 final  COMMISSION STAFF WORKING DOCUMENT  EVALUATION  of the 2007-2013 rural development programmes - synthesis  [Art 87 of Reg. (EU) 1698/2005]      {SWD(2022) 183 final}  
 
 
Table of contents 

1. 

INTRODUCTION ................................................................................................................................ 3 

Purpose and scope............................................................................................................................................ 3 

2. 

BACKGROUND TO THE INTERVENTION ..................................................................................... 3 

Description of the intervention and its objectives ............................................................................................ 3 

Baseline and points of comparison .................................................................................................................. 7 

3. 

IMPLEMENTATION / STATE OF PLAY .......................................................................................... 8 

4.  METHOD............................................................................................................................................ 10 

4.1.  Method for the evaluation support study ........................................................................................ 11 

4.2.  Internet based public consultation .................................................................................................. 13 

4.3.  European Economic and Social Committee Report ........................................................................ 13 

4.4.  Limitations and robustness of findings ........................................................................................... 14 

5.  ANALYSIS AND ANSWERS TO THE EVALUATION QUESTIONS .......................................... 15 

5.1.  EFFECTIVENESS .............................................................................................................................. 15 

5.1.1. Axis 1. Improving the competitiveness of the agricultural and forestry sector .............................. 15 

5.1.2. Axis 2. Environment and the countryside ....................................................................................... 23 

5.1.3. Axis 3. Improving the quality of life in rural areas and encouraging diversification of the 

rural economy ................................................................................................................................. 31 

5.1.4. Axis 4. Building local capacity (LEADER) ................................................................................... 37 

5.2.  EFFICIENCY...................................................................................................................................... 41 

5.2.1. Qualitative assessment ..................................................................................................................... 41 

5.2.2. Quantitative assessment ................................................................................................................... 42 

5.3.  COHERENCE ..................................................................................................................................... 51 

5.3.1. Coherence of rural development policy with other CAP funds and other EU interventions in the same 
programme area ............................................................................................................................................. 51 

5.3.2. Coherence with the overall rural development priorities ..................................................................... 52 

5.4.  RELEVANCE ..................................................................................................................................... 53 

5.5.  EU ADDED VALUE .......................................................................................................................... 55 

6. 

CONCLUSIONS ................................................................................................................................. 56 

ANNEX 1. LEAD DG, DECIDE PLANNING/CWP REFERENCES ........................................................ 62 

ANNEX 2. STAKEHOLDER CONSULTATION ....................................................................................... 66 

ANNEX  3.  DATA  ON  IMPLEMENTATION  OF  RURAL  DEVELOPMENT  PROGRAMMES 
BY MEASURE ............................................................................................................................................. 74 

ANNEX 4. INTERVENTION LOGIC BY AXIS ........................................................................................ 92 

1 

 
 
 
Term or acronym 

Meaning or definition 

Glossary 

AWU 

CAP 

CMEF 

EAFRD 

EESC 

ENRD 

ESIF 

EU 

GDP 

GVA 

LAG(s) 

LEADER 

RI 

SWOT 

UAA 

Annual Work Unit 

Common Agriculture Policy 

Common Monitoring and Evaluation Framework 

European Agricultural Fund for Rural Development  

European Economic and Social Committee 

European Network for Rural Development 

European Structural and Investment Funds 

European Union 

Gross Domestic Product 

Gross Value Added 

Local Action Groups 

Liaison Entre Actions de Développement de l’Économie Rurale 

Result Indicator 

Strengths, Weaknesses, Opportunities and Threats 

Utilised Agricultural Area 

2 

 
 
 
1. 

INTRODUCTION 

Purpose and scope 

As part of the implementation of the 2007-2013 Rural Development policy, in 2015 Member 
States had to carry out the ex post evaluation of their rural development programmes.1 These 
evaluations  had  to  examine  the  degree  of  utilisation  of  resources,  the  effectiveness  and 
efficiency  of  the  programming  of  the  European  Agricultural  Fund  for  Rural  Development 
(EAFRD), its socio-economic impact and its impact on the Community priorities. They also 
had  to  cover  the  goals  of  the  programme  and  aimed  to  draw  lessons  concerning  rural 
development policy. They were expected to identify the factors that contributed to the success 
or  failure  of  the  programmes’  implementation,  including  as  regards  sustainability,  and 
identify best practice. 

The current evaluation provides a summary of the findings of these ex post evaluations and 
analyses the effectiveness, efficiency, coherence, relevance and EU added value of the 2007-
2013 Rural  Development  Policy  based on  a synthesis  of the work of the Member States.  It 
builds on the ex post evaluations of the rural development programmes in 26 Member States: 
Croatia  did  not  have  an  EAFRD  financed  rural  development  programme  in  the  2007-2013 
period.  Bulgaria did not  provide an ex post evaluation of its rural  development  programme 
for the period in question during the preparation of the evaluation support study2. 

A  number  of  the  issues  raised  in  this  evaluation  had  already  been  identified  during  the 
implementation of the programmes and were addressed in the legal framework for the 2014-
2020  programming  period  (for  example,  revising  the  Common  Monitoring  and  Evaluation 
Framework to improve the intervention logic, reduce the number of indicators and simplify 
the  evaluation  questions,  and  streamline  reporting).  The  lessons  drawn  from  this  synthesis 
have further served to inform the preparation of the post 2020 Commission proposals for the 
modernisation  of  the  Common  Agricultural  Policy  (CAP)  and  will  be  useful  for  the 
assessment of the Member States’ CAP Strategic Plans that are central in the Commission’s 
proposals3. 

The conclusions of this evaluation is also very relevant for the long-term vision for the EU’s 
rural areas4, which aims to enable rural areas to make the most of their potential and support 
them in facing their own unique set of issues, from demographic change to connectivity, the 
risk of poverty and limited access to services. 

2.  BACKGROUND TO THE INTERVENTION 

Description of the intervention and its objectives 

The EU’s rural development policy aims at helping the rural areas of the EU to meet a wide 
range  of  economic,  environmental  and  social  challenges.  Frequently  called  "the  second 

1   Article 86 of Council Regulation (EC) No 1698/2005, OJ L 277, 21.10.2005, p. 1–40. 
2   Synthesis of Rural Development Programmes (RDPs) ex-post evaluations of period 2007-2013 
3   COM (2018) 392 final. 
4  European Commission, A long-term Vision for the EU’s Rural Areas, COM(2021)345 final, 

EUR-Lex 52021DC0345 - EN - EUR-Lex (europa.eu). 

3 

 
 
                                                 
pillar”  of  the  Common  Agricultural  Policy  (CAP),  it  complements  the  system  of  direct 
payments  to  farmers  and  the  measures  to  manage  agricultural  markets  (the  so-called  "first 
pillar").  EU  rural  development policy  offers  a flexible approach, based on the principles of 
subsidiarity and partnership. When designing rural development programmes, Member States 
have  a  significant  degree  of  flexibility  in  finding  a  balance  between  the  sectoral  dimension 
(i.e.  agricultural  restructuring)  and  the  territorial  dimension  (i.e.  land  management  and  the 
socio-economic  development  of  rural  areas).  From  a  menu  of  approximately  40  support 
measures,  Member  States  select  those  best  suited  to  address  the  specific  strengths  and 
weaknesses of individual programming areas. 

In  a  first  step,  based  on  a  thorough  analysis  of  the  economic,  social  and  environmental 
situation  of  their  rural  areas  and  their  potential  for  development,  Member  States  submitted 
national strategy plans translating  to the Member State situation the EU priorities agreed in 
the Community strategic guidelines for rural development5. These priorities were: improving 
the  competitiveness  of  the  agricultural  and  forestry  sector;  improving  the  environment  and 
the countryside; improving the quality of life in rural areas and encouraging diversification of 
the  rural  economy;  building  local  capacity  for  employment  and  diversification;  ensuring 
consistency  in  programming  (maximise  synergies  between  axes);  and  complementarity 
between Community instruments.  

In  a  second  step,  based  on  a  SWOT  (Strengths,  Weaknesses,  Opportunities  and  Threats) 
analysis, choosing from a set of measures for which they could receive Community financial 
support,  Member  States  established,  at  national  or  regional  level,  integrated  rural 
development programmes, specifying what funding was to be spent on which measures in the 
period 2007-2013. Member States and regions had to spread their rural development funding 
between three thematic axes: Axis 1 - economic concerns (competitiveness of agriculture and 
forestry),  Axis  2  -  the  environment  and  the  countryside  (biodiversity,  climate  change, 
sustainable  resource  use  in  agriculture  and  forests)  and  Axis  3  -  social  aspects  (quality  of 
life). Moreover, a part of the funding had to support the implementation of local development 
strategies by the local action groups of LEADER (Liaison Entre Actions de Développement 
de l’Économie Rurale). This "LEADER approach" to rural development involves individual 
projects  designed  and  executed  by  local  partnerships  to  address  specific  local  problems  in 
line  with  a  local  development  strategy  (LDS).  This  horizontal  approach  was  implemented 
through Axis 4 of the Rural Development. 

The whole process of preparing the rural development programmes was carried out in close 
cooperation between the Member States and the Commission services. 

Funding from the European Agricultural Fund for Rural Development (EAFRD) of each rural 
development programme had to be spread between the four axes, as a safeguard to ensure that 
the  programme  reflected  the  main  policy  objectives.  The  required  minimum  funding  was 
10% for Axis  1, 25% for Axis  2, 10% for  Axis 3 and 5% for  LEADER (2.5% for the new 
Member States). These minimum percentages were sufficiently low to leave Member States 
or  regions  a  high  margin  of  flexibility  to  emphasize  the  policy  axis  in  function  of  their 

5  Council Decision 2006/144/EC. 

4 

 
                                                 
situation and needs.  The EAFRD  had a total  endowment  of  EUR 96.2 billion for the 2007-
2013 period6. 

Table 1. Overview of rural development measures 

Axis 1 - competitiveness 

111 - Vocational training and information actions 
112 - Setting up of young farmers 
113 - Early retirement 
114 - Use of advisory services 
115 - Setting up of management, relief and advisory services 
121 - Modernisation of agricultural holdings 
122 - Improvement of the economic value of forests 
123 - Adding value to agricultural and forestry products 
124 - Cooperation for development of new products, processes and technologies in the agriculture and food 

sector and in the forestry sector 

125 - Infrastructure related to the development and adaptation of agriculture and forestry 
126 - Restoring agricultural production potential 
131 - Meeting standards based on EU legislation 
132 - Participation of farmers in food quality schemes 
133 - Information and promotion activities 
141 - Semi-subsistence farming 
142 - Producer groups 
143 - Providing farm advisory and extension services 
144 - Holdings undergoing restructuring due to a reform of a common market organization 

Axis 2 – Environment and countryside 

211 - Natural handicap payments to farmers in mountain areas 
212 - Payments to farmers in areas with handicaps other than mountain areas 
213 - Natura 2000 payments and payments linked to Directive 2000/60/EC 
214 - Agri-environment payments 
215 - Animal welfare payments 
216 - Non-productive investments 
221 - First afforestation of agricultural land 
222 - First establishment of agroforestry systems on agricultural land 
223 - First afforestation of non-agricultural land 
224 - Natura 2000 payments 
225 - Forest-environment payments 
226 - Restoring forestry potential and introducing prevention actions 
227 - Non-productive investments 

Axis 3 – Diversification and quality of life 

311 - Diversification into non-agricultural activities 
312 - Support for business creation and development 
313 - Encouragement of tourism activities 
321 - Basic services for the economy and rural population 
322 - Village renewal and development 
323 - Conservation and upgrading of the rural heritage 
331 - Training and information 
341 - Skills-acquisition and animation measure with a view to preparing and implementing a local 
development strategy 

6 

Including  amounts  arising  from  the  application  of  the  modulation  system  introduced  in  the  2008  CAP 
health check. 

5 

 
 
 
 
 
                                                 
Axis 4 - LEADER 

411 - Competitiveness 
412 - Environment/land management  
413 - Quality of life/diversification 
421 - Implementing cooperation projects 
431 - Running the LAG, skills acquisition, animation 
Source: DG Agriculture and Rural Development 

The  figure  below  presents  a  high-level  intervention  logic  for  the  2007-2013  rural 
development  programmes.  A  more  detailed  intervention  logic  per  axis  is  presented  in  the 
Annex 3. 

Figure 1. Intervention logic for the 2007-2013 rural development programmes 

Source: DG Agriculture and Rural Development 

In 2008, a CAP policy review process, known as the ‘health check’, included an increase in 
modulation, whereby direct payments to farmers were reduced and the funding transferred to 
rural  development  (Council  Regulations  (EC)  No. 73/2009  and  (EC)  No. 74/2009).  In 
addition,  a  further  EUR 1.02 billion  was  made  available  to  Member  States  and  regions  to 
reinforce  their  rural  development  programmes  as  part  of  the  European  Economic  Recovery 
Plan  agreed  in  December  2008.  The  additional  funding  was  reserved  for  actions  related  to 
climate  change,  renewable  energy,  water  management,  biodiversity,  innovation  linked  to 
these four areas, developing broadband internet in rural areas, or for accompanying measures 
in the dairy sector. 

An  important  element  of  the  2007-2013  rural  development  policy  was  the  creation  of  a 
common  monitoring  and  evaluation  framework,  including  an  indicator  set  (output,  result, 
impact  and  context  indicators)  and  periodic  evaluations  to  be  carried  out  by  the  Member 
States on the basis of predefined evaluation questions. 

The  ex  post  evaluation  of  a  rural  development  programme  is  the  final  part  of  ongoing 
evaluation of the programming period of 2007-2013, built upon its monitoring and evaluation 
activities conducted throughout the programme implementation period. 

6 

 
 
Baseline and points of comparison  

In  2006,  which  served  as  baseline  for  the  ex  post  evaluations,  the  EU-277  rural  areas 
(predominantly rural and intermediate regions) represented 91% of the territory and 56% of 
the  population8.  The  corresponding  shares  for  predominantly  rural  areas  were  54.4%  of  the 
territory  and  19.2%  of  the  population.  Rural  areas  are  therefore  particularly  important  in 
terms of territory. Among the Member States, the importance of rural areas varied from the 
more "urban" ones (Belgium, Netherlands, Malta) to the more "rural" ones (Ireland, Finland, 
Slovenia)  along  a  continuum  where  intermediate  regions  can  play  a  major  role.  Even  if 
economic  activity  tends  to  be  concentrated  in  more  densely  populated  areas,  rural  areas  in 
2006  generated  43%  of  the  Gross  Value  Added  (GVA)  in  the  EU-27  and  provided  almost 
55%  of  the  employment9.  However,  compared  to  urban  areas,  rural  areas  lagged  behind  as 
regards a number of socio-economic indicators: demographic situation in some areas, income 
per capita, lower employment rate and higher unemployment rate, human capital, activity of 
women and young people, development of the tertiary sector as well as other aspects linked 
to the quality of life. 

The  impact  assessment  in  view  of  the  post  2006  rural  development  policy10  carried  out  in 
2004 and the ex-ante evaluations11 pointed to the difficulties of many rural areas to adjust to 
changes  brought  about  by  a  combination  of  factors,  including  continuing  technological 
change, a decline in real food prices and in the proportion of income spent on food, and the 
difficulties of competing in increasingly global food markets. 

As a result, at the time, rural regions faced significant economic problems, including: 

  high  rates  of  unemployment,  which  stood  at  11.1%  in  predominantly  rural  areas, 

compared to an average of 9.8% across the EU-25 as a whole (1999/2001 average); 

  widespread problems of underemployment;  
 

low  levels  of  Gross  Domestic  Product  (GDP)  per  head,  which  in  predominantly  rural 
areas stood at 71% of the EU-25 average in 1999-2001; and  
 a relative shortage of new development opportunities in many rural areas.  

 

At the start of the programming period, Member States were at different levels of dependence 
on the primary sector. Within the EU-27, employment in the primary sector in 2006 was 6%, 
yet  with  wide  variations,  from  1.5%  in  the  UK  and  1.6%  in  Luxembourg  to  20.5%  in 
Bulgaria  and  30%  in  Romania.  The  central  and  eastern  European  Member  States  were 
particularly  heavily  dependent  on  agriculture,  however,  also  here  significant  variations  are 
apparent,  less  than  4%  of  the  workforce  of  Czechia  and  Slovakia  were  employed  in 
agriculture in 200612. 

In terms of gross value added, there were also large variations: the primary sector accounted 
for 0.4% of total GVA in Luxembourg, but for 8.8% in Romania in 200613. 

7  The 27 countries that were member of the European Union in 2006. 
8  Rural development in the EU statistical and economic information: report 2009. 
9 
10  https://ec.europa.eu/smart-regulation/impact/ia_carried_out/docs/ia_2004/sec_2004_0931_en.pdf . 
11  https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/cmef/rural-

See footnote 8. 

areas/synthesis-ex-ante-evaluations-rural-development-programmes-2007-13_en. 

12  See footnote 8. 
13  See footnote 8. 

7 

 
                                                 
At  the  social  level,  the  more  peripheral  local  areas  were  characterised  by  depopulation, 
caused by negative rates of change in natural population (where there are more deaths than 
births) and  high rates of out-migration (especially  among  young people), leaving behind  an 
ageing population. Rural population is usually older than average.  

At the same time, many less remote rural areas in Europe faced very different issues, as they 
often presented an attractive alternative to living in cities, and were experiencing population 
growth.  In  many  Member  States,  in-migration  to  rural  areas  from  urban  areas  was  an 
increasing trend, often involving increased populations of commuters and retired people. This 
led to other problems such as increased development pressures in the countryside, a change in 
the  balance  of  rural  communities,  and  shortages  of  affordable  housing  as  wealthier  urban 
incomers out-bid local residents. 

The 2004 impact assessment also pointed out that Europe’s rural environment was subject to 
a variety of pressures, stemming from the intensification of land management in many areas, 
and its abandonment in others. 

The marginal viability of both agriculture and forestry has brought a widespread risk of land 
abandonment  to  many  rural  areas  with  consequences  for  the  landscape  and  environment. 
Agriculture and forestry are the main land users and play a key role in the management of the 
natural  resources  in  rural  areas  and  in  shaping  rural  landscapes  and  wildlife  habitats. 
Managed farmland and forests make an important contribution to maintenance of high natural 
value areas in the EU. 

3. 

IMPLEMENTATION / STATE OF PLAY 

The  2007-2013  programming  period  was  fully  closed  by  2020.  The  overall  financial 
implementation rate for the 92 programmes for the 2007-2013 period reached 97.0%, where 
EUR 93.4 billion funds were consumed in comparison with the EUR 96.2 billion of initially 
available EU funds.  

Figure 2. EAFRD expenditure by Member State (in millions) 

16.000

14.000

12.000

10.000

8.000

6.000

4.000

2.000

0

BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK

Source: DG Agriculture and Rural Development 

8 

 
 
Overall,  the  largest  share  of  EAFRD  spending  went  to  Axis  2  (Environment),  followed  by 
Axis  1  (Competitiveness).  These  two  account  for  above  80%  of  EAFRD  spending.  The 
differences in Member States choices are illustrated in Figure 4. 

Figure 3. Share of EAFRD spending by axis 

6,1%

12,6%

32,7%

48,6%

Axis 1 (Competitiveness)

Axis 2 (Environment and the countryside)

Axis 3 (Diversification of the rural economy) Axis 4 (LEADER)

Source: DG Agriculture and Rural Development 

Figure 4. EAFRD spending by Axis per Member State 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

AT BE BG CY CZ DE DK EE ES FI FR GR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK

Source: DG Agriculture and Rural Development 

axis 1

axis 2

axis3

axis4

9 

 
 
 
 
Figure 5 (below) presents an overview of the most important measures in  terms of share of 
the EAFRD contribution for the EU-27. 

Figure 5. EAFRD measures by importance 

M113 (Early retirement)

2,9%

M322 (Village renewal and development)

M112 (Setting up young farmers)

M321 (Basic services for the economy and rural
population)

M413 (Implementation of local development
strategies)

M125 (Improving and developing infrastructure
related to the development and adaptation of…
M123 (Adding value to agricultural and forestry
products)
M211 (Natural handicap payments to farmers in
mountain area)

M212 (Payments to farmers in areas with handicaps,
other than mountain areas)

3,4%

3,5%

3,9%

4,2%

4,6%

4,7%

7,9%

8,2%

M121 (Modernisation of farms)

12,5%

M214 (Agri-environment payments)

25,2%

0%

5%

10%

15%

20%

25%

30%

Source: DG Agriculture and Rural Development 
Overall,  the  rural  development  programmes  in  the  programming  period  contributed  among 
other to: 

  578 000 farm modernisation projects; 
  start-up support for 192 000 young farmers; 
  385 000 farmers' involvement in quality schemes; 
  more than 6.8 million training days for farmers; 
  More than 48 000 000 physical hectares supported under agri-environment. 

4.  METHOD 

The  purpose  of  this  evaluation  is  to  provide  a  synthesis  and  an  analysis  of  the  ex  post 
evaluations  of  the  2007-2013  rural  development  programmes  submitted  by  the  Managing 
Authorities,  to  identify  common  trends,  highlight  differences  between  the  programmes  and 
provide conclusions  and lessons  learned. This  evaluation  is  based on three main sources  of 
input: 

  The  evaluation  support  study  of  the  external  contractor.  This  is  based  on  the 

evaluations carried out by the Member States14. 

  A public consultation that ran  from  22 January  2018 to  20 April 2018  and obtained 

720 replies. 

14  The contractor used 91 rural development programme ex post evaluation reports. 

10 

 
  
                                                 
  The European Economic and Social Committee (EESC) information report ‘Ex post 

evaluation of rural development programmes 2007-2013’15. 

Additionally, findings published in Special Reports of the European Court of Auditors were 
used where relevant for this evaluation. 

4.1.  METHOD FOR THE EVALUATION SUPPORT STUDY 

The evaluation support study is based on the Member States’ ex post evaluations. These were 
carried out by either external or in some cases in-house, but always functionally independent 
evaluators, based on a set  of evaluation  questions predefined at  EU level. The Commission 
provided  guidance  on  intervention  logic,  evaluation  questions,  indicators  and  evaluation 
methods  via  the  publication  of  guidance  documents16,  the  setting  up  of  an  evaluation 
helpdesk17 and by providing a forum for the exchange of good practices via the creation of the 
Expert Committee on Evaluation of rural development programmes. Despite these efforts, the 
quality of the ex post evaluation reports were varying from one programme to another. 

As  a  first  step,  the  evaluation  support  study  had  to  provide  a  synthetic  answer  to  a  set  of 
evaluation questions based on the replies given by each individual Member State to exactly 
the  same  set  of  standardised  questions  in  their  ex  post  evaluation  of  the  rural  development 
programmes. 

These questions were either: 

  Programme  related,  assessing  the  effectiveness  of  the  programme  in  reaching  its 
objectives  and  the  efficiency  of  the  rural  development  programmes  as  a  whole 
(‘programme related questions’), 

  Measure  related,  assessing  the  effectiveness  of  the  individual  measures  in  the  rural 

development programmes (‘measure related’). 

Additionally, a few questions addressed specifically the implementation and effectiveness of 
LEADER. 

Member  States’  evaluators  could  select  the  evaluation  methodology  they  found  best  suited, 
allowing them to take into account local circumstances. 

The  Member  States’  ex  post  evaluation  reports  contained  both  quantitative  and  qualitative 
information on target and implementation values (output and result indicators). However, the 
quantitative data could not be used to provide an overall judgment on the effectiveness of the 
implemented  rural  development  programmes,  as  target  values  were  adjusted  multiple  times 
during the life cycle of the programme. Moreover some of the adjustments made to the target 
values  consisted  of  unnecessary  reductions,  resulting  in  multiple  cases  where  ex  post 
evaluations  observed a degree of implementation (comparing implemented to  target  values) 
above  100%,  sometimes  even  largely  above  this  figure.  Therefore  the  qualitative  data 
provided  in  the  ex  post  evaluation  reports  bore  particular  importance  in  the  overall 
assessment of both the single measures and programmes performance. 

15  NAT/699-EESC-2017-00690-00-00-RI-TRA. 
16  European Evaluation Network for Rural development, “Capturing the success of your RDP: Guidelines for 

the ex post evaluation of 2007-2013 Rural development programmes”, Brussels, 2014. 
17  A contractor who provided evaluation-related technical and administrative assistance. 

11 

 
                                                 
Therefore,  the  programme-,  measure-  and  LEADER-related  questions  were  assessed  using 
three criteria: 

1)  Extent (of contribution): 

For  each  of  the  questions,  the  Member  States’  evaluations  were  categorised  by  the 
contractor on the basis of the quantitative and particularly qualitative data provided in 
the ex post evaluation reports in relation to the measures’ impact as follows: 

- positive contribution; 
- limited contribution; 
- no contribution; 
- negative contribution; 
- not clear; 
- not measured. 

Based on the share of reports that reported a positive conclusion over all those that provided a 
conclusion  for  the  question  at  stake  (so  excluding  those  categorised  in  “not  clear”  or  “not 
measured”), the extent was judged as  

- very limited if the share is 25% or lower; 
- limited if the share is 26-49%; 
- medium if the share is 50-75%; 
- high if the share is above 75%. 

2)  Plausibility: 

This  measures  if  the  judgement  made  on  extent  of  contribution  is  based  on  sufficient 
evidence. Plausibility of the answers was based on the share of the ex post evaluation reports 
that provided a conclusion. Reports for which the contribution was not clear or not measured 
were considered as not having provided a conclusion. 

- very plausible: >85% of the reports provide a conclusion; 
- plausible: 50-85% of the reports provide a conclusion; 
- not plausible <50% of the reports provide a conclusion. 

3)  Certainty: 

Finally,  for  the  programme  related  questions,  certainty  judges  the  quantitative  assessment 
based on the completeness and comparability of the quantitative data: 

- certain: >80% of the regions/MS have comparable indicators; 
- partly certain: between 50-80% have comparable indicators; 
- not certain: <50% have comparable indicators. 

As  a  second  step,  the  support  study  provided  answers  to  eight  synthesis  questions.  These 
covered the evaluation dimensions of effectiveness, efficiency, relevance, coherence and EU 
value added of the Rural Development Policy. The answers to these synthesis questions are 
based  on  the  relevant  programme,  measure  and  LEADER  evaluation  questions  in  the 
Member States evaluations, as well as other sources of information such as input, output and 
result indicators. 

For  each  synthesis  question,  the  relevant  programme  and  measure  related  evaluation 
questions were identified. Then, using each time the answers to the relevant (programme and 

12 

 
measure) questions, the number of answers indicating negative contribution is deducted from 
the number of reports stating positive contribution. The number of reports providing limited 
contribution have a score of 0.5 while reports indicating positive contribution have a score 1. 
All contributions (positive, limited and negative) are divided by the total number of reports 
used.  For  the  programmer-related  questions  the  total  number  is  91  while  for  the  measure-
related questions  the total  number is  equal  to  the number of regions  or  Member States that 
implemented the measure. The calculation of the score follows the following formula: 

E = (P - N + C*L) / R18 

The system leads to a final score that can reach values between 1 and 0; these are labelled as 
follows: 

Label 

High extent 

Moderate extent 

Limited extent 

Very limited extent 

No extent 

Criterion 

Score for the extent of contribution of 0.76 – 1 

Score for the extent of contribution of 0.51 – 0.75 

Score for the extent of contribution of 0.26 – 0.50 

Score for the extent of contribution of 0.01 – 0.25 

Score for the extent of contribution of 0 

4.2. 

INTERNET BASED PUBLIC CONSULTATION 

Another  source  of  information  was  an  internet-based  public  consultation.  This  was  online 
from 22 January until 20 April 2018 and generated 720 answers; the questionnaire contained 
open  and  closed  questions  and  allowed  for  the  upload  of  documents.  After  checking  for 
campaigns,  the  questionnaire  was  analysed  using  the  classical  statistical  tools  (frequency 
tables,  cross-tables).  The  results  of  the  public  consultation  (see  Annex  2.  Stakeholder 
Consultation for a more  detailed analysis of the  public consultation)  were used in  this  staff 
working document to corroborate the findings of the evaluation support study in particular as 
regards the answers to the synthesis questions. 

4.3.  EUROPEAN ECONOMIC AND SOCIAL COMMITTEE REPORT 

A final source of information, as mentioned in the methodology, was the EESC information 
report  on  the  “Ex  post  evaluation  of  2007-2013  rural  development  programmes”19.  This 
aimed  at  assessing  the  effectiveness,  relevance  and  EU  value  added  of  the  measures  in  the 
2007-2013 rural development programmes. This report, which from the onset was designed 
by the EESC as a complement to the Commission’s evaluation, focussed on three questions: 

  What were the main shortcomings of the rural development programmer 2007-2013? 
  What was the main added value of the rural development programmer 2007-2013? 
  To  what  extent  and  how  was  civil  society  included  in  the  rural  development 

programmer 2007-2013? 

18  Final score (E); Number of all reports (R); Number of positive results (P); Number of negative results (N); 

Number of limited results (L); Constant factor of 0.5 for weighting of limited results (C). 

19  See footnote 14. 

13 

 
 
                                                 
The report was based on: 

  The information collected during fact-finding missions in 4 Member States20.  During 
the  missions,  the  Members  conducted  semi-structured  interviews  civil  society 
organisations  to  gather  evidence  of  the  practical  experiences  with  the  rural 
development programme. 

  A consultation (online questionnaire) of organisations in 13 Member States21 on their 
views  concerning  the  strengths  and  weaknesses  of  the  programme  implementation. 
The  questionnaire  was  targeted  at  organisations  representing  aggregate  interests 
rather than at individual citizens. 

4.4.  LIMITATIONS AND ROBUSTNESS OF FINDINGS 

The  rural  development  policy  was  designed  17  years  ago,  well  before  the  current  better 
regulation context and its performance management. This meant in particular that the issues 
such as baseline, targeting and indicators (definition and data quality) and intervention logic 
had received considerably lower attention than nowadays. 

The  evaluation  was  largely  based  on  a  synthesis  of  substantive  results  coming  from  the 
Member States’ ex post evaluations. Notwithstanding the help offered by the Commission to 
Member States in preparing the evaluations, a number of difficulties and limitations made it 
de facto very challenging to reliably assess the substantive results: 

  Lack  of  capacity  for  evaluation  and  lack  of  harmonised  evaluation  methodologies 

used by the evaluators in the different Member States/regions; 

  The uneven quality of and different level of detail in the different evaluations; 
  The incompleteness or implausible values of some of the indicator data; 
  The ex post evaluation reports’ quantitative information on target and implementation 
values (output and result indicators) could not be used to provide an overall judgment 
about the effectiveness of the implemented rural development programmes, as target 
values  were  adjusted  multiple  times  during  the  life  cycle  of  the  programme. 
Moreover,  some  of  the  adjustments  made  to  the  target  values  consisted  of 
unnecessary  reductions,  resulting  in  multiple  cases  where  ex  post  evaluations 
observed  a  degree  of  implementation  (comparing  implemented  to  target  values) 
above  100%,  sometimes  even  largely  above  this  figure.  Therefore  the  multiple 
adjustments of targets during the programme implementation made the use of target 
indicators unreliable for benchmarking. 

These  limitations  led  the  external  evaluator  responsible  for  the  support  study  to  base  the 
judgements largely on the approach explained above. The support study nevertheless presents 
quantitative information using result and impact indicators, but as explained by the evaluator 
in the report these should rather be considered as illustrations. 

This approach has its limitations: as it mechanistically compares the positive cases over the 
total,  it  cannot  take  into  account  the  extent  of  the  realisations  of  the  rural  development 

20  Poland (Warsaw), Italy (Florence), Finland (Helsinki/Turku) and Spain (Seville). 
21  Austria,  Belgium,  Bulgaria,  Finland,  France,  Germany,  Ireland,  Italy,  Luxembourg,  the  Netherlands, 

Poland, Spain and the UK. 

14 

 
                                                 
programmes; neither does it take into account whether or not the Member States’ evaluation 
could establish a causal relationship between the intervention and the result. 

Despite  these  limitations,  it  is  reassuring  that  the  overall  findings  of  the  support  study,  the 
public consultation and the fact-finding done by the EESC are confirming each other in broad 
terms. 

5.  ANALYSIS AND ANSWERS TO THE EVALUATION QUESTIONS 

As indicated in the evaluation roadmap, the evaluation conclusions are drawn on a summary 
of  the  replies  to  the  complete  set  of  revised22  common  evaluation  questions23  of  the  2007-
2013  ex  post  evaluations  carried  out  by  the  Member  States  and  the  set  of  evaluation 
questions.  

This entails that the evaluation support study treats in total 53 evaluation questions, most of 
them further broken down in sub-questions. 

The report is supported by drawing analysis from the EESC report as well as from internal 
DG  Agriculture  and  Rural  Development  data  and  other  EU  Commission  data  sources 
(Eurostat). 

5.1.  EFFECTIVENESS 

Effectiveness is measured through the achievement of the objectives and the extent to which 
it is due to the rural development programmes. 

The  results,  and  the  assessment  of  the  impact  made  by  the  rural  development  programmes 
described in this Staff Working Document have to be considered in the context of the overall 
economic, social and environmental situation and trends in the rural areas, which were in the 
middle of the programming period also hit by the economic crisis. The December 2013 Rural 
Development Report24 presents a comprehensive set of data describing the situation at the end 
of  2013.  For  later  years,  information  is  published  online25.  The  following  information  is 
derived from these sources, unless otherwise indicated. 

5.1.1.  AXIS  1.  IMPROVING  THE  COMPETITIVENESS  OF  THE  AGRICULTURAL 

AND FORESTRY SECTOR  

Axis I measures aimed to boost modernisation and competitiveness in the agricultural sector, 
which  would  lead  to  economic  development.  Particularly  investments  aiming  to  improve 
productivity,  efficiency  and  sustainability  are  key  to  increase  GVA  in  the  primary  sector 
while  also  creating  positive  spill-over  effects  on  the  economy.  Axis  1  also  targeted 

22  The  assessment  of  the  mid-term  evaluation  reports  in  2011  revealed  the  need  to  enhance  the  quality  of 
evaluation  since  frequently  these  reports  did  not  succeed  in  adequately  demonstrating  the  achievements, 
results and impacts of the rural development programmes. Therefore it was suggested to revise and reduce 
the number of the current set of evaluation questions outlined in the CMEF. 

23  Guidelines for the ex post evaluation of 2007-2013 Rural Development Programmes, pages 29 and 30. 
24  https://ec.europa.eu/agriculture/sites/agriculture/files/statistics/rural-development/2013/full-text_en.pdf. 
25  See DG AGRI data dashboards. 

15 

 
                                                 
employment in agriculture, and promoting knowledge transfer and training, which led to the 
employment of young people in sectors other than the primary sector. 

5.1.1.1 Productivity 

Agricultural  labour  productivity  increased  drastically  during  the  programming  period 
(+48%),  from  EUR 11 887 per  annual  work  unit  (AWU)  in  2006  to  EUR 17 585 /AWU  in 
2015.  Moreover,  total  factor  productivity  grew  by  8.5%  over  the  same  period  (Figure  6). 
However,  there  still  are  important  disparities  between  Member  States:  in  2015  labour 
productivity in agriculture varied from EUR 4 015 /AWU in Latvia to EUR 68 402 /AWU in 
the  Netherlands.  Besides  differences  in  level,  there  are  also  strong  differences  between 
Member States in terms of development: while in Estonia productivity more than doubled to 
12 345 EUR /AWU 
in  Malta  from 
EUR 14 309 /AWU to EUR11 612 /AWU26. 

it  decreased 

the  same 

in  2015, 

timespan 

in 

The increase in productivity was driven by the replacement of human capital by machinery. It 
was thus accompanied by a decrease in the total number of agricultural holdings, from 13.8 
million in 2007 to 10.8 million in 201327, pointing towards a concentration of UAA (Utilised 
Agriculture Areas) in larger farms (those holdings of 100 ha or more)28. 

Over the same period, factor income per AWU29 increased by 39% in real terms.  Income in 
agriculture increased faster in the Member States which joined the EU after 2004, in line with 
the  strong  productivity  gains  after  accession,  supported  by  the  rural  development  policy 
(151% average increase). 

Figure 6. Total factor productivity in agriculture in EU-2730 

110

105

100

95

90

85

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Source: DG Agriculture and Rural Development  

Member States have spent EUR 30 billion in measures aiming at improving competitiveness 
mainly through investments in farm modernisation (M121),  adding value to agricultural and 

26  See DG AGRI data dashboards: CTX_SEC_14_1. 
27  See DG AGRI data dashboards: CTX_SEC_17_1. 
28  See DG AGRI data dashboards: CTX_SEC_17_2. 
29  See DG AGRI data dashboards: CTX_SEC_25_1. 
30  Note: total factor productivity (TFP) compares total outputs relative to the total inputs used in production of 
the output. As both output and inputs are expressed in term of volume indices, the indicator measures TFP 
growth. The TFP a composite indicator for land, capital and labour productivity growth. The  comparison 
between Member States of the change over time of TFP growth is meaningful but not the comparison of the 
indicator as such. This is an index, in the first step 2010 is set at 100, then 3 year-averages are calculated to 
smooth the effect of weather e.g. on the indicator. Therefore, in the graph 2010 corresponds to the (2008-
2010) average. 

16 

 
 
                                                 
forestry  products  (M123),  and  improving  infrastructure  in  rural  areas  related  to  the 
development and adaptation of agriculture (M125) (Figure 7). 

A majority (59%) of the Member States/regions stated in their ex post evaluation reports that 
the  effects  of  the  policy  on  competitiveness  were  positive.  These  effects  can  be  attributed 
mainly to trainings and investments in modern machinery and technology. 

This is confirmed by the results of the public consultation, distinguishing clearly between the 
positive  impact  on  competitiveness  in  agriculture,  which is judged more  favourable than in 
the ex post evaluations with 74% of positive views31 and forestry, with not as strong positive 
views  (44%  of  positive  views32).  There  were  no  major  difference  of  opinion  between 
stakeholder groups. 

Figure 7. Expenditure by measure in Axis 1 

Rest of the measures
9%

M125
14%

M123
15%

M113
9%

M111
3%

M112
11%

M121
39%

Note:  M111  corresponds  to  vocational  training  and  information  actions;  M112,  setting  up  of  young  farmers; 
M113,  early  retirement  of  farmers  and  farm  workers;  M121,  modernisation  of  farms;  M123,  adding  value  to 
agricultural and forestry products, M125,  improving infrastructure related to the development and adaptation 
of agriculture and forestry 
Source: DG Agriculture and Rural Development 

Some  rural  development  programmes  attempted  to  quantify  the  impact  of  the  rural 
development policy on competitiveness in the agricultural and forestry sector. Based on these 
figures, the support study estimated that EU labour productivity increased by 4.1% thanks to 
the  rural  development  policy  (the  median  was  +3.2%)  and  concluded  that  the  objective  of 
higher  competitiveness  was  achieved  to  a  moderate  extent.  On  the  other  hand,  the  support 
study  could  not  conclude  on  the  contribution  of  the  rural  development  policy  to  improved 
competitiveness  in  the  overall  rural  economy,  due  to  the  limited  number  of  reports  (18%) 
including  data  result  indicators  and  the  high  variability  of  the  results  (-6%  to  17% ).  Many 

31  Sum of ‘strongly positive’ and ‘moderately positive’ views. 
32 

It also should be noted that 31% of the respondents provided no opinion on the increase of competitiveness 
in forestry (compared to 10% of competitiveness in agriculture). If the analysis is made only of those that 
provided an opinion, the positive view increases to 64% of the respondents, with no significant differences 
between stakeholder groups. 

17 

 
 
                                                 
rural  development  measures  have  a  significant  impact  on  the  competitiveness  of  the 
agricultural and forestry sector. 

M121 (modernisation of farms) had a total expenditure of EUR 11.7 billion, implemented 
by 27 Member States across 88 regions. The main aim of the measure was to modernise the 
technology, management and practices that are applied in agricultural holdings. This measure 
supported  467 324  investment  operations  in  the  equivalent  of  4%  of  EU  holdings33.  The 
overall investments led to an increase in GVA in the supported holdings of EUR 19.3 billion 
(11.1%  of  the  agricultural  sector  GVA).  These  results  were  confirmed  by  the  qualitative 
analysis, explaining that the competitiveness was increased in multiple ways: 39% of the ex 
post evaluations  found an increase of GVA, 31% an increase of labour  efficiency, 21% the 
introduction  of  new  or  better  products,  and  21%  the  introduction  of  new  technologies. 
Furthermore,  of  those  reports  that  provided  a  conclusion  on  M121  (86%  of  the  total),  83% 
stated  a  positive  contribution34.  Thus,  the  support  study  concluded  that  the  measure 
contributed to an improved competitiveness to a great extent. 

Another significant measure is M123 (adding value to agricultural and forestry products), 
with  a  total  level  of  expenditure  of  EUR 4 413 million,  supporting  28 265  enterprises.  The 
aim  of  the  measure  was  to  modernise  operations,  introduce  innovative  procedures  and 
promote the  integration  of value  chain  segments to  increase the value added of agricultural 
and  forestry  products.  It  was  implemented  by  25  Member  States  in  85  regions  and 
contributed towards two result indicators, one of which is the increase in GVA in supported 
enterprises  that  equaled  EUR 30 billion  (17.4%  of  the  GVA  of  the  agricultural  sector  in 
2015). The other result indicator ‘number of holdings with  new products and/or techniques 
introduced under M123’ amounted to 14 484 holdings supported under this measure (0.1% of 
the total agricultural holdings in the EU). The qualitative analysis confirms this result, as 76% 
of  the  reports35  found  that  the  measure  had  a  positive  contribution  to  competitiveness.  The 
support  study  concluded  that  this  measure  contributed  to  a  great  extent  to  an  improved 
competitiveness. 

In  addition,  under  M125  (improving  infrastructure  related  to  the  development  and 
adaptation of agriculture and forestry) the investments were aimed at roads and irrigation 
systems.  The  measure  was  implemented  in  24  Member  States  with  71%  of  the  reports  that 
provided a conclusion on it stating a positive contribution36. Out of all the reports signalling a 
positive  effect  on  increasing  competitiveness,  27%  attributed  it  to  improved  road  structure 
and access, which resulted in reduced costs of transportation along the value chain and 26% 
attributed  it  to  the  new  irrigation  structures,  which  significantly  reduced  the  cost  of  water. 
Overall,  M125  supported  56 779  operations  and  generated  a  value  added  of  EUR 7 billion, 
making  it  one  of  the  most  successful  measures  in  generating  value  added,  4%  of  the  total 
GVA for the agricultural sector in the implementation period.  

M113  (early  retirement  of  farmers  and  farm  workers)  promotes  competitiveness  by 
supporting  farmers  and  farm  workers  with  early  retirement,  allowing  access  for  younger 

33  This is an over-estimate, given that several operations might have taken place on the same holding. 
34  76 of the ex-post evaluations reported on the contribution of the measure. 
35  70 of the ex-post evaluations provided a conclusion on M123. 
36  59 of the ex-post evaluations provided a conclusion on M125. 

18 

 
                                                 
farmers  to  farms  and  farmland.  It  allows  young  farmers  to  profit  from  economies  of  scale 
through the expansion of their company, and/or improving old farms through the introduction 
of  modern  farming  techniques.  EUR 2.7 billion  was  spent  on  Measure  113  by  16  Member 
States across 51 regions, resulting in an output of 28 398 farmers and 231 farm workers with 
early retirement, and 493 516 hectares of land released. Out of the total number of farmers, 
0.1% has enjoyed early retirement under M113. Out of the total amount of arable land in the 
EU,  0.3%  was  released.  Several  case  studies,  like  Andalusia  and  Aragón,  showed  that  the 
early  retirement  led  to  an  increase  in  competitiveness  in  the  agricultural  sector. 83%  of  the 
rather  small  number  of  ex  post  evaluation  reports37  analysing  the  measure  found  that  if 
contributed positively to improving the competitiveness of the beneficiaries. 

Although  the  evaluation  support  study  found  that  the  measure  contributed  to  an  improved 
competitiveness  to  a  great  extent,  it  also  concluded,  along  with  the  Evaluation  on 
Generational  Renewal38  that  there  is  very  weak  or  no  correlation  between  support  for  early 
retirement (M113) and the change in the number of young farm managers. The ratio of young 
farmers per elderly farmers did not change between 2007 and 2013 and stayed at 19 young 
farmers  (under  40)  per  100  elderly  farmers  (those  older  than  65)39.  The  measure  was  also 
discontinued  in  the  current  programming  period,  as  it  was  not  suited  to  older  farmers’ 
specific  needs  and  in  addition,  the  measure  was  criticised  also  by  the  European  Court  of 
Auditors40 for being cost-inefficient. 

Young  farmers  stimulate  competitiveness  as  they  are  more  inclined  to  modernise  farms, 
introduce new methods and techniques, and start innovative processes.  Thus, it was the aim 
of M112 (setting up of young farmers) to set up young farmers, either through supporting 
the creation of a self-owned business, or through employment in already existing businesses. 
It  was  implemented  by  24  Member  States  across  69  regions41,  with  a  total  expenditure  of 
EUR 3.3 billion. The total number of farm managers under the age of 40 supported to set-up 
was  192 003.  Of  those  reports  that  provided  a  conclusion  on  M112  (59),  78%  stated  a 
positive  contribution  on competitiveness  from  the  increase  of  young  farmers  in  agriculture, 
producing  an  increase  of  gross  value  added  of  EUR 6 131.8 million  in  these  Member 
States/regions  (3.6%  of  the  GVA  in  the  agricultural  sector  in  the  EU-28  in  2015  level). 
Therefore, the support study  concluded that  the  measure  contributed to  a great  extent to  an 
improved competitiveness. 

A  total  budget  of  EUR 840.5 million  was  spent  on  M111  (vocational  training  and 
information  actions)  by  26  Member  States  across  75  regions42.  Outputs  of  6.4 million 
participants in  training and 6.8  million days  of  training  were  reported, representing 29% of 
active farm workers in the EU as a whole. However, this comparison is not straight forward 
as the same farmers may have participated several  times in training activities. Furthermore, 
the  result  indicators  for  this  measure  show  that,  out  of  the  6.4 million  participants,  1.86 
passed  trainings  by  achieving  a  certificate,  degree  or  diploma  (on  average  80 971  per  MS) 

37  Only 40 of the ex-post evaluation reports provided a conclusion on M113. 
38  Evaluation staff working document on the impact of the CAP on generational renewal. 
39  See DG AGRI data dashboards: CTX_SEC_23_5. 
40  https://www.eca.europa.eu/en/Pages/DocItem.aspx?did=41529. 
41  78% (59) of those ex-post evaluation reports that provided a conclusion on M112. 
42  71% (58) of those ex-post evaluation reports that provided a conclusion on M111. 

19 

 
                                                 
and  1 987 552  implemented  the  achieved  skills  (on  average  132 503  per  MS).  The  support 
study  concluded  that  this  measure  contributed  to  a  moderate  extent  to  an  improved 
competitiveness. 

Member States also assessed the impact of rural development programmes on milk, which is 
presented in detail in Box 1.  

20 

 
Box 1. Dairy sector re-structuring  

In their ex-post evaluations, Member States had to assess the contribution of the rural 
development policy to the restructuring of the dairy sector, in view of the abolition of 
the milk quotas in 2015.  

Following the milk crisis of 2009, 2010-2013 was a recovery period in most Member 
States.  Despite  the  decrease  in  number  of  dairy  cows  throughout  the  EU 
(from 22.4  million in 2006 to 21.4 in 2015), the milk yield increased by 11% in the 
2006-2015 period. Furthermore data from the Farm Structure Survey shows that the 
number  of  cows  per  farm  increased  by  52%  from  2005  to  2016  (32  dairy  cows  per 
farm  to  49).  Additionally,  this  concentration  is  seen  in  the  UAA,  increasing  from 
27 ha per farm in 2005 to 38 ha in 2016.  

Figure 8. Number of dairy cows and milk production in the EU. 

150

145

140

135

130

125

120

23,0

22,5

22,0

21,5

21,0

20,5

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Dairy cow milk production (million t)

Dairy cows in million heads

Source: DG Agriculture and Rural Development, Agricultural outlook report data 

The role of the rural development policy in this development is not always clear and 
only qualitative data was available in the rural development reports (as there was no 
impact indicator assigned to the objective of restructuring of the dairy sector). Of the 
91  ex-post  evaluation  reports  24%  indicated  positive  effects  on  the  restructuring  of 
the  dairy  sector,  mainly  due  to  the  investments  in  farm  modernisation  and  in  the 
processing sector. Another 19% reported limited or low effects and in 19% of these 
reports  the  impact  was  not  clearly  described.  38%  of  the  ex-post  evaluation  reports 
did not assess the effects on the restructuring of the dairy sector.  

The  positive  impacts  of  the  policy  are  mainly  linked  to  measures  M121 
(Modernisation of agricultural holdings) and M123 (Adding value to agricultural and 
forestry products). The modernisation processes (as an indicator for the restructuring 
process)  were  in  many  cases  combined  with  an  increase  in  herd  size  and  a  parallel 
decrease in dairy farm numbers. Only in a few cases, alternatives were described, e.g. 
how  organic  farming  can  be  a  reorientation  for  agricultural  holdings  or  how  M214 
(agro-environment-climate)  could  offer  a  restructuring  perspective  for  conventional 
dairy farms under income pressure. 

21 

 
 
 
5.1.1.2 Employment in agriculture 

During the programming period, employment in the primary sector has further decreased. In 
2016, the farming sector was employing 9.5 million workers, a figure 25% below 200743. 

This decline is, nevertheless, overestimated, because of changes in survey thresholds (mostly 
between 2007 and 2010) that excluded some farms (e.g. those below 1 ha in Poland) from the 
statistics. The decrease in farm labour was greater in those Member States that joined the EU 
in  or  after  2004  (EU-N13)  than  in  the  older  Member  States  (EU-15)44,  especially  over  the 
period  2005-2011.  This  reflects  structural  changes  after  accession  to  the  EU.  The  greatest 
reductions in the number of farm workers took place in Bulgaria throughout the period, while 
in Slovakia, Romania, Estonia and Latvia in particular between 2005 and 2011. 

At  the  end  of  the  implementation  period,  in  2015,  agriculture  still  accounted  for  4.17%  of 
employment in the EU-28, down from 4.85% in 2008; for forestry these figures were stable at 
0.25%45. 

Member States/regions reported in the ex post evaluation the number of jobs created thanks to 
the rural development policy under result indicators RI8.1 (gross number of jobs created in 
agriculture)  and  RI8.2  (gross  number  of  jobs  created  in  forestry).  They  amounted  to 
respectively 1.1% and 1.0% of the total number of people working in agriculture and forestry. 

As  regards  the  employment  of  young  farmers,  both  the  evaluation  support  study  and  the 
Evaluation Staff Working Document on Generational Renewal46, (as confirmed by the CAP 
Performance  report47)  found  that  the  generational-renewal  measures  (direct  payments, 
setting-up  and  investment  support)  do  not  influence  significantly  the  number  of  young 
farmers  across  the  EU  as  a  whole.  They  mainly  target  the  maintenance  or  protection  of 
farming jobs, particularly in marginal areas, rather than the creation of new farming jobs. It 
is  also  important  that  support  be  delivered  in  a  targeted  way  with  advice  and  training  to 
improve the quality of those jobs and the performance of supported businesses. In particular, 
the  World  Bank  report  Thinking  CAP48  highlighted  that  the  CAP  supported  the  creation  of 
better  (i.e.  more  remunerative)  jobs  for  the  workers  who  remained  behind  in  agriculture, 
while it improved quality of life and reduced poverty in agricultural areas. 

The JRC analysis on the CAP’s impact49 also concluded that all CAP support and particularly 
CMO  and  direct  payments  had  a  large  causal  impact  on  safeguarding  employment  in 
agriculture. 

43  See Eurostat (online data table aact_ali01). 
44  The decrease in the EU-N13 was 3% per year in 2007-2016 and in the EU-15 it was 2% per year for the 

same period. 

45  See DG AGRI data dashboards: CTX_SEC_13_2b. 
46  See footnote Error! Bookmark not defined.. 
47  CAP performance: 2014-20 | European Commission (europa.eu). 
48  http://pubdocs.worldbank.org/en/369851513586667729/Thinking-CAP-World-Bank-Report-on-the-EU.pdf. 
49  Dumangane,  M.,  Freo,  M.,  Granato,  S.,  Lapatinas,  A.  and  Mazzarella,  G.,  An  Evaluation  of  the  CAP 
impact:  a  discrete  policy  mix  analysis,  Publications  Office  of  the  European  Union,  Luxembourg,  2020, 
JRC125451. 

22 

 
                                                 
5.1.2.  AXIS 2. ENVIRONMENT AND THE COUNTRYSIDE 

The  status  of  natural  resources  deteriorated  over  the  programming  period.  Nevertheless, 
Member  States/regions  reported  positive  contributions  from  the  rural  development  policy, 
suggesting  that  the  deterioration  of  natural  resources  would  have  been  worse  without  the 
policy,  notably  because  of  land  abandonment.  On  this  basis,  the  evaluation  support  study 
concluded that the rural development programmes contributed to better water management, to 
a moderate extent to the protection of natural resources and landscape and to climate change 
mitigation to a low or unclear extent. Regarding the supply of renewable energy, despite the 
positive impact, the extent of it was difficult to determine and quantify. 

The EESC report on the “Ex post evaluation of rural development programmes 2007-2013”50 
also  concluded  that  rural  development  programmes  played  a  big  role  in  promoting  more 
environmentally-friendly  production  methods  in  agriculture.  The  public  consultation  also 
pointed  to  the  positive  impact  on  the  environment:  (75%  positive  views51)  and  on  the 
countryside (74% positive views), with no major difference between stakeholders’ opinions. 

Over  the  programming  period,  Member  States  spent  EUR 44.7 billion  on  environmental 
measures.  The  share  of  agricultural  area  under  beneficial  farm  practices  supported  by  the 
CAP was: 46% for biodiversity, 30% for water quality, 35% for soil, 30% for water quality 
and 49% for the avoidance of marginalisation and land abandonment. 

Member  States  spent  EUR 11 billion in  measures  aiming  to  improve  quality  of  life  in  rural 
areas and encourage diversification of the  rural  economy, mainly through agri-environment 
payments  (M214),  payments  to  farmers  in  areas  with  handicaps  other  than  mountain  areas 
(M212) and payments to farmers in mountain areas (M212). 

Figure 9. Expenditure by measure in Axis 2 

M215
2%

M221
4%

M226
3%

Other measures
4%

M211
16%

M214
53%

M212
17%

M213
1%

Note:  M211  corresponds  to  natural  handicap payments  to  farmers  in  mountain  areas;  M212 payments  to  farmers  in  areas 
with  handicaps  other  than  mountain  areas;  M213,  Natura  2000  payments  and  payments  linked  to  Directive  2000/60/EC; 
M214,  agri-environment  payments;  M215,  animal  welfare  payments;  M221,  first  afforestation  of agricultural  land; M226, 
restoring forestry potential and introducing prevention actions 
Source: DG Agriculture and Rural Development 

50  See footnote 14. 
51  Sum of ‘moderately’ and ‘strongly’ positive opinion. 

23 

 
 
                                                 
5.1.2.1.Protection and enhancement of environment, landscape and forestry 

Over  the  programming  period,  the  Farmland  Bird  Index  continued  its  downward  trend 
(except for forest species). The share of estimated agricultural  area affected by moderate to 
severe water erosion (>11 t/ha/year) stood at 6.7% of total agricultural area in 2010. The soil 
mean organic content decreased slightly from 43.28 g/kg (in 2009) to 43.10 g/kg (in 2015). 
By  contrast,  nitrates  surplus,  affecting  water  quality, 
reduced  on  average  by 
15.8 kg N/ha/year. In addition, the area under organic farming increased by 10% from 2012 
to 2015 to 6.2% of the UAA. 

In  2015,  EU-28  UAA  stood  at  179  million hectares,  3.7%  below  the  2006  baseline. 
Permanent  grassland  and  meadow,  key  for  carbon  sequestration  and  biodiversity,  remained 
stable at 33.8%52 of UAA. The share of the different land cover categories varies across the 
EU and is correlated with the physical characteristics of the territory such as mountains and 
remoteness  of  the  area53.  Nevertheless,  the  total  area  used  for  extensive  grazing  increased 
significantly  between  2007  and  2013,  from  20.6%  of  the  total  UAA  in  2007  to  29.4%  in 
201354. 

61%  of  the  ex  post  evaluations  reported  positive  effects  on  the  protection  and 
enhancement  of  natural  resources  and  landscape,  particularly  biodiversity  and  High 
Nature  Value  farming  and  forestry,  through  measures  preventing  land  abandonment55.  The 
programmes were either said to improve the situation or prevent further degradation. 

Figure 10. Evolution of the farmland bird index (2005-2019) 

110

105

100

95

90

85

80

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

All common species

Common farmland species

Common forest species

Source: DG Agriculture and Rural Development on the basis of Agridata (CTX_ENV_35_1) 

52  See DG Agriculture and rural development data dashboards: CTX_ENV_31. 
53  Staff Working Document Evaluation Impact of the CAP on biodiversity, soil and water. 
54  See DG Agriculture and rural development data dashboards: CTX_ENV_33_2. 
55   The link between land abandonment and biodiversity loss (among other issues) is demonstrated in literature, 

i.e.: Assessing the risk of farmland abandonment in the EU 

24 

 
 
                                                 
M214  (Agri-environment  payments)  was  of  key  importance  with  respect  to  protecting 
natural resources and biodiversity, as all programmes have implemented this measure, and it 
accounted for the largest proportion of  expenditure (26%).  Almost  90% of reports  giving a 
clear  judgement  on  this  measure  concluded  that  its  implementation  made  a  positive 
contribution to the environment, through both the extent of area covered by commitments and 
their  effectiveness.  Biodiversity  and  High  Nature  Value  farming  were  identified  as  most 
significantly  positively  affected  (69%),  improved  soil  quality  in  66%  and  water  quality  in 
61% of reports. 

Overall,  Member  States  spent  EUR 23.6 billion  on  different  operations  aimed  at  improving 
the environmental situation. Most regions have implemented a variety of sub-measures with 
different  focuses,  which  involved  more  than  1.5 million  farms  (14%  of  the  total)  and  more 
than  12 000  other  land  managers.  The  measure  concerned  48 million hectares  and  0.97 
million livestock units (0.7% of the total livestock units in the EU56); as well as: 

-  42.5 million ha  under  land  management  beneficial  for  biodiversity.  Organic  farming 
and extensive cultivation methods (including the renunciation of biocides), especially 
extensive  grassland  management,  are  favourable  cultivation  methods  for  the 
promotion  of  biodiversity.  Furthermore,  positive  impacts  on  biodiversity  were 
explicitly attributed to the promotion of beekeeping and to the support of the use of 
indigenous breeds at risk of extinction on livestock farms, among others.  

-  35.7 million ha under land management beneficial for water quality (see Improvement 

of water management, below, for more detailed information), 

-  36 million ha  under  land  management  beneficial  for  soil  quality.  The  effects  were 
mainly attributed to  the  introduction of organic  farming  and livestock  and extensive 
grassland management, though only a few partial measures are aimed directly at soil 
protection. However, all contractual nature conservation measures as well as measures 
with  the  main  objective  of  improving  water  quality  contributed  to  the  protection  or 
improvement of soil. 

-  19.6 million ha under commitments  to  avoid marginalisation and land  abandonment. 
Rural  development  programmes  shown  that  organic  farming,  extensive  grassland 
management  and  contractual  nature  conservation  measures  in  particular  prevent 
marginalisation  and  land  abandonment.  Nevertheless,  although  most  of  programmes 
reported on the impact  of this measure, only  25% of the evaluation  reports rated its 
contribution to avoidance of marginalisation and land abandonment as positive. 

Based on these findings the evaluation support study concluded that the measure contributed 
to the improvement of the environmental situation to a high extent. 

Some  of  the  other  most  relevant  measures  under  Axis  2  were  M211  (natural  handicap 
payments  to farmers in mountain area) and  M212 (payments to farmers in areas with 
handicaps, other than mountain areas). They compensate farmers for the additional costs 
and  income  losses  arising  from  the  difficulties  of  agricultural  production  in  areas  with 
handicap.  Their  core  objective  is  preventing  land  abandonment,  to  which  they  contributed 

56  See DG Agriculture and rural development data dashboards: CTX_SEC_21_1. 

25 

 
                                                 
positively  for  60%  of  the  Member  States/regions.  These  measures  were  implemented  in  25 
Member States and covered 52.8 million ha. 

M211 was implemented in 15 Member States in a total of 60 regions, with a total budget of 
EUR 7 391.1 million.  The  measure  resulted  in  1  million  (9.7%  of  the  total  agricultural 
holdings  in  2013)  supported  farm  holdings  and  16  million  hectares  covered  (one  Member 
State implementing the measure did not report the output indicators). This amounted to 57% 
of the UAA in the less-favoured mountain areas of the Member States that implemented the 
measure  and  to  56.7%  of  the  UAA  in  mountainous  areas  in  the  EU  as  a  whole.  Over  two 
thirds of the reports stated that it made a positive contribution to the environment (especially 
biodiversity  and  high  nature  value  farming/forestry),  mainly  through  maintaining  extensive 
agricultural  systems  in  areas  where  appropriate  land  management  is  important  for 
biodiversity  and  High  Nature  Value  habitats.  It  was  also  recognised  as  helping  retain 
population  and  employment  in  fragile  rural  areas.  The  support  study  concluded  that  the 
measure contributed to an improvement of the environmental situation to a high extent. 

M212  (Payments  to  farmers  in  areas  with  handicaps,  other  than  mountain  areas)  was 
implemented in 27 Member States in 75 regions, with a total budget of EUR 7 681 million. 
On  average,  Member  States  spent  10%  of  their  total  EAFRD  expenditure  in  Measure  212, 
with wide disparities. This resulted in an output of 1.8  million supported farm holdings (17% 
of the total) and 36.8 million hectares covered, corresponding to 59% of the UAA in the less-
favoured  areas  other  than  mountain  areas  of  the  Member  States  that  have  offered  the 
measure. 

The  majority  of  the  ex  post  evaluation  reports  that  assessed  it,  confirmed  the  measure’s 
positive  impact  on  improving  the  environment  through  prevention  of  land  abandonment57. 
The positive impact is mainly attributed to its support to maintain agricultural cultivation on 
sites,  which  otherwise  would  have  been  threatened  by  land  abandonment  and  a  possible 
degradation of natural values. Some reports also stated that the measure promoted extensive 
farming practices. 

Both  measures’  main  environmental  effect  was  on  biodiversity  and  high  nature  value 
farming/forestry, with  28% of the Member States and regions  quoting a  positive impact  on 
biodiversity, while 14% a rather limited impact, 17% no contribution, 10% unclear (14% did 
not  assess  this  aspect).  This  is  due  to  the  fact  that  the  maintenance  of  local  agricultural 
techniques is a basis for the conservation of animal and plant communities dependent on this 
management  and  that  the  measure  covers  ecologically  valuable  areas.  Additional  positive 
effects resulting from the implementation of these measures on other natural resources (soil, 
water) and climate mitigation are possible but not plausible according to the analysis in the 
evaluation support study. 

Another  significant  measure  was  M213  (Natura  2000  payments  and  payments  linked  to 
Directive  2000/60/EC),  which  with  a  total  expenditure  of  EUR 267.5 million  supported 
farmers’ incomes in more than 75 000 supported farm holdings (0.7% of the total EU farms), 
in  13  Member  States  that  implemented  it  on  1.1 million hectares  (28  rural  development 

57  73% (52) of those ex-post evaluation reports that provided a conclusion on M211 and M212. 

26 

 
                                                 
programmers,  15.3%  of  agricultural  area  in  Natura  2000  of  the  Member  States  that  have 
offered the measure). It compensated them for financial losses due to using different farming 
practices beneficial for the designated habitats/species. Whilst the management practices are 
compulsory, even without these payments, positive effects on biodiversity were reported due 
to improved understanding and acceptance of Natura 2000 requirements and high coverage of 
target  areas.  The  actual  effects  on  the  environmental  aspects  were  not  clear  (on  soil, 
mitigation and adaptation of climate change and prevention of land abandonment) except for 
biodiversity,  which  was  generally  considered  somewhat  more  positive  than  the  overall 
environmental  impact.  In  28%  of  the  ex  post  evaluation  reports  the  general  contribution  of 
M213  to  improving  the  environment  was  assessed  as  positive,  while  31%  stated  a  limited 
effect and 17% saw no contribution. 10% of the evaluations of the measure indicated that the 
effect was not clear (and 14% did not carry-out the assessment). The support study concluded 
that  the  measure  contributed  to  an  improvement of  the  environmental  situation  to  a  limited 
extent. 

20 Member States spent EUR 1.6 billion on M221 (first afforestation of agricultural land) 
and reported on it in 63 ex post reports58. In addition to the afforestation of agricultural land 
and the expansion of the entire forest area, the measure also pursued the goal of introducing 
sustainable  forest  management  in  these  areas.  This  measure  reached  a  total  output  of 
203 944 hectares  of  afforested  land  in  42 531  supported  actions,  representing  0.12%  of  the 
total  forest  and  wooden  lands  (FOWL)59.  Nevertheless,  to  the  improvement  of  the 
environmental  situation  mostly  regarding  biodiversity,  mitigation  of  climate  change  and 
water quality. This was largely attributed to the diverse and various ecological functions of 
forests  and  hence  the  afforested  areas  were  often  assessed  positively  without  further 
consideration. 

Another measure under this axis was M226 (restoring forestry potential and introducing 
prevention actions), with a total expenditure of EUR 1 542.1 million, was assessed as highly 
positive  for  the  environment,  mostly  through  preventing  fires  and  flooding.  These  actions, 
implemented  by  16  Member  States  across  56  regions,  supported  10  million  hectares  of 
damaged  forests  (for  a  total  of  77 359  actions)60.  In  78%  of  the  positive  cases  the 
improvement of the environmental situation was attributed to the fields of fire damages and 
prevention.  Improved water quality and flood mediation  and biodiversity were also  pointed 
at. On the basis, the evaluation support study concluded that the measure contributed to the 
improvement of the environmental situation to a medium extent. 

5.1.2.2.Climate change mitigation, adaptation and renewable energy 

In 2015, agricultural emissions of greenhouse gases (GHG) in the European Union amounted 
to  494  million  tons  of  CO2  equivalents.  This  accounted  for  about  12%  of  total  EU-28 
emissions  for  that  year61.  While  total  net  emissions  from  agriculture  declined  by  3% 
compared  to  2006  baseline,  the  share  of  agriculture  in  GHG  emissions  showed  an  increase 

58  40 (53.4%) of the ex-post reports provided positive conclusions on M225. 
59  See DG Agriculture and rural development data dashboards: CTX_SEC_29_1. 
60  62 (72.1%) of the ex-post reports provided positive conclusions on M226. 
61  See DG Agriculture and rural development data dashboards: IMP_07_2 and IMP_07_1. 

27 

 
                                                 
over  the  last  years.  This  is  due  to  the  decrease  in  total  GHG  emissions  in  the  overall  EU 
economy, greater than the decrease of agricultural emissions. 

Figure 11. Greenhouse gas emissions from agriculture 

700.000

600.000

500.000

400.000

300.000

200.000

100.000

0

14%

12%

10%

8%

6%

4%

2%

0%

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

Total net emissions from agriculture

% of total GHG emissions

Source: DG Agriculture and Rural Development (IMP_07_2 and IMP_07_1) 

The production of renewable energy from agriculture increased by 600% between 2006 
and 2015, to 292 million MWh62. 

Only  a  reduced  number  of  Member  States  (7)  reported  quantitative  figures  on  energy 
production and the reported production capacity installed thanks to rural development support 
was  small  (614 779  MWh  for  the  2007-2013  period).  Therefore  the  contribution  of  rural 
development  programmes  towards  the  supply  of  renewable  energy  (on  just  the  basis  of 
energy production) is not certain. 

Despite  the  data  limitations,  the  qualitative  data  shows  that  the  rural  development 
programmes  positively  contributed  to  the  supply  of  renewable  energy,  but  only  to  a  very 
limited extent (in 12% of the Member States/regions).  In the majority of these regions, this 
positive development is based on the support for biogas and biomass energy. In some regions, 
investments  in  solar  energy  and  distribution  systems  contributed  to  an  expansion  of 
renewable energies. For another 42% of reports, positive effects were reported, however with 
an unclear extent. Limited effects were reported for 26% of the regions. 

Although renewable energy production was not the specific focus of any rural development 
measures, the ex post evaluations reported on it in relation to measure M114 (use of advisory 
services  by  farmers  and  forest  holders)  and  M311  (diversification  to  non-agricultural 
activities). The ex post evaluation reports indicated that Member States or regions enhanced 

62  See agridata: CTX_ENV_43_1. 

28 

 
 
                                                 
the  transition  from  fossil  sources  to  renewable  biomass  based  sources,  installed  renewable 
energy  production  plants  or  generally  produced  energy  from  renewable  sources  through 
M311. 

As  regards  climate  change  mitigation  and  adaptation,  overall  only  6%  of  the  Member 
States/regions  reported  on  the  environmental  measures’  positive  effects  in  relation  to 
mitigation, which were however seen rather as a side effect than as a result of clear targeting 
in  the rural  development  programmes.  Positive effects,  however with  an unclear extent,  are 
found in 69% of regions. For another 19% limited effects of climate change mitigation and 
adaptation are stated. 

The  following  measures  were  identified  as  positively  contributing:  forest-related  measures 
like  afforestation  and  forest  management,  agri-environmental  measures  and  measures 
concerning energy-savings and the production of renewable energies. 

Member  states  reported  in  their  rural  development  programmes  a  reduction  of  GHG 
emissions  of  742 849 tons  CO2eq  per  year,  thanks  to  the  rural  development  policy.. 
Compared  to  agricultural  emissions,  the  reduction  represents  0.15%  of  the  agricultural 
emissions  in  201563.  The  reported  level  of  carbon  sequestration  sums  up  to  349 387 Mega 
tons CO2eq/a, resulting from measures on woodland and agricultural land. Compared to the 
assumed  overall  potential  of  carbon  sinks  in  forests  and  croplands  in  the  EU,  the  rural 
development programmes’ contribution accounts for a share of 0.08%. The total area under 
land  management  contributing  to  mitigating  climate  change  supported  by  the  rural 
development programmes amounted to 4 813 km² (0.15% of the total area of agriculture and 
forestry in the EU-28, 3 220 159 km²). 

The  support  study  concluded  that  M214  (Agri-environmental  payments)  had  a  positive 
impact  on  climate  protection  through  the  reduction  of  greenhouse  gas  emissions,  but  the 
effect was very limited, only indirect and difficult to measure, given especially that climate 
protection was not the focus of these measures, although M214 covered 25.5 million hectares 
with measures contributing to mitigating climate change. 

M221  (first  afforestation  of  agricultural  land)  also  positively  contributed  to  climate 
mitigation,  according  to  the  ex  post  evaluations.  Through  site-specific  afforestation  and 
sustainable use, forests can be established as a long-term carbon sink. The contribution of the 
measure  to  mitigating  climate  change  was  assessed  as  predominantly  positive  (46%  of  the 
reports).  Particular  emphasis  was  placed  on  the  positive  effects  on  CO2  storage  function  in 
biomass and soil of the newly established forest stands (73%), but also the long duration and 
slow  process  should  be  kept  in  mind  (12%).  Afforestation  further  reduces  greenhouse  gas 
emissions as it generally introduces a more extensive management on the area (23%). 

Another measure with positive effect was M215 (animal welfare) and it was also explicitly 
mentioned in the ex post evaluation reports through the consolidation of environment-friendly 
farming practices, related to extensification and low livestock density. 

63  CTX_ENV_45_1a. 

29 

 
                                                 
Most of the other measures under this axis also showed to have effect on climate mitigation, 
but based on the analysis made by the contractor and the low number of reporting Member 
States, climate mitigation was achieved as an indirect effect of these measures. 

5.1.2.3.Improvement of water management 

The  total  irrigated  area  barely  increased  from  2007  to  2013,  from 173.7 million hectares  to 
174.6 million64 hectares. In 2012, the share of monitoring sites of nitrates in groundwater with 
a poor quality stood at  11.7%% and 14.2% with  moderate quality, and  for surface water  at 
11.4%  and  31.7%  respectively65.  In  2013  the  pressure  from  agriculture  was  decreasing, 
although  not  uniformly,  in  terms  of  numbers  of  animals  and  the  consumption  of  inorganic 
fertilisers, continuing a long-term trend66. 

The ex post  evaluation  reports do not use the term  “water management”  in  a uniform way, 
leading to  a very different  approach to  the evaluation  of use, quality and quantity of water. 
Furthermore, ex post evaluations very rarely reported on those issues67 and with a significant 
lack of consistency in the use of measurements. Therefore, the effects of the CAP on water 
use and water quantity could only be assessed qualitatively and with difficulty. Nevertheless, 
overall more than half of the ex post evaluation reports indicated that the rural development 
programmes positively contributed to water management. Out of 91 Member States/regions, 
64% suggest positive impact on water management, and 16% limited or no impact. 20% 
of  evaluations  did  not  provide  information  or  stressed  that  such  an  impact  could  not  be 
assessed based on the available data. 

As it was mentioned before, M214 (Agri-environmental payments) was a key measure also 
for water quality improvement. The area under successful land management contributing to 
water quality was 35.7 million hectares in 27 Member States, making it the most widespread 
measure  in  regard  to  water  quality.  61%  of  the  ex  post  evaluation  reports  found  positive 
contributions  of this measure to  the quality of groundwater  and surface  water, although the 
protection of water resources was not emphasized in all sub-measures. M214 was focused on 
the reduction of nitrogen input into groundwater, but reports also described indirect positive 
impacts  in  the  reduction  of  nutrient  and  pollutant  inputs  in  surface  waters  (phosphorus).  In 
addition  to  the  reduction  of  fertilizer  and  pesticides,  the  most  successful  instruments  were 
promoting  adapted  soil  cultivation,  permanent  covering/vegetation  strips,  low-emission 
spreading technology, preservation of semi-natural pasture habitats, retention dikes. 18% of 
the ex post evaluation reports attested that M214 had a limited contribution to water quality, 
mainly because the effects were only indirect and difficult to assess. No contribution to water 
quality  was  seen  in  5%  of  the  evaluated  reports,  10%  could  not  clearly  identify  a 
contribution. 

An  indirect  contribution  to  water  management  came  from  M121  (modernisation  of 
agricultural  holdings),  as  it  fomented  innovation,  and  27%  of  the  ex  post  evaluations 
referred  specifically  to  environmental  benefits  coming  mostly  from  water  management  and 

64  See DG Agriculture and rural development data dashboards: CTX_SEC_20_01. 
65  See DG Agriculture and rural development data dashboards: IMP_11. 
66  Report  on  the  implementation  of  Council  Directive  91/676/EEC  for  the  period  2.008–2011.  (COM  (2013) 

683 final). 

67  From 91 evaluations, 13% of the reports reported on water usage and only one refers to water quantity. 

30 

 
                                                 
green  technology,  and  another  16%  to  environmental  benefits  coming  from  innovations. 
Another  measure  that  the  ex  post  evaluation  reports  highlighted  as  contributing  positively 
towards  better  water  management,  was  M125  (improving  infrastructure  related  to  the 
development and adaptation of agriculture and forestry), by promoting investments in newer 
irrigation systems that allowed for better use of water resources, reducing the overall water 
consumption. 

The  direct  impact  of  many  other  relevant  measures  in  water  management,  even  when 
potentially positive, was deemed as not possible to substantiate by the analysis made by the 
contractor for measures such as support to areas with handicaps, mostly due to the very low 
number of Member States/regions reporting on water management and water quality, and low 
number of clear positive impacts in the ex post evaluations. 

5.1.3.  AXIS  3.  IMPROVING  THE  QUALITY  OF  LIFE  IN  RURAL  AREAS  AND 

ENCOURAGING DIVERSIFICATION OF THE RURAL ECONOMY 

Member States spent EUR 11 billion in measures aiming to improve quality of life in rural 
areas  and  encourage  diversification  of  the  rural  economy,  mainly  through  support  to 
investments  in  basic  services  for  the  economy  and  rural  population  (M321)  and  for  village 
renewal and development (M322). Relatively few rural development programmes contributed 
to  both  aspects  of  Axis  3  and  a  larger  number  contributed  to  either  quality  of  life  or 
diversification. 

Figure 12. Expenditure per measure under axis 3 

M331
1%

M323
10%

M311
9%

M341
1%

M322
27%

M312
12%

M313
8%

M321
32%

Note: M311 corresponds to diversification into non-agricultural activities; M312 to support for business creation 
and development; M313 to  encouragement of tourism activities; M321 to basic services for the economy  and 
rural population; M322 to village renewal and development; M323 to conservation and upgrading of the rural 
heritage;  M331,  training  and  information;  M341  to  skills-acquisition  and  animation  measure  with  a  view  to 
preparing and implementing a local development strategy. 
Source: DG Agriculture and rural development 

Out  of  the  four  objectives  of  rural  development  policy,  this  is  the  objective  for  which  the 
evaluation support study concluded to the most limited degree of achievement, but it is also 
the  one  for  which  there  are  fewer  measures  with  a  direct  effect  and  the  lowest  evidence  in 
Member States/regions reports, as well as low quality data. 

31 

 
 
5.1.3.1.Growth and diversification of the rural economy 

The  importance  of  the  primary  sector  in  the  total  economy  (EU-28)  has  slightly  decreased 
from 1.66% of total GVA in 2006 to 1.6% in 201668. Rural areas’ importance in the overall 
economy also decreased, representing 9.5% in 2006 to 12% in 2015. 

Roughly one third of all EU farmers (34%) were engaged in gainful activities other than their 
farm work in 2010. For the vast majority of farmers engaged in other gainful activities, these 
were the main source of income, according to the support study. 

The  importance  of  the  tertiary  sector  (services)  in  employment  increased  during  the  period 
2006-2015  while  the  one  of  the  primary  sector  decreased  further.  In  2015,  it  accounted  for 
only 4.7% of total employment (from 5.8% in 200669). In rural areas it declined from 15.7% 
to 11.8%, in intermediate areas from 6.5% to 5% and in urban from 1.2% to 1%70. 

Figure 13. Structure of employment by branch 

90
80
70
60
50
40
30
20
10
0

primary
sector

secondary
sector

tertiary
sector

primary
sector

secondary
sector

tertiary
sector

primary
sector

secondary
sector

tertiary
sector

Rural

Intermediary

2006

2015

Urban

Note: Primary sector covers agricultural production, forestry, fishing and mining; the secondary sector refers to 
manufacturing, the tertiary sector are services. 
Source: DG Agriculture and Rural Development on the basis of Eurostat 

The impact  on the  quality of life was commented on in  47  ex post evaluation reports. The 
positive  effects  can  be  mainly  attributed  to  basic  infrastructure  services  (e.g.  mobility  and 
communication) and the social dimension (such as governance, social sustainability). 

The  impact  on  the  diversification  of  the  rural  economy  was  commented  on  in  37  ex  post 
evaluation reports. The non-agricultural sector most often mentioned was tourism. 

Only  half  of  the  ex  post  evaluation  reports  provided  qualitative  data  regarding  the 
contribution of the rural development programmes to the growth of the whole rural economy.  
The qualitative data provided in the rural development programmes show that the policy had 
positive effects on economic growth in 57% of the Member States/regions. These effects can 
be  attributed  mainly  to  investments  in  modernisation  and  labour  productivity,  as  well  as  to 

68  See DG AGRI data dashboards: CTX_SOC_10_2a. 
69  See DG Agriculture and rural development data dashboards: CTX_SOC_2. 
70  See  DG  Agriculture  and  rural  development  data  dashboards:  CTX_SOC_11_6,  CTX_SOC_11_5;  

CTX_SOC_11_6. 

32 

 
 
                                                 
investments in human capital. Although 20% of the reports found that the rural development 
programmes  had  limited  effects  on  the  growth  of  the  rural  economy,  at  least  9  evaluations 
noted  that  they  have  mitigated  the  effects  of  economic  recession  in  a  significant  way,  by 
limiting the loss of jobs and the decrease in the number of farms. 

Based  on  the  limited  quantitative  overview,  the  contribution  of  the  rural  development 
programmes to improving the quality of life in rural areas and encouraging diversification of 
the  rural  economy  is  not  certain.  However,  the  qualitative  overview  indicates  that  the  rural 
development programmes have contributed to a very limited extent. 

the  measures 

One  of 
impacting  most  economic  diversification  has  been  M311 
(diversification  to  non-agricultural  activities).  This  measure  was  implemented  by  20 
Member  States  across  65  regions  and  a  total  budget  of  EUR 1.1 billion.  This  resulted  in  a 
total  of  41 940  beneficiaries,  though  amounting  to  less  than  0.5%  of  the  total  number  of 
holdings in the EU. Investment on this measure increased GVA in supported businesses by 
EUR 563.6 million, and created 27 881 jobs. In addition, 52% of all the  ex post evaluations 
found the measure to have a positive impact on improving the economic diversification of the 
beneficiaries,  contributing  to  the  stabilisation  of  farms,  enabling  farmers  to  increase  their 
overall  performance,  assisting  farm  households  to  maintain  or  increase  their  income, 
supporting farms to maintain employment or even to create new jobs. 

In order to improve the quality of life in rural areas, EUR 3.7 billion was spent by 23 Member 
States across 70 regions on M321 (basic services for the economy and rural population). 
This  produced  an  output  of  63 215  supported  actions,  and  in  the  Member  States  that  have 
offered the measure, there has been one action per 1 298 person (1 545 at fully EU level) in 
relation to the total population of the rural  area. Furthermore, more than 45 million persons 
benefitted from improved services in rural areas and more than 16 million persons benefitted 
from  improved  internet  coverage  in  rural  areas  The  positive  impact  was  confirmed  58%  of 
the qualitative ex post evaluation reports, which found that the measure positively contributed 
to  improving  the  quality  of  life  of  the  beneficiaries.  Life  quality  improvements  came  from 
social infrastructure investments (within the thematic complex of day-care, schools, families, 
community  facilities  as  well  as  health),  as  well  as  further  internet  access  (see  rural 
development  programme’s  contribution  to  the  creation  of  access  to  broadband  internet  for 
more  detailed  information  on  the  topic).  Furthermore,  waste/drinking  water  infrastructure, 
electricity and heat were named, as well as the field of transport and roads, as being improved 
by this measure. In terms of the sectors in which the quality of life was improved, the focus 
was on the ‘(public) services’ sector in general (64%) and on the social dimension (16%). 

M322 (Village renewal  and development) was  implemented by 50 regions in  22 Member 
States, with a total spending of EUR 3.2 billion. Its objective was to counteracting population 
decline  by  making  villages  attractive  places  to  live  and  work,  and  promoting  business 
activity.  The  implementation  of  this  measure  resulted  in  41 577  villages  were  actions  took 
place  for  40  million  persons.  In  relation  to  the  total  population  of  the  rural  area,  in  the 
Member  States  that  have  offered  the  measure,  there  has  been  one  action  per  1 651  person. 
The  ex  post  evaluation  reports  confirmed  that  the  measure  contributed  positively  to 
improving the quality of life of the beneficiaries in 77% of the Member States which reported 

33 

 
on  this  measure.  The  improvement  can  be  mainly  attributed  to  intangible  aspects  (such  as 
social  cohesion,  political  participation,  collective  ownership  in  shaping  the  community 
environment,  or  local/regional  identity),  infrastructure  (such  as  meeting  places),  the 
attractiveness  of  villages  for  housing  and  technical  and  traffic  infrastructure  (including 
waste/drinking water infrastructure, roads and other public spaces). 

5.1.3.2.Job creation in Rural Areas 

The rural  employment  rate for the age  group  from  15-64  year olds  slightly increased, from 
63.3% in 2006 to 65.0% in 2015 halving the gap with the overall employment figures which 
stood at 64.3% in 2006 and 65.6% in 2015. 

The  quantitative  data  shows  that  the  rural  development  programmes  contributed  to  create 
more than 159 000 new jobs, not just in the primary sector but also in the entire economy. It 
should be mentioned that the validity of these results could be diminished as only 45%71 of 
the  reports  provided  data  on  the  number  of  jobs  provided  and  it  does  not  account  for  the 
support to generational renewal and to the maintenance of farmers in agriculture. 

While  the  largest  share  of  new  jobs  was  created  in  the  agricultural  sector,  most  reports 
concluded that the programmes helped the creation of new jobs in other sectors, particularly 
food and tourism, but also culture and services. 

The  qualitative  data  shows  that  48%  of  the  rural  development  programmes  had  a  positive 
effect  on  the  creation  of  new  jobs,  which  is  reflected  by  the  quantitative  results  too.  
Furthermore, the reports highlighted the important role of the rural development programmes 
in limiting the effects of the economic recession on the job market, and in preserving existing 
jobs.  

Even  when  the  creation  of  employment  happened  mostly  in  the  agricultural  sector,  reports 
acknowledged  that  rural  development  programmers  also  led  to  the  creation  of  new  jobs  in 
other  sectors  and  especially  food  and  tourism.  The  creation  of  employment  prospects, 
especially  for  young  generations  in  rural  areas  also  limited  the  abandonment  of  farms, 
notably in mountainous regions. 

M322  (village  renewal  and  development)  was  identified  as  having  a  positive  impact  for 
non-beneficiaries as well as beneficiaries of the support, and in 85% of the ex post evaluation 
reports,  additional  economic  effects  were  named  (mainly  jobs  and  diversification).  M313 
(encouragement of tourism activities) allowed for the  creation of tourism  actions (24 518 
created)  and  jobs  17 578  in  22  Member  States  that  reported.  Other  measures,  like  M323 
(conservation  and  upgrading  of  the  rural  heritage)  or  M321  (Basic  services  for  the 
economy and rural population) also indirectly impacted job creation in rural areas, though 
they did not have associated job related result indicators, and therefore their impact cannot be 
quantified. 

71  Another  28%  of  the  reports  did  not  provide  data  on  number  of  jobs  created  as  it  was  not  a  programme 

priority. 

34 

 
                                                 
The European Economic and Social Committee showed in its report that rural development 
programmes  contributed  to  maintain  agriculture  and  promoted  competitiveness  of  rural 
businesses and employment and diversified rural economies. The public consultation pointed 
also  to  a  positive  impact  on  the  quality  of  life:  (75%  a  positive  contribution)  and  the 
countryside  (74%  a  positive  contribution),  with  no  major  difference  between  stakeholder 
groups  for  none  of  the  questions.  These  results  contrast  with  the  qualitative  data  stemming 
from  the  ex  post  evaluation  reports,  where  only  18%  of  the  91  Member  States/regions 
identified a positive impact for both domains (i.e. quality of life and diversification) and 9% 
identified a limited impact. 

The  recent  JRC  study  on  the  effects  of  the  CAP  proved  the  positive  effect  of  the  CAP  in 
general  and  of  rural  development  policy  in  particular  (see  Box  2)  with  regard  to  not  only 
safeguarding employment in agriculture, but also creating jobs in rural areas. 

5.1.3.3.Introduction of innovative approaches 

The  rural  development  programmes  helped  introducing  innovation  across  different  areas  in 
55%  of  the  target  regions  through  modernising  infrastructures  and  introducing  new 
technologies  and  products,  as  well  as  by  introducing  changes  in  behaviours  and  processes, 
especially thanks to LEADER solutions and concepts. However, not all measures contributed 
to  introducing  innovative  approaches  and  26  reports  found  that  rural  development 
programmes  had  a  small  or  no  impact  on  innovation.  The  fact  that  the  programmes  had  a 
different  way  of  defining  innovation  posed  some  challenges  to  the  achievement  and 
measurement of such results. In addition, several reports pointed out that innovation was not 
a specific objective of the policy. 

From  a  quantitative  perspective,  the  contribution  of  the  policy  to  the  introduction  of 
innovative  approaches  was  small,  33 027  holdings  introduced  innovative  products  and 
techniques  thanks  to  CAP  support,  which  only  accounted  for  0.3%  of  the  total  agriculture 
holdings in the EU in 2013. Besides, there were very large differences registered  across the 
programmes,  where  the  number  of  holdings  introducing  innovation  variated  from  23  to 
20 000 (these figures are based on 15% of the regions/Member States collected good quality 
data). 

The qualitative data indicates that the  rural  development programmes have contributed to  a 
medium extent to the introduction of innovative approaches. 

One of the measures that provided some innovative approaches to beneficiaries in rural areas 
was  M331  (training  and  information),  implemented  by  32  regions  in  13  Member  States, 
with  a  total  expenditure  of  EUR  92.2  million.  More  than  700 000  training  participants 
completed a training successfully. The total number of participants that successfully ended a 
training  activity  accounted  for  5%  of  the  total  number  of  people  employed  in  agriculture, 
food and forestry in 2013. The measure improved relevant skills, as well as networking and 
capacity building. Nevertheless, the measure had a very limited impact, as only 17% of all the 
ex post evaluation reports found that the measure contributed positively to the improvement 
of economic diversification, and in most cases to a limited extent (36%). 

35 

 
Box 2. JRC study on the effects of the CAP 

The  methodological  approach  taken  in  the  JRC  study  for  the  elaboration  of  a 
counterfactual impact evaluation study provides causal estimates of the CAP’s impact 
on  a  set  of  regional  economic  (GDP  per  capita,  total  gross  value  added  (GVA)  and 
employment)  and  agri-sector  related  economic  outcomes  (GVA  in  the  agri-sector, 
employment  in  agriculture,  land  and  employment  productivity)  .  The  analysis 
addresses the CAP’s performance at regional level and in particular the convergence 
of rural regions using the Generalised Propensity Score method. 

The JRC analysis is based on a NUTS3 level description of the regional dimension of 
the  CAP  in  the  period  2011-2018.  This  implies  a  characterisation  of:  (i)  the  rural 
regions, according to their economic aspects and in particular of their agri-sector and; 
(ii) of the regional CAP  mixes (of Pillar 1 and Pillar 2 groups of measures) in time 
intervals characterised by the implementation of relevant CAP reforms. 

The JRC analysis of the CAP’s impact found that CAP support and particularly rural 
development  support)  are  effective  in  stimulating  the  local  economic  performance 
(particularly in developed peripheral rural regions and traditional rural regions), with 
high relevance in bolstering gross value added and contributing to a significant total 
employment  growth  in  predominantly  rural  areas,  with  effects  increasing  over  time 
and  no  significant  differences  in  the  role  of  the  various  instruments.  Without  the 
CAP  supporting  the  maintenance  of  farms  in  most  remote  areas,  the  labour 
outflow from rural areas towards urban areas would have been bigger. 

The  study  also  concluded  that  “although  rural  development  payments  do  not  target 
specifically  the  agricultural  sector,  they  aim  to  improve  the  quality  of  life  in  rural 
areas and create additional non-agricultural employment. By supporting other sectors 
such  as  construction  or  tourism,  these  payments  may  be  effective  in  creating  new 
rural  jobs,  which  can  lead  to  a  loss  or  continuation  of  agricultural  employment 
depending  on  whether  they  are  substitutes  or  complements.  By  making  farm 
households  and  rural  areas  more  multifunctional,  they  help  to  stabilize  regional 
incomes and employment”. 

5.1.3.4.Rural development programme’s contribution to the creation of access to 

broadband internet 

For  the  vitality  of  rural  areas,  broadband  access  is  key.  Coverage  of  fixed  broadband 
remained  at  97%  in  2015,  and  about  6%  lower  in  rural  areas.  Next  Generation  Access 
technologies72 were available to only 53.7% of the EU-27 in 2012 and around 80% in 2017.73  

In general, effective internet take-up lags behind broadband coverage. In 2012, 72.5% of all 
EU households had subscribed to a broadband connection. In the rural areas of the EU, this 

72  Technologies needed to meet the Digital Agenda of the 30 Mbps objective. 
73  Digital  Economy  and  Society  Index  Report  2018  - Use  of  Internet  Services;  https://ec.europa.eu/digital-

single-market/en/use-internet. 

36 

 
 
                                                 
was only 64.3% of the households. These figures were slightly higher in 2017 (75% and 68% 
respectively).  The  gap  between  households  having  subscribed  to  broadband  connection  in 
rural  areas  and  at  national  level  was  10.3  pp  in  2008,  8.2  pp  in  2012  and  7 pp  in  2017, 
showing that rural areas are nevertheless catching up. 

The main measure that contributed towards broadband access in rural areas was M321 (basic 
services for the economy and rural population). The quantitative data (provided in 19% of 
the  reports  only),  shows  that  the  rural  development  programmes  created  new  or  improved 
access to broadband internet in 1.4 million households or businesses (15% of the total rural 
population). The average number of households or businesses with new or improved internet 
access was 81 315 per region, with the lowest region having only 7 that benefitted from these 
changes. 

The  qualitative  data  shows  that  the  rural  development  programmes’  contribution  to  the 
creation of  access  to  broadband internet  was positive in  35% of  all  Member States/regions. 
These  effects  can  be  attributed  mainly  to  regions  that  effectively  activated  the  fibre  optic 
infrastructure  and  enabled  additional  phone  lines,  thus  laying  the  ground  for  subsequent 
access  to  internet  by  the  residents.  15%  of  the  reports,  however,  found  that  the  rural 
development  programmers  had  limited  effects  on  improving  access  to  broadband  internet. 
This  was  primarily  due  to  administrative  problems  with  the  implementation,  which  started 
late  and  therefore  delayed  concrete  results.  Finally,  37%  of  the  reports  established  that  the 
initiative did not apply to the specific Member State/region. 

5.1.4.  AXIS 4. BUILDING LOCAL CAPACITY (LEADER)  

LEADER (Axis 4) is a horizontal axis thus affecting aspects of the other EAFRD axes. The 
evaluation support study concluded that the rural development programmes have contributed 
positively  and  to  a  medium  extent  to  building  local  capacities  for  employment  and 
diversification  through  LEADER.  This  conclusion  also  goes  along  the  European  Economic 
and  Social  Committee’s  report,  where  LEADER  was  praised  by  all  the  interviewed 
stakeholders,  as  they  found  that  it  provided  beneficial  results  for  both  the  regions  and  the 
communities.  Furthermore,  it  is  also  confirmed  in  the  public  consultation,  with  a  majority 
positive recognition by all questioned stakeholder groups. 

The measures under this axis, especially M411 (Competitiveness), M412 (Environment), and 
M413  (Diversification)  were  often  jointly  programmed  and  evaluated  in  several  Member 
States/regions.  As  a  result,  they  are  reported  on  as  M41  (Implementation  of  local 
development  strategies).  Some  measures  of  the  other  Axis  (mainly  of  Axis  3)  were  also 
programmed  under  LEADER.  The  table  on  next  page  gives  an  overview  of  the  main 
objectives under each LEADER measure. 

37 

 
Table 2. Main objective of LEADER measures 

M411 
M412 
M413 

M421 

M431 

Implementation  of  local  development  strategies 
and a focus on : 

  Competitiveness 
  Environment and land management 
  Quality of life and diversification 

Implementation  of  co-operation  projects,  inter-
territorial and transnational cooperation 
local  action  groups,  skills 
Management  of 
development,  support  to  the  functioning  of  the 
Local  Action  Group  for  capacity  development 
and promotion 

Source: DG Agriculture and Rural Development 

Member  States  spent  a  total  of  EUR  5.6  billion  on  LEADER  measures,  which  were 
implemented as follows: 

  Measure  411(competitiveness):  22  Member  States;  66  regions;  total  EAFRD 

expenditure EUR 471.5 million.  

  Measure 412: 16 Member States; 37 regions; EUR 58.9 million; 
  Measure 413: 27 Member States; 88 regions; EUR 3.977 billion; 
  Measure 421: 27 Member States; 74 regions; EUR 170.8 million;  
  Measure 431: 27 Member States; 88 regions; EUR 897.7 million. 

Figure 14. Expenditure per measure under axis 4 

M412
1%

M431
16%

M411
9%

M421
3%

M413
71%

Note:  M411  corresponds  to  competitiveness;  M412,  environment/land  management;  M413,  quality  of 
life/diversification;  M421,  implementing  cooperation  projects;  M431,  running  the  local  action  group,  skills 
acquisition, animation 
Source: DG Agriculture and Rural Development 

As regards the quantitative overview, the output indicators reported  for Measures 411, 412, 
413 (together referred to as M41), are aggregated. Overall, measure 41 resulted in a total of 
2 417  Local  Action  Groups  (LAGs)  covering  4.1  million  km2  and  143  million  inhabitants 
and  18.5 million  beneficiaries.  In  total  222 794  projects  were  financed  by  the  local  action 
groups, i.e. on average 92 by LAG.  

38 

 
 
 
Measure  421  supported  a  total  of  5 524  cooperation  projects  in  which  7 432  LAGs 
cooperated  with  each  other.  13  ex  post  evaluation  reports  provided  information  on  the 
creation of in total of 4 784 jobs (gross value). Over a quarter (27%) of the evaluation reports 
found that measure 421 contributed to the LEADER approach to a great extent. 17% reported 
to a medium extent, 4% a limited contribution and 13% an unclear contribution. 

Measure 431(running the local action group, skills acquisition, animation) supported 349 061 
action  groups  and  5 863  participants  ended  a  training  activity  successfully  under  this 
measure. 

However,  the  output  indicators  have  to  be  treated  with  caution  as  there  are  major  issues 
regarding  the  land  size  and  the  population  covered.  E.g.  according  to  the  output  indicators, 
the  LAGs  cover  approximately  200%  of  the  total  rural  area  in  Europe  (not  possible  by 
definition) or 93% of the total land area. 

5.1.4.1.  LEADER’s  contribution 
diversification  

to  building 

local  capacities 

for  employment  and 

About  half  of  the  Member  States  reported  on  the  contribution  of  LEADER  to  job  creation. 
The figures are small, however, the quantitative information is not sufficiently consistent to 
allow for a judgment. According to the ex post evaluation reports, 28 242 jobs were created 
through M411 (competitiveness) in the 15 Member States that reported this indicator, 6 505 
through  M412  (environment/land  management)  in  3  reporting  Member  States  and  12 525 
through  M413  (quality  of  life/diversification)  in  13  reporting  Member  States.  Additionally, 
149 534  participants  ended  a  training  successfully  through  M411  (competitiveness),  58 
through  M412  (environment/land  management)  and  11 998  through  M413  (quality  of 
life/diversification).  

According  to  the  available  qualitative  information,  measure  41  contributed  to  enhancing 
employment to a limited extent. 40% of the ex post evaluation reports found that M41 (M411, 
M412, M413 together) had a positive effect on employment. 15% reported a limited effect, 
7% no contribution and 11% other effects. In addition for 27% no information was available.  

The  contribution  of  M431  (running  the  local  action  group,  skills  acquisition,  animation)  to 
build local capacities for employment was considered positive in 19 out of 82 reports (23%). 
12% reported a limited contribution and in 42 reports (51%) no data was available. This leads 
to the conclusion that the measure contributed to building local capacities for employment to 
a medium extent, with 65% of all judgments being positive. 

Only 10% of the evaluation reports reported positive effects of M41 (M411, M412, M413) on 
diversification.  13%  reported  a  limited  effect,  6%  no  contribution  and  1%  other  effects. 
While the contributions to employment can be considered plausible, the evidence presented 
in the Member States’ evaluations on diversification was weak and thus not plausible. 

5.1.4.2.  The  Local  Action  Group’s  contribution  to  achieving  the  objectives  of  the  local 
development strategies and those of the rural development programmes 

The local development strategies are designed to reflect a multi-sectoral approach, where the 
priorities cover the needs and expectations of the stakeholders of the regions.  

39 

 
The contributions of M41 (aggregated M411, M412 and M413) to achieve the objectives of 
the  total  rural  development  programmer  was  deemed  positive  in  34%  of  the  evaluation 
reports and with limited effect in 17% of the reports. LEADER contributed to the three main 
axes of the rural development programmer and to the crosscutting objectives of the EAFRD.   

LAGs  played  an  important  role  in  preparing  and  implementing  the  local  development 
strategies. The contribution of LEADER to achieve the objectives of the local strategies was 
considered positive in 36% of the reports. A number of reports stated a limited contribution 
(17%).  However,  as  in  a  substantial  number  of  reports  no  data  was  available  (35%),  the 
overall contribution is judged to be small. 

The qualitative overview indicates that the LAGs have contributed to achieving the objectives 
of the local strategy and the rural development programmes to a medium extent, yet, due to 
the  limited  share  of  reports  that  provided  conclusions,  this  qualitative  assessment  of  the 
contribution has to be taken as indicative only. 

5.1.4.2. LEADER’s contribution to improving local governance  

EUR  897.7  million  was  spent  on  M431  (running  the  local  action  group,  skills  acquisition, 
animation) by 27 Member States across 88 regions, which resulted in 5 863 participants that 
successfully ended a training activity and a total of 349 061 actions supported. Unfortunately, 
it is not clear what kind of actions or projects were supported. 

The  contribution  of  M431  to  local  governance  was  considered  “high”  (30%)  to  “medium” 
(21%),  although  many  data  was  missing  in  several  evaluation  reports  (28%).  One  of  the 
clearest effects of LEADER was the implementation of public/private partnerships, enabling 
stakeholders’ long-term involvement in the development of a local strategy. In general, this 
effect was hard to quantify given the lack of indicators to characterise local governance.  

The  qualitative  overview  indicates  that  the  implementation  of  the  LEADER  approach 
contributed  to  improving  local  governance  to  a  medium  extent,  however  this  assessment  is 
based on a low level of input from Member States evaluations. 

Conclusion 

The overall assessment of LEADER cannot be considered plausible due to the small share of 
reports  that  provided  conclusions  (with  the  exception  of  the  contribution  to  enhancing  the 
employment situation). A general issue is that quantifiable indicators were not able to capture 
the  specific  characteristics  and  objectives  of  the  LEADER  approach,  e.g.  improving  local 
governance or increasing local participation. The aspects that were quantified are not highly 
relevant for LEADER (e.g. job effects). 

As Axis 4 is horizontal, it affects aspects of the other EAFRD axes and some measures under 
other axes,  especially  Axis  3, were programmed under  LEADER. At times it was not  clear 
whether  such  measures  were  reported  on  under  Axis  3  or  4  in  the  evaluation  reports.  The 
synthesis  approach  did  not  sufficiently  allow  for  consistently  dealing  with  this  aspect, 
amongst other specifics of LEADER. 

Furthermore,  consistency  was  weakened  by  evaluators  using  different  approaches  in 
answering the evaluation questions. 

40 

 
5.2.  EFFICIENCY 

5.2.1.  QUALITATIVE ASSESSMENT 

The  majority  of  ex  post  evaluation  reports  do  not  provide  a  judgment  on  efficiency  of 
resource allocation at programmer level: 37% do not provide information or judgments at all 
and 23% only provide a judgment at measure, axes or objectives level. Out of all the reports 
that provide a judgment, 45% judge the resource allocation in relation to achieved outputs as 
“efficient”,  while  13%  report  low  levels  of  efficiency  (inefficient),  and  5%  suggest  no 
efficient allocation at all. Yet, only about half of the ex post evaluation reports (52%) provide 
a  definition  of  the  term  efficiency  and  only  33%  provide  a  definition  that  is  clearly  in  line 
with the definition used in the Better Regulation Guidelines. 

The  public  consultation  assessment  of  efficiency  is  close  to  the  one  in  rural  development 
reports.  Overall,  44%  of  the  respondents  thought  that  the  rural  development  programmes 
were good or very good value for money, 31% thought they had limited value for money and 
10% no value for money, with no major difference between stakeholders. 

The  difficulties  to  demonstrate  the  efficiency  of  the  2007-2013  Rural  Development  Policy 
were also amply highlighted in the Court of Auditors special report 12/201374. The Court 
observed that the rural  development  programmes did  not  sufficiently set  specific objectives 
with targets for the results and that the indicators were not sufficiently reliable. The European 
Court  of  Auditors  also  pointed  to  certain  issues  of  efficiency.  For  instance,  in  the  Special 
Report No 20 of 201575 they pointed out in relation to non-productive investments (measure 
216) that “overall, the support has contributed to the achievement of objectives linked to the 
sustainable  use  of  agricultural  land,  but  in  a way  it  was  not  cost-effective”.    Similarly,  in 
their Special Report No 12 of 201576, related to the measures promoting a knowledge-based 
rural economy (measures 111, 114, 115 and 331) the Court found weaknesses related to cost-
effectiveness. They also concluded that there was considerable scope for making real savings 
in  Rural  Development  project  grants  in  the  2014–2020  programming  period  by  better 
approaches to controlling the costs. (Special report No 22 of 2014)77. 

The  European  Economic  and  Social  Committee  (EESC)  concluded  in  their  report  that 
there is a strong need for further simplification and less bureaucracy both at EU and Member 
State level, as well as at the regional and local level, when it comes to all procedures, from 
application  through  implementation  to  final  reporting78.  It  stated  that  procedures  were  too 
complex and that this discouraged potential beneficiaries. The Committee also pointed to the 
strong  criticism  expressed  by  stakeholders  to  the  long  time  needed  to  get  the  programme 
running. 

Given  the  lack  of  robust  evidence  mentioned  above,  it  is  very  hard  to  derive  an  overall 
conclusion  on  the  proportionality  of  Rural  Development  expenditure  with  regard  to  the 

74  https://www.eca.europa.eu/Lists/ECADocuments/SR13_12/SR13_12_EN.pdf. 
75  https://www.eca.europa.eu/Lists/ECADocuments/SR15_20/SR15_20_AGRI_INVEST_EN.pdf. 
76  https://www.eca.europa.eu/Lists/ECADocuments/SR15_12/SR_RURAL_TRAINING_EN.pdf. 
77  https://www.eca.europa.eu/Lists/ECADocuments/SR14_22/SR14_22_EN.pdf. 
78  See footnote 14. 

41 

 
                                                 
benefits achieved at EU level. It is clear however that there are wide variations in efficiency 
between  programmes  and  between  measures.  Member  States  evaluations  pointed  to  several 
factors limiting efficiency: 

  The regulatory framework: the evaluations pointed to an, in general, “inappropriate 
regulatory framework and  application of the law”. Fundamental  design  errors of the 
legal framework, individual regulations and very rigid legal interpretations in terms of 
error  prevention  were  more  pronounced.  The  changes  resulting  from  the  ‘health 
check’  reform  (increasing  demands  on  documentation,  data  and  reporting  and  a 
growing  number  of  controls  and  supervisory  authorities),  were  also  seen  as  limiting 
the efficiency. 

  Design  of  programmes  and  measures:  One  report  stated  that  'standard  measures', 
which are already offered over various funding periods with relatively large financial 
volumes  and  are  more  efficient  due  to  the  administrative  routine  and  greater 
acceptance  by  beneficiaries  than  newer  measures,  which  often  also  have  lower 
financial budgets. 

  Programme  implementation:  lack  of  staff  and  its  insufficient  availability,  leading 
e.g.  to  long  waiting  time  for  beneficiaries,  or  the  delays  in  starting  the  programmes 
are often mentioned. Another issue raised is the “lack of innovative actions”. For Axis 
2  (environment  and  the  countryside),  evaluators  suggest  “increased  actions  for 
environmental  development”  and  “improved  knowledge  structures,  indicators, 
research,  development  work  to  strengthen  the  instruments  that  capture  variables  for 
environmentally friendly farming”. Improvement for axes 3 (improving the quality of 
life in rural areas) and 4 (Leader) could be the reduction of administrative burden, the 
development of qualitative indicators to highlight networks, social trust and belief in 
the future; better definition of objectives with regards to community led development. 
  Low  uptake  of  measures,  low  expenditure  rates:  this  issue  was  found  in  several 
reports. The reduction of number of measures programmed with an increased focus on 
targeting could be a solution. 

5.2.2.  QUANTITATIVE ASSESSMENT 

Thus, since the Member States evaluations  did  not  provide a  clear answer to  the efficiency 
question,  an  alternative  approach,  i.e.  calculating  the  costs  per  result  achieved,  was  used. 
This, however, also proved to be fairly difficult due to the low data quality on achievements, 
and  it  can  only  provide  an  approximation,  which  could  not  be  used  for  a  proper 
benchmarking. 

The  main  limitation  to  the  quantitative  analysis  of  efficiency  is  that  contextual  conditions 
vary substantially between Member States. Therefore, there is no use in comparing calculated 
levels  of  efficiency  between  Member  States.  Furthermore,  there  are  no  benchmarks  for  the 
proportionality of costs available, neither from earlier evaluations of programmes, nor at the 
aggregate  EU  level.  Where  individual  values  for  Member  States  are  provided,  they  aim  to 
illustrate the variability and they are not intended to judge overall proportionality of costs for 
this Member State. 

42 

 
A  further  limitation  is  that  total  EAFRD  expenditure  is  reported  per  measure,  but  result 
indicators do not always match the measures. For example, result indicators are reported by 
operations for M111 (training), in relation to several measures (R4: M131 and M132) and in 
relation  to  some  measures  different  indicators  are  reported  (M121  to  M124,  M131,  M311, 
M312). Expenditure cannot be disaggregated by operation or indicator, therefore efficiency is 
calculated for each indicator/ operation by dividing it by the total EAFRD expenditure. Thus 
the outcomes only provide a rough estimation of costs per results and do not take into account 
double counting. 

Furthermore, the analysis made by the evaluator of efficiency did not include administrative 
costs. 

5.2.2.1. Axis 1. Competitiveness 

Cost  per  number  of  participants  that  successfully  ended  a  training  activity  related  to 
agriculture and/or forestry (RI1) 

Achieved results for this result indicator were reported for only one measure M111 (training) 
for  two  criteria:  1)  Passing  with  certificate,  degree  or  diploma;  and  2)  Implementing  the 
achieved  skills.  It  is  not  obvious  therefore  if  the  achieved  results  could  have  been  reported 
twice under both  criteria. Of the 26 Member States  which implemented  M111,  13 Member 
States reported on both criteria and one did not provide any information. Extreme values are 
found  in  France,  Ireland  and  Portugal,  which  can  be  caused  by  unspecified  relation  of 
expenditure to the two criteria reported for RI1. They were not considered in the calculation 
of  average  costs  estimated  around  EUR  330/participant.  Not  all  the  expenditure  in  training 
(EUR  8.4  billion)  lead  participants  to  actually  pass  the  training  programs  with  a  certificate 
expenditure. 
thus 
and/or 

implementing 

difference 

skills, 

the 

its 

in 

43 

 
 
 
 
Table 3. Participants successfully ending a training under RI1 

expenditure 

Measure reported under RI1 
Number of reporting Member States 
Total  EAFRD 
for 
reporting  Member  States  (Million 
EUR)  
Total participants (Million) 
Cost  range  (min  –  max)  (EUR)  per 
participant 
Average cost / participant (EUR)  
Source: Evaluation support study 
Note: the average cost exclude extreme values. 

Passing by achieving certificate, 
degree or diploma 
M111 
23 
775.5 

Implementing 
achieved skills  
M111 
15 
686  

the 

1.86  
(36 - 6 630) 

335   

1.99 
(14 - 109 520) 

333   

Cost for EUR 1 000 increase in GVA in supported holdings (RI2) 

The calculations illustrate the costs for an increase in GVA by EUR 1 000. The attribution of 
the effect to the intervention is not as clear as with the other Result Indicators, as changes in 
GVA  in  supported  holdings  are  influenced  by  a  variety  of  factors,  and  not  only  by  the 
measures. The results of this calculation have therefore to be understood as indicative only.   

In total, 10 Axis 1 (competitiveness) measures are related to RI2; Denmark, Luxemburg, and 
the Netherlands did not report any data on this indicator. Some data provided were negative: 
to  be  interpreted  as  expenditure  that  resulted  in  a  decrease  in  GVA.  The  average  cost  to 
achieve an increase of EUR 1 000 of GVA across all reporting Member States is EUR around 
330.  However,  the  variability  is  enormous,  and  7  measures  reported  a  negative  relation 
between costs and GVA increase. Extreme values are found  in Belgium, Latvia, and Spain, 
which may indicate inconsistency in unit of measurements for RI2. They were not included in 
the calculation.  

Among  the  relevant  measures,  and  taking  into  account  the  evidence  base,  M122 
(improvement of the economic value of forests), and M123 (adding value to agricultural and 
forestry products) have shown the highest effectiveness in cost per achieved output ranging 
from  EUR  100  to  EUR  150  of  EAFRD  expenditure  per  EUR  1 000  achieved  GVA  in 
supported holdings. Furthermore, with an overall average one-time cost of EUR 333 per EUR 
1 000 increase in GVA each year, it can be said that the measures under RI2 have efficiently 
contributed to increasing GVA in agriculture. 

44 

 
 
 
 
Table 4. Achieved increase in GVA under RI2 

Measures reported under RI2  
Number of reported values 
Total  EAFRD  expenditure  for  reporting 
Member States (Million EUR) 
Total GVA increase (Million EUR)  
Cost  range  (min  –  max)  (EUR)  per  EUR 
1 000 GVA increase 
Average  cost  /  €  1 000  GVA  increase 
achieved (EUR)  
Source: Evaluation support study 

M112 – M115, M121 – M125, M131 
116 
 22 536  

65.78  
( -318 000 to +316 000) 

333 

Cost per number of enterprises introducing new products and/or techniques (RI3) 

On the 4 measures that reported on RI3 (M121 – Modernisation, M122 – improvement of the 
economic value of forests, M123 – adding value to agricultural and forestry products, M124 – 
cooperation), a total of 73 valid entries have been made. The introduction of new products or 
techniques  has  cost  on  average  close  to  EUR  80 000  per  enterprise.  Out  of  the  4  relevant 
measures,  M124  (Cooperation  for  the  development  of  new  products,  processes  and 
technologies  in  the  agriculture  and  food  sector  and  in  the  forestry  sector)  shows  the  best 
efficiency with an average cost of EUR 17 800 per enterprise. 

It  has  to  be  noted  that  there  are  large  variations  in  the  total  number  of  enterprises  reported 
under  this  result  indicator,  pointing  at  some  methodological  issues  and  leading  to  a  wide 
range of estimated costs from EUR 2 550 to EUR 2 620 000 per enterprise. 

Table 5. Number of enterprises introducing new products and/or techniques under RI3 
Measures reported under RI3 
Number of reported values 
Total  EAFRD  expenditure 
Member States (Million EUR)  
Total number of supported enterprises  
Cost range (min – max) (EUR) per enterprise 
Average cost / holding (EUR) 
Source: Evaluation support study 

201 778  
(2 550 to 2 621 500) 
79 065 

M121 to M124  
73  
15 954 

reporting 

for 

 Cost per EUR 1 000 of agricultural production under recognised quality label achieved 
thanks to CAP support (RI4) 

Values of agricultural production under recognised quality label were disaggregated between 
European and national labels/standards. Due to a low number of reporting Member States (15 
for EU labels and 14 for national labels) the results have to be treated with caution. Several 
countries did not report any values despite implementing at least one of the relevant measures 
(Austria,  Denmark,  Estonia,  Germany,  Latvia  and  the  Netherlands).  The  average  costs 
calculated  per  achieved  EUR 1 000  of  production  value  vary  between  EUR  8 100  for  EU 
labels and EUR 12 500 for national labels. The range between minimum and maximum cost 
also varied significantly, from EUR 2.4 to EUR 2 019.5 for EU labels and from EUR 0.9 to 
EUR 62 660 for national labels. 

45 

 
Cost per number of farms entering the market (RI5) 

Only 12 Member States implemented at least one of the two related measures, and only four 
of  them  reported  on  RI5,  namely  Bulgaria,  Cyprus,  Lithuania  and  Romania.  Thus,  the 
relevance of the findings about efficiency at an aggregate level is low. The calculation of cost 
per achieved results hints on an average cost for a farm entering the market of EUR 108 770, 
with a minimum cost of EUR 10 280 and maximum of EUR 3 million. 

5.2.2.2. Axis 2. Environment and the countryside 

Cost per ha under land management (RI6) 

Only one result indicator (RI6) is  applied to monitor outcomes of Axis 2 (environment and 
the countryside) measures. Still, RI6 “Areas under land management (ha)” reports separately 
for  the  different  objectives  biodiversity,  water  quality,  climate  change,  soil  quality  and 
avoidance  of  marginalisation.  A  slightly  different  approach  is  taken  here  by  calculating  the 
cost  at  the  level  of  measures,  as  the  same  hectares  (in  which  the  corresponding  RI6  is 
expressed)  can  serve  several  purposes.  Particularly  for  water  quality,  climate  change,  soil 
quality less results were reported. Examples for biodiversity and avoidance of marginalisation 
are provided in the table below. As there are too many gaps in data on the other objectives; it 
is not possible to know which part of the expenditure was used for actions targeting specific 
objectives; and it is not possible to rule out double counting, a calculation of cost per benefits 
for those would be not appropriate. 

Table 6. Average cost per supported ha under land management (RI6) 

Measures  

Number of 
Member 
States 
implementing  

Number 
of 
reporting 
Member 
States  

Total 
EAFRD 
expenditure 
for 
reporting 
Member 
States (in 
Million 
EUR)  

Area 
coverage 
in 
million 
ha  

Average 
cost in 
EUR / 
ha  

Biodiversity 

M211/212 
payments to 
farmers in 
mountain areas 
and other areas 
with handicaps 
M213 Natura 
2000 payments 
M214 agri-
environmental 
measures 

27 

25 

14 230 

18.9 

754 

13 

27 

12 

27 

267 

1.1 

238 

23 619 

42.5 

556 

46 

 
Measures  

Number of 
Member States 
implementing  

Number 
of 
reporting 
Member 
States  

Total 
EAFRD 
expenditure 
for reporting 
Member 
States (in 
Million 
EUR)  

Area 
coverage 
in million 
ha  

Average 
cost in 
EUR / ha  

M215 animal 
welfare 
M216 support 
for non-
productive 
investments 
M221 First 
afforestation of 
agricultural land 
M223 First 
afforestation of 
non-agricultural 
land 
M224 Natura 
2000 payments- 
forestry 
M225 forest-
environment 
payments 
M226 restoring 
forestry 
potential 
M227 support 
for non-
productive 
investments 

Avoidance of 
marginalisation 
M211/212 
payments to 
farmers in 
mountain areas 
and other areas 
with handicaps 
M213 Natura 
2000 payments 
M214 agri-
environmental 
measures 
M216 support 
for non-
productive 
investments 
M221 First 
afforestation of 
agricultural land 
M223 First 
afforestation of 
non-agricultural 
land 

11 

16 

20 

10 

11 

13 

16 

13 

5 

13 

18 

8 

11 

12 

13 

11 

360 

1.2 

311 

555 

0.6 

844 

1 583 

0.5 

3 269 

155 

0.08 

1 933 

74 

70 

0.2 

302 

0.4 

165 

1 517 

9.6 

158 

691 

3.2 

217 

27 

25 

14 230 

58.1 

245 

13 

27 

16 

20 

10 

12 

27 

13 

18 

8 

267 

0.5 

391 

23 619 

19.6 

1 208 

555 

0.7 

844 

1 583 

0.3 

5 670 

155 

0.03 

5 877 

47 

 
Measures  

Number of 
Member 
States 
implementing  

Number 
of 
reporting 
Member 
States  

Total 
EAFRD 
expenditure 
for 
reporting 
Member 
States (in 
Million 
EUR)  

Area 
coverage 
in 
million 
ha  

Average 
cost in 
EUR / 
ha  

11 

13 

74 

12 

11 

901 

0.08 

M224 Natura 
2000 payments- 
forestry 
M225 forest-
environment 
payments 
M226 restoring 
forestry 
potential 
M227 support 
for non-
productive 
investments 
Note: For the full label of measures see Table 1. Measures with 5 of less Member States reporting were dropped. 
Source: Evaluation support study 

1 517 

1 288 

337 

691 

578 

2.6 

0.2 

0.5 

70 

13 

11 

16 

13 

There  are  large  variations  in  the  costs  per  supported  ha,  which  can  be  to  some  extent 
attributed  to  the  limitations  in  the  calculation  but  also  to  the  level  of  ambition  of  the 
commitment.  The  most  cost  efficient  measures  across  both  objectives  appear  to  be  M213 
(Natura 2000), M225 (Forest-environment) and M226 (Restoring forestry). 

Some  of  the  forestry  measures  (particularly  M221  to  M223,  related  to  first  afforestation  of 
agricultural and non-agricultural land) are less cost efficient than those related to agricultural 
area for both of the considered sub-indicators biodiversity and avoidance of marginalisation. 
However, this can be due to the cost intensive nature of these measures. 

5.2.2.3. Axis 3. Diversification of the rural economy and quality of life in rural areas 

Cost for EUR 1 000 increase in non-agriculture GVA (RI7) 

Measures  related  to  RI7  were  implemented  in  25  Member  States  out  of  which  five  did  not 
report  any  data:  Belgium,  Cyprus,  Denmark,  Luxemburg  and  the  Netherlands.  The 
calculations  show  how  much  it  costs  to  increase  non-agriculture  GVA.  On  average  this 
amounts  to  a  one-time  cost  of  EUR  2 000  for  an  increase  in  non-agriculture  GVA  of 
EUR 1 000  per  year.  Again,  variations  are  significant  between  Member  States.  However, 
there  seems  to  be  no  significant  difference  in  efficiency  between  the  different  measures. 
Extreme  values  are  found  in  Latvia,  which  may  indicate  inconsistency  in  unit  of 
measurements for RI6. They are not included in the calculation of minimum, maximum and 
average costs. 

Table 7. RI7 increase in non-agricultural GVA 

Measures reported under RI7  
Number of reported values  
Total EAFRD expenditure of reporting Member States 
(Million EUR)  

M311 – M313  
50 
3 232  

48 

 
Total achieved RI in implementing Member States 
(Million EUR) 
Min/max cost / EUR 1 000 GVA increase achieved (EUR)  91 to 99 720 
Average cost / EUR 1 000 GVA increase achieved (EUR) 
Source: Evaluation support study 

1 570  

2 013  

Cost per gross number of jobs created (RI8) 

This  indicator  is  relevant  not  only  for  Axis  3  (diversification)  measures,  but  also  for  most 
Axis 4 (Leader) measures. However, no data was reported on LEADER-related measures in 
the annual  monitoring tables. Axis  3 measures reported under RI8 were implemented in  25 
Member  States.  The  calculations  result  in  an  average  cost  per  job  created  of  around  EUR 
29 000. However, there is a large variability between measures and between Member States. 

M312 (Support for business creation and development of micro-enterprises) has the highest 
efficiency  with  about  EUR  22 500  of  EAFRD  expenditure  per  job  created;  however  this 
calculation does not take into account the provided national or private expenditure that relates 
to the measure. 

Table 8. Gross number of jobs created under RI8 

Measures reported under RI8  
Number of reported values  
Total EAFRD expenditure for reporting 
Member States (Million EUR)  
Total number of jobs created  
Cost range (min – max) (EUR) 
Average cost / job created (EUR)  
Source: Evaluation support study 

M311 – M313, (M411 – M413, M421)  
46 
3 271  

105 819  
864 to 157 972 
29 414  

Cost per additional number of tourist visits (RI9) 

Only  M313  (Encouragement  of  tourism  activities)  is  reported  under  RI9,  which  was 
implemented  in  22  Member  States.  RI9  was  reported  by  two  separate  measurements: 
“number of overnight stays” and “number of day visits”. As there is no information whether a 
single activity could have led to effects in both categories, and no disaggregated expenditure 
data  available,  the  sum  of  both  indicators  is  used  in  the  calculation.  The  average  cost  per 
additional visit was calculated to be EUR 35. 

Table 9. Additional number of tourist visits under RI9 

Measures reported under RI9  
Number of implementing and reporting 
Member States  
Total EAFRD expenditure for reporting 
Member States (Million EUR)  
Total number of additional tourist visits 
(Million) 
Cost range (min – max) (EUR) 
Average cost / additional visit (EUR)  
Source: Evaluation support study 

M313  
18  

788  

22.6 

0.65 to 1 545 
34.9  

49 

 
Cost per addition person in rural areas benefiting from improved services (RI10) 

The  three  related  measures  for  RI10  have  been  implemented  in  26  Member  States.  The 
average  cost  for  an  additional  person  benefitting  from  improved  services  is  EUR  52.  An 
extreme value is found for one Member State (Malta), which might indicate an inconsistency 
of units of measurement. It is not included in the calculation of average costs. 

The  calculations  made  by  the  contractor  in  the  evaluation  support  study  show  that  M323 
(Conservation  and  upgrading  of  the  rural  heritage)  has  the  lowest  average  EAFRD 
expenditure  per  person  benefitting  from  improved  services  with  only  EUR  17  per  person. 
However,  the  large  difference  in  relation  to  the  other  relevant  measures  can  possibly  be 
explained with their different scopes. 

Table 10. Population benefitting from improved services 

Measures reported under R10  
Number of reported values  

M321 – M323  
61  

7 958  

Total EAFRD expenditure for reporting 
Member States (Million EUR)  
Total rural population benefitting 
(Million) 
Cost range (min – max) (EUR) 
Average cost / person benefitting (EUR)  
Source: Evaluation support study 
Costs per person benefitting from increase in internet penetration in rural areas (RI11) 

1.1 to 4 219 
52.3  

151.9  

The increase in internet penetration in rural areas is measured through the population that has 
access  to  (broadband)  internet  connection.  The  indicator  is  only  relevant  for  M321  (basic 
services  for  the  economy  and  rural  population).  Extreme  values  were  found  in  Greece,  the 
Netherlands and Austria, which may indicate inconsistency in unit of measurements for RI11. 

Table 11. Population benefitting from improved internet connection 

Measure reported under RI11  
Number of reported values  
Total EAFRD expenditure for reporting 
Member States (Million EUR)  
Number of persons benefitting (Million)  
Cost range (min – max) (EUR) 
Average cost / person benefitting (EUR)  
Source: Evaluation support study 

M321  
17  
2 921  

16.7  
1.9 to 12 134 100 
164.5  

5.2.2.4. Axis 4. LEADER 

Cost per participant that successfully ended a training activity (RI12) 

In  17  Member  States,  measures  reported  under  RI12  have  been  implemented,  and  Member 
States all reported on the indicators (though not  all for  each of the measures). The  average 
cost  per  participant  that  successfully  ended  a  training  activity  was  EUR  200.  An  extreme 
value is found for one Member State (France), which might indicate an inconsistency of units 
of measurement. It is not included in the calculation of average costs. 

50 

 
Table 12. Average cost per participant successfully ending a training activity 
Measures reported under RI12  
Number of reported values  
Total EAFRD expenditure for reporting 
Member States (Million EUR)  
Total number of participants  
Cost range (min – max) (EUR) 
Average cost / participant (EUR)  
Source: Evaluation support study 

M331, M341  
23  
188  

751 673  
1.8 to 47 191 
199.9  

5.3.  COHERENCE 

5.3.1.  Coherence  of  rural  development  policy  with  other  CAP  funds  and  other  EU 
interventions in the same programme area 

The assessment of the coherence and complementarity of the rural development programmes 
with  other  CAP  funds  is  restricted  by  the  fact  that  only  five  programmes  reported  on  it79. 
Most Member States did not address this issue in their ex post evaluations, since it was only 
part of the ex-ante assessments of the rural development programmes, and not mandatory for 
the ex post evaluation. Furthermore, the information available is limited to such an extent that 
only a qualitative description of the five cases is available. 

The ex-ante assessment had already concluded that generally the programmes did not always 
look actively for synergies between the different EU interventions in the same programming 
area,  but  rather  for  clear  demarcation  and  avoidance  of  overlaps  between  different  funds80. 
The other significant  funds in  rural  areas included the  EU Structural  and  Investment  Funds 
(ESIF),  which  include  the  European  Regional  Development  Fund,  focusing  on  regional 
development,  economic  competitiveness  and  infrastructure;  the  European  Social  Fund, 
focusing  on  the  development  of  human  capital,  employment  and  social  inclusion  and  the 
European Agricultural Fund for Rural Development. 

The ex post evaluations showed that some Member States strongly differentiated and ensured 
no overlapping between the funds. Nevertheless, this approach also had the negative effect of 
lack  of  synergies.  In  most  cases,  ensuring  complementarity  between  these  funds  took  the 
form of establishing demarcation lines and coordination mechanisms. Only in some cases a 
more strategic vision for the coordinated use of EU funds was chosen by Member States. The 
guiding principles were set in the National Strategy Plans, while some programmes provided 
a  detailed  description.  The  coordinated  use  of  EU  funds  was  ensured  also  by  the  different 
managing  authorities  during  the  start-up  phase  of  the  programmes  For  example,  in  the 
programmer  of  Brandenburg/Berlin  a  range  of  complex  projects  were  identified  and 
coordinated in a coherent manner, integrating funding possibilities towards a single goal. The 
ex  post  evaluations  of  Castilla  La  Mancha  and  Latvia  also  attribute  the  successes  to  clear 
coordination. 

79  Brandenburg/Berlin  (Germany),  Castilla  La  Mancha  (Spain),  England  (United  Kingdom),  Hamburg 

(Germany) and Latvia. 

80  See synthesis of ex-ante evaluations of rural development programmes 2007-2013. 

51 

 
                                                 
Communication and coordination were deemed important for complementarity and synergies 
between  Community  instruments,  yet  issues  were  found  in  the  coordination  in  two 
programmes (England and Hamburg). Furthermore, the EESC in its report81 pointed to a lack 
of coordination, complementarity and consistency with the actions of the other structural and 
cohesion funds that hindered the overall aim of a more balanced territorial development. 

These rather mixed (with very small number of programmes reporting) results are in contrast 
with  the  results  of  the  Public  Consultation,  where  68%  of  the  respondents  found  external 
coherence positive (sum of very positive and moderately positive view) and only 12% found 
a lack of it, with stakeholders “farms” and “individual citizens of rural areas” finding it less 
consistent  than  the  rest  of  the  groups  (but  still  mostly  positive).  The  other  20%  had  no 
opinion. 

5.3.2. Coherence with the overall rural development priorities 

The outcomes of the rural development programmes are to a varying extent consistent with 
the  four  Rural  Development  objectives.  While  relatively  few  instances  of  issues  being 
reported can on the one hand be interpreted as an absence of contradictory effects, this might 
also  be  due  to  evaluators  having  difficulty  in  grasping  such  effects.  The  internal  coherence 
with regards of the specific objectives is the following 

  Objective  1  (improving  the  competitiveness  of  the  agricultural  and  forestry  sector), 
was achieved to a moderate extent. a small share of ex post evaluation reports stated 
negative  and  contradictory  effects  on  competitiveness,  bargaining  power  and  labour 
productivity/profits,  though  the  overall  ex  post  analysis  showed  a  moderate  positive 
coherence.  A  negative  contribution  in  this  respect  was  reported  for  only  one 
programme and for one measure (M142 – setting-up producer groups). The negative 
effect  on  competitiveness  was  based  on  negative  effect  on  GVA,  productivity,  and 
employment.  Contradictory  other  effects  were  reported  in  some  cases  from  M141 
(Semi-subsistence  farming)  with  relation  to  the  decreased  bargaining  power  of  non- 
beneficiaries;  for  M224  (Natura  2000)  payments  were  considered  partly  as 
insufficient (taking into account the long production period of a forest (> 100 years); 
as 
labour 
productivity/profit;  and  for  M312  (business  creation)  the  negative  effect  was  due  to 
decreased competitiveness. 

the  negative  effect  was 

(diversification) 

for  M311 

linked 

to 

  Objective 2 (improving the environment and the countryside) was considered overall 
positive,  however  the  extent  of  coherence  couldn’t  be  quantified  for  all  domains. 
Considering the individual domains the extent ranges between moderate and high, as 
far  as  quantifiable:  climate  change  mitigation:  high  extent,  water  management:  high 
extent, protection of natural resources/landscape: moderate extent, renewable energy 
supply: positive impact, but difficult to quantify. 
For  a  small  share  of  programmes,  negative  environmental  effects  were  reported, 
which  are  arising  from  M121  –  modernisation  (while  at  the  same  time,  the  overall 
environmental  effect  of  the  measure  was  stated  to  be  positive),  M132  –  Quality 
schemes. The nature of these effects was not further specified. 

81  See footnote 14. 

52 

 
                                                 
  For  objective  3  (improving  the  quality  of  life  in  rural  areas  and  encouraging 
diversification  of  the  rural  economy),  although  there  were  no  negative  contributions 
nor contradictory other effects identified in the ex post evaluation reports and positive 
contribution was stated in the few ex post evaluation reports that reported on it, it is 
difficult to determine and quantify the overall coherence due to the lack of a higher-
quality evidence base. 

  For objective 4 (building local capacity for employment and diversification), there are 
no negative contributions or contradictory other effects at measure level, however the 
coherence of the programmes with objective 4 is difficult to qualify. 

Overall, the coherence with the rural development objectives tend to depend on the quality of 
the evidence base reported, which is higher for the longer-established domains of Axis I and 
II. This results in higher visibility of these axes’ contributions, as compared to more complex 
domains such as quality of life and newer approaches such as LEADER. 

5.4.  RELEVANCE 

The analysis of the relevance of the Rural Development measures is based on the needs listed 
beneath, covering the social, economic and environmental dimensions. These needs are then 
compared to the programmes’ contributions addressing them. 

53 

 
 
 
Table 13. List of needs being addressed by the rural development measures 

Economic 
Structural adjustments and 
modernisation (productivity 
deficits, fragmentation, capital, 
dependency) 
Value chains, added value, 
integration between sectors 

Lack of specialisation / 
diversification / de-
concentration / quality 

Source: Evaluation support study. 

Social 
Unemployment / disparities / 
create job-offers / income 
alternatives  

Environmental 
Natural resources / nature 
protection 

Demographic change (migration, 
aging, depopulation, brain drain 

Basic services (access, 
provision, housing) 

Physical infrastructures 
(creation, adaption access). 

Sustainable practices (in 
land/forest management), 
awareness 
Biodiversity, ecological 
structures, habitats  

Furthermore,  the  magnitude  of  the  expenditure  by  axes  correspond  to  the  main  needs,  thus 
expenditure shares can be used as a basis of the analysis of the needs, enabling an overview at 
EU level. Nevertheless, it is not feasible to relate regional-level needs to the way they were 
addressed  in  the  same  region.  It  is  only  possible  to  provide  a  comparison  of  the  main  EU-
level  needs  to  how  they  were  addressed  by  programmes  across  regions  overall.  Moreover, 
these needs identified at EU level in the synthesis of ex-ante evaluations are not specified in 
detail, so only a part of them can be linked precisely to topics covered by Rural Development 
measures and related indicators. 

Regarding  the  need  of  “structural  adjustments  and  modernisation”,  despite  not  having  a 
specific  result  indicator  associated  (but  part  of  the  Axis  I  needs),  it  was  considered  in  the 
reports as positively addressed. 

Similarly,  for need “value chains,  added value, integration between sectors” the increase in 
gross value added in supported holdings/enterprises (RI2) demonstrates the relevance of the 
policy. 

For  “lack  of  specialisation/diversification/de-concentration/quality”, 
the  Member 
States/regions  reporting  on  it,  the  increase  in  the  value  of  agricultural  production  under 
recognised  quality  label/standards  highlights  the  policy  relevance.  However,  due  to  a  very 
low number of Member States reporting on the indicator, these results cannot be extrapolated 
for the whole EU-28. 

in 

In  the  social/socio-economic  dimension,  overall  the  rural  development  programmes 
addressed the issues of the relevant social needs to a moderate extent. The rural development 
programmes  helped  to  create  new  job  opportunities,  which  amounted  to  respectively  1.2% 
and 0.4% of the total number of people working in agriculture and forestry. 

In  addition,  through  the  rural  development  programmes’  interventions,  154 million  people 
could  benefit  from  improved  services  in  rural  areas  and  around  15%  of  the  total  rural 
population could benefit from new or improved internet services in the rural areas (RI11). 

The  last  two  needs,  “Demographic  change”  and  “Physical  infrastructures”  do  not  have  a 
relevant matching result indicator, and therefore its relevance can only be addressed through 
the  reports.  Physical  infrastructures  was  judged  by  Member  States/regions  as  positively 

54 

 
 
 
 
addressed (yet  only moderately).  For the demographic change need, the results were not  so 
clear, and depended on the specific domain the measures were acting on. 

As  regards  the  environmental  dimension,  overall,  the  rural  development  programmes 
addressed the issues of the relevant environmental needs to a moderate extent. With a volume 
of  expenditures  that  amounts  to  the  highest  share  among  the  three  dimensions  (i.e.  nearly 
twice the average). 

More than half of the ex post evaluations concluded that the rural development programmes 
had  a  major  positive  contribution  to  protect  and  enhance  natural  resources  and  landscape, 
including  biodiversity  and  high  nature  value  farming  and  forestry.  Half  of  the  ex  post 
evaluations also found that the rural development programmes played a very positive role in 
improving water management. 

5.5.  EU ADDED VALUE 

EU added value was not addressed in the ex post evaluations carried out by Member States, 
and  thus  even  the  qualitative  information  for  the  judgment  is  very  limited,  therefore  the 
analysis is based on the results of the effectiveness and efficiency analysis, the assessment of 
coherence, and conclusions on subsidiarity from the synthesis of the ex-ante evaluations. The 
EAFRD funding via the rural development programmes ensured EU added value to a certain 
extent,  and  it  depended  on  the  specific  aspects  considered.  Nevertheless,  the  quality  of 
reflection  upon  the  question  of  EU  added  value  is  not  sufficient  in  the  ex  post  evaluation 
reports  nor  there  is  information  derived  from  the  relevant  assessment  results.  In  addition, 
there is no common approach to assess subsidiarity and proportionality at programme level. 
Where conformity  with  these criteria is  declared, it is  not  underpinned with descriptions  of 
the mechanisms ensuring them. 

The  evaluation  can  conclude  that  the  implementation  of  EAFRD  funding  via  rural 
development programme has been effective in achieving EU level objectives and supporting 
key EU priorities to a variable extent. It appears that programmes have been more successful 
and  effective  in  achieving  Axis  I  and  II  objectives.  However,  the  lower  extent  reported  to 
achieve  Axis  III  objectives  could  also  be  a  result  of  overall  difficulties  in  measuring  the 
effects. 

Regarding the principles of subsidiarity and proportionality, there are good examples for the 
various CAP supports’ EU added value, e.g.: private and civic actors are involved at all levels 
of decision making in the programming process (Czech case study); the financing decisions 
can  be  taken  more  closely  to  the  final  beneficiaries.  The  EU  added  value  of  funding  is 
especially  relevant,  where  support  of  rural  areas  would  otherwise  be  very  difficult  (Greece 
case). 

The EU added value is illustrious in the case of LEADER. For example, in the Brandenburg 
case study it was found that the LEADER method not only illustrates the successful capacity 
building of subsidiary planning and decision-making structures, but it is also in line with the 
objectives  of  an  overarching  federal  structure.  The  state  had  very  little  role  in  the 
identification and selection of projects and was thus only able to bring federal cultural policy 
goals into play to a limited extent. The projects were mainly aimed at intra-local and micro-
regional  use  within  the  respective  LEADER  area.  The  micro-regional  orientation  of  the 
projects is a result of bottom-up planning. 

55 

 
With regards to the public consultation results, respondents  were majorly positive about the 
EU added value and only few respondents did not see the benefits of EU funding instead of 
Member  State  action,  or  had  a  feeling  that  the  EU  funding  leads  to  a  distortion  of 
competition. In general, EU funding is considered a stable funding source, which also led to 
an increase in national funding through the co-financing principle. EU funding can also have 
a spill over effect and attract other developments in rural areas. Respondents indicated that it 
is important to them that EU funding is not influenced by local political  dynamics and that 
there  is  more  equality  between  the  beneficiaries.  Furthermore,  the  variety  between  projects 
that could be subsidised with EU funding was perceived higher than national funding. 

The positive perception  of EU added value  was  also  confirmed by the European Economic 
and  Social  Committee  in  their  report82,  particularly  in  relation  to  the  early  and  effective 
inclusion of civil  society organisations in  the bottom-up preparation and implementation of 
the programmer, which is emblematic in the case study on Tuscany. However, there are cases 
where the added value was rather poor, e.g. in Poland, where small NGOs were given little 
room to try and influence the decisions taken by the government. 

6.  CONCLUSIONS 

The ex post evaluations for rural development programmes, strategies and frameworks for the 
period  2007-2013,  as  well  as  the  stakeholders  consulted  are  rather  positive  about  the 
contribution of rural development programmes, however the extent of achievement of the 
four objectives differs. 

A majority (59%) of the Member States/regions stated in their ex post evaluation reports that 
the  effects  of  the  CAP  on  competitiveness  were  positive  (25%  reported  limited  impact  and 
16%  negative).  The  support  study  thus  concluded  that  overall  the  competitiveness  of  the 
agricultural  and  forestry  sector  (objective  1)  improved  to  a  moderate  extent.  EU  labour 
productivity increased by 4.1% thanks to the rural development policy. Investments aiming to 
improve productivity, efficiency and sustainability were key to increase GVA in the primary 
sector  while  also  creating  positive  spill-over  effects  on  the  whole  economy,  namely 
investments in farm modernisation (M121), adding value to agricultural and forestry products 
(M123), and improving infrastructure in rural areas related to the development and adaptation 
of agriculture (M125), training and information actions (M111). 

The evaluation support study found that the generational-renewal measures (early retirement 
(M113),  setting-up  (M112)  and  investment  support)  did  not  influence  significantly  the 
number of young farmers across the EU as a whole. They rather targeted the maintenance and 
protection  of  farming  jobs,  particularly  in  marginal  areas,  rather  than  the  creation  of  new 
farming jobs. 

The support study could not conclude on the contribution of the rural development policy to 
improved competitiveness in the overall rural economy, due to the limited number of reports. 

As  regards  the  environment  and  countryside  (objective  2),  although  the  status  of  natural 
resources  and  particularly  biodiversity  deteriorated  over  the  programming  period,  Member 

82  See footnote 14. 

56 

 
                                                 
States/regions reported positive contributions from the rural development policy, suggesting 
that the deterioration would have been worse and land abandonment would have been higher 
without  the  CAP.  On  this  basis,  the  evaluation  support  study  concluded  that  the  rural 
development  programmes’  interventions  contributed  to  the  protection  of  natural  resources 
and  landscape  (to  a  moderate  extent)  and  climate  change  mitigation  (to  a  low  or  unclear 
extent).  61%  of  the  ex  post  evaluations  reported  positive  effects  on  the  protection  and 
enhancement  of  natural  resources  and  landscape,  particularly  biodiversity  and  High  Nature 
Value  farming  and  forestry.  The  agri-environmental  measures  (M214)  were  of  particular 
importance with respect to protecting natural resources and biodiversity also due to the fact 
that all programmes implemented the measure and it accounted for the largest proportion of 
expenditure (26%). 

Measures  with  the  core  objective  of  preventing  land  abandonment,  (M211,  M212)  had  a 
positive  effect  particularly  on  biodiversity  and  high  nature  value  farming/forestry,  mainly 
through  maintaining  extensive  agricultural  systems  in  areas  where  appropriate  land 
management is important for biodiversity and High Nature Value habitats. They also helped 
retain population and employment in fragile rural areas. 

Renewable energy production was not the specific focus of any rural development measures. 
The qualitative data showed that the rural development programmes positively contributed to 
the  supply  of  renewable  energy,  but  only  to  a  very  limited  extent  (in  12%  of  the  Member 
States/regions),  which  was  based  on  the  support  for  biogas  and  biomass  energy.  In  some 
regions, investments in solar energy and distribution systems contributed to an expansion of 
renewable energies. Renewable energy production was reported on it in relation to measure 
M114 (use of advisory services by farmers and forest holders) and M311 (diversification to 
non-agricultural  activities).  The  ex  post  evaluation  reports  indicated  that  Member  States  or 
regions  enhanced  the  transition  from  fossil  sources  to  renewable  biomass  based  sources, 
installed  renewable  energy  production  plants  or  generally  produced  energy  from  renewable 
sources through M311. 

As  regards  climate  change  mitigation  and  adaptation,  overall  only  6%  of  the  Member 
States/regions  reported  on  the  environmental  measures’  positive  effects  in  relation  to 
mitigation, which were however seen rather as a side effect than as a result of clear targeting 
in the rural development programmes. 

The  ex  post  evaluations  very  rarely  reported  on  water  management  issues,  therefore  the 
effects of the CAP on water use and water quantity could only be assessed qualitatively and 
with  difficulty.  Nevertheless,  overall  more  than  half  of  the  ex  post  evaluation  reports 
indicated 
to  water 
management. 

the  rural  development  programmes  positively  contributed 

that 

Out of the four objectives the rural development programmes’ contributed to improving the 
quality  of  life  in  rural  areas  and  encouraging  diversification  of  the  rural  economy 
(objective  3)  to  the  most  limited  extent.  However  there  are  fewer  measures  with  a  direct 
effect  on  this  objective  and  the  lowest  evidence  and  low  quality  data  in  Member 
States/regions evaluation reports. In addition, interventions encouraging diversification of the 
rural  economy  prove  to  produce  less  direct  and  measurable  effects  in  the  short  term.  The 

57 

 
CAP’s impact on quality of life can be mainly attributed to basic infrastructure services (e.g. 
mobility  and  communication)  and  the  social  dimension  (such  as  governance,  social 
sustainability). 

The quantitative data shows that the rural development programmes contributed to create new 
jobs,  not  just  in  the  primary  sector  but  also  in  the  entire  economy,    particularly  food  and 
tourism, but also culture and services. The creation of employment prospects, especially for 
young  generations  in  rural  areas  also  limited  the  abandonment  of  farms,  notably  in 
mountainous regions. 

The recent JRC study on the effects of the CAP proved the positive effect of the CAP in 
general  and  of  rural  development  policy  in  particular  with  regard  to  not  only  safeguarding 
employment in agriculture, but also creating jobs in rural areas as well as boosting the gross 
value added. 

The European Economic and Social Committee showed in its report that rural development 
programmes  contributed  to  maintain  agriculture  and  promoted  competitiveness  of  rural 
businesses and employment and diversified rural economies. 

While  rural  development  programmes  have  been  overall  successful 
in  promoting 
competitiveness,  results  under  innovation  do  not  seem  to  be  very  significant.  The 
introduction of innovative approaches as a result of the policy was rather small, and mainly 
covered  beneficiaries  in  rural  areas  through  M331  (training  and  information).  The  main 
measure  that  contributed  towards  broadband  access  in  rural  areas  was  M321  (basic 
services for the economy and rural population). The quantitative data (provided in 19% of the 
reports only), shows that the rural development programmes created new or improved access 
to  broadband  internet  in  1.4  million  households  or  businesses  (15%  of  the  total  rural 
population). The average number of households or businesses with new or improved internet 
access was 81 315 per region, with the lowest region having only 7 that benefitted from these 
changes. 

Regarding  building  local  capacity  for  employment  and  diversification (objective  4),  the 
evaluation support study found that the local action groups contributed to a limited extent to 
achieving the objectives of the local strategy and that of the rural development programmes, 
however the rural development programmes have contributed to a medium extent to building 
local capacities for employment and diversification through LEADER. 

However, the overall assessment of LEADER cannot be considered plausible due to the small 
share  of  reports  that  provided  conclusions  (with  the  exception  of  the  contribution  to 
enhancing employment). In addition, the quantifiable indicators were not able to capture the 
specific  characteristics  and  objectives  of  the  LEADER  approach,  e.g.  improving  local 
governance or increasing local  participation.  Furthermore, as Axis  4 is  horizontal, it affects 
aspects  of  the  other  EAFRD  axes  and  some  measures  under  other  axes,  especially  Axis  3, 
were  programmed  under  LEADER.  At  times  it  was  not  clear  whether  such  measures  were 
reported  on  under  Axis  3  or  4  in  the  evaluation  reports.  The  synthesis  approach  did  not 
sufficiently  allow  for  consistently  dealing  with  this  aspect,  amongst  other  specifics  of 
LEADER. 

58 

 
As regards the efficiency of the rural developments, it is difficult to assess the proportionality 
of  costs  to  the  benefits  achieved  based  on  the  ex  post  evaluation  reports  and  the  available 
input,  output,  and  result  indicators  tables.  Overall,  62%  of  reports  provided  some  sort  of 
judgment  regarding  the  efficiency  of  resources  allocated  to  the  programmes.  Taking  into 
consideration the limitations of the data, it was not possible to provide an overall judgment of 
proportionality of EAFRD expenditure with regards to benefits achieved at the EU level. The 
difficulties  to  demonstrate the  efficiency of the  2007-2013 Rural  Development Policy  were 
also  highlighted  in  the  Court  of  Auditors  special  report  12/201383.  The  Court  observed  that 
the rural development programmes did not sufficiently set specific objectives with targets for 
the results and that the indicators were not sufficiently reliable. 

The  evaluation  support  study  also  concluded  that  the  limitations  were  also  attributed  to  the 
regulatory  framework,  particularly  the  very  rigid  legal  interpretations  in  terms  of  error 
prevention.  In  addition,  the  changes  resulting  from  the  policy  revision  called  the  ‘health 
check’  leading  to  high  adjustment  costs  due  to  increasing  demands  on  documentation,  data 
(including  IT systems)  and reporting,  as well  as  a  growing number of higher-level  controls 
and  supervisory  authorities,  were  also  seen  as  limiting  the  efficiency.  Some  reports  also 
raised  shortcomings  with  regard  to  the  steering  structure  of  the  programmes  and  measures, 
including the lack of staff, and the low expenditure rates on some of the measures. Often the 
causes and effects of these issues are interrelated. 

the  coherence  of 

the  programmes  with 

Considering 
the  four  rural  development 
objectives/priorities, it was judged to a limited, or moderate extent. Negative contributions to 
the  objectives  were  marginally  reported.  The  consistency  of  rural  development  programme 
projects with other funding from the first pillar of the CAP has been evaluated only in the ex-
ante  assessments,  therefore,  a  conclusion  cannot  be  provided  based  on  the  information 
available.  

As regards the coherence and complementarity with other CAP funds, the rural development 
programmes  aimed  at  clear  demarcation  and  avoidance  of  overlaps  between  the  funds. 
However, this approach had the negative effect of lack of synergies.  

Overall,  the  rural  development  programs  have  contributed  to  addressing  the  needs  in  the 
programme  area  to  a  moderate  extent.  In  the  social/socio-economic  and  economic 
dimensions,  there are considerable differences  in  the extent to  which individual needs were 
addressed  by  the  rural  development  programmes,  while  in  the  environmental  dimension 
needs  were  addressed  more  homogeneously.  More  specifically,  within  the  social  needs,  the 
rural  development  programmes  were  moderately  relevant  (in  terms  of  contribution)  within 
the  area  of  basic  services  and  physical  infrastructures  and  least  for  demographic  change. 
Regarding  economic  needs,  the  programmes  were  moderately  relevant  in  the  area  of  value 
chains,  added  value,  and  integration  between  sectors.  As  for  the  environmental  needs,  the 
rural  development  programmes  were  moderately  relevant  as  regards  natural  resources, 
sustainable  practices  and  biodiversity,  ecological  structures,  habitats,  whereas  the  positive 
effects on climate change mitigation could be considered rather as side-effects of the positive 
impacts of the environmental measures and not the result of clear targeting. 

83  See footnote 74. 

59 

 
                                                 
The  question  of  EU  added  value  was  not  sufficiently  addressed  in  the  ex  post  evaluation 
reports.  Based  on  the  overall  judgments  on  the  three  criteria  (effectiveness  in  achieving 
objectives,  coherence  with  EU  priorities  and  complementarity  with  other  instruments,  and 
subsidiarity),  it    can  be  concluded  that  EAFRD  funding  via  the  rural  development 
programmes  ensured  EU  added  value  to  a  medium  and  variable  extent.  It  needs  to  be 
considered that the judgment varies with regard to the individual criteria. 

The conclusions of this evaluation is very relevant for the long-term vision for the EU’s rural 
areas84, which aims to enable rural areas to make the most of their potential and support them 
in facing their own unique set of issues, from demographic change to connectivity, the risk of 
poverty85 and limited access to services. 

The  core  lessons  learnt  relate  to  the  monitoring  and  evaluation  framework.  The  ex  post 
evaluations on the 2007-2013 funding period were the first ones completed using a Common 
Monitoring  and  Evaluation  Framework  (CMEF)86,  and  adjustments  to  the  framework  were 
made  even  during  the  programming  period.  In  particular,  following  the  experience  of  the 
mid-term evaluations, the evaluation questions were reviewed and rationalised prior to the ex 
post  evaluation  exercise.  Nevertheless,  there  is  a  wide  variety  in  approaches  and  overall 
quality of the Member States evaluations. Thus, whilst the CMEF represents a step forward 
from the previous situation, the limitations in the relevance, calculation and use of indicators, 
and difficulties to establish and maintain realistic target make it difficult to fully demonstrate 
the  outcome  of  the  policy.  The  evaluation  points  to  a  clear  need  for  an  improved,  better 
regulated  data  framework,  including  clear  description  of  concepts,  metadata  and  realistic 
targets.  Any  changes  in  targets  need  to  be  made  explicit  and  related  to  the  programme 
strategy, rather than shifts of resources between measures, and should be accompanied by a 
record of the timing and reason of the changes. 

As  it  takes  time  for  the  impact  of  a  policy  to  become  visible,  evaluation  requirements  and 
design  should  take  into  account  the  variable  time  lag  between  interventions  expressed  in 
achieved output and results, and the attributable impacts. 

As far as the reporting structures are concerned, there is clearly a need for a more prescriptive 
comprehensive structure and maximum report size. It is also suggested to propose appropriate 
approaches and structures for those evaluation questions and information needs that are really 
relevant for EU-level policy information. The CMEF was reviewed and fully revised for the 
2014-2020 period and took account of the lessons learned during the implementation of the 
2007-2013 programmes87. 

The results from the evaluation support study were available to feed into the preparation of 
the CAP post 2020 proposals. The introduction of the performance framework as laid down 

84 

85 

European Commission, A long-term Vision for the EU’s Rural Areas, COM (2021)345 final,  EUR-Lex  - 
52021DC0345 - EN - EUR-Lex (europa.eu). 
For the purpose of this evaluation, risk of poverty or social inclusion is defined as ‘the sum of persons who 
are  either at risk of poverty, or severely  materially and socially deprived or living in a household  with  a 
very low work intensity’. 

86  This is different from the CMEF that covered the whole of the CAP in the 2014-2020 programming period. 
87  Council Regulation (EC) 1305/2013 and Regulation (EC) 808/2014. 

60 

 
                                                 
in  the proposed CAP  strategic plan regulation  and the definition of the evaluation  elements 
addresses  issues  raised  in  this  ex  post  evaluation.  This  includes  the  definition  of  a  clear 
indicator framework with agreed approaches to calculate the targets and indicator values, as 
well as clear and well-defined performance reporting obligations feeding into a performance 
review and a simplified and more flexible evaluation framework for Member States. 

Under  the  new  CAP,  climate  features  prominently  among  the  new  CAP’s  10  specific 
objectives. In terms of policy design, each Member State must assess its needs and integrate 
all  tools  to  address  them  in  a  single  strategic  plan.  The  new  CAP  largely  discontinues  the 
one-size-fits-all  approach  of  direct  support.  Member  States  have  more  flexibility  to  design 
and combine the policy tools. Reducing the administrative burden and simplifying procedures 
is in the focus to improve outreach and uptake too. Increasing the attractiveness of rural areas 
requires integrating this policy with national policies. In particular, the policy for generational 
renewal  in  agriculture  must  be  based  on  such  an  integrated  approach,  aided  by  substantial 
CAP funding. 

61 

 
 
 
ANNEX 1. LEAD DG, DECIDE PLANNING/CWP REFERENCES 

Lead DG: Directorate-General Agriculture and Rural Development (DG AGRI) 

Decide planning reference: PLAN/2016/527 - AGRI 

1.  ORGANISATION AND TIMING 

This was a policy evaluation project included in the DG AGRI evaluation plan 2016-2020. It 
followed the Better Regulation guidelines (2017) with regard to evaluations. The evaluation 
work  was  carried  out  through  an  external  evaluation  study,  contracted  through  a  service 
request under a framework contract, conducted in conformity with the DG AGRI procedure 
for  the  organisation  and  management  of  policy  evaluations  carried  out  by  external 
contractors.  The  project  was  supervised  under  the  technical  as  well  as  the  contractual 
management of AGRI unit C.4 in charge of Monitoring and Evaluation (As of 2022 unit A.3 
“Policy Performance”). 

An Inter-service Steering Group (ISG) was set up by the Commission in March 2017, with 
the mandate to provide information, prepare the terms of reference, monitor the work of the 
external study team, discuss and give advice on the approval of the final report, comment on 
the draft evaluation SWD. 

The  ISG  was  composed  of  the  Secretariat-General  of  the  Commission  and  DGs  ENV, 
CLIMA,  JRC,  REGIO,  RTD,  MARE  and  AGRI  (14  different  units).  The  Steering  Group 
started its meetings in March 2017 and held 6 meetings. 

The evaluation roadmap was published on the 19th of June 2017 and set out the context, scope 
and aim of the exercise. The roadmap presented the questions to be addressed under the five 
categories of effectiveness, efficiency, relevance, coherence and EU added value. During the 
feedback  period  on  the  roadmap  two  contributions  were  received.  None  of  them  required 
changes of the approach towards the evaluation. 

The evaluation project carried out by the external contractor started in August 2017. The final 
deliverable was received on 24th of April 2018 and accepted. The external evaluation study 
provided the basis for this SWD. 

The EESC finalised on the 6th of October 2017 the information report “Ex post evaluation of 
rural development programmes 2007-2013”88. 

88  See footnote 14. 

62 

 
 
 
                                                 
2.  CONSULTATION OF THE RSB  

The RSB scrutinized this evaluation SWD in the meeting held on 3 July 2019 and provided a 
negative opinion. The comments raised have been addressed in the following way: 

Regulatory Scrutiny Board remark 
1. The report does not sufficiently present the 
limitations of what this synthesis evaluation can 
deliver. Conclusions on effectiveness of the 
programmes are not supported by the evidence 
presented. 

2. The report does not explain how the weaknesses 
in policy design and implementation which 
prevented conclusions being drawn on the results 
of the 2007-2013 programmes have been 
addressed in the current and proposed future 
programming periods. 

3. The information presented is sometimes 
contradictory. It is not clear how the scoring 
system links to the programmes’ objectives and 
whether it was applied consistently across country 
reports. 

Considerations for the report 
All the chapters of the evaluation report have been 
revised, including Chapters 4.4. On the limitations 
and robustness of findings and particularly chapter 
5.1 on effectiveness that provides for a thorough 
assessment of effectiveness for all the four Axes. 
The conclusions were revised to match the facts 
presented in detail in chapter 5.1 effectiveness. 
In terms of policy design and efficiency, as now 
explained in the conclusion, the CAP post 2020 
proposals took into account the need of a strategic 
approach and to integrate the CAP and national 
policies especially to improve the quality of life in 
rural areas. Simplification and more flexibility are 
key aspects of the reform, as well as a better 
targeting of the climate objective. 
The core lessons learnt relate to the monitoring 
and evaluation framework. The ex post 
evaluations on the 2007-2013 funding period were 
the first ones completed using the Common 
Monitoring and Evaluation Framework (CMEF). 
Adjustments to the framework were made even 
during the programming period. In addition, the 
CMEF was fully revised for the 2014-2020 period 
and took account of the lessons learnt during the 
implementation of the 2007-2013 programmes.  
The CAP post 2020 proposes further 
improvements: the new performance and 
evaluation framework has fewer indicators, 
streamlined across all areas and funding sources. 
In addition, the evaluation framework for Member 
States is simplified and more flexible. 
The evaluation report has been re-structured to 
remove any contradiction or to explain the 
remaining contradictions by providing clear 
information on the sources.  
The scoring system is described in detail in 
chapter 4.1 -method of the evaluation support 
study, together with its limitations. The scoring 
system elaborated by the contractor was applied 
consistently across country reports and served to 
draw the final EU level conclusions. 
Finally, the conclusions provided in the synthesis 
report specifically address the extent to which the 
rural development programmes contributed to the 
specific objectives in a qualitative way. 

3.  EVIDENCE USED 

This  evaluation  was  designed  as  a  synthesis  of  the  evaluations  carried  out  by  the  Member 
States. The support study used the following inputs: 

-  91 Rural development programme ex post evaluation reports; 

63 

 
 
-  27 National Strategy Plans; 
-  88 Rural development programmes; 
-  2 National Frameworks; 
-  National Rural Development Network programmes. 

The Member States submitted this material to the Commission in the national language. The 
evaluation support study provides more details on the exact title and content of these reports. 
The  ex  post  evaluation  reports  were  drafted  by  independent  country  expert  evaluators 
according to predefined templates. 

Besides  this,  the  Commission  made  available  to  the  evaluator  responsible  for  the  support 
study  the  financial  tables  including  expenditure  per  measure  and  axis  for  all  rural 
development programmes (Input indicators), tables including the results for output indicators 
for each Member State and tables including the results for result indicators for each Member 
State. 

Additionally, the evaluation could draw on input from the public consultation (see Annex 2) 
and  the  evaluation  report  NAT/699-EESC-2017-00690-00-00-RI-TRA  carried  out  by  the 
European Economic and Social Committee: 

-  https://www.eesc.europa.eu/fr/sections-other-bodies/sections-commission/agriculture-

rural-development-and-environment-nat/information-reports; 

Also  the  synthesis  of  the  ex-ante  and  mid-term  evaluations  of  the  rural  development 
programmes 2007-13 were used: 

-  https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-

policy/cmef/rural-areas/synthesis-ex-ante-evaluations-rural-development-
programmes-2007-13_en (synthesis); 

-  https://op.europa.eu/en/publication-detail/-/publication/aaefb39b-aa88-4f6f-b4dd-

4bbd48c43c56 (mid-term). 

4.  QUALITY AND LIMITATIONS OF THE EVIDENCE USED 

In all the cases, and in spite of the adjusted methodologies, the quality and availability of data 
continued to be a limitation throughout the project. 

1) In general, the quality of the rural development programmer ex post evaluation reports was 
not  uniform.  Some  of  the  reports  provided  substantial  analyses  with  well-argued  examples, 
while other reports lacked clear reasoning and presented conclusions without substantiation. 
In addition, some reported values seemed out of the scope of possibilities, either being much 
larger or smaller than what would seem feasible for the specific aspect being measured. 

2)  A  second  issue  is  the  mostly  qualitative  nature  of  analyses  in  the  ex  post  evaluation 
reports,  and  the  limited  quantitative  support  to  justify  the  effects  claimed.  Attempts  to  use 
output, result and impact indicators to validate or test the findings of the qualitative analysis 
were only to a limited extent successful due to the low quality of the data. 

3) There were limitations to the data for indicators and targets: There are inaccuracies in the 
data from rural development programmer annual reports reported by Member States, as in the 
case of the data provided on the result indicators, and potential inconsistencies between data 

64 

 
from rural development programmer annual reports reported by Member States and indicator 
values reported and used for the judgments in the ex post evaluation reports. 

4) The output and result indicator targets have in many cases proven not to be realistic. This 
can be explained by the lack of experience of the Managing Authorities in setting targets. As 
a  result,  targets  were  often  adjusted  during  programme  implementation  and  were  therefore 
not considered reliable to provide benchmarking. While adjustments throughout a life-cycle 
of a programme can reflect changes made to the programme, the adjusted targets were often 
drastically  reduced  and,  when  compared  to  the  final  outputs,  not  always  substantiated. 
Without  being able to  use  the targets,  it was often difficult  to  assess the extent of the  rural 
development  programmes’ achievements. Where  possible, result and output  indicators were 
compared  to  the  context  indicators,  and  triangulation  between  the  qualitative  and  limited 
quantitative data was used, but such comparisons could solve the problem to only a limited 
extent. 

65 

 
 
 
ANNEX 2. STAKEHOLDER CONSULTATION 

Before contracting the support study, the Commission offered stakeholders the possibility to 
give feedback on the evaluation roadmap during the four week period from 20 June 2017 and 
18  July  2017.  Only  two  feedbacks  were  received,  both  related  to  rural  development  and 
agricultural policy in general and hence not requiring changes to the evaluation design. 

In  the  framework  of  the  2007-2013  ex  post  evaluation  report  of  each  rural  development 
programmer,  there  were  already  extensive  consultations  targeting  the  following  main 
stakeholders:  public  authorities  responsible  for  implementation  of  the  rural  development 
programmes including paying agencies and bodies delivering farm advisory services; farmers 
and  farmers'  organisations;  academia  and  experts  as  well  as  NGOs  and  other  civil  society 
organisations active in the field of rural development. The aim of those consultations, which 
took  the  form  of  surveys  and  interviews,  was  to  seek  information  and  feedback  from  the 
relevant  stakeholders  and  wider  public  in  relation  to  practical  experience  with  the 
implementation and the effects of each individual rural development programmer. 

Also the European Economic and Social Committee (EESC) produced an information report89 
assessing three rural development programmer axes (Competitiveness; Environment and land 
management;  Quality  of  life  in  rural  areas  and  diversification  of  the  rural  economy), 
collecting data through: 1) online questionnaire to civil society organisations; 2) fact-finding 
missions  (and  analysis  of  case-studies)  from  Finland,  Poland,  (Andalucía)  and  Italy.  Both 
questionnaire and fact-finding missions took place in the period April-May 2017. 

In  order  not  to  duplicate  work  already  carried  out  at  Member  State  level,  consultation 
activities  consisted  of  the  open-based  public  consultation  and  the  cooperation  with  the 
(EESC). 

For this  public consultation,  citizens were asked  to  give their opinion about  policy that has 
undergone  some  changes  during  the  2013-2018  period.  Rural  development  remains  an 
ongoing process that is subject to innovation and policy change. Although it can be expected 
that a large part of the respondents have filled in the survey in the light of the post 2020 CAP 
reform, the results still give a good insight in the perception of the 2007-2013 policy among 
citizens and it can form a valuable input into the discussion on the CAP reform. 

The internet based public consultation was held in all official EU languages from 22 January 
until the 23 April 2018. The survey results were analysed using the standard spreadsheet tools 
for the numerical and replies, and using the Commission’s DORIS tool for textual entries. A 
check for campaigns did not identify significant issues, as there were only three respondents 
with very similar replies. 

All citizens and organisations were welcome to contribute to this consultation. In particular, 
contributions  from  the  following  rural  development  programmes  beneficiaries  were  sought 
for: 

  Farmers; 
  Processors; 
  Retailers; 

89  See footnote 14. 

66 

 
                                                 
Individual citizens of rural areas; 

  Wholesalers; 
 
  National public authorities; 
  Regional public authorities; 
  Business organisations (including associations, chambers of commerce, etc.); 
  Non-governmental and civil society organisations; 
  Other public institutions. 

At the time of the deadline, 720 replies were received, covering responses from all but two 
Member States (Malta,  Cyprus). Of the respondents,  56% identified themselves as  citizens, 
44% as professionals or organisations. 

Figure 15. Number of respondents per Member State  

120

100

80

60

40

20

0

Source: Evaluation support study 
Note: No responses from Cyprus nor Malta 

In  addition  to  the  responses  to  the  survey  questions,  144  respondents  gave  additional 
comments  on the  rural  development  programme  2007-2013 and 26 unique documents  were 
uploaded. Two documents were received outside the formal consultation context. 

The  format  of  the  questionnaire  followed  the  better  regulation  criteria:  effectiveness, 
efficiency, relevance, coherence and EU added value. Most of the criteria were dealt with in 
closed  questions,  only  for  EU  added  value  an  open  question  was  used.  Besides  the  better 
regulation  criteria,  the  questions  focussed  on  the  main  goals  of  the  rural  development 
programmes. The following topics were addressed: 

Increasing the competitiveness of agriculture and forestry; 
Improving the environment, countryside and quality of life in rural areas; 

 
 
  Encouraging diversification of the local economy and the local capacity to diversify; 
  Building the local capacity for employment. 

67 

 
 
In general, a majority of the respondents gave a positive answer to the questions. No striking 
differences  were  found  between  the  different  stakeholder  groups  and  between  the 
beneficiaries of the different axis. However, some farmers are less positive about the impact 
and  relevance  of  the  rural  development  programmes.  When  assessing  the  results  per 
stakeholder group in this report, the nuances between the groups are mentioned. Overall, the 
effectiveness,  efficiency,  relevance  and  coherence  of  the  policy  was  overall  considered 
positively. Stakeholders that are related to the agricultural sector and those who are involved 
in  environmental  conservation  and  restoration  appeared  to  be  the  least  positive  about  the 
impact  of  the  rural  development  programmers.  Groups  that  work  on  social  cohesion  are 
generally more positive about the effects of the rural development programmer. Furthermore, 
respondents  (without  any  major  difference  by  stakeholder  group)  concluded  that  the  rural 
development programmes have added value and are able to address the economic, social and 
environmental needs of rural areas. Among citizens is thought that EU funding is better able 
independent  funding.  Lastly,  bureaucracy  and 
to  provide, 
administrative  burden  are  seen  as  the  main  barriers  in  the  application  process  and  it  could 
lead  to  a  decrease  in  the  uptake.  Many  respondents  asked  for  simplification  of  the  future 
policy design and administration. 

long-term  focussed  and 

Individual  respondents  represented  56%  (403  respondents)  of  the  total  sample.  More  than 
half  of  the  respondents  are  farmer  or  other  supply  chain  actors  (processors,  retailers, 
wholesalers). Citizens of rural areas present one third of this group of respondents. Only 36% 
of the individual respondents are beneficiaries under the rural development programmes. Of 
this  36%  most  of  the  beneficiaries  are  farmers.  Farmers  are  mostly  beneficiaries  of  Axis  1 
(competitiveness  of  agriculture  and  forestry)  or  multiple  funding  sources,  whereas  rural 
citizens  are  recipients  under  Axis  3  (economic  diversification  and  quality  of  life)  and 
LEADER.  Most  of  the  group  of  other  individual  respondents  indicated  that  they  were 
receiving funding under LEADER and Axis 2 (environment and land management). Claims 
that will be made later on in this report could be influenced by the uneven division between 
stakeholder groups. 

Table 14. Distribution of individual respondents groups’ 

Category 

Included survey answers 

Respondents 

% of total 

Rural citizen 

Individual citizen rural area 

Farmers and supply chain 
actors  

Farmer 

Processor 

Retailer 

Wholesaler 
Total 

Other 

None of the above 

Total individuals 

* Numbers do not add up, because of some of these respondents are also a fulfilling multiple roles 
Source: Own elaboration on the basis of the public consultation 

131 

203* 

9* 

2* 

0 
208 

64 

403 

33% 

51% 

16% 

100% 

68 

 
 
In total, 317 responses were received from professionals and organisations, which represents 
44% of the total sample. Nearly half of this group were civil society organisations. One third 
of  the  respondents  were  from  the  private  sector.  Almost  two  third  of  the  professionals  and 
organisations  that  responded  to  the  survey  are  beneficiaries,  of  which  almost  half  of  it  is  a 
civil society organisation. The source of the funding that is received by the professionals and 
organisations  is  more  distinctive  than  in  the  case  of  the  individuals.  Public  sector 
organisations such as local and regional governments often receive more funding under more 
than one axis. Almost half of the private sector companies receive funding under axis 1 and 
LEADER is the main source of funding for civil society organisations (77%). 

Table 15. Distribution of professional and organisation respondents groups’ 

Category 

Survey categories 

respondents  % of total 

Private sector 

Private enterprise 

Professional consultancy, law firm, self-employed consultant 

Trade, business or professional association 

Farm or farmers association 

Total 

9 

15 

11 

51 

86 

3% 

5% 

3% 

16% 

27% 

Category 

Survey categories 

respondents 

% of total 

Public sector 

International or national public authority  

-  National government 
-  National public authority or agency 
Regional or local authority (public or mixed) 

-  Local public authority 
-  Regional public authority 
-  Network of public sub-national authorities 
-  Public private sub-national organisation 

Total 

Civil society 

Non-governmental organisation, platform or network 

-  Local Action Groups 
-  Environmental organisations 
-  Other 
Research and academia 

Churches and religious communities 

Total 

Total organisations 

Source: Own elaboration on the basis of the public consultation 

69 

5 

3 

2 

100 

59 

37 

3 

1 

105 

116 

86 

11  

19 

9 

1 

126 

317 

2% 

1% 

1% 

32% 

19% 

12% 

1% 

0% 

33% 

37% 

27% 

3% 

6% 

3% 

0% 

40% 

100% 

 
 
 
 
 
 
 
 
Individual  respondents:  since  the  survey  allowed  respondents  to  identify  themselves  as 
belonging to more than one category, farmers often also identified themselves as ‘individual 
citizens  of  a  rural  area’.  Because  this  is  a  regular  combination,  the  choice  was  made  to 
include these cases only in the ‘farmer’ category. Other doublings with ‘individual citizens of 
a rural area’ were grouped in the category ‘individual citizens of a rural area’. 

The general trends that can be observed in the answers are: 

  Professional respondents and organisations respond more positively than individuals. 
  Beneficiaries of rural development programme funding respond more positively than 

 

non-beneficiaries. 
Individual farmers and the group of professional farmers and farmers associations are 
more negative about the impact and relevance of rural development programme. They 
also indicate more often that they have observed no effect of the policy measures. 
  Beneficiaries  of  Axis  2  funding  are  the  least  positive  about  the  contributions  of  the 

rural development programme. 

Competitiveness of agriculture and forestry 

In  general,  more than 70% of the respondents  within the different  stakeholder groups think 
that  rural  development  programmes  have  improved  the  competitiveness  of  agriculture. 
Comparing the different beneficiary groups, Axis 2 beneficiaries were the least positive: 17% 
of  this  group  indicated  that  they  thought  rural  development  programme  had  a  negative 
contribution. 

On the  rural  development  programme’s contributions to  the competitiveness  of the forestry 
sector, 29% of the respondents answered with ‘no opinion’. Another 20% perceived no effect 
of the measures. It might be more difficult to answer this question because the growth cycle 
of forest is a long-term process. 

Improving of the environment, countryside and quality of life 

Of the 11 environmental organisations that participated in the consultation, 30% thought rural 
development  programme’s  contributed  negatively  to  the  environment.  This  was  the  only 
question  in  which  individual  farmer  were  more  positive  about  the  rural  development 
programme’s  contributions  than  other  individual  citizens.  It  was  also  interesting  to  see  that 
18%  of  the  Axis  2  beneficiaries  gave  a  negative  response,  which  is  almost  double  the 
percentage of the other beneficiaries. 

For Axis 2 beneficiaries, similar results were found in the responses to the questions on the 
RPD’s  contribution  to  improving  the  countryside:  22%  answered  negatively.  Public  sector 
and civil society were very positive about the impact on the countryside, approximately 90% 
of  these  organisations  were  positive.  The  broad  interpretation  possibilities  of  the  question 
could have led to differences in the results per stakeholder groups. 

Considering  the  impact  on  quality  of  life,  farmers  are  the  least  positive  about  the 
achievements  under  the  rural  development  programme  s:  of  the  professional  farmers,  22% 
thinks  there  is  no  effect  and  10%  think  rural  development  programme  has  had  a  negative 
impact on their quality of life. Similar trends were seen for individual citizens in rural areas 
(15% and 10% respectively). 

70 

 
Diversification 

Two questions were related to diversification. One focussed on the contribution of the rural 
development  programme  to  encouraging  diversification  and  the  other  on  building  local 
capacity for diversification. Considering the first topic, beneficiaries of Axis 3 funding were 
the  most  positive,  together  with  the  civil  society  organisations  (>  80%).  Axis  1  and  2 
beneficiaries  most  often  saw  no  effect  of  the  measures.  Local  capacity  for  diversification 
received slightly different answers. More respondents saw no effect or perceived a negative 
contribution. Private sector organisations and individual farmers were the least positive about 
the impact. 

Employment and Quality of life 

Although  the  overall  perception  of  the  impact  of  the  rural  development  programme  of  the 
local capacity to create employment was positive, still 21% of respondents thought that the 
programmes  have  had  no  effect.  The  stakeholder  groups  can  be  found  in  this  group  of 
respondents  were  individual  respondents  in  general  and  actors  form  the  private  sector.  The 
private sector gave far more negative responses that the other professionals and organisation, 
9% compared to 2%. 

Only 10% of the respondents indicated that the rural development programme did not provide 
value for money. The largest group of negative respondents were found in individual farmers 
(18%), private sector companies (14%), Axis 1 beneficiaries (16%) and Axis 2 beneficiaries 
(14%). 

The  rural  development  programme  2007-2013  was  thought  to  be  consistent  with  other  EU 
funded  interventions  in  the  respondents’  areas.  The  private  sector  was  the  least  positive 
stakeholder group: 19% of this respondent group thought the rural development programme 
were not consistent. 

Similar  results  were  found  in  the  question  on  whether  rural  development  programme  fitted 
the  needs  of  the  area.  22%  of  the  private  sector  companies  responded  that  the  programmes 
did not fit the needs. This was also the case for the individual farmers (21%). Considering the 
beneficiaries, Axis 1 and 2 beneficiaries were the most negative, 17% and 22% respectively. 

Analysis of the open questions  

Respondents  were  given  the  chance  to  share  their  personal  views  on  the rural  development 
programmes  2007-2013.  The  survey  contained  four  open  questions  and  a  field  in  which 
respondents could add further comments of any kind. A majority of the respondents filled in 
the  open  questions  and  144  respondents  filled  in  the  field  for  further  comments.  These 
comments were often an enforcement of statements that were given elsewhere in the survey. 
Others  included  specific  local  situations  or  problems  with  the  implementation  of  the  rural 
development programmes in specific Member States or regions. 

Respondents  were  asked  what  the  most  essential  benefits  of  EU  financing  were  for  rural 
development programmes that would not have been achieved by the Member States/regions 
acting on their own. A wide range of answers were given. In general, respondents are positive 
about  the  EU  added  value.  Only  a  few  respondents  do  not  see  the  benefits  of  EU  funding 
instead of Member State action, or have a feeling that the EU funding leads to a distortion of 
competition. A few times unfair practices with EU funding was mentioned. 

71 

 
In general, EU funding is considered a stable funding source, which also led to an increase in 
national  funding  through  the  co-financing  principle.  EU  funding  can  also  have  a  spillover 
effect and attract other developments in rural areas. Respondents indicated that it is important 
to them that EU funding is not influenced by local political dynamics and that there is more 
equality  between  the  beneficiaries.  Furthermore,  the  variety  between  projects  that  could  be 
subsidised with EU funding was perceived higher than national funding. 

The answers of the respondents that do think there is EU added value can be broadly split up 
in four categories: agriculture, environment, rural development, and local empowerment. 

According  to  respondents,  EU  funding  has  stimulated  modernisation  and  innovation  in 
agriculture.  Many  respondents  think  that  the  member  states  on  their  own  would  not  have 
made  available  (enough)  funding  to  help  farmers  to  invest  in  their  companies.  EU  funding 
has stimulated agricultural sectors that otherwise would have had more difficulty to be self-
sustaining, such as organic agriculture and agro-forestry. 

Many respondents think that the EU funding has led to a better protection of the environment. 
There  is  a  belief  that  national/regional  government  bodies  would  not  have  had  the  same 
priorities when acting on their own. Considering environment, climate action and biodiversity 
the respondents value the EU intervention and see the need to set more overarching goals. 

Considering  rural  development,  respondents  see  the  EU  funding  as  stimulance  for 
beneficiaries and farmers to invest in their local areas, which would otherwise have been too 
costly.  Some  respondent’s  belief  that  member  states  would  focus  their  subsidies  and 
investment too much on urban areas and economic development, whereas rural development 
programme  is  creating  a  more  territorially  balanced  intervention.  Investment  in  vital 
infrastructure was mentioned several times as something that would have gotten less funding 
through national investment programs. 

Finally,  many  respondents  see  EU  funding  as  a  stimulator  for  local  integration  and 
partnerships. The bottom-up approach that is incorporated in LEADER, is useful to address 
specific  needs  of  local  areas.  Many  respondents  appreciate  this.  The  rural  development 
programmes are perceived as solidarity measure within the EU as a whole and between the 
member  states.  Furthermore,  respondents  indicated  that  the  funding  stimulates  cross-border 
cooperation and exchange of best practices. 

Improving living conditions 

Respondents  were  asked  if  they  have  suggestions  on  how  future  rural  development 
programmes  could  further  improve  living  conditions  in  rural  areas.  Again  this  had  led  to  a 
broad variety in answers. Some of the topics that were often mentioned were: simplification 
and  less  administrative  burden;  focus  on  better  connecting  the  rural  areas  with  urban  areas 
(both  hard  infrastructure  as  well  as  broadband);  increasing  the  usage  of  the  bottom-up 
approach; more focus on small and medium enterprises and farms; stimulating environmental 
conservation and restoration. 

Simplification 

Respondents were asked about their opinion on what could be simplified in order to improve 
the management and implementation of rural development programmes. The general trend in 
the  answers  includes  a  demand  for  simplification  of  the  application  procedure  and  the 

72 

 
administration.  Red  tape  seems  to  be  a  general  point  of  frustration.  Other  things  that 
respondents  regularly  mention  are  a  need  for  more  transparency  of  the  application  process 
and more information about the funds that are available to apply for. 

Future application 

On  the  question  whether  and  why  respondents  would  apply  for  future  funds  or  not,  most 
respondents indicate that they will. Many respondents mention that it is important for them 
that rural development will remain to be supported. The EAFRD is an important factor in the 
development  of  in  rural  areas.  One  of  the  barriers  that  is  often  pointed  out  is  again  the 
bureaucracy. 

Uploaded documents 

As stated above, 33 respondents have uploaded additional documents to the survey answers. 
Two documents were received outside the formal context of the survey, but by email. In total, 
28 unique documents were received. A large number of documents address the future of the 
CAP post 2020 or focus on the period 2014-2020. Most likely this is due to the dominance of 
the  topic  in  the  CAP  debate.  As  a  result,  these  documents  fall  outside  the  scope  of  the 
evaluation study and are not included in the analysis of this report. 

A few documents dealt with general topics related to agriculture and rural development. For 
example, two respondents uploaded a position paper on the lack of communication about the 
positive  impact  of  agriculture  on  rural  development  concerning  for  example  the  ecosystem 
services delivered by agricultural landscapes. 

Three documents  did  focus on the 2007-2013 period. The respondents  gave information  on 
specific issues with the implementation of rural development programmes and the impact in 
their  own  member  state.  For  example,  an  evaluation  report  on  the  environmental  impact  of 
the  rural  development  programme  in  Ireland,  or  the  impact  of  the  rural  development 
programme on mountain farming in Austria. This is valuable information, but too specific to 
be incorporated in the general evaluation of the rural development programmes. 

73 

 
 
 
ANNEX  3.  DATA  ON  IMPLEMENTATION  OF  RURAL  DEVELOPMENT  PROGRAMMES  BY 
MEASURE 

Axis 1 - Competitiveness 

Measure 111: Vocational training and information actions 

to 

improve 

In  order 
total  budget  of 
EUR 840.5 million has been spent on M111 by 26 Member States across 75 regions. This has 
resulted in: 

the  competitiveness  of  the  beneficiaries,  a 

  An output of 6 378 034 participants in training and 6 826 136 training days received. 
With more than 6 million participants in training, the measure reaches 28.7% of active 
farm workers in the EU as a whole. 

  Result indicators for this measure are the number of participants passing by achieving 
certificate,  degree  or  diploma  and  the  number  of  participants  implementing  the 
achieved  skills.  In  total  1 862 342  participants  passed  trainings  by  achieving  a 
certificate,  degree  or  diploma  (on  average  80 972  per  Member  State).  Out  of  the 
participants,  1 987 552  implemented  the  achieved  skills  (on  average  132 503  per 
Member State). 

55%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 14% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  were  limited  and  8%  of  the  evaluation  reports 
concluded  the  measure  did  not  contribute.  The  increase  in  competitiveness  was  mainly 
attributed  to  an  increase  in  the  education  level  of  farmers,  which  resulted  in  a  better 
performance  of  their  farms,  including  in  terms  of  environmental  management.  The 
information  judging  the  contribution  of  the  measure  is  based  on  75  reports  of  which  58 
reported on the contribution of the measure. 

Of  those  reports  that  provided  a  conclusion  on  M111,  71%  stated  a  positive  contribution. 
Based  on  these  evaluations,  it  is  concluded  that  the  measure  contributed  to  an  improved 
competitiveness to a medium extent. 

Measure 112: Setting up of young farmers 

The majority (66%) of the programme level ex post reports identified a positive contribution 
to improving the competitiveness of beneficiaries, and that of the sector as a whole, because 
young  farmers are more inclined to  introduce new methods and techniques.  In more than a 
third of these cases, the measure is also considered to have facilitated structural adjustment of 
farm holdings, and a number also reported positive environmental benefits. However, some 
reports  identified  significant  deadweight.  Overall  M112  is  considered  as  one  of  the  most 
effective means of increasing competitiveness. 

Good  practice  identified:  In  ES  Basque  Country,  the  combination  of  training  under  M111  and  installation 
support under M112 increased competitiveness on the holdings concerned. 

to 

improve 

In  order 
total  budget  of 
EUR 3 271 million has been spent on M112 by 24 Member States across 69 regions. This has 
resulted in: 

the  competitiveness  of  the  beneficiaries,  a 

74 

 
An  output  of  192 003  assisted  young  farmers  and  a  total  volume  of  investment  of 
EUR 17.4 million. The assisted young farmers amount to 29.8% of the farmers in the EU in 
that age category. The total volume of investment is limited to around 0.1% of the total GVA. 

The  result  indicator  for  this  measure  is  the  increase  in  total  GVA  in  supported 
holdings/enterprises. A total increase of EUR 6.1 billion was reported. 

Compared to the other measures, this measure is one of the most successful in increasing the 
GVA of the supported holdings/enterprises. 

66%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 10% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  were  limited  and  9%  of  the  evaluation  reports 
concluded the measure did not contribute. The increase in competitiveness resulting from this 
measure  was  mainly  attributed  to  the  modernisation  process  that  was  started  when  young 
farmers took over businesses. The above information is based on 59 reports. 

Of  those  reports  that  provided  a  conclusion  on  M112,  78%  stated  a  positive  contribution. 
Based  on  these  evaluations,  it  is  concluded  that  the  measure  contributed  to  an  improved 
competitiveness to a great extent. 

As  far  as  other,  indirect  effects  are  concerned,  positive  effects  on  the  environment  are  the 
most  prominent  (28%).  This  is  because  young  farmers  have  more  knowledge  on 
environmentally  friendly  practices.  Young  farmers  applied  more  environmentally  friendly 
practices  than  older  farmers.  This  resulted  in  an  improvement  in  natural  environmental 
conditions. Also effects on increase in available jobs and on reduction in population decrease 
were noted. 

Measure 113: Early retirement of farmers and farm workers 

Less  than  a  third  of  the  ex  post  evaluation  reports  found  that  the  measure  made  a  positive 
contribution  to  competitiveness.  A  similar  proportion  reported  other  benefits  such  as 
improved land management and/or reduction of land abandonment. Reasons why the measure 
was not considered more successful include low levels of funding and uptake. Compared to 
other  measures,  support  for  early  retirement  is  considered  to  have  made  only  a  marginal 
contribution to increasing GVA on the supported holdings. 

A total budget of EUR 2.7 billion has been spent on M 113 by 16 Member States across 51 
regions. 

31%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 19% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  were  limited  and  21%  of  the  evaluation  reports 
concluded the measure did not contribute. By facilitating early retirement of farmers, farms 
and farmland becomes available for younger farmers. Hence, these were able to improve their 
competitiveness  by  profiting  from  economies  of  scale  through  the  expansion  of  their 
company,  and  by  improving  old  farms  through  the  introduction  of  modern  farming 
techniques. The information is based on 51 reports of which 40 reported on the contribution 
of the measure. 

Of  other  effects  observed,  mainly  improvement  in  land  management  (33%)  was  the  most 
important. 

75 

 
Measure 114: Use of advisory services by farmers and forest holders 

The majority of advisory services provided focussed on compliance with EU standards rather 
than  competitiveness.  Implementation  was  relatively  low,  reaching  less  than  2%  of  EU 
farmers,  and  0.4%  of  forest  holders.    This  is  perceived  to  be  due  to  lack  of  interest  in  the 
services  on  offer,  in  part  because  of  insufficient  focus  on  competitiveness.  However, 
environmental improvements were identified in one third of evaluations. 

M114 aimed to increase the beneficiaries’ competitiveness by supplying support to providing 
advisory services that directly improved operational as well as agricultural practices. A total 
of EUR 133 million was spent by 20 Member States in 55 regions. The overall results were: 

178 498 farmers,  representing  2%  of  the  EU  total  of  farmers  in  2013  received  advisory 
services under this measure. Additionally, 2 406 forest holders, representing 0.4% of the EU 
total of forest holders in 2013 received advisory services. 

A total GVA increase of EUR 642 million was reported. Compared to the other measures and 
based  on  this  indicator  M114  measure  was  only  moderately  successful  in  creating  value 
added. 41% of the evaluations that provided a conclusion on this measure found that it had a 
positive contribution to competitiveness. 

Only  37%  of  the  evaluations  identified  other  effects,  where  they  were  identified  they  were 
mainly environmental. 

Measure 115: Setting up of farm management, farm relief and farm advisory services, 
as well as of forestry advisory services 

M115  was  implemented  in  7  Members  States  and  27  regions  with  total  budget  of 
EUR 31.7 million in total. The measure concerned setting up advisory services to assess farm 
performance  and  identify  possible  improvements  to  increase  competitiveness.  It  was 
generally  considered  to  make  a  positive  contribution  to  increasing  the  beneficiaries’ 
competitiveness, particularly for small and medium sized farms that did not previously have 
access to this type of expert support. In some cases too great a focus on compliance issues, 
rather  than  competitiveness,  limited  the  attractiveness  of  the  measure  to  potential 
beneficiaries.  Complicated  administrative  procedures  were  seen  as  the  main  constraint  to  a 
more effective implementation. 

For  41%  of  the  evaluation  reports,  this  measure  had  a  positive  contribution  to 
competitiveness  of  the  beneficiaries.  This  positive  effect  was  attributed  to  a  more  efficient 
and sustainable use of resources in 10% of the cases, since the advisory service offered the 
farmers a system to assess farm performance and pinpoint possible improvements to increase 
competitiveness. 60% of the positive reports found that M115 helped farmers improve both 
their  techniques  and  management,  which  ultimately  led  to  a  better  market  position.  In 
addition,  10%  of  the  positive  reports  mentioned  that  the  measure  helped  to  commercialize 
ecological products. 

30%  of  the  ex  post  evaluation  reports  mentioned  a  limited  contribution  to  competitiveness 
under  M115.  This  was  attributed  primarily  to  administrative  issues  in  the  implementation, 
which  was  halted  by  complicated  procedures  and  paused  operation.  In  some  cases,  the 
offered services were not considered to be oriented towards to farmer’s interests, which had a 
demotivating effect on the applicants. 

76 

 
22%  of  the  rural  development  programmes  reported  no  contribution  to  competitiveness.  In 
these cases, 66% reports explained that the measure’s focus on the promotion of compliance 
to  statutory  requirement  meant  there  were  no  competitiveness  impacts.  For  33%  of  the 
reports,  the  measure  was  not  fully  executed,  which  also  prevented  any  impacts  from 
materializing. 

Based  on  these  evaluations,  it  is  assessed  that  the  measure  contributed  to  an  improved 
competitiveness only to a limited extent. 

Measure 121: Modernisation of agricultural holdings 

This  measure  was  implemented  in  all  rural  development  programmes  (88),  and  provided 
11.7 billion EUR of  public  support,  reaching  4.3%  of  farm  holdings  across  the  EU.  It  was 
found  to  have  increased  competitiveness,  production  and  labour  efficiency,  and  to  have 
introduced  new  methods  and  products.  Where  environmental  effects  were  reported,  the 
impact was considered positive in 86% of cases and negative in only 8%. 

467 324 farm holdings  were  supported.  166 749 holdings introduced new techniques  and/or 
products.  A  total  increase  in  the  gross  value  added  in  the  supported  holdings  of 
EUR 19.3 billion was observed. Compared to the other measures, this measure is one of the 
most successful in supporting the introduction of new products and/or new techniques and in 
increasing the GVA of the supported holdings/enterprises. 

71%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 10% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  were  limited  and  5%  of  the  evaluation  reports 
concluded the measure did not contribute. The increase in competitiveness resulting from this 
measure was mainly attributed to its focus on modernisation. 

When  studying  other  effects,  effects  on  the  environment  were  referred  to  in  27%  of  the  ex 
post evaluations. These effects relate to emissions, energy and the reduction of soil erosion. 

Measure 122: Improvement of the economic value of forests 

Although  the  total  support  granted  through  this  measure  was  small,  it  was  found  to  have  a 
positive impact in the majority of cases where it was implemented, generating a considerable 
increase  in  the  GVA  of  the  forestry  sector  (almost  three  times  the  investment  provided). 
Environmental  improvements  and  contributions  to  climate  change  mitigation  were  also 
identified,  as  were  positive  contributions  to  diversifying  the  rural  economy,  and  improving 
the conditions of forestry workers (increased safety and reduced working hours). 

M122 had a level of expenditure of EUR 309 million dedicated to improving competitiveness 
through  the  improvement  of  the  economic  value  of  forests.  This  budget  was  spent  by  17 
Member  States  in  49  regions.  26 322 holdings  received  investments  support  under  this 
measure, totalling an investment of 936 million. 7 573 holdings introduced new products and 
techniques.  It  generated  an  increase  in  GVA  of 2 754  million,  making  it  one  of  the  more 
successful  measures  in  generating  value  added  and  representing  11%  of  the  total  GVA  for 
forestry for the time period. 

43%  of  the  reports  found  that  the  measure  had  a  positive  contribution  to  competitiveness, 
27% found that the contribution was limited, and 12% found that there was no contribution. 
Of  those  reports  that  provided  a  conclusion  on  M122,  53%  stated  a  positive  contribution 

77 

 
hence it can be concluded that that the measure contributed to an improved competitiveness 
to a medium extent. 

25%  of  the  evaluations  also  mentioned  additional  effects,  mainly  contribution  to  the 
sustainable management of forestry. 

Measure 123: Adding value to agricultural and forestry products 

This  measure,  which  was  widely  implemented  (85  rural  development  programmes  in  25 
Member States) was considered to improve the competitiveness of the industry beneficiaries 
in two thirds of reports, making a limited contribution in a further 20%. It improved product 
quality, introduced new processes and reduced costs. 19% of the reported increase in GVA of 
the sector over the period could be attributed to support through this measure. Positive effects 
on the environment (better resource management, more environmentally friendly processes) 
and employment were also found in some cases. 

M123 had a total level of expenditure of EUR 4 413 million dedicated to adding value to the 
agricultural  and  forestry  products).  28 265 enterprises  were  supported;  The  total  volume  of 
investment  under  M123  is  EUR 22 billion,  increase  in  GVA  in  supported  enterprises  under 
M123 is EUR 30 billion, representing 19% of total GVA increase for  the sector in the time 
period; 14 484 holdings with new products and / or techniques introduced under M123 were 
registered. 

66%  of  the  evaluation  reports  found  that  the  measure  had  a  positive  contribution  to 
competitiveness, 20% found that the contribution was limited, and 1% found that there was 
no contribution. 

Of  those  reports  that  provided  a  conclusion  on  M123,  76%  stated  a  positive  contribution. 
Based on these evaluations, it can be concluded that the measure contributed to an improved 
competitiveness to a great extent. 

Additional effects mentioned in the evaluation reports were mainly maintenance/creation of 
jobs. 

Measure 124: Cooperation for development of new products, processes and technologies 
in the agriculture and food sector and in the forestry sector 

The  most  widely  reported  effects  of  this  measure  were  increased  levels  of  innovation  and 
more  productive  value  chains.  Although  accounting  for  a  very  small  proportion  of 
expenditure, it accounted for 6% of reported introductions of new techniques and products. In 
many  cases  it  was  considered  that  the  contribution  to  competitiveness  will  only  become 
significant in the medium to long term. 

The  level  of  expenditure  under  M124  was  of  a  total  of  EUR 234.3 million  spent  on  the 
cooperation for development of new products, processes and technologies. This amount was 
spent by 14 Member States in 51 regions. The overall results were as follows: 

A total of 5112 cooperation initiatives were supported as a result of M124. 

The  number  of  enterprises  introducing  new  techniques  and  /  or  products  under  M124  was 
12 972. The measure contributed 6% of the holdings with new techniques and products under 
the entire rural development programmes. 

78 

 
The  result  indicator  of  increase  in  GVA  in  supported  enterprises  under  M124  is 
EUR 122.6 million. 

33%  of  the  reports  found  that  the  measure  had  a  positive  contribution  to  competitiveness, 
26% found that the contribution was limited, and 11% found that there was no contribution. 
Of  those  reports  that  provided  a  conclusion  on  M124,  47%  stated  a  positive  contribution. 
Based on these evaluations, it can be concluded that the measure contributed only to a limited 
extent to an improved competitiveness. 

Most  quoted  other  effects  were  mainly  environmental;  the  fostered  cooperation  resulted  in 
knowledge transfer on more sustainable practices. 

Measure 125: Improving and developing infrastructure related to the development and 
adaptation of agriculture and forestry. 

Investments  supported  through  this  measure  were  found  to  have  a  positive  effect  on 
competitiveness in the majority of cases, particularly through reducing transport costs along 
the  value  chain  (improved  roads)  and  reducing  input  costs  (irrigation  infrastructure).  The 
therefore 
investments 
environment/climate benefits. Improved accessibility also improved the quality of life of rural 
residents and increased tourism activity. 

to  reduced  water  consumption  and 

irrigation  also 

lead 

in 

improving  and  developing 
EUR 4 317 million  was  devoted  under 
infrastructure  related  to  the  development  and  adaptation  of  agriculture  and  forestry.  This 
budget was spent by 24 Member States in 78 regions. 

this  measure 

to 

In the output indicator of total volume of investment, M125 received EUR 10 billion; 

The output indicator of number of operations supported under M125 reached a total of 56 779 
operations;  For  the  result  indicator  of  increase  in  GVA  in  supported  holdings,  M125 
generated a value added of EUR 7 billion, making it one of the most successful measures in 
generating value added. 

59%  of  the  reports  found  that  the  measure  had  a  positive  contribution  to  competitiveness, 
18% found that the contribution was limited, and 6% found that there was no contribution. 
Where  there  was  a  limited  contribution,  this  was  often  due  to  the  objective  of  the 
infrastructure,  which  was  not  necessarily  improving  competitiveness,  but  bringing  basic 
infrastructure to regions that lacked it. 

The  information  is  based  on  the  59  ex  post  evaluation  reports  that  reported  on  the 
contribution of the measure, out of the total of 71 reports. 

Of  those  reports  that  provided  a  conclusion  on  M125,  71%  stated  a  positive  contribution. 
Based  on  these  evaluations,  it  can  be  concluded  that  the  measure  contributed  to 
competitiveness to a medium extent. 

As  additional  effects,  a  positive  environmental  effect  was  mentioned  as  a  result  of  new 
irrigation techniques allowing for a better use of water resources and reducing overall water 
consumption. 

79 

 
Measure 126: Restoring agricultural production potential damaged by natural disasters 
and introducing appropriate prevention action 

This  measure  was  implemented  in  only  7  Member  States  (30  rural  development 
programmes), mostly to restore damaged production potential. Where it was used, the effect 
was  generally  considered  positive.  Prevention  measures  supported  (such  as  flood  defences) 
were considered positive not only for direct beneficiaries, but for industry, local communities 
and the environment. 

A total budget of EUR 648.5 million has been spent on M126 to support 2.9 million hectare 
of damaged agricultural  land. 42% of the ex post evaluation reports found that the measure 
contributed positively  to improving the  competitiveness  of the beneficiaries. 17% of the  ex 
post evaluations concluded the measure’s effects on competitiveness were limited and 38% of 
the  reports  concluded  the  measure  did  not  contribute.  In  67%  of  the  positive  cases  the 
increase  in  competitiveness  was  attributed  to  the  ability  to  restore  factors  of  production. 
Prevention of economic losses and technical improvement were also pointed at as results of 
the measure which have increased. 

Based  on  these  evaluations,  it  can  be  assumed  the  measure  contributed  to  an  improved 
competitiveness to a limited extent. 

Measure 131: Helping farmers to adapt to demanding standards based on Community 
legislation 

Both the coverage and expenditure for this measure were very low, concentrated in a small 
number of rural development programmes. Insufficient evidence was found to draw general 
conclusions  as  to  its  effects.  However,  some  specific  benefits  were  identified,  such  as 
reducing  the  cost  of  electronic  ear-markers  for  sheep  and  goats  in  Hungary,  which  helps 
farmers to comply with the relevant requirements. 

A total budget of EUR 62.1 million has been spent on M131 by 11 Member States across 20 
regions, supporting 29 644 beneficiaries. This is a marginal share (0.1%) of the total amount 
of active farmers within the EU; the total increase in GVA in supported holdings/enterprises 
was reported in only 1 of the Member States that implemented the measure; hence no general 
conclusion concerning the increase of GVA in supported holdings/enterprises can be drawn.  
24%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 24% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  were  limited  and  24%  of  the  evaluation  reports 
concluded the measure did not contribute. 

The  measure  helped  to  fulfil  legal  requirements  based  on  Community  legislation.  This  has 
increased  the  competitiveness  of  beneficiaries.  On  the  other  hand,  the  measure  is  seen  as 
compensation for extra cost, and thus does not increase the competitiveness of beneficiaries. 
Of  those  reports  that  provided  a  conclusion  on  M131,  33%  stated  a  positive  contribution. 
Based  on  these  evaluations,  the  measure  can  be  considered  to  contribute  to  an  improved 
competitiveness only to a limited extent. 

80 

 
Measure 132: Supporting farmers who participate in food quality schemes 

This  measure  was  implemented  by  15  Member  States  (47  rural  development  programmes), 
with  a  very  small  budget  share  (EUR 91.2 million).  A  positive  contribution 
to 
competitiveness and changing production methods was reported in over a third of the relevant 
evaluation  reports,  but  the  effect  was  limited.  A  similar  proportion  of  reports  identified 
environmental benefits, principally reductions in chemical use and emissions. 

578 983 farm  holdings  that  participated  in  a  food  quality  scheme  were  supported.  In 
comparison  with  the  total  number  of  holdings  with  livestock  in  the  EU,  around  8%  of  the 
total holdings has participated in food quality schemes; 37% of the ex post evaluation reports 
found  that  the  measure  contributed  positively  to  improving  the  competitiveness  of  the 
beneficiaries.  22%  of  the  ex  post  evaluations  concluded  the  measure’s  effects  on 
competitiveness  were limited and 20% of the evaluation  reports concluded the measure did 
not contribute. Results were limited due to low amounts of funding. One ex post evaluation 
also pointed to a 100% deadweight loss. 

Overall, it can be concluded that his measure contributed to an improved competitiveness to a 
limited extent. 

Measure 133: Supporting producer groups for information and promotion activities for 
products under food quality schemes 

Another  “small”  measure,  implemented  in  16  Member  States  across  41  regions  and 
accounting  for  less  than  1%  of  expenditure  in  all  cases  except  one.  A  total  budget  of 
EUR 128.4 million  has  been  spent  for  111 12  supported  actions.  Overall  the  measure  had 
some  positive  effects  in  promoting  awareness  of  quality-labelled  products,  but  effects  were 
small due to low budget and limited targeting. 

44%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 15% of the ex post evaluations concluded 
the  measure’s  effects  on  competitiveness  as  limited  and  15%  of  the  evaluation  reports 
concluded  that  the  measure  did  not  contribute.  Positive  contributions  were  attributed  to  an 
increase  in  awareness  of  local  produce,  which  boosted  the  competitiveness  of  the 
beneficiaries. Limited contributions have occurred due to various reasons like a low budget or 
a  low  implementation  rate.  Based  on  the  evaluations,  it  can  be  stated  that  the  measure 
contributed to an improved competitiveness to a limited extent only. 

Measure  141:  Supporting 
restructuring 

semi-subsistence  agricultural  holdings  undergoing 

This measure was implemented in 8 Member States where semi-subsistence farms constitute 
a  significant  proportion  of 
increased 
competitiveness,  higher  value  products,  and  social  benefits  were  reported  in  80%  of  the 
relevant evaluation reports. 

farm  holdings.  Positive  effects, 

including 

to 

improve 

In  order 
total  budget  of 
EUR 772 million has been spent on M141. This has resulted in 66 051 semi-subsistence farm 
holdings supported and 3 585 new farms entering the market. 

the  competitiveness  of  the  beneficiaries,  a 

81 

 
40%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the competitiveness of the beneficiaries. 40% of the ex post evaluations concluded 
the measure’s effects on competitiveness were limited and 20% of the evaluation reports did 
not  give  a  clear  conclusion.  Based  on  these  evaluations,  the  measure  is  considered  to 
contribute to an improved competitiveness to a medium extent. 

Measure 142: Supporting setting up of producer groups 

This measure, which was implemented in 11 Member States or regions with total budget of 
EUR 235 million, is considered one of the least effective, with no reports concluding that the 
measure  made  a  significant  positive  contribution  to  competitiveness.  A  limited  effect  was 
identified  in  44%  of  cases,  for  example  increased  sales  volumes,  and  improved  quality  of 
produce or better bargaining power. 

The aim of this  measure was to  improve the market  efficiency of the agricultural  sector by 
encouraging and supporting the setting up of Producer Groups.  The majority of evaluation 
reports (44%) found that the measure had only a limited contribution to the improvement of 
competitiveness, some pointed to a negative effect. 

Measure  143:  Provision  of  farm  advisory  and  extension  services  in  Bulgaria  and 
Romania 

This  measure  was  only  available  to  two  Member  States,  and  had  a  total  budget  of 
10 million EUR. Evaluation results were only available for Romania which found that it had 
only a limited contribution to economic growth and productivity, although it helped improve 
management capacity and knowledge of EU standards. 

Measure 144: Holdings undergoing restructuring due to a reform of a common market 
organisation 

This  measure  specifically  aimed  to  support  tobacco  farms  following  the  reform  of  the 
common  market  organisation  and  was  implemented  in  5  Member  States  (11  rural 
development programmes). It does not appear to have been effective, with a positive impact 
identified  in  only  one  report,  achieved  through  the  implementation  of  associated  business 
plans. 

The  total  level  of  expenditure  under  M144  was  of  EUR 180.8 million,  spent  on  supporting 
holdings undergoing restructuring due to a reform of a common market organisation. Half of 
the evaluation reports found there was no contribution to competitiveness, only one found a 
positive  contribution.  There  were  no  indirect  effects  noted.  Hence,  the  contribution  of  this 
measure to competitiveness has to be judged as extremely limited. 

AXIS 2 Environment and the countryside 

Measure 211: Natural handicap payments to farmers in mountain area  

M 211 was implemented in 15 Member States in a total of 60 regions, with a total budget of 
EUR 7 391.1 million. The main objective was to compensate farmers for the additional costs 
and income losses arising from the difficulties of agricultural production in mountain areas. 
The  aim  is  to  maintain  the  countryside  through  continual  use  of  agricultural  land  and  to 

82 

 
promote  the  systems  of  sustainable  agricultural  production,  thereby  supporting  the 
improvement of the environment. 

The measure resulted in 1 049 665 supported farm holdings and 16 052 054 hectares covered 
(one  Member  State  implementing  the  measure  did  not  report  the  output  indicators).  This 
amounts to 57.4% of the UAA in the less-favoured mountain areas of the Member States that 
have  offered  the  measure  and  to  56.7%  of  the  UAA  in  mountainous  areas  in  the  EU  as  a 
whole. 

Over two thirds of the reports stated that it made a positive contribution to the environment, 
principally  through  maintaining  extensive  agricultural  systems  in  areas  where  appropriate 
land management  is  important  for  biodiversity  and High Nature Value habitats.  It was also 
recognised as helping retain population and employment in fragile rural areas. 

Measure 212: Payments to farmers in areas with handicaps, other than mountain areas 

A positive contribution of M212 to the environment was reported in almost half the reports, 
mainly through avoidance of land abandonment. A further 25% indicated some contribution 
to  the  environment,  with  the  benefits  limited  due  to  lack  of  environmental  requirements 
associated with the payments. There was no obligation to  farm sustainably/extensively, and 
intensification and loss of permanent grassland was observed in some cases. 

In  order  to  compensate  farmers  for  difficulties  of  agricultural  production  in  less  favoured 
areas other than mountain areas, 27 Member States implemented M212, covering 75 regions 
and  spending  a  total  budget  of  EUR 7 681.4 million.  On  average,  Member  States  invested 
10% of their total EAFRD expenditure in M 212, with wide disparities. This has resulted in: 

An output of 1 843 831 supported farm holdings and 36 836 442 hectares covered (two of the 
27  Member  States  that  implemented  the  measure  did  not  report  on  the  Output  Indicators). 
With about 37 million hectares of arable land, the measure covers 59.2% of the UAA in the 
less-favoured  areas  other  than  mountain  areas  of  the  Member  States  that  have  offered  the 
measure. 

In 46% of the ex post evaluation reports the general contribution of M212 to improving the 
environment  was  assessed  as  positive,  25%  stated  a  limited  effect  and  6%  saw  no 
contribution.  The  positive  effects  on  the  environment  resulting  from  this  measure  were 
mainly attributed to its support to maintain agricultural cultivation on sites, which otherwise 
would be threatened by land abandonment and a possible degradation of natural values. Some 
reports stated that the measure has made a positive contribution to the promotion of extensive 
management practices, while others concluded that it was not expected to have a significant 
impact  on  promoting  extensive  farming.  However,  the  lack  of  specific  environmental 
protection requirements under M212 and M211 was a reason for limited ratings. Overall, it is 
considered that the measure contributed to the improvement of the environmental situation to 
a medium extent. 

Measure 213: Natura 2000 payments and payments linked to Directive 2000/60/EC 

This  measure  was  recognised  as  supporting  farmers’  incomes  in  the  13  Member  States  (28 
rural  development  programmes)  where  it  was  implemented,  by  compensating  them  for 
financial losses due to using farming practices beneficial for the designated habitats/species. 

83 

 
Whilst  the  management  practices  are  compulsory,  even  without  these  payments,  positive 
effects  on  biodiversity  were  reported  due  to  improved  understanding  and  acceptance  of 
Natura 2000 requirements and high coverage of target areas. 

In order to compensate farmers for disadvantages caused by Natura 2000 regulations or the 
Water  Framework  Directive  in  agricultural  areas,  13  Member  States  implemented  M213, 
covering 28 regions and spending a total budget of EUR 267.5 million. It has resulted in 75 
199 supported farm holdings. The measure covers 15.3% of the UAA in Natura 2000 areas of 
the Member States that have offered the measure. In 28% of the ex post evaluation reports the 
general contribution of M213 to improving the environment was assessed as positive, while 
31%  stated  a  limited  effect  and  17%  saw  no  contribution.  10%  of  the  evaluations  of  the 
measure indicated that the effect was not clear. 

The  assessments  have  described  in  several  cases  that  the  measure  itself  did  not  have  any 
impact and/or that the effects are exclusively due to the underlying mandatory provisions of 
the Natura 2000 network, i. e. are indirect in nature. It was stressed that the rules laid down in 
the respective EU directives must be complied with, even without any support under M213. 
However,  several  reports  concluded  that  the  measure  has  improved  the  knowledge  and 
understanding  of  farmers  and  beneficiaries  in  relation  to  the  regulatory  requirements  and 
hence  contributed  to  the  conservation  objectives  pursued  by  the  Natura  2000  network. 
Several  reports have highlighted the option of a  combination of Natura 2000 compensation 
with other measures such as M214 – in particular regarding the potential synergies in terms 
of environmental impact. 

Based on the evaluations, the measure is considered to have contributed to the improvement 
of the environmental situation to a limited extent. 

Measure 214: Agri-environment payments 

All  rural  development  programmes  had  to  include  this  measure,  and  it  accounted  for  the 
largest  proportion  of  expenditure.  Almost  90%  of  reports  giving  a  clear  judgement  on  this 
measure concluded that its implementation made a positive contribution to the environment, 
through both the extent of area covered by commitments and their effectiveness. Biodiversity 
and  High  Nature  Value  farming  were  identified  as  most  significantly  affected  (69%), 
improved soil quality in 66% and water quality in 61% of reports. This measure was judged 
as  having  made  the  largest  contribution  to  mitigating  climate  change,  through  reducing 
GHGs, sequestering carbon and reducing fire risks. A variety of indirect effects on quality of 
life,  retention  of  population  and  employment/diversification  opportunities  were  also 
identified. 

Member States spent a total budget of EUR 23 619.4 million on different operations aimed at 
improving  the  environmental  situation.  Most  regions  have  implemented  a  variety  of  sub-
measures  with  different  focuses.  On  average,  Member  States  invested  almost  26%  of  their 
total EAFRD expenditure in M214. This has resulted in 1 521 872 farms that were supported 
and 12 237 other land managers.  The measure concerned 968 086 livestock units; as well as 

-  42.5 million ha under land management contributing to biodiversity, 
-  35.7 million ha contributing to water quality, 
-  36 million ha contributing to soil quality, 

84 

 
-  25.5 million ha contributing to mitigating climate change, 
-  19.6 million ha to the avoidance of marginalisation and land abandonment. 

Since several actions are possible on the same area, a comparison with reference values is not 
possible. 

Of those reports that provided a clear conclusion on M214 (i.e. “positive”, “limited” or “no 
contribution”), 87% stated a positive contribution. Based on these evaluations, it can be stated 
that  the  measure  contributed  to  the  improvement  of  the  environmental  situation  to  a  high 
extent. 

Measure 215: Animal Welfare 

This  measure  was  implemented  in  11  Member  States  (30  rural  development  programmes), 
with a total EAFRD expenditure of EUR 1 billion. Its main objective was to improve animal 
welfare.  It  was  perceived  as  making  a  positive  (34%)  or  limited  (17%)  contribution  to  the 
environment  in  half  the  cases.  The  benefits  identified  included  extensification  and  lower 
livestock  density,  with  effects  on  pasture  species  composition,  reduced  N  and  P  water 
pollution  and  improved  soil  structure  and  fertility.  In  a  small  number  of  cases,  improved 
animal welfare was identified as contributing to improved animal health and production, and 
hence competitiveness. 

The  main  topics  in  the  29  reports  –  when  explained  in  more  detail  –  address  whether 
production  systems  (e.g.  support  of  free-range  husbandry,  ecological  livestock  production 
systems)  or  animal  groups  were  targeted  (dairy  cows,  pig  breeding,  poultry  farming, 
aviculture  etc.).  79 435 farm  holdings  were  supported  and  143 099 contracts  made.  The 
measure reached 1.7% of the total number of holdings with livestock in the Member States 
that offered the measure. This corresponds to 1.1% of all holdings with livestock in the EU. 
The impact of the measure is therefore limited. 

Since  28%  of  the  reports  attributed  no  contribution  of  M215  to  an  improvement  of  the 
environmental situation, another 7% gave no information on the topic and 14% was unclear 
on the contribution to the environment, the assessment is indicative only. 

Measure 216: Support for non-productive investments 

Support provided under this measure covered a wide variety of non-productive investments. 
A  positive  environmental  contribution,  particularly  to  biodiversity,  landscape,  HNV  and 
Natura  2000  areas,  was  reported  in  43%  of  reports  (more  than  half  of  those  providing  a 
judgement), and a limited contribution in a further 27%. Where the benefits were considered 
“limited”, constraining factors mentioned included late implementation  of the measure, low 
uptake, and the small scale of supported projects. 

In  order  to  support  non-productive  investments  in  farm  holdings,  a  total  budget  of 
EUR 621.0 million  was  spent  on  M216  by  16  Member  States  across  53  regions.  This  has 
resulted 
investment  volume  of 
EUR 1 190 million. 

in  44 294 farm  holdings  supported  and  a 

total 

Result indicators are reported on Axis level, concerning the number of hectares supported by 
the measure reported by 13 Member States. The strongest impact is reported for soil quality, 

85 

 
marginalisation and biodiversity. However, it is not clear, how the relatively high numbers of 
hectares for these environmental aspects are related to non-productive investments. 

According  to  the  synthesis,  43%  of  the  reports  attribute  a  positive  contribution  to  the 
measure.  A  rather  large  number  of  aspects  were  considered  as  improvement  for  the 
environment  and  the  landscape.  The  conservation  and  development  of  habitats  and 
biodiversity  were  mentioned  several  times.  Further  topics  were  the  reduction  of  erosion, 
stability  of  slopes,  better  soil  quality  management,  and  improvement  of  water  quality, 
preventing  natural  hazards  and  increasing  carbon  sequestration.  Landscape-related  topics 
were the conservation and improvement of the scenery. 

A  limited  contribution  of  the  measure  is  found  in  27%  of  the  reports.  8%  of  the  reports 
attributed no contribution of the measure, 20% did not deliver any information on the topic 
(N/A) and 2% provided other classifications (not clear). It is concluded that the measure has 
contributed to a medium extent to improving the environmental situation. 

Measure 221: First afforestation of agricultural land 

A total budget of EUR 1 586 million has been spent on M221 by 20 Member States across 63 
regions  for  first  afforestation  of  agricultural  land.  This  resulted  in  203 944 hectares  of 
afforested land in 42 531 supported actions. The measure reached 0.1% of the total UAA or 
0.2% of the total forest area across the Member States that offered the measure. 

37% of the ex post evaluation reports assessed a positive contribution of the measure to the 
improvement  of  the  general  environmental  situation  (mostly  regarding  biodiversity, 
mitigation of climate change and water quality). This was largely attributed to the diverse and 
various  ecological  functions  of  forests  and  hence  the  afforested  areas  were  often  assessed 
positively without further consideration. However, as 39% of the ex post evaluation reports 
did  not  include  a  detailed  examination  of  the  measure's  impact  on  the  environmental 
situation, the available information  covers the regions  which implemented the  measure to  a 
small extent only. 

Breaking down the assessment of the general environmental situation in different topics, 43% 
of the reports noted a positive contribution to biodiversity, 35% on water quality, and 46% on 
mitigating  climate  change  and  26%  on  soil  quality  but  only  7%  on  avoidance  of  land 
abandonment. 

In summary, the measure can contribute to improving the environmental situation depending 
on  the  utilisation,  design  and  initial  local  environmental  situation.  It  can  be  stated  that  the 
measure contributed to the improvement of the environmental situation to a medium extent.  

Measure 222: First establishment of agroforestry systems on agricultural land 

A  total  budget  of  EUR 1.5 million  has  been  spent  on  M222  by  5  Member  States  across  8 
regions, which has resulted in 2 905 hectares of supported utilised agricultural area (UAA) in 
291  supported  actions.  In  comparison  with  other  measures,  only  a  very  small  share  of  the 
UAA  was  supported  with  this  measure  (0.0017%  on  EU  level).  Very  limited  consolidated 
information is available concerning its effects. Specific comments make reference to the new 
habitat  increasing  biodiversity,  reducing  chemical  inputs,  and  improving  soil  and  water 
quality. Due to the low utilisation of the measure in the rural development programmes and 

86 

 
the limited impact on the individual aspects of the result indicator, it is assessed that  M222 
contributed to the improvement of the environmental situation to a very limited extent. 

Measure 223: First afforestation of non-agricultural land 

A total budget of EUR 168 million has been spent on M223 by 10 Member States across 32 
regions. This resulted in 84 265 hectares of afforested land in 10 680 supported actions. 27% 
of  the  ex  post  evaluation  reports  assessed  a  positive  contribution  of  the  measure  to  the 
improvement  of  the  environmental  situation  (mostly  regarding  the  mitigation  of  climate 
change). However, detailed explanations were rarely presented, but the very broad impact of 
the measure on various environmental aspects  has been emphasised  and reference has been 
made  to  the  in-depth  analyses  of  M221;  No  or  limited  contributions  of  the  measure  were 
assessed in 23% of the cases. These evaluations are based on the very low utilisation and area 
coverage  of  the  measure  and  therefore  not  on  its  design.  In  summary,  the  measure  can 
contribute to improving the environmental situation depending on the utilisation, design and 
initial  local  situation,  yet the measure contributed to  the improvement of the environmental 
situation to a limited extent. 

Measure 224: Natura 2000 payments – forestry 

Although this measure was implemented on a minor scale in only 11 Member States (13 rural 
its 
development  programmes)  and  spending  a 
environmental  impact  was  assessed  as  positive  (76%  of  reports,  albeit  42%  qualifying  the 
impact as limited, due to its nature as compensation for compulsory management practices). 
It  is  considered  to  preserve  high  quality  habitats,  to  increase  awareness  and  improve 
environmental management. 

total  budget  of  EUR 74.3 million, 

On  average,  Member  States  invested  less  than  0.25%  of  their  total  EAFRD  expenditure  in 
Measure  224.  This  has  resulted  in  14 391  supported  forest  holdings  and  278 975  hectares 
woodland covered. The measure covers 2.3% of forests in Natura 2000 areas of the Member 
States that have offered the measure. This corresponds to 0.7% of forests in Natura 2000 in 
the EU as a whole; 

On  the  one  hand,  the  measure  was  attested  to  positively  contribute  to  improving  the 
environmental situation (33%), the justification being mainly based on the achievement of the 
target  values  and not  taking a closer look  at  the individual  environmental aspects.  Some of 
the  changes  that  can  also  be  seen  in  the  forest  (e.g.  deadwood  content),  which  are  actually 
due to higher-level regulations and not the measure itself, are mentioned here. 

On  the  other  hand,  these  regulation-induced  changes  were  taken  up  in  the  second  group  of 
reports,  in  which  the  contribution  to  the  improvement  of  the  environmental  situation  was 
evaluated as limited (42%). Since the restrictions and management requirements of the Birds 
and Habitats Directives are to be complied with even without funding via M224, this measure 
has generally only had a limited additional effect on improving the environmental situation. 

Measure 225: Forest-environment payments 

Whilst implemented in 13 Member States (27 rural development programmes), this measure 
only  accounted for 70 million EUR. Where it was implemented it was generally  considered 

87 

 
positive, but the very small coverage limited results. Much of the area covered was in Natura 
2000 areas, so supported important habitats. 

This  has  resulted  in  an  output  of  0.4  million  hectare  supported  forest  area  and  a  total  of 
12 000 management contracts. 39% of the ex post evaluation reports found that the measure 
contributed  positively  to  improving  the  environmental  situation.  30%  concluded  the 
measure’s  effects  on  the  environment  were  limited  and  4%  concluded  the  measure  did  not 
contribute. In 78% of the positive cases the improvement of the environmental situation was 
attributed  to  higher  ecological  and  biodiversity  values.  Improved  soil  quality  and  improved 
conditions  regarding  climate  change  were  also  pointed  at  as  results  of  the  measure  which 
have improved the environmental situation. 

Based on these evaluations, it can be plausibly considered that the measure contributed to the 
improvement of the environmental situation to a medium extent.  

Measure 226: Restoring forestry potential and introducing prevention actions 

This measure was assessed as highly positive for the environment, mostly through preventing 
fires and flooding. These actions improved biodiversity, soil and water quality, and mitigated 
climate change. 

In  order  to  improve  the  environmental  situation,  a  total  budget  of  EUR 1 542.1 million  has 
been spent on M226 by 16 Member States across 56 regions. 10 million hectare of damaged 
forests were supported (a total of 77 359 actions). 

62%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the environmental situation. 15% of the ex post evaluation reports concluded the 
measure’s  effects  on  the  environment  were  limited  and  9%  of  the  evaluation  reports 
concluded the measure did not contribute. In 78% of the positive cases the improvement of 
the  environmental  situation  was  attributed  to  the  fields  of  fire  damages  and  prevention. 
Improved water quality and flood mediation and biodiversity were also pointed at as results 
of the measure which have improved the environmental situation. Based on these evaluations, 
it  is  considered  that  the  measure  contributed  to  the  improvement  of  the  environmental 
situation to a medium extent. 

Measure 227: Support for non-productive investments (in the forest sector) 

The  results  of  the  implementation  of  this  measure  (13  Member  States  and  68  rural 
development  programmes  spending  EUR 698.6 million)  will  become  more  evident  over  the 
medium-long  term,  making  it  difficult  to  evaluate  clearly  at  the  end  of  the  programming 
period.  However,  the  ex  post  evaluation  reports  consider  that  the  contribution  is  positive, 
particularly for biodiversity and nature conservation, forest health and resilience against risks. 

M227  has  resulted  in  an  output  of  an  investment  volume  of  EUR 1.7 billion  and  a  total  of 
131.555 forest holders supported. 

52%  of  the  ex  post  evaluation  reports  found  that  the  measure  contributed  positively  to 
improving the environmental situation. 17% of the ex post evaluation reports concluded the 
measure’s  effects  on  the  environment  were  limited  and  5%  of  the  evaluation  reports 
concluded the measure did not contribute. In 56% of the positive cases, the improvement of 
the environmental situation was attributed to improved biodiversity and nature conservation. 

88 

 
Environmental improvements in general and forest health improvements and improved forest 
stability towards hazards were also pointed at as results of the measure which have improved 
the environmental situation. 

Based on these evaluations, we assess that the measure contributed to the improvement of the 
environmental situation to a medium extent. 

Axis 3 - Diversification of the rural economy and quality of life in rural areas 

Measure 311: Diversification to non-agricultural activities 

This  measure  was  implemented  by  20  Member  States  (65  rural  development  programmes) 
and was considered to contribute positively to the economic performance of beneficiaries in 
52% of cases, rising to 90% when “limited” contributions are taken into account. 3% found 
no  contribution.  A  wide  range  of  activities  were  supported,  including  rural  tourism,  horse 
livery  and  renewable  energy  production.  It  appears  to  have  been  relatively  effective  in 
increasing GVA and jobs on the beneficiaries’ farms. 

A total  budget  of EUR 1.1 billion  has been spent on M311 by 20 Member States across 65 
regions. This has resulted in 41 940 beneficiaries that received support for efforts to diversify. 
The  result  indicators  for  this  measure  are  the  increase  in  total  non-agricultural  GVA  in 
supported businesses and the total  number of jobs created. The increase in  non-agricultural 
GVA  in  supported  businesses  is  EUR 563.6 million.  The  total  number  of  jobs  created  is 
27 881. 

Through  the  diversification,  the  measure  contributed  to  the  stabilisation  of  farms,  enabled 
farmers  to  increase  their  overall  performance,  assisted  farm  households  to  maintain  or 
increase their income, supported farms to maintain employment or even to create new jobs. 
Based on these evaluations, the measure is considered to have contributed to improving the 
economic diversification of the beneficiaries to a medium extent. 

Measure 312: Business creation and development 

A total  budget  of EUR 1.4 billion has been spent on M312 by 21 Member States  across 46 
regions. This has resulted in 74 138 supported micro-enterprises. The result indicators for this 
measure are the increase in total non-agricultural GVA in supported businesses and the total 
number  of  jobs  created.  The  increase  in  non-agricultural  GVA  in  supported  businesses  is 
EUR 823.7 million. The total number of jobs created is 68 843. 42% of the ex post evaluation 
reports  found  that  the  measure  contributed  positively  to  improving  the  economic 
diversification  of  the  beneficiaries.  36%  concluded  the  measure’s  effects  on  the  economic 
diversification  of  the  beneficiaries  were  limited  and  2%  concluded  the  measure  did  not 
contribute.  The  measure  contributed  to  improving  the  economic  diversification  of  the 
beneficiaries to a medium extent. 

Measure 313: Encouragement of tourism activities 

This  measure  is  perceived  more  positively  than  either  M311  or  M312.  However,  its 
efficiency  appears  to  be  considerably  lower  when  considered  as  increased  GVA  or  jobs 
created in relation to the investment made. The positive assessment may be linked to indirect 

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effects  (such  as  spending  by  additional  tourists  in  the  area,  impact  on  other  touristic 
infrastructure). 

In  order  to  improve  the  economic  diversification  of  the  beneficiaries,  a  total  budget  of 
EUR 887.9 million has been spent on M313 by 22 Member States across 67 regions. This has 
resulted in 24 518 new tourism actions that received support. The increase in non-agricultural 
GVA  in  supported  businesses  is  EUR 350.4 million.  The  total  number  of  jobs  created  is 
17 578. 48% of the ex post evaluation reports found that the measure contributed positively to 
improving the economic diversification of the beneficiaries. 38% of the  ex post evaluations 
concluded  the  measure’s  effects  on  the  economic  diversification  of  the  beneficiaries  were 
limited  and  10%  of  the  evaluation  reports  concluded  the  measure  did  not  contribute.  The 
encouragement of tourism activities has led to substantial increases of the revenues from new 
agricultural  products  and  services.  Based  on  these  evaluations,  it  is  considered  that  the 
measure  contributed  to  improving  the  economic  diversification  of  the  beneficiaries  to  a 
limited extent. 

Measure 321: Basic services for the economy and rural population 

This measure was implemented in 23 Member States (70 rural development programmes). It 
supported improved services for more than 45 million rural inhabitants, and provided internet 
coverage to an additional 16.6 million people living in rural areas. Improvements in quality of 
life highlighted in the reports focussed on social  infrastructure such as day care, health and 
community  facilities,  and  digital  infrastructure.  Smaller  impacts  were  reported  on 
water/waste water, electricity and roads. The overall assessment of this measure is positive. 

Measure 322: Village renewal and development 

This  measure  was  implemented  in  22  Member  States  (50  rural  development  programmes). 
The  evaluation  reports  identified  its  effects  on  quality  of  life  in  rural  areas  as  strongly 
positive, covering both physical infrastructure such as meeting places, and intangible aspects 
such as social cohesion and local/regional identity. The projects implemented also generated 
additional effects such as new employment, and counteracting depopulation. 

Measure 323: Conservation and upgrading of the rural heritage 

This  measure  was  implemented  in  22  Member  States  (70  rural  development  programmes), 
and  is  also  considered  to  have  had  significant  positive  impact  on  quality  of  life,  improving 
services for 66.4 million rural residents. 

Measure 331: Training and information 

Expenditure  on  this  measure  was  much  lower  than  for  investment  measures  within  Axis  3, 
although it was implemented by 13 Member States (32 rural development programmes). The 
evaluation  assessments  were  mixed,  with  only  17%  identifying  a  positive  contribution  to 
economic  diversification  and  25%  of  quality  of  life,  with  36%  a  limited  contribution  to 
economic diversification and 22% to  quality of life. This  may be because the  main activity 
supported  was  training  to  increase  human  capital,  the  benefits  of  which  may  only  become 
evident in the long term, or in conjunction with other activities, such as business start-up. 

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Measure 341: Supporting skill acquisition for developing local strategies 

This measure was implemented in 15 Member States (33 rural development programmes) and 
was  intended  to  develop  human  capacity  to  develop  and  implement  local  development 
strategies.  The  effects  of  this  measure  were  assessed  as  much  more  positive  than  those  of 
M331 (32% identified positive contributions to economic diversification and 44% to quality 
of life, with 24% and 18% of reports respectively identifying further limited contributions). 
The  findings  focussed  on  the  impact  of  the  networks  and  relationships  created,  and  the 
enhancement of collective capacity to implement LEADER. 

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ANNEX 4. INTERVENTION LOGIC BY AXIS 

Axis 1. Improving competitiveness of the agricultural sector 

Axis 2. Improving the environment and the countryside 

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Axis 3. Quality of life in rural areas and diversification of the rural economy 

Axis 4. LEADER 

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