Investment support under rural development policy : executive summary.
Date: 2015-02-17
Institutions: Directorate-General for Agriculture and Rural Development
Subjects: agricultural performance, common agricultural policy, competitiveness, cost-benefit analysis, econometrics, input-output analysis, investment aid, rural development

Investment Support under 
Rural Development Policy 
Contract 30-CE-0609852/00-41 

EXECUTIVE SUMMARY 
12 November 2014 

Written by Metis/WIFO/aeidl 
November – 2014 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EUROPEAN COMMISSION 

Directorate-General for Agriculture and Rural Development 
Directorate E — Economic analysis, perspectives and evaluation; communication 
Unit E.4 — Evaluation and studies 

E-mail: agri-evaluation@ec.europa.eu 

European Commission 
B-1049 Brussels 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Investment Support under 
Rural Development Policy 
Contract 30-CE-0609852/00-41 

EXECUTIVE SUMMARY  
12 November 2014 

Directorate-General for Agriculture and Rural Development  

Investment Support under Rural Development Policy 

2014 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Luxembourg: Publications Office of the European Union, 2014 

ISBN 978-92-79-41104-5 
doi: 10.2762/63445 

© European Union, 2014 
Reproduction is authorised provided the source is acknowledged. 

Printed in Austria 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Executive Summary 

Final Report – Executive Summary 

Objective and scope of the study  

The  objective  of  this  evaluation  is  to  review,  analyse  and  test  different  methods  for 
evaluating investment support measures in Rural Development Programmes (RDP).The 
selected  methods  were  used  to  analyse  investment  support  measures  in  eleven 
Member  States.  Results  of  this  evaluation  focused  firstly,  on  assessing  the  strengths 
and weaknesses of different methodological approaches and identifying types of results 
to  be  obtained  by  six  different  methods.  Secondly,  the  effectiveness,  efficiency  and 
impact of investment support measures were explored by applying these methods in the 
case  study  territories.  Finally,  the  results  of  the  case  studies  were  used  to  assess  to 
what  extent  the  different  approaches  to  targeting  investment  support  have  been 
effective in meeting the general objectives of rural development policies.  

related 

infrastructure 

Investment  support  measures  in  RDP  aim  at  increasing  productivity  within  the 
agricultural  and  forest  sector  and  to  diversify  production  in  non-agricultural  activities. 
Furthermore, 
investments 
supporting agri-environmental schemes are supported. The target groups are economic 
entities  (farm  and  forestry  holdings;  micro,  small  and  medium  sized  enterprises  in 
sectors  processing  agricultural  and  forest  product)  within  the  agricultural  and  forest 
sector  and  individuals  attempting  to  diversify  and  establish  businesses  or  services 
outside  the  agricultural  sector,  including  tourism.  These  measures  are  part  of  Axes  1 
and  3  (investment  support  to  private  beneficiaries  and  infrastructure  investments)  and 
partly, of Axis 2 (non-productive investments).  

investment  and  non-productive 

Six methods were used to evaluate these investment support measures: 

 

IO  (Input-Output  model),  a  computational  model using quantitative  tools based 
on  a  specific  theory  of  economic  behaviour  which  applies  widely  available 
regional and national statistics on sectors and households as primary data input,; 
the  IO  method  includes  sectoral  analysis,  but  is  in  fact  a  general  equilibrium 
programming approach; 

  PSM (propensity score matching) is an econometric method that uses micro-data 
(data  on  individuals  and  firms)  or  data  on  a  large  number  of  regions  and 
programme  information.  The  objective  of  PSM  is  to  identify  comparable 
observations  of  those  who  received  and  those  who  did  not  receive  investment 
support and calculate the difference in the indicator of interest (e.g. Gross Value 
Added). 

  MAPP  is  a  method  that  combines  qualitative  and  quantitative  approaches  by 
exploring  the  opinion  of  stakeholders  on  the  outcomes  of  a  programme.  One  of 
the  results  is  a  shared  view  of  the  participants  on  indicators  of  interest.  Such 
results are derived in an interactive process. 

  TBE  (theory-based  [impact]  evaluation)  is  a  method  that  defines  procedures  to 

derive evaluation results from desk research and expert interviews. 

  SEA (strategic environmental assessment) is an approach rather than a method 
and is based on the SEA Directive 2001/42/EC. Member States have to carry out 
a  SEA  as  part  of  the  ex-ante  evaluation  to  determine  whether  the  RDP  has 
significant environmental effects; 

  CEA  (cost-effectiveness  analysis)  is  a  set  of  different  methods,  that  combine 
economic  and  environmental  data  in  order  to  evaluate  the  effects  of  measures 
taken  to  enhance  environmental  quality;  in  many  cases  -  but  not  always  -  CEA 
results  are  based  on  combining  quantitative  tools  used  in  economic  and 
environmental sciences. 

page 5 

 
 
 
Final Report – Executive Summary 

Methodology 

Different approaches were applied to answer the three overarching evaluation questions 
(EQ) of the study:  

EQ11 focuses on the appropriateness and suitability of methods. Thus concise and 
clear  descriptions  including  strengths  and  weaknesses  were  developed  for  each 
method.  A  factsheet  with  a  short  description  of  the  measure,  data  requirements,  the 
approach how the counterfactual situation is established, the scale of indicators and the 
method  for  measuring  efficiency,  effectiveness  and  impact  is  presented.  A  typical 
workflow  highlights  the  activities  necessary  to  conduct  the  specific  method.  Data 
requirements  are  described  in  detail.  The  appropriateness  of  each  measure  is  judged 
using  the  criteria  rigour,  robustness  and  validity  and  practicability  based  on  views  of 
experts in the project team and literature. 

Answering EQ22 different methods had to be applied in selected territories: A total 
of  eleven  different  RDP  territories  with  a  geographical  balance  and  representation  of 
different types of measures and reasonable data availability were chosen (AT, CZ, CY, 
DE/Hessen,  DK,  ES/Galicia,  FR,  GR,  PL,  SK,  UK/Scotland).  For  each  of  the  methods 
the  core  team  of  experts  specified  the  data  requirements  and  geographic  experts 
assessed  the  data-availability  during  a  first  screening  exercise.  For  the  fieldwork  the 
necessary  data  for  applying  the  tests  were  used.  A  large  variety  –  but  not  every 
combination  -  of  investment  measures  in  the  study  regions  was  analysed  by  different 
methods  (in  total  126  cases  of  different  combinations  of  study  regions,  methods  and 
investment  support  measures).  In  order  to  derive  comparable  results  only  a  small 
number of indicators were used (mainly focusing on employment, income, value added 
and environmental effects, if applicable). 

The  third  evaluation  question3  (EQ3)  asked  for  the  effectiveness  of  different 
approaches  to  targeting 
in  meeting  objectives  of  rural 
development policies. Three criteria were identified, that reflect approaches to targeting:  

investment  support 

  eligibility criteria (by territory, investment type, beneficiary characteristics etc); 

  aid-intensity differentiation (more funding for targeted groups); and  
  criteria used for ranking by administrative authorities. 

These  criteria  are combined  in  various  ways  in  the RDPs  leading  to  a  high  number  of 
approaches  to  targeting.  They  were  used  to  analyse  the  effectiveness  of  targeting  to 
achieve the objectives of the RDP and also to divert funds to the targeted groups. The 
evaluation  question  was  addressed  by 
testing  a  specific  hypothesis:  Different 
approaches to targeting might differ in how efficient they are in achieving the objectives 
of the RDP. It was thus envisaged that it might be possible to directly link the results for 
EQ2 where the efficiency is estimated to the question of targeting.  

1  To which extent are the different evaluation methods described and/or tested in this exercise appropriate for 

the assessment of the effectiveness, efficiency and impact of the different types of investment support 
considered? 

2  What is the effectiveness, efficiency and impact of the investment support studied in the selected RDP 

territories? 

3  To what extent have the different approaches to targeting investment support studied been effective in 

meeting the general objectives of rural development policy and/or specific objectives included in the relevant 
RDPs? 

page 6 

 
 
 
 
                                                           
Final Report – Executive Summary 

Selected results of case studies  

The  application  of  the  selected  methods  is  explained  in  detail  for  each  method 
separately  as  applied  to  one  case  study  territory,  where  the  conditions  were 
specifically favourable.  

For  Austria  all  A  and  B-type  measures  were  evaluated  firstly  by  an  Input-Output 
analysis,  where  the  total  economic  effects  of  the  RDP  were  assessed  to  increase 
output,  income  and  employment.  Secondly,  an  econometric  counterfactual  method 
was applied, to analyse the effects of an investment support measure (M121): Indicators 
of  programme  beneficiaries  were  compared  to  target  values  and  to  outcomes  of  a 
control-group of non-beneficiaries. Also the structure of the total increase as the result 
indicators  was  analysed.  From  the  results  it  became  clear  that  the  conditional  PSM 
method4  appeared  to  be  the  most  rigorous,  transparent  and  reliable  method.  A  naive 
before-after  approach  generated  results  which  were  highly  biased  by  over-estimating 
result  indicators  to  a  magnitude  of  factor  2-25  (!).  On  this  basis  a  detailed  PSM 
assessment  of  effectiveness,  efficiency  and  impact  could  be  provided,  also  comparing 
farm-level  based  results  with  country-wide  data.  At  the  same  time,  considerable  time 
and  administrative  efforts  were  necessary  to  receive  from  national  authorities  all 
required farm bookkeeping/FADN and Paying Agency data.  

The  MAPP  method  is  explained  for  Scotland,  where  six  of  the  most  important 
investment schemes were analysed with a focus group of stakeholders. In several steps 
the  expert  and  the  focus  group  established  the  overall  context,  analysed  trends  for 
performance and impact indicators, discussed an influence matrix for RDP schemes and 
external  drivers  and  developed  an  impact  profile.  The  discussions  revealed  that  RDP 
investment  support  had  had  an  important  impact  on  generation  of  non-farm  jobs, 
especially long-term jobs in the food sector. Also RDP investment support has helped at 
best  to  maintain  farm  jobs  among  beneficiaries  while  jobs  have  declined  in  non-
participating  businesses.  Results  are  judged  to  be  of  good  quality,  as  the  tools  have 
worked  well.  Problems  were  in  finding  the  right  participants  and  overcoming  a  certain 
group  fatigue.  The  method  needs  careful  preparation  in  order  to  achieve  good 
outcomes.  

In  the  Czech  Republic’s  case  study  the  Programme-theory-based  evaluation 
method  was  illustrated.  Based  on  a  conceptual  model  according  to  the  RDP 
intervention logic, the main project outputs at operations level have been compiled. This 
leads  from  the  projects/operations  level  to  gross  results  for  the  target  group,  e.g. 
holdings,  small  enterprises.  During  the  judging  phase  the  evaluator  drew  evidence-
based  conclusions  on  the  effectiveness  of  the  interventions  and  identified  gross  direct 
effects. It transpired that the effectiveness is quite high ranging from “medium”, “high” to 
even “very high”. For the Czech RDP all “building blocks” to establish a TBE along the 
intervention  logic  could  be  established  at  good  quality  level.  Accordingly,  robust 
judgements  were  possible.  The  main  problem  encountered  was  to  put  the  information 
together in a consistent way, direct access to the monitoring system was a prerequisite 
for this.  

A  Strategic  Environmental  Assessment  and  a  Cost-Effectiveness  Analysis  were 
illustrated  for  investment  in  public  infrastructures  in  Greece.  The  SEA  has  highlighted 
the explicit and implicit intervention logic in relation to the environmental issues and has 
shown  areas  for  improvement  in  the  programme-specific  result  indicators  and  the 
options for assessment of impacts.  

4  combination of a binary PSM and DID 

page 7 

 
 
                                                           
Final Report – Executive Summary 

CEA is a method where the strength lies in the credibility of the numbers feeding both 
the  numerator  and  denominator.  Even  when  using  ex  ante  values  the  results  can  be 
used  to  trigger  the  debate  for  the  explanation  of  deviations  among  operations  and 
regions. 

result 

renders 

indicator  values 

lack  of  current 

the  discussion  of 

the 
The 
representativeness  of  results  impossible;  however  the  theory-based  assumptions  are 
sound  and  valid.  For  both  methods  the  consideration  of  the  environmental  dimension 
has been plausible for a measure under Priority Axis 1; the formulation of the “theory of 
change”  on  environmental  aspects  is  clear,  but  incomplete  on  secondary  effects  (soil, 
energy). Problems encountered relate to the lack of periodic reporting of result indicator 
values  and  the  lack  of  tracking  of  context  indicators.  These are necessary  for  a  better 
understanding  of  the  effects  of  a  measure  in  a  given  timeframe  and  spatial  context. 
There is no real solution to this problem: application forms, environmental permits and 
other documents have been screened and discussed but no systematic solution exists.  

Findings and conclusions 

Comparing methods (EQ1) 

When  comparing  the  different  methods  against  the  judgement  criteria  for  EQ1  it 
becomes evident, that there is not one but rather a range of methods that is best suited 
to address different aspects of an evaluation.  

In  order  to  assess  the  appropriateness  of  methods  to  analyse  investment  support 
measures,  fundamental  problems  related  to  the  rigour  of  any  evaluation  have  to  be 
considered:  This relates  for  example  to  assessing  the  counterfactual,  i.e.  what  would 
have happened if the programme was not in place.  

To identify and test causal relations between a policy intervention and an outcome is 
one  of  the  biggest  challenges  of  every  evaluation.  Only  a  small  set  of  approaches 
(typically  specific  econometric  methods  or  experiments)  are  suited  to  provide  such 
results  by  empirically  estimating  the  counterfactual  situation.  If  such  estimates  are  not 
available, assumptions about the causal effects need to be made. In the context of this 
study, PSM was applied to identify causal effects. For other methods either findings in 
the  literature  or  monitoring  reports,  assumptions  and  statements  of  stakeholders  or 
results of PSM were used. Furthermore it is worthwhile considering specific effects such 
as leverage or deadweight effect. PSM can be used to directly address these effects 
by quantifying them at farm or firm level. At sector or regional level other effects need to 
be  considered,  including  the  increase  of  demand  for  investment  goods  and  capacity 
adjustment  after  an  investment  was  made.  IO  can  be  used  to  directly  address  these 
effects by quantifying them. 

It  is  worth  considering  not  only  the  generic  characteristics  of  a  method,  but  also  the 
context in which it is applied. In this study the practicability of methods in the context 
of  EU  RDPs  was  also  a  topic  of  interest.  All  methods  need  data  (among  them 
programme  documents,  reports,  evaluation  studies,  etc.).  Such  data  are  partly  readily 
available (e.g. input-output tables for most Member States), some data are available but 
scattered  on  different  places  (programme  details  and  data  on  implementation  and 
outputs), other data are available but accessible only with restrictions (e.g. many micro-
data), or have to be collected (e.g. interviews, participatory activities). In the context of 
this  study,  expenditure  for  data  acquisition  has  been  surprisingly  low.  Much  more 
resources were necessary to locate, collect and prepare data.  

page 8 

 
 
Final Report – Executive Summary 

Another finding is that even if data that are necessary for a given method are known to 
exist, they may not be available due to data protection concerns or lack of capacity to 
match  different  data  sets  and  make  them  useable  for  an  evaluation.  Based  on  an 
overview of the resources used in this study, methods can be ranked: 

  data collection and field work were most resource intensive for TBE, followed by 

PSM, MAPP, and IO; SEA and CEA required the least resources; 

  applying  PSM  required  the  most  resources  in  order  to  derive  results  and 
considerable  fewer  resources  per  case  study  were  necessary  for  handling  data 
and deriving results when applying MAPP, IO and TBE; the least resources were 
used for SEA and CEA.   

The resource intensity is only one small facet and it is necessary to link the resources 
to  the  quality  and  depth  of  an  analysis.  SEA  and  CEA  needed  the  least  resources, 
assuming that necessary data would be available in the course of standard monitoring 
and reporting; unfortunately this was not the case.  

The  report  suggests  a  decision  tool  that  can  facilitate  the  identification  of  a  method 
which  best  fits  to  the  preferences  and  capacities  of  the  user.  Because  the  need  for 
resources is an eminent element of any evaluation, it is evident that some results may 
be attainable only at higher costs. The tool should help a decision maker to structure the 
problem of method selection in a transparent and concise manner. 

Effectiveness,  efficiency  and  impact  of  the  investment  support  studied  in  the 
selected RDP territories (EQ2)  

There  are  as  many  answers  as  investigated  indicators  (efficiency,  effectiveness,  and 
impact),  cases  and  methods  used  to  obtain  results.  Furthermore  information  on 
environmental  outcomes  of  investment  support  measures  (measured  by  SEA  and/or 
CEA) is rarely available and if available, often not conclusive.  

Efficiency  of  programmes  depends  firstly,  on  the  specific  result  of  interest  (e.g.  value 
added  or  labour)  and,  secondly,  on  the  method  used  to  measure  efficiency.  In  most 
cases efficiency was at levels expected and observed already in previous studies. 

  Only  two  methods  (IO  and  PSM)  provide  quantitative  results  on  efficiency.  TBE 

gives no results on efficiency and results of MAPP are very scant. 

  There is a large variance of efficiency indicators across regions when measured 

by the same method (either IO or PSM).  

 

In  several  cases  efficiency  of  the  same  investment  measure  was  analysed  with 
different  methods  in  the  same  region.  As  expected,  results  deviated.  Even 
contradictory results were obtained.  When  scrutinised  these results  showed  that 
contradictions  are  either  due  to  subtle  differences  of  definitions  of  efficiency 
between the methods or due to the fact that one method was using exogenously 
given parameters to measure efficiency (IO) while the other measured efficiency 
directly (PSM). 

  Results  for  efficiency  obtained  by  PSM  show  in  almost  all  cases  that  for  each 
Euro  of  public  funding  spent,  the  GVA  (Gross  Value  Added)  and  family  farm 
income had increased by (sometimes substantially) less than one EUR by the end 
of the programme period.  

page 9 

 
 
 
 
Final Report – Executive Summary 

Results on effectiveness were provided by applying IO, PSM, and TBE methods. One 
general conclusion from the analyses is that in many cases targets are not reported and 
if  they  are  reported  there  is  not  a  good  correspondence  between  achievements  and 
target.  

Impacts are effects that go beyond beneficiaries of the programme. Results on impacts 
were  provided  by  applying  IO,  PSM,  and  MAPP.  A  major  finding  -  derived  from  the 
analysis with the IO method - is that support of investments creates additional demand 
in the regions where the beneficiaries are located and frequently triggered an expansion 
of  outputs.  The  benefit  of  using  more  than  one  method  is  exemplified  by  showing  the 
effects of regional output responses when they are based either on reports of Managing 
Authorities  or  derived  from  micro-data  by  PSM.  Results  based  on  the  latter  are 
consistently lower. 

Effectiveness of targeting investment support (EQ3) 

The  study  did  not  find  a  significant  relationship  between  the  efficiency  of  the  policy 
intervention  and  approaches  to  targeting.  Three  reasons  can  explain  the  lack  of 
significant relationships:  

  First, and most likely, not enough observations were available. The noise through 
efficiency  and  targeting  approach  measurement  combined  with  insufficient 
variation  prohibited  uncovering  possible  relationships  between  efficiency  and 
approach to targeting.  

  Second, the approach to targeting does not in fact have a substantial impact on 

efficiency as indicated by the insignificant results.  

  Third, the approaches to targeting described in the programme documents did not 

actually divert the funds to the targeted groups.  

In order to further investigate these question, an in depth analysis was made in Austria 
on  measure  121.  Measure  121  in  Austria  includes  eligibility  criteria,  aid  intensity 
differentiation  and  selection  criteria.  To  test  if  these  criteria  divert  funds  to  the  groups 
specified,  FADN  survey  data  are  used.  Using  the  survey  design  information  (weights 
and strata) it is possible to estimate population statistics. 

Based  on  the  analysis  the  study  concluded  that  not  all  elements  of  the  approach  to 
targeting  necessarily  work.  Eligibility  criteria,  as  they  were  easy  to  check,  worked.  For 
aid intensity differentiation criteria a statistically significant effect on average investment 
support was not found. Interestingly, even though simple to apply and check, eligibility 
criteria were not used extensively.  

The major conclusion from this analysis is that targeting approaches are as complex as 
programmes  are.  In  order  to  better  understand  the  ways  targeting-approaches 
contribute to the efficiency of programmes it seems to be necessary to work further on 
deepening the knowledge by analyses as carried out in this study. 

Further conclusions 

In  addition  to  the  responses  to  EQ1,  EQ2  and  EQ3  further  conclusions  have  been 
derived from this study. 

Use of combinations of methods: The number of users of evaluation results is large 
and  each  user  has  specific  expectations.  While  some  users  need  quantitative  results, 
others  are  more  interested  in  subtleties  that  cannot  be  expressed  in  figures.  To  serve 
both prototypical groups calls for a combination of methods.  

page 10 

 
 
Final Report – Executive Summary 

On  the  positive  side  various  methods  are  available  but  some  contradictory  results  are 
likely  to  turn  up.  Further  methodological  improvements  may  help  to  overcome  this 
situation. At the same time, using more than one approach to measure the outcomes of 
a RDP contributes to a more complete picture of the overall effects. 

Costs  of  applying  methods:  One  important  observation  is  that  non-quantitative 
methods impose high variable costs – each case study costs more or less the same and 
the  costs  are  not  negligible.  Quantitative  methods  such  as  IO  or  PSM  exhibit  scale 
economies – analysing a large number of cases implies that the costs per case drop as 
more  cases  are  analysed.  However,  in  order  to  use  such  methods,  it  is  necessary  to 
invest  in  specific  infrastructure  like  micro-data  sets  or  regional  IO  tables.  These 
economic  implications  are  important  to  consider  when  programmes  and  evaluation 
strategies are developed. 

Specific knowledge: In order to analyse measures of RDP, very specific knowledge is 
necessary.  The  programmes  are  very  complex  and  the  situations  are  heterogeneous, 
even within countries. This is not unexpected because the programmes are fine-tuned to 
the situations in a given region.  

Use of standardised data sets: The availability of standardised data sets (e.g. input-
output  tables  for  EU  Member  States,  FADN  data)  is  a  big  advantage  for  quantitative 
methods. There are significant economies of scale for methods using such data. Given 
data were available for all regions, it might even be possible to analyze a large number 
of measures for all regions with a small team of experts. Such an approach seems to be 
necessary  even  in  cases  where  in  one  region  sample  sizes  of  beneficiaries  or  non-
beneficiaries  are  too  small.  Having  more  regions  where  the  same  measure  is  applied 
might increase the sample size. 

FADN  data:  FADN  data  are  very  useful;  however  their  usefulness  is  contingent  upon 
the link to other administrative data. For the purpose of evaluation, such a link should be 
the standard procedure in all regions and programmes. This would be a way to identify 
causal effects for a large number of cases. Using such an approach would improve the 
validity of the evaluation studies considerably. 

IO case studies: The case studies show that this method and those that use the same 
data  may  deliver  a  wide  range  of  interesting  results.  The  IO  method  is  a  standard 
approach  in  economics  and  because  it  is  so  standardised  there  is  large  expertise 
available. What is not available are sufficient data for all regions. One recommendation 
is to establish the necessary data that are used for IO or similar models already at the 
beginning of the programming period (in particular regional input output tables). Such an 
approach  would  allow  consistently  deriving  targets,  and  carrying  out  mid-term  and  ex 
post  analyses  within  the  same  methodological  framework  for  a  number  of  important 
indicators. 

Recommendations for planning evidence-based evaluations: If it is not possible to 
identify a method that can be used to evaluate the intended effects of a measure, it is 
strongly  recommended  to  reconsider  the  implementation  of  the  measure.  This 
recommendation  is  based  on  the  insight  that  "you  cannot  control  what  you  cannot 
measure". When a programme is designed and when targets are set, it is advisable to 
keep already in mind which method to use to evaluate the outcomes. It is evident that 
quantitative input data are necessary when quantitative results are expected. Collecting 
this  information  not  only  for  beneficiaries  but  also  for  non-beneficiaries  is  important 
when econometric methods are intended to be used.  

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doi: 10.2762/63445