Ex-Post Evaluation of the Rural Development …...Ex-Post Evaluation of the Rural Development...

Ex-Post Evaluation of the Rural Development Programme Ireland (2007-2013)

Final Report

Submitted to

Department of Agriculture, Food and the Marine

By

Indecon International Economic Consultants

in association with the

Countryside and Community Research Institute, University of Gloucestershire

www.indecon.ie

23rd January 2017

http://www.indecon.ie/

Contents

Indecon International Consultants and Countryside and Community Research Institute


Executive Summary i

1 Introduction and Background 1

1.1 Introduction 1 1.2 Background 1 1.3 Report Structure 2 1.4 Acknowledgements and Disclaimer 3

2 The Evaluation Context 4

2.1 Overview of Strategic and Policy Context for Programme 4 2.2 Review of Developments in External Environment to Programme 6 2.3 Summary 11

3 Methodological Approach 13

3.1 Introduction 13 3.2 Overview of Methodological Approach to Evaluation 13 3.3 Consultation Programme 15 3.4 Extensive New Survey Evidence 15 3.5 Detailed Analysis of Indicator Data 17 3.6 Case Studies 17 3.7 Bio-Economy Input-Output Model 18 3.8 Econometric Counterfactual Impact Evaluation 18 3.9 GIS Spatial Analysis 19 3.10 Summary 19

4 Description of Programme, Measures and Budget 20

4.1 Introduction 20 4.2 Programme Implementation and Composition 20 4.3 Intervention Logic 25 4.4 Budget and Programme Funding Balance 25 4.5 Overall Programme-level Expenditure Progress 31 4.6 Summary 32

5 Answers to Evaluation Questions: Programme Level 34

5.1 Introduction 34 5.2 Measuring Wider Social and Economic Impacts 34 5.3 Technical Assistance 39 5.4 Summary 40

6 Answers to Evaluation Questions: Axis 1 41

6.1 Introduction 41 6.2 Implementation and Composition of Axis 1 41 6.3 Axis 1 – Indicators 44 6.4 Measure 112/113 – Early Retirement Scheme and Young Farmers Installation Scheme 45 6.5 Measure 121: Modernisation of Agricultural Holdings 62 6.6 Summary 78

Contents

Indecon International Consultants and Countryside and Community Research Institute


7 Answers to Evaluation Questions: Axis 2 80

7.1 Introduction 80 7.2 Implementation and Composition of Axis 2 80 7.3 Axis 2 - Indicators 83 7.4 Measure 212 – Less Favoured Areas Scheme 84 7.5 Measures 213, 214 and 216 – Agri-Environmental Measures 96 7.6 Measure 111 – Agri-Environmental Training 116 7.7 Organic Farming Scheme 119 7.8 Summary 125

8 Answers to Evaluation Questions: Axis 3/4 127

8.1 Introduction 127 8.2 Implementation and Composition of Axis 3 and 4 127 8.3 Axis 3 and 4 - Indicators 136 8.4 Summary 150

9 Conclusions and Recommendations 151

9.1 Introduction 151 9.2 Detailed Conclusions from Evaluation 151 9.3 Recommendations 161

Indecon International Consultants


Tables & Figures

Table 2.1: Irish Economic Indicators, 2007 to 2013 7

Table 3.1: Primary Research – Details of Response Rates Achieved 16

Table 3.2: Primary Research - Tests of Validity of Samples 17

Table 4.1: Rural Development Programme, Ireland (2007-2013) – Summary of Programme Priorities/Axes and Measure-level Supports 21

Table 4.2: Indicators and Targets for Axis 1 24

Table 4.3: Rural Development Programme for Ireland – Comparison of 2010 Revisions with Original Budgetary Allocations 28

Table 4.4: Indicative Breakdown by Rural Development Measure 29

Table 4.5: Financial Implementation of the Rural Development Programme and National Strategy Plan – Overall Funding and Expenditure Summary (2007-2013) 31

Table 4.6: Financial Implementation of the Rural Development Programme and National Strategy Plan - Overall Funding and Expenditure Summary (2007-2014) 32

Table 5.1: Direct + Indirect Multiplier Impacts of Primary Agriculture Sectors, 2010 35

Table 5.2: Estimated RDP Expenditure Impacts, 2007-2013 36

Table 5.3: Estimated Overall RDP Expenditure, Direct, Indirect and Induced Impacts, 2007-2013 36

Table 5.4: Estimated Overall Employment Impacts of RDP Expenditure Direct, Indirect and Induced Impacts, 2007-2013 36

Table 5.5: Estimated Regional RDP Expenditure Impacts, 2007-2013 38

Table 5.6: Estimated Regional Employment Impacts of RDP Expenditure, 2007-2013 38

Table 5.7: Supply-side Impacts of RDP 39

Table 6.1: Actual v Financial Plan Expenditure (Axis 1) 44

Table 6.2: Rural Development Programme – Axis 1 Indicators 44

Table 6.3: Measures 112-113 – Annual Expenditure – 2007-2013 48

Table 6.4: Output Targets and Indicators for Measure 112 under the RDP 2007-2013 49

Table 6.5: Output, Impact and Result Targets and Indicators for Measure 113 under the RDP 2007-2013 50

Table 6.6: Current Age of Retired Farmers Who Participated in ERS Scheme 52

Table 6.7: Current Age of Successor to Farmers Who Participated in ERS Scheme 52

Table 6.8: Views on Targeting of Early Retirement Scheme 53

Table 6.9: Main Factors Behind Farmers’ Decision to Retire 54

Table 6.10: Views on the Change in the Management of the Farm 54

Table 6.11: Counterfactual Scenario In Absence of ERS 56

Table 6.12: Percentage Estimates of relationship between Output and being over 65 58

Table 6.13: Impact of Farmer Age on Output – Econometric Panel Data Models 59

Table 6.14: Impact of age on productivity panel models 60

Table 6.15: Targeted Agricultural Modernisation Scheme (TAMS) – 2010-2013 64

Table 6.16: Programme Logic Model – Measure 121 – On-Farm Investment 65

Table 6.17: Annual On-Farm Investment (Measure 121) Expenditure – 2007-2013 65

Table 6.18: On-Farm Investment (Measure 121) Expenditure – Actual versus Budgeted 66

Table 6.19: Output, Impact and Result Targets and Indicators for the Combined Measure 121 under the RDP 2007-2013 66

Table 6.20: Output Indicators for Measure 121 under the RDP, 2013 68



Table 6.21: Results from Measure 121 68

Table 6.22: Scheme Used by Farmer 69

Table 6.23: Type of Farming Activity Practiced by Farmer 69

Table 6.24: Nature of Investment Supported by the Scheme 70

Table 6.25: Counterfactual Scenario - Funding in Absence of TAM/FIS Supports 72

Table 6.26: Counterfactual Scenario - Activities in Absence of TAM/FIS Supports 73

Table 6.27: Impact of Investment on Farm 73

Table 6.28: Econometric results - Impact of Capital input on output (Translog model) 74

Table 6.29: Summary of Capital Elasticity of Output 74

Table 6.30: Impact of investment on output panel models 75

Table 6.31: New Econometric Evidence of Impact of Building Grants and Land Improvement Grants on Output 76

Table 6.32: New Econometric Evidence of Impact of Building Grants and Land Improvement Grants on Productivity 77

Table 7.1: Actual v Budgeted Expenditure (Axis 2) 82

Table 7.2: Rural Development Programme - Axis 2 Indicators 83


Table 7.4: Extent of Impact of LFA Scheme Requirements on Farming Methods 94

Table 7.5: Views on Adequacy of Levels of Compensation in LFA Scheme 95

Table 7.6: Views on Effects of LFA Payments on Farm Outcomes 95


Table 7.8: Overall Output, Impact and Result Targets and Indicators for Measure 214 under the RDP 2007-2013 102

Table 7.9: Family Farm Income and Direct Payments for REPS and Non REPS Farms by Type of Farming, 2009 103

Table 7.10: Square Kilometres of land in receipt of REPS funding by County 104

Table 7.11: Extent of Impact of REPS/AEOS Scheme Requirements on Farming Methods 110

Table 7.12: Views on Adequacy of Levels of Compensation in REPS/AEOS Schemes 111

Table 7.13: Views on Effects of REPS/AEOS Payments on Farm Outcomes 111

Table 7.14: Impact on farms of receipt of REPS and AEOS funding in terms of farm output levels 112

Table 7.15: Impact on farms of receipt of REPS and AEOS funding in terms of farm productivity 113

Table 7.16: Impact of investment on output panel models 114

Table 7.17: Impact of age on productivity panel models 115


Table 7.19: Views on Usefulness of Training 118

Table 7.20: Views on Usefulness of Training by Type of Scheme 118

Table 7.21: Expenditure on Organic Farming Scheme (2007-2013) 120

Table 7.22: Payments applicatiable under the OFS/AEOS (2007-2013) 121

Table 8.1: Programme Logic Model - Measure 112/113 128

Table 8.2: Actual v Budgeted Expenditure (Axis 3 and 4) 130

Table 8.3: Views on Administration of the Scheme 131

Table 8.4: Views on Level of Support and Advice Provided Whilst Running the LAG 132

Table 8.5: Views on Potential Additional Training 132



Table 8.6: Views on Level of Community Participation in the Development of Proposals 133

Table 8.7: Views on Main Obstacle Faced by Applicants 133

Table 8.8: Views on Quality of Grant Applications 134

Table 8.9: Level of Interaction with Other LAGs 134

Table 8.10: Rural Development Programme - Axis 3 Indicators - Summary of Progress versus Target 135

Table 8.11: Views on Achievement of Key LEADER Principles 136

Table 8.12: Views on Overall Impact of LEADER Programme on Rural Development 136

Table 8.13: Measure 311 - Diversification into Non-Agricultural Activities – Quantified Targets for EU Common Indicators 137

Table 8.14: Measure 311 - Diversification into Non-Agricultural Activities - Output Indicators 137

Table 8.15: Measure 312 - Support for Business Creation and Development – Quantified Targets for EU Common Indicators 139

Table 8.16: Summary of Result Indicators by Measure – Measure 312: Support for Business Creation and Development 139

Table 8.17: Measure 313 – Encouragement of Tourism Activity – Quantified Targets for EU Common Indicators 140

Table 8.18: Summary of Output and Result Indicators – Measure 313: Encouragement of Tourism Activities 140

Table 8.19: Measure 321 – Basic Services for the Economy and Rural Population – Quantified Targets for EU Common Indicators 141

Table 8.20: Summary of Output and Result Indicators – Measure 321: Basic Services for the Economy and Rural Population 141

Table 8.21: Measure 322 – Village Renewal and Development – Quantified Targets for EU Common Indicators 142

Table 8.22: Summary of Output and Result Indicators – Measure 322: Village Renewal and Development 143

Table 8.23: Measure 323 – Conservation and Upgrading of the Rural Heritage – Quantified Targets for EU Common Indicators 143

Table 8.24: Summary of Output and Result Indicators – Measure 323: Conservation and Upgrading of the Rural Heritage 144

Table 8.25: Measure 331: Training and Information – Quantified Targets for EU Common Indicators 144

Table 8.26: Summary of Output and Result Indicators – Measure 331: Training and Information 145

Table 8.27: Views on Training Opportunities Available to Members of Community 145

Table 8.28: Measure 341: A Skills-Acquisition and Animation Measure– Quantified Targets for EU Common Indicators 146

Table 8.29: Summary of Output and Result Indicators – Measure 341: Skills acquisition, animation and implementation 146

Table 8.30: Views on Level of Community Activism in the Region 147

Table 8.31: Measure 41 (inclusive of Measures 411 and 413): Implementing Local Development Strategies – Quantified Targets for EU Common Indicators 149

Table 8.32: Measure 421: Implementing Co-Operation Projects – Quantified Targets for EU Common Indicators 149

Table 9.1: Estimated Regional RDP Expenditure Impacts, 2007-2013 160

Table 9.2: Recommended Actions 161



Figure 2.1: Irish Unemployment Rate and Live Register Figures 2007-2013 7

Figure 2.2: Agriculture, Forestry and Fishing GVA as a Percentage of Total GVA (2006-2013) 9

Figure 2.3: Employment in the Agriculture, Forestry and Fishing Sector (2007-2013) 10

Figure 2.4: Agricultural Input and Output Price Indices (2007-2013) 10

Figure 3.1: Schematic Description of Methodological Approach to Evaluation 13

Figure 4.1: RDP Specific Intervention Logic 25

Figure 6.1: RDP Expenditure on Measures in Axis 1 - Ireland v EU27 (As a Percentage of Overall RDP Expenditure) 42

Figure 6.2: RDP Expenditure on Measures in Axis 1 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure) 43

Figure 6.3: Balance of Budget between Measures 112 and 113 for Ireland and EU27 48

Figure 6.4: Gender Impact of YFIS and ERS 51

Figure 6.5: Level of Education of Respondent and Successor to Farm for ERS Beneficiaries 53

Figure 6.6: Outcome of YFIS without Installation Aid 55

Figure 6.7: Average Age of Irish Farmers, 2000-2010 57

Figure 6.8: CAO applications for Agriculture/Horticulture, 2000-2016 62

Figure 6.9: Supply of Credit and Changes in Bank Lending Conditions, 2007-2010 71

Figure 6.10: Breakdown of Supported Holdings by Age of Approved Applicants 72

Figure 7.1: RDP Expenditure on Measures in Axis 2 - Ireland v EU27 (As a Percentage of Overall RDP Expenditure) 81

Figure 7.2: RDP Expenditure on Measures in Axis 2 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure) 82

Figure 7.3: Programme Logic Model - Measure 212 85

Figure 7.4: Number of beneficiaries of Measure 212 86

Figure 7.5: Survey Reponse on Importance of CAP to Stimulate Growth/Jobs in Rural Areas 88

Figure 7.6: Family Farm Income, Broken down by LFA/DAS recipients and non-recipients, 2010 88

Figure 7.7: Share of direct payments & total subsidies in agri factor income (2010-4 average) 90

Figure 7.8: Map of Areas of Highest Threat of Farm Abomdonment (main) 91

Figure 7.9: Land use in Ireland, 1990-2012 92

Figure 7.10: Hierarchy of Environmental Requirements/Supports 97

Figure 7.11: Programme Logic Model – Agri-Environmental Measures 100

Figure 7.12: REPS Funded Land and Natura 2000 SPA in 2013 105

Figure 7.13: REPS Funded Land and Natura 2000 SACs in 2013 106

Figure 7.14: REPS Funded Land Holdings and Natura 2000 SACs in 2013 107

Figure 7.15: Programme Logic Model – Measure 111 117

Figure 7.16: Programme Logic Model – Organic Farming Scheme 119

Figure 7.17: Extent of Organic Farming in Europe 123

Figure 8.1: Number of Projects under Measure M311 - Diversification into non-agricultural activities, by year, 2007-2013 129

Figure 8.2: Maximum, Minimum and Average Expenditure Across Measures by Local Action Groups, 2007-2013 130

│ Executive Summary



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Executive Summary

Introduction and Background

This independent report is submitted to the Department of Agriculture, Food and the Marine, and the European Commission, Directorate-General for Agriculture and Rural Development, by Indecon International Research Economists in association with the Countryside and Community Research Institute, University of Gloucestershire. The report concerns the Ex-Post Evaluation of the Rural Development Programme, Ireland (2007-2013).

The background and policy context for the ex-post evaluation of the RDP for Ireland is Council Regulation (EC) No 1698/2005 which sets the legal framework for rural development support for the period 2007-2013. Taking into account the EU and Irish policy contexts, and an assessment of the baseline position in terms of the stage of development of the rural economy and the agriculture and agri-food sectors, the Programme identified the following priority areas:

Axis 1: Improving the competitiveness of agriculture by supporting restructuring, development and innovation;

Axis 2: Improving the environment and the countryside by supporting land management; and

Axes 3 and 4: Improving the quality of life in rural areas and encouraging diversification of economic activity.

There is a requirement for an ex-post evaluation of all Member States RDPs to be carried out and submitted to the European Commission by December 2016. This evaluation addresses a detailed terms of reference which meets European Commission and national requirements. This is also consistent with the need for an evidence-based approach to ensure the most effective use of scarce EU and national resources.

Evaluation Context

The 2007-2013 RDP represented the action plan which resulted from the National Strategy Plan (NSP) for rural development (2007-2013). The NSP was guided by the White Paper on Rural Development, in which the Irish Government underlined its commitment to ensuring the economic and social wellbeing of rural communities. As noted in the NSP, the White Paper “defined the policy agenda as all government policies and interventions that are directed towards improving the physical, economic and social conditions of people living in rural areas. It emphasised that policies would aim to facilitate balanced and sustainable regional development while tackling the issues of poverty and social inclusion.” The RDP was consistent with the EU strategic guidelines for rural development. It also reflected a number of national policy documents and a detailed baseline assessment of the area covered by the Programme.

The national policy influences on the 2007-2013 RDP included the findings of the 2006 report of the Agri Vision 2015 Committee. This report identified a number of issues that were crucial to the development of the Irish agri-food sector and on foot of this made a number of recommendations to address these concerns, including inter alia the requirements to facilitate and encourage market-driven development of the sector; make explicit and provide adequately for agriculture’s role in the production of environmental goods; and provide an appropriate framework to encourage an approach to rural development that takes account of the prevailing economic and social realities of rural Ireland.




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The allocation of funding across the axes of the 2007-2013RDP was designed to conform to a specific balance requirement in relation to the EU/EAFRD funding component, as follows:

Competitiveness of agricultural sector (Axis 1) – 10% of overall EAFRD funding;

Improving the environment and the countryside (Axis 2) – 80% of overall EAFRD funding;

Diversification/quality of life – Axes 3 and 4 – 10% of overall EAFRD funding.

The priority given to improving the environment and the countryside is noteworthy.

Ireland faced a major economic crisis in the early years of the last RDP. This was in part due to the international recession and the related credit crunch on international financial markets. It also reflected structural problems in the Irish economy including the unsustainably high level of activity in Ireland’s construction sector. The crisis manifested in a surge in unemployment and a sharp decline in Irish economy GDP/GNP. Following a long period of rapid economic growth, GDP and GNP declined sharply in 2008 and 2009. The Irish economy only returned to economic growth in 2011.

Due to the rapid deterioration in the Exchequer financial position following the crisis in 2008/09, there was a fundamental re-prioritisation of resources and a change in approach to the nature and type of activities funded under the RDP. In particular, the budgetary situation resulted in the decision to suspend some schemes to new applicants and to reductions in support levels on other schemes. In the latter half of the programme period some schemes were reopened or changed. The following outlines some of the key changes made to schemes during the 2007-2013RDP:

Closure of the Farm Improvement Scheme (Measure 121) in October 2007, due to the scheme being fully subscribed at that point;

Suspension/closure to new applicants of the Young Farmers Installation Scheme (Measure 112) and the related Early Retirement Scheme (Measure 113) in October 2008;

Reduction of the maximum hectare limit on which payments were made available under Less Favoured Areas scheme (Measure 212) in October 2008;

Reduction in the rate of the Rural Environment Protection Scheme (REPS) (Measure 214) payments in 2009 and the subsequent closure of the fourth iteration of the scheme to new entrants in the same year;

Closure to new entrants in July 2009 of a Natura 2000 measure linked to REPS 4 (although a new reduced-budget Natura 2000 scheme was introduced linked to AEOS); and

Changes to the Disadvantaged Areas Scheme in 2012.

Methodological Approach to Evaluation

In line with European Commission guidance and suggestions,1 Indecon has attempted to use a range of advanced and rigorous methods to empirically evaluate the impact of the 2007-2013 RDP Ireland. We have, where feasible, applied a ‘triangulation’ of methodologies, with the objective of cross-confirming qualitative and quantitative measures and, where possible, to evaluate counterfactual impacts. As the RDP assistance covered so much of the farming sector in Ireland, counterfactual analysis is difficult, but we have addressed this challenge with a number of different methodologies.

1 See: Ex Post Evaluation of RDPs 2007-2013 Expectations and Use, GPW Methods for assessing impacts of RDPs, 2007-2013. Practices and Solutions for the ex post evaluation, Palermo, July 2016, Fernando Fonseca DG Agri, Unit 4, Evaluation and Studies.




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Specifically, given the above issue, combined with the diversity of the Programme and the data constraints which exist, our approach has involved the application of the following seven methodologies:

1. Bio-Economy Input-Output Model;

2. Econometric Counterfactual Models;

3. Spatial, GIS-based Analysis;

4. Consultation Programme;

5. Case Studies;

6. Extensive New Survey Evidence;

7. Detailed Analysis of Indicator Data.

Budget and Expenditure

As background context it is important to compare the outturns on programme expenditure levels to the budgets set for the programme and its constituent measures/supports. Overall cumulative expenditure on the 2007-2013 RDP for Ireland totalled €4,228 million, which included expenditure that took place in 2014 and 2015 which was funded from the Programme. Total final programme expenditure expressed as a percentage of the revised allocation for the overall RDP was 98.2%. The largest component of overall programme expenditure was under Axis 2, which spent €3,532.5 million, or 98% of the final funding allocation for this axis. Axes 1 and 3/4 spent over 97% of their budgets, with expenditure amounting to €378.9 million and €326.4 million respectively.

Financial Implementation of the Rural Development Programme and National Strategy Plan - Overall Funding and Expenditure Summary (2007-2015)

Axis and Total

Revised Funding Allocation in € Million (2007 – 2013) (EAFRD +

Matching National +Health Check + EERP funds)

Actual Cumulative Expenditure - 2007-

2014 - € Million

Expenditure to date as % of RDP Allocation

Axis 1 388.4 378.9 97.6%

Axis 2 3,593.2 3,521.5 98.0%

Axes 3/4 324.6 326.4 100.6%

Total Axes 1 to 4 4,306.2 4,226.8 98.2%

Technical Assistance 1.9 1.9 100.0%

Overall RDP 4,308 4,228.7 98.2%

Source: Analysis based on data supplied by Department of Agriculture, Food and the Marine




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In relation to Axis 1, the budget shares of each measure relative to the aggregate of axis expenditure are shown in the figure overleaf. While the proportion of overall expenditure on Measure 121 (modernisation of Agricultural Holdings) was less than one quarter of that across the EU27, when expressed as a proportion of aggregate Axis 1 expenditure the two are of similar scale. Measure 121 accounted for almost one-third of Ireland’s expenditure under Axis 1, compared to approximately 40% of EU27 expenditure. The figure also illustrates the relatively large budget share dedicated to the Early Retirement Scheme compared to elsewhere in Europe, accounting for approximately 60% of Ireland’s expenditure within Axis 1. This in part reflected the strategic challenge of the age profile of the Irish farming sector.

RDP Expenditure on Measures in Axis 1 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure)

Source: Indecon analysis

The budget shares of each measure compared with the aggregate of Axis 2 expenditure are shown in the figure overleaf. The analysis illustrates that the budgetary share allocated to each measure in Ireland closely matched the distribution across the EU if Measure 211 and Measure 212 are considered as de-facto a single measure.




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RDP Expenditure on Measures in Axis 2 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure)


Overall Impact on Rural Economy in Ireland

Our modelling results based on the application of a bio-economy input-output model suggests that the RDP expenditure had a significant impact on the level of economic activity in the broader rural economy in Ireland. Expenditures resulted in significant benefits both to farmers and the rural communities within which they live.

The results of the analysis are shown in the table overleaf. They indicate that the total direct plus indirect impact of RDP expenditure on the rural economy was of the order of €3,532m in output, compared to the aggregate national impact of RDP expenditure of €4,184m. As such, 84% of the estimated direct plus indirect benefit of RDP expenditures was felt within the rural economy. This excludes the economic and social benefits of any wider supply-side impacts.

M227-Non-productive investments

M226-Restoring forestry potential and introducing prevention actions

M225-Forest-environment payments

M224-Natura 2000 payments

M223- First afforestation of non-agricultural land

M222-First establishment of agroforestry systems on agricultural land

M221-First afforestation of agricultural land


M215-Animal welfare payments

M214-Agri-environment payments

M213-Natura 2000 payments and payments to Dir. 2000/60/EC

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

M211-Natural handicap payments to farmers in mountain areas

0% 10% 20% 30% 40% 50% 60%

EU27 Ireland




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Estimated Regional RDP Expenditure Impacts, 2007-2013

Direct Impacts

Direct + Indirect Impacts

Direct + Indirect + Induced Impacts

€m

Regional Impact – Output* €2,240 €3,185 €3,532

Source: Indecon Expenditure Impact Assessment Model

* These are derived by getting the product of the RDP expenditure by first-round regional expenditure share

Indecon’s modelling also estimates that expenditures under the 2007-2013 RDP Ireland supported 4,692 jobs on an annual basis in the rural economy (see table below). This represents an important programme-wide socio-economic benefit of the 2007-2013 RDP.

Estimated Regional Employment Impacts of RDP Expenditure, 2007-2013

Employment Annually

Employment Impacts 4,692


Axis 1 Objectives and Measures

The aim of Axis 1 of the 2007-2013 RDP was to contribute to improving the competitiveness of agriculture by supporting restructuring, development and innovation. This was achieved through two policy streams – addressing the age profile of Irish farming (namely through Measures 112 and 113) and promoting on-farm investment (via Measure 121). At the outset of the programme, the Early Retirement Scheme (Measure 113) was the largest scheme within this axis, accounting for around two-thirds of total budgeted expenditure, with the Farm Improvement Scheme (Measure 121) constituting a large majority of the remainder, and relatively limited expenditure on the Young Farmers Installation Scheme (Measure 112).

The two schemes aimed at promoting a structural improvement in the age profile of Irish farming, namely the Early Retirement Scheme and the Young Farmers Installation Scheme, were not of a sufficient scale to have a material impact on the overall age distribution of farmers. However, econometric evidence presented in this report shows that older farmers have lower levels of output relative to other farmers, which supports the rationale for implementing policies designed to deliver a structural improvement in the age profile. Younger farmers may also be more open to implementing measures to enhance the environmental impact of the agri sector.

Indecon believes it is important to examine the counterfactual impact of RDP expenditures where feasible and in particular to examine what levels of investment would have occurred without the RDP. To undertake this our econometric modelling included an explanatory variable for ‘capital investment’. We ran the models for Building Grants, and Land Improvement Grants as the ‘treatment’, and for each of ‘output’ and ‘productivity’ as the dependent variable.




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In general, the econometric research found that building grants funded under the RDP had small and positive statistically significant impacts on output and productivity, while land improvement grants had an insignificant impact. The estimated impact is the ATET or ‘Average Treatment Effect on the Treated’, so the interpretation is that farm output or farm productivity for the ‘average’ farmer who received the grant is higher than it otherwise would have been, had they not received the grant, and controlling for the explanatory factors including, labour, capital, fuel, age, soil type, size and year.

The results of the counterfactual impact modelling on output as the dependent variable suggest that building grants increased output by approximately 3.4%, holding all other factors equal, that is to say, a 10% increase in the grant increases output by 3.4%. The impact of Land Improvement grants was insignificant.

The responses to Indecon’s survey research among RDP beneficiaries also indicated a positive perception among beneficiaries of both of the on-farm investment schemes (FIS and TAMS) regarding their impact on the competitiveness of their farms. Further, econometric evidence suggests that increased investment in agriculture is likely to enhance output and productivity.

The extent of change brought about by the financial crisis caused significant disruption to the operation of the 2007-2013 RDP, though the extent of the financial crisis could not reasonably have been predicted in advance by the designers of the Programme. However, it is likely that some of the measures, in particular the FIS/TAMS measure, are likely to have helped to mitigate some of the effects of the financial crisis on the farming community during this period.

Overall, Axis 1 measures are believed to have positively contributed to the competitiveness of the agri sector (common evaluation question 15), mainly through the on-farm investment schemes, as the two age-related schemes (ERS and YFIS) were of too small a scale in aggregate to have had a significant impact.

Axis 2 Objectives and Measures

The aim of Axis 2 of the 2007-2013 RDP was to improve the environment and the countryside by supporting land management. The axis accounted for a large majority of total RDP spend. Taking into account the introduction of the new Agri-Environmental Options Scheme and the Natura 2000 measure, half of the proportion of overall programme funding was devoted to agri-environment schemes, while funding allocated to the Less Favoured Areas scheme accounted for just under one third of total programme expenditures.

The core objective of the LFA scheme was based on the contention that the environmental and related public goods that are of value in the countryside stem from appropriate land management, and specifically agricultural management. These are difficult to assess given the nature of the results and impact indicators available. However, it is of note that a Eurobarometer survey conducted in 20152 suggested that the majority of Europeans consider investing in rural areas to stimulate economic growth and job creation (47%), and strengthening the farmer’s role in the food chain (45%) to be “very important”.

For Irish respondents, the figures were 63% and 59% respectively, suggesting strong support for the contention that stimulating economic life in areas which might otherwise suffer land abandonment represents ‘public goods’.

2 Published in 2016.




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Our analysis suggests that it is likely that in the absence of the Common Agricultural Policy (CAP) and the supports provided by the RDP more significant levels of land abandonment would have resulted. As a result of these supports, land abandonment does not appear to be an imminent threat.

EU research on the risk of farm abandonment in different Member States is consistent with the designation of disadvantaged regions in Ireland under the 2007-2013 RDP, which targeted those areas where the threat of land abandonment was greatest.

Indecon has undertaken a counterfactual econometric model to assess the impact of farmers’ participation in the agri-environmental measures, including REPS and AEOS. The models suggest that REPS and AEOS grants increased output by 2.1%, holding all other factors equal, for every 10% increase in the level of grant funding received. This is the average impact on the treated. Such an increase in output and its impact on farm viability, is also likely to have potential environmental benefits if it results in reducing the risk of land abandonment.

The available indicator data for Axis 2 measures were not sufficient to evaluate the specific environmental impacts of the individual measures. Other qualitative evidence, however, suggests that the impact of programme supports on the environment is likely to have been positive. A majority (70.2%) of farmers surveyed by Indecon suggested that the agri-environmental schemes under the 2007-2013 RDP had a moderate or significant impact on their farming methods. It also showed that 93.6% of farmers felt that it had helped protect the environment and 77.3% felt that it had impacted on water management, while 77.1% felt that it had impacted on biodiversity on the farm. Caution should be exercised in basing conclusions on subjective survey results and as part of this evaluation we have examined other approaches to evaluate the likely impacts.

Specifically, Indecon has applied an innovative GIS/spatial analysis to provide insights into the extent to which the agri-environmental schemes were applied in areas of most environmental and ecological significance in Ireland. This analysis is similar to the interesting spatial analysis presented by Slovenia at the European Commission’s workshop in Palermo in July 2016.3 Indecon obtained data on the areas of land in receipt of REPS and AEOS payments in 2013 and completed a spatial analysis in tandem with data on Special Protected Areas (SPA) and Special Areas on Conservation (SAC) under Natura 2000 in Ireland.

This spatial analysis suggests that the distribution of REPS funding in Ireland, while spread across the country, was particularly focused in those regions of the country which contained the largest areas designated as being of particular environmental or ecological significance. This is important in considering the counterfactual impact analysis of these measures.

The next table overleaf presents aspects of this spatial analysis and examines the evidence on the number of land holdings in receipt of REPS funding on a county-by-county basis with both the SACs and SPAs overlaid. The research suggests that the amount of land as a proportion of total land in receipt of REPS funding and the number of land holdings in receipt of funding appears to accord with the national distribution of designated Natura 2000 sites.

3 Use of a GIS-based method for assessment of contribution of RDP to biodiversity Mojca Hrabor, Oilos, Slovenia, EU Good Practice Workshop. Palermo July 2016




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REPS Funded Land Holdings and Designated Natura 2000 SACs in 2013

Special Areas of Conservation (SACs) Special Protected Areas (SPAs)

Source: Indecon spatial analysis of Dept. of Agriculture data

Overall, Axis 2 measures are believed to have positively contributed to improving the environmental situation in Irish rural areas (common evaluation question 16). However, Indecon believes that additional monitoring data on environmental impacts is needed to confirm these findings and we understand that research on this is being carried out under the current AEC measure (GLAS). Axis 3 and 4 Objectives and Measures

The aim of Axes 3 and 4 of the 2007-2013 RDP was to improve quality of life in rural areas and to encourage the diversification of economic activity. It had been originally expected that Axes 3 and 4 would commence early in 2008, though the process for selecting LEADER Local Action Groups (LAGs) to deliver the Axis 3 measures had to be postponed, and the first year of full implementation was 2010.

The process for dividing the budget between different LAGs was based on an independent review of the business plans of each of the groups. The allocations were subsequently amended in 2012, though some respondents to Indecon’s survey of LAGs reported dissatisfaction at this process.

In general, evidence from Indecon’s survey research suggests that a high degree of community engagement took place through the LAGs, with 89.9% of respondents indicating that LAGs significantly contributed to achieving the objectives of the local strategy and the RDP (evaluation question 22). 77.8% believed that LEADER had a significant impact in building local capacities for employment and diversification (evaluation questions 17 and 21), with a further 22.2% saying it had a moderate impact. Half of respondents stated that the implementation of the LEADER approach had a significant impact in relation to improving local governance, with 42.3% saying that there was a moderate impact from the LEADER approach.




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Indecon believes that the existence of the LEADER approach over four programme cycles is likely to have had created a local competence and resource, and encouraged communities to self-identify projects which could improve the quality of life and economic resilience of many rural towns and countryside areas.

Programme Design

Programme design across the RDP was generally good, with appropriate monitoring arrangements in place. This is of relevance to common evaluation question 14, which asks the extent to which the resources allocated were used efficiently. However, the Farm Improvement Scheme is likely to have benefited from a more rigorous screening process to ensure that investments were of a sufficiently high quality to merit public support, while the small size of the Young Farmers Installation Scheme meant it was unable to take advantage of economies of scale in scheme implementation.

Generally, the cost and weight of administration on beneficiaries was reasonable, with the exception of the Axis 3 and 4 measures, where the burden of administration appeared to be heavy for a community-led programme. However, we would caution against any specific changes which would hinder obtaining key data necessary to ensure regulatory compliance and facilitate rigorous evaluation.

Indecon found that the indicator data in many cases did not strongly contribute to an understanding of the success or otherwise of the programme. While useful in measuring inputs and activities, indicators intended to measure output, result and impact were of more limited use.

There was no formal programme intervention logic model developed as part of the Programme and this should be included in all new programmes. Indecon, however, developed such a model for this RDP which demonstrated a logical rationale for the measures implemented.

Recommendations

A number of recommendations based on the findings of the ex-post evaluation have been formulated with the objective of informing the design of future policy to support agriculture and rural communities. These recommendations are summarised in the table below.

Recommended Actions

Recommended Action(s) Suggested Responsibility

Design and administration

1. Set out the programmes intervention logic in detail; 2. Allow all scheme administration requirements to be conducted

online; 3. The impact of administrative costs should be considered when

evaluating new small schemes; 4. Improve the indicators to facilitate RDP evaluations;

DAFM

Improving the competitiveness of Irish farms

5. Address the structural issues within Irish farming; 6. Ensure sufficient finance for viable of capital projects;

DAFM

Protecting the rural environment

7. Maintain targeted payments to farmers in disadvantaged areas; 8. Improve measurement of the environmental impacts of supports; 9. Review the level of support for Organic Farming;

DAFM

Supporting rural communities

10. Streamline the administration burden on beneficiaries/project promoters while ensuring essential data is collated;

DAHRRG




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In summary, these recommendations are:

Recommendation 1: Set out the programmes intervention logic in detail

It is important in designing multi-faceted programmes of the complexity of the RDP, that the intervention logic is clearly stated, and that tensions in such programmes which aim at a number of policy goals should be adequately acknowledged and, where possible, quantified. This will give rise to better, more transparent, decision making, and more effective overall policy design.

Recommendation 2: Allow all scheme administration requirements to be conducted online

All application systems should be available on-line. This would have the effect of reducing the burden on farmers and advisors, allow for the development of databases in relation to scheme actions, help improve compliance and reduce the need for compliance checks. It would also assist in relation to programme monitoring.

Recommendation 3: The impact of administrative costs should be considered when evaluating new small schemes

Indecon believe that it is important to consider the administration costs in small schemes. However, Indecon accepts that in certain circumstances small targeted schemes to address specific issues or to pilot an innovative approach or project may be appropriate.

Recommendation 4: Improve the number of indicators required in RDP evaluations

While useful in measuring inputs and activities, indicators in the 2007-2013 RDP intended to measure output, result and impact were of more limited use. In future programmes, additional resources should be allocated to ensure the availability of relevant and rigorous indicator data.

Recommendation 5: Address the Structural Issues within Irish Farming

Irish farming has a major structural problem in relation to ageing of the farming population, which has not yet been adequately addressed. Indecon recommends that a focus is retained on addressing the structural problem of age in Irish farming, though we recognise that there is a number of possible ways that this could be achieved.

Recommendation 6: Ensure Sufficient Finance for Viable Capital Projects

Indecon believes that there is a need for ongoing focus on promoting investments which yield value-for-money in terms of improvements in productivity, competitiveness and enhancing the environment. Indecon recommends that all sources of potential support to ensure sufficient finance for viable capital investment should be investigated, including the potential use of Financial Instruments.




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Recommendation 7: Maintain targeted payments to farmers in disadvantaged areas

Indecon believes that targeted support to farmers in disadvantaged areas is appropriate to retain farming levels. However, Indecon recommends that a stricter approach based on scientific criteria relating to land quality should be implemented, to better target support at the farm land most at risk of abandonment.

Recommendation 8: Improve measurement of the environmental impacts of supports

The motivation for agri-environmental schemes is built on the contention that certain restrictions or practices which impose costs on farmers have a significant environmental benefit. While Indecon has applied a number of methods to evaluate environmental measures including econometric counterfactual modelling and geospatial analysis, we recommend that continued efforts are needed to measure the specific environmental impacts of funding to ensure that public funds are being appropriately used.

Recommendation 9: Raise the level of support for Organic Farming

Ireland may have some comparative advantages in the organic production sector. The level of subsidy available under the Organic Farming Scheme during 2007-2013 was relatively low. Indecon recommends that the rate of support should be reviewed if Ireland is to become a major source of organic food.

Recommendation 10: Streamline the administration burden on beneficiaries/project promoters

The aim of Axis 3 and 4 of the RDP was to improve the quality of life in rural areas and encouraging diversification of economic activity. The use of the bottom-up approach represents a very useful addition to the broader RDP, by creating a means to communities to develop their own projects. These measures were also important as they were the only part of the RDP which allows for the support of elements of the rural community other than farmers. The future vision of a vibrant rural Ireland will require primary, secondary and tertiary industries, and non-farming projects should continue to be funded through the RDP. Ways to reduce administrative burdens on beneficiaries/ project promoters should be considered. There are a number of ways in which these could be applied in the RDP 2014 – 2020. For example, the introduction of a small number of targeted indicator data would reduce administration. In addition we recommend greater use of online systems as standard for meeting administrative requirements. However, Indecon strongly supports ensuring that sufficient information is obtained in order to facilitate evaluation and full regulatory compliance.

Acknowledgements and Disclaimer

We would like to take this opportunity to express our gratitude to the wide range of organisations and individuals who played an important role in, or contributed to, the completion of this evaluation. We would particularly like to thank senior officials and staff within the Department of Agriculture, Food and the Marine, and within the Department of Arts, Heritage, Regional, Rural and Gaeltacht Affairs, who provided extensive inputs and assistance throughout the course of the evaluation. In addition, we would like to thank senior members of the National Rural Network for their inputs and assistance.




xiii

We would also particularly like to acknowledge the inputs of the wide range of other Departments, agencies and external organisations, including members of the RDP Monitoring Committee, who provided submissions to or who engaged with members of the evaluation team throughout the evaluation process.

Many of these individuals also attended the National Workshop that was hosted by Indecon on 27th September 2016 as part of the evaluation process and we would like to thank these individuals for their valuable contributions to the discussions during this workshop.

We are also particularly grateful to a number of senior members of staff at Teagasc, who provided access to research as well as detailed microdata from the National Farm Survey, and to staff members who participated at the National Workshop. We also acknowledge data available from the CSO.

We would like to thank the very large number of beneficiaries of RDP schemes/measures who took time from their busy schedules to contribute to this evaluation, most notably those farmers and Leader Local Action Groups who responded to Indecon’s survey research and provided valuable inputs and insights on their experiences with the programme and its impacts. A number of farmers and Leader Local Action Groups also attended the National Workshop and we were very grateful for their contributions as part of these discussions.

We would also like to express our gratitude to the European Commission and to delegates attending the Good Practice Workshop “Methods for Assessing Impacts of Rural Development Programmes 2007-2013”, held on 4-5 July 2016 in Palermo, Italy, which was also attended by Indecon.

Finally, we would like to express our gratitude to our associates on this evaluation, including Professor Janet Dwyer and Dr John Powell at the CCRI in the University of Gloucestershire, who contributed valuable inputs to a number of aspects of the evaluation.

The usual disclaimer applies and the analysis in this report remains the sole responsibility of Indecon.

1 │ Introduction and Background



1

1 Introduction and Background

1.1 Introduction

This independent report is submitted to the Department of Agriculture, Food and the Marine, and the European Commission, Directorate-General for Agriculture and Rural Development, by Indecon International Economic Consultants in association with the Countryside and Community Research Institute, University of Gloucestershire. The report concerns the Ex-Post Evaluation of the Rural Development Programme, Ireland (2007-2013).

1.2 Background

The background and policy context for the ex-post evaluation of the RDP for Ireland is Council Regulation (EC) No 1698/2005 which sets the legal framework for rural development support for the period 2007-2013. This inter alia states that an ex-post evaluation is required to be carried out by independent evaluators on each Member State’s programme and must be submitted to the Contracting Authority for onward submission to the European Commission by the 31st December 2016. Once all ex-post reviews are completed, a synthesis of individual Member State RDP ex-post evaluation reports will be undertaken by the Commission.

In line with the requirements of the Commission’s Common Monitoring and Evaluation Framework (CMEF), and the detailed guidelines provided by the European Evaluation Network for Rural Development4 (hereafter referred to as the ‘EU Guidelines’), the overall objective of this ex-post evaluation is to achieve a holistic, strategic and robust evaluation of the RDP programme in Ireland. The subject of the evaluation is the rural policy objectives set up at EU and national level, which are at the core of the programme intervention logic. The objectives of rural development policy set up by Community strategic guidelines for rural development in the programming period 2007-2013 are as follows:

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 (maximising synergies between axes); and

Achieving complementarity between Community instruments.

As a consequence of the Health Check of the Common Agricultural Policy reform, a new set of rural development priorities reflecting recent challenges for EU agriculture and rural areas, were added to the policy priorities. These important priorities are discussed further in Section 2 of this report.

4 “Capturing the Success of your RDP: Guidelines For The Ex-Post Evaluation Of 2007-2013 RDPs,” European Evaluation Network for Rural Development, European Commission’s Directorate-General for Agriculture and Rural Development, June 2014.




2

In accordance with EU and national requirements, this ex-post evaluation:

Examines the degree of utilisation of resources, the effectiveness and efficiency of the programming, its broader socio-economic impact and its impact on Community priorities;

Addresses the Common Evaluation Questions (CEQs), as set out in the CMEF guidance;

Judges the degree to which the RDP has contributed to achieving the objectives set out in the national and Community strategy, particularly in terms of direct beneficiaries;

Identifies the factors that contribute to the success or failure of programme implementation, including as regards sustainability and addressing the most important needs in the programme area;

Assesses the efficiency of the RDP in terms of the relationship between the resources allocated in the programme and the outputs/impacts achieved as a result;

Proposes measures to improve the quality of the programme and its implementation;

Reviews programme goals and identifies best practice for future policy design;

Presents conclusions and recommendations based upon the findings; and

Advises on best practice regarding future evaluation of rural intervention programmes.

A rigorous methodology was applied by Indecon in completing this evaluation, details of which are set out in Section 3 of this report. This included both qualitative and quantitative analysis, and incorporated, where feasible, best practice methodologies as discussed in the EU Good Practice Workshop in Palermo, Italy, in July 2016.5

1.3 Report Structure

The structure of this evaluation report has been informed by the CMEF guidance, and the remainder of this document is structured as follows:

Section 2 examines the strategic and policy strategic context for the RDP 2007-2013. It also examines the developments in the external environment to the programme.

Section 3 describes the work programme and methodological/analytical tools applied in completing this evaluation.

Section 4 recaps on the structure and composition of the RDP, and assesses the overall performance and expenditure outturns across the programme.

Section 5 addresses the evaluation questions at overall programme level including the broader socio-economic impact.

Section 6 addresses the evaluation questions in respect of the Axis 1 measures.

Section 7 responds to the evaluation questions in relation to the Axis 2 Disadvantaged Areas support and agri-environmental supports.

Section 8 examines the evaluation questions in relation to Axes 3-4 rural development-related measures.

Section 9 integrates the findings from the detailed evaluations undertaken in the preceding sections to develop overall conclusions and formulate recommendations.

5 See Fernando Fonscesa, Ex Post Evaluation of RDPs 2007-2013, Expectations and Use, DG Agri, Unit E4, Evaluation and Studies, Palermo July 2016




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1.4 Acknowledgements and Disclaimer

We would like to take this opportunity to express our gratitude to the wide range of organisations and individuals who played an important role in, or contributed to, the completion of this evaluation. We would particularly like to thank senior officials and staff within the Department of Agriculture, Food and the Marine, and within the Department of Arts, Heritage, Regional, Rural and Gaeltacht Affairs, who provided extensive inputs and assistance throughout the course of the evaluation. In addition, we would like to thank senior members of the National Rural Network for their inputs and assistance.

We would also particularly like to acknowledge the inputs of the wide range of other Departments, agencies and external organisations, including members of the RDP Monitoring Committee, who provided submissions to or who engaged with members of the evaluation team throughout the evaluation process.

Many of these individuals also attended the National Workshop that was hosted by Indecon on 27th September 2016 as part of the evaluation process and we would like to thank these individuals for their valuable contributions to the discussions during this workshop.

We are also particularly grateful to a number of senior members of staff at Teagasc, who provided access to research as well as detailed microdata from the National Farm Survey, and to staff members who participated at the National Workshop. We also acknowledge data available from the CSO.

We would like to thank the very large number of beneficiaries of RDP schemes/measures who took time from their busy schedules to contribute to this evaluation, most notably those farmers and Leader Local Action Groups who responded to Indecon’s survey research and provided valuable inputs and insights on their experiences with the programme and its impacts. A number of farmers and Leader Local Action Groups also attended the National Workshop and we were very grateful for their contributions as part of these discussions.

We would also like to express our gratitude to the European Commission and to delegates attending the Good Practice Workshop “Methods for Assessing Impacts of Rural Development Programmes 2007-2013”, held on 4-5 July 2016 in Palermo, Italy, which was also attended by Indecon.

Finally, we would like to express our gratitude to our associates on this evaluation, including Professor Janet Dwyer and Dr John Powell at the CCRI in the University of Gloucestershire, who contributed valuable inputs to a number of aspects of the evaluation.

The usual disclaimer applies and the analysis in this report remains the sole responsibility of Indecon.

2 │ The Evaluation Context



4

2 The Evaluation Context

2.1 Overview of Strategic and Policy Context for Programme The Rural Development Programme for Ireland (‘RDP’) represents the action plan which resulted from the National Strategy Plan (‘NSP’) for rural development (2007-2013), published in 2007,6 and formulated jointly by the former Department of Agriculture, Fisheries and Food (now the Department of Agriculture, Food and the Marine) and the former Department of Community, Rural and Gaeltacht Affairs (the rural development-related functions of which were subsequently transferred into the Department of the Environment, Community and Local Government).7

The NSP was guided by the White Paper on Rural Development,8 in which the Government underlined its commitment to ensuring the economic and social wellbeing of rural communities. As noted in the NSP, the White Paper “defined the policy agenda as all Government policies and interventions that are directed towards improving the physical, economic and social conditions of people living in rural areas. It emphasised that policies would aim to facilitate balanced and sustainable regional development while tackling the issues of poverty and social inclusion.” The RDP is consistent with the EU strategic guidelines for rural development. It also reflects a number of national policy documents and a detailed baseline assessment of the area covered by the Programme.

The national policy influences included the findings of the report of the Agri Vision 2015 Committee in 2006. This report identified a number of issues that were crucial to the Irish agri-food sector and on foot of this made a number of recommendations to address these concerns, including inter alia the requirements to:

Facilitate and encourage market-driven development of the sector;

Make explicit and provide adequately for agriculture’s role in the production of environmental goods; and

Provide an appropriate framework to encourage an approach to rural development that takes account of the economic and social realities of rural Ireland today.

These recommendations resulted in a subsequent action plan for the agri-food sector, entitled Agri Vision 2015 Action Plan. This action plan envisaged “an industry attaining optimal levels of efficiency, competitiveness and responsiveness to the market while also respecting and enhancing the physical environment.”

In 2010, the Minster for Agriculture, Fisheries and Food decided that it was necessary to renew the strategy outlined in Agri Vision 2015. This resulted in Food Harvest 2020, which was designed to be a “roadmap for the industry to build capacity, adapt to challenge and grow in the context of emerging opportunities in the decade ahead”. The three pillars of the vision of this new strategy were Smart, Green, and Growth. Smart involved developing new skills, new technologies, new markets, enhancing productivity and competitiveness. Food Harvest 2020 outlined the need to maintain Ireland’s association with ‘green’, through the implementation of world-class environmental practices. The combination of the two previous aspects leads to the third, growth.

6 Ireland Rural Development National Strategy Plan – 2007-2013. See: http://www.agriculture.gov.ie/ruralenvironment/ruraldevelopment/strategiesandprogrammes/.

7 It should be noted that the Axes 3-4 measures within the RDPI were overseen during the period 2007-2011 by the Department of Community, Rural and Gaeltacht Affairs and during the period 2011-2013 by the Department of the Environment, Community and Local Government. Axis 1 and 2 measures were overseen by the Department of Agriculture, Fisheries and Food between 2007 and 2011, and by the present Department of Agriculture, Food and the Marine between 2011 and 2013.

8 White Paper on Rural Development, 1999. See: http://www.agriculture.gov.ie/publications/1996-1999/whitepaperonruraldevelopment/

http://www.agriculture.gov.ie/ruralenvironment/ruraldevelopment/strategiesandprogrammes/

http://www.agriculture.gov.ie/publications/1996-1999/whitepaperonruraldevelopment/

http://www.agriculture.gov.ie/publications/1996-1999/whitepaperonruraldevelopment/




5

The strategy outlines its objectives for the value of primary output (to increase by €1.5 billion), for value-added outputs (increase by €3 billion) and the value of exports (to increase to €12 billion).

In October 2009 the ‘Renewed Programme for Government’ was published. This reaffirmed the Government’s commitment to the agriculture, food and rural development sectors. Commitments were provided for obtaining EU approval for the revised RDP and its implementation, consistent with full drawdown of EU funding. Assurances were included regarding increasing the area of land under organic farming, providing supports to organic farming and domestic horticulture production, and declaring Ireland as a GM-Free country.

During 2009, there was also official recognition of the ‘Environmental Pillar’ as the sixth pillar of social partnership. The Irish Environmental Network, a network of over 25 national environmental organisations, took part in social partnership and also in Monitoring Committee meetings for the Rural Development Programme, as well as the coordinating committee for the National Rural Network.

Taking into account the EU and Irish policy contexts, and an assessment of the baseline position in terms of the stage of development of the rural economy and the agriculture and agri-food sectors, the NSP developed a framework of national policies which translated into the subsequent action plan in the form of the RDP. The programme identified the following priority areas:

Improving the competitiveness of agriculture by supporting restructuring, development and innovation;

Improving the environment and the countryside by supporting land management; and

Improving the quality of life in rural areas and encouraging diversification of economic activity.

Through its support under Axis 1, the RDP was designed to enhance the competitiveness of the agri-food sector. The programme also sought to complement Ireland’s overall strategy for science, technology and innovation, which covered the period to 2013 and which provided a major commitment for research and development in agriculture and food, focusing particularly on research in sustainable agricultural production; food quality, safety and nutrition; product innovation and the rural economy.

Sustainable development is encouraged through the actions foreseen under Axis 2. In the case of Axes 3 and 4, actions include those targeting research/innovation and development, diversification, and culture/leisure/community facilities. In addition to promoting competitiveness, the Axis 3 measures also serve the objective of contributing to the Lisbon agenda in relation to social inclusion.9

Over the period of the Programme a number of changes were implemented reflecting in part the need to adjust the levels of resources allocated. In October 2008, the Early Retirement Scheme and the Young Farmers Installation Scheme were both suspended to new applications, while the maximum hectarage supported under the Less Favoured Areas scheme was also reduced. In April 2009 further adjustments were deemed necessary, including reductions in the rate of payment under the REPS Scheme.

9 In Ireland all measures listed under Axis 3 (Quality of life in rural areas and diversification of the rural economy) were delivered using the Axis 4 (LEADER) approach.




6

At EU Community level, the Health Check of the CAP was completed in 2008. As regards rural development, new challenges were identified as part of the review of the Community strategic guidelines for rural development. The Health Check provides for additional progressive modulation of direct payments for these new challenges as follows:

Climate change;

Renewable energies;

Water management;

Biodiversity;

Innovation linked to the four priorities mentioned above; and

Measures accompanying restructuring of the dairy sector.

The total original funding allocation for the RDP for Ireland amounted to €5.8 billion between 2007 and 2013. 40% of this funding was to come from the European Agricultural Fund for Rural Development (EAFRD), with the remainder coming from national funding.

In November 2008, in response to the deepening economic crisis, the European Commission launched a recovery plan which combined national action with EU policy. The European Economic Recovery Plan (EERP) proposed measures designed to boost purchasing power and generate growth and jobs. Reflecting the CAP Health Check and the EERP, additional EU funding of €146m was made available for investment under the Rural Development Programme in Ireland.

Given the scale of funding allocated to the RDP and the need to ensure the most efficient and effective use of scarce EU and national resources, this evaluation is of particular importance.

2.2 Review of Developments in External Environment to Programme

As well as the policy context it is important to consider the external environment to the RDP Programme. These developments had implications for Programme budgets and for the role played by the agricultural sector in the Irish economy. They also represent an input to evaluating the rationale and continued relevance of the Programme.

General Macro-Economic Developments

Ireland faced a major economic crisis in the early years of the RDP. This was in part due to the international recession with the related credit crunch on international financial markets. It also reflected structural problems in the Irish economy including the unsustainably high level of activity in Ireland’s construction sector. This manifested itself in a surge in unemployment, and a sharp decline in GNP. Table 2.1 overleaf presents an overview of economic developments in Ireland over the period of the RDP. Following a long period of rapid economic growth, GDP and GNP declined sharply in 2008 and 2009. The Irish economy only returned to economic growth in 2011.




7

Table 2.1: Irish Economic Indicators, 2007 to 2013

Annual % Volume Changes 2007 2008 2009 2010 2011 2012 2013

GNP (at current market prices) 5.2% -4.7% -12.9% -0.8% 1.5% 1.1% 6.1%

GDP (at current market prices) 6.6% -4.8% -9.7% -1.9% 4.7% 0.5% 2.6%

Exports 9.7% -1.3% -0.8% 6.5% 5.7% 2.5% 1.6%

Imports 5.7% 0.0% -9.1% 5.7% 5.1% 9.6% -0.3%

Inflation (CPI) 4.9% 4.1% -4.5% -1.0% 2.6% 1.7% 0.5%

Employment 3.1% -3.4% -7.8% -3.3% -0.5% 0.1% 3.3%

Source: Indecon analysis of CSO data Note: Export and Imports include both merchandise and services

Figure 2.1 below also shows the dramatic increase in unemployment following the onset of the economic crisis which meant that the role of the RDP was potentially very significant in responding to the crisis in the Irish economy. The latter three years of the RDP saw a recovery in the economy and unemployment declined in the last year of the RDP (2013).

Figure 2.1: Irish Unemployment Rate and Live Register Figures 2007-2013

Source: Indecon analysis of CSO data

Structure of Irish Agriculture

In evaluating the RDP it is important to consider the structure of Irish agriculture. Teagasc 2013 National Farm Survey (NFS) found that the average age of a farmer was 57 years, with an estimated two-thirds of farmers above this level. This is an important structural feature of Irish agriculture, which the RDP has attempted to influence. The average annual family farm income was €25,437 in 2013. Of particular significance to the RDP in the context of land abandonment objectives and in supporting the viability of rural communities is that of the 79,103 farms in Ireland, 23% had an annual family income of below €5,000. Other aspects of the structure of Irish agriculture and the rural nature of the economy compared to other EU countries is presented in Case Study 1.

0

100

200

300

400

500

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

2007 2008 2009 2010 2011 2012 2013

No. onLive

Register(000s)

UnemploymentRate (%)

Unemployment Rate No. on Live Register




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Box 2.1: Case Study 1: – Context for the Irish RDP and Comparison with EU27 – Key Findings

Introduction

In this case study, we review and contrast the national context and implementation of the RDP in comparison with other EU countries. Ireland’s regions are largely rural in character, with a landscape characterised by medium-sized and small market towns, villages and open countryside. Despite the rapid urban growth witnessed over the last three decades, Ireland is still characterised by a low-level of urbanisation, with only five main urban centres – Dublin, Cork, Galway, Limerick and Waterford. The areas with settlements of less than 5,000 persons are clustered in the West, North-west and, to a lesser extent, the Midlands. These areas are structurally weaker and traditionally linked to the agricultural economy. In recent years, many farms in these areas have obtained most of their farm incomes from non-market payments.

62% of GDP and 72% of population live in a rural environment, highlighting the importance that rural regions continue to have in terms of Ireland’s socio-economic profile. Employment patterns and GVA are also concentrated in predominantly rural regions, with 69% of employment and 62% of GVA in this type of region, against only 12% in the EU-25. These figures highlight the need for developing sustainable agriculture and the importance of diversification and growth in the non-farm rural economy.

The average farm size in Ireland is 31.8 ha. The majority of Ireland’s farms (75.2%) are between 5 and 50ha, with 17% of farms higher than 50 ha. In Ireland, around three-quarters of farmland is pasture, whereas the proportion for EU-25 is only one-third. All of Ireland’s farmland are Nitrate Vulnerable Zones (NVZ), and 6% is designated as a Natura 2000 area.

Comparative review RDP choices and rationales

Ireland’s 2007-2013 RDP was strongly focussed on agri-environmental issues. Along with the UK and to a lesser extent the Nordic countries of Sweden, Finland and Denmark, Ireland is unusual in having allocated by far the largest share of its RDP funding (80%) to agri-environmental management.

The Irish RDP was managed by the Department of Agriculture, Food and the Marine (DAFM) Rural Development Division. The (then) Department of Community, Rural and Gaeltacht Affairs (DCRGA) was originally responsible for delivering Axes 3 and 4 of the RDP, prior to subsequent departmental restructuring mid-Programme. This split approach reflected the dual nature of the programme, with the largest part focused upon agricultural land management and a separate element concerned with economic and social goals in rural communities’ development. In most other Member States, the RDP was designed by only one Ministry – typically, the agricultural one, but on occasion a more broadly-based economic or environmental body.

Across the EU-27, those RDPs in which LEADER project expenditure is most significant as a total proportion of the planned spending (Ireland, Spain, Denmark, Estonia) included some countries and regions which had longstanding LAGs and a commitment to LEADER dating back to the mid-1990s. However, the plans for LAGs in the 2007-2013 RDPs were significantly different from those which applied previously. Most notably in Ireland, LEADER groups were transformed into ‘Local Development Companies’, and were tasked with delivering funding to tackle rural social exclusion. This was particularly evident in Ireland.

Conclusion

The financial crisis, which emerged following the start of the 2007-2013 programme, dominated the implementation of the RDP in many countries across Europe. The Irish RDP was designed to assist the national challenge of maintaining employment and population for the significant percentage of population who live in a rural environment.

When broken down by region, farms in the South-East10 had the highest income per hectare (€691) and income per farm (€37,928), whilst farms in the West11 had the lowest average income per hectare (€368). These farms were also the smallest on average, with the average farm being 39 hectares. Farms in the West region also had the lowest income per farm (€14,357).

10 Which comprises of Carlow, Kilkenny, South Tipperary, Wexford, Waterford City & County.

11 Which comprises of Mayo, Roscommon, Galway and Galway City




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Developments in the Agriculture Sector

During Ireland’s economic crisis the agricultural sector also faced major challenges. The 2020 Food Harvest Report states that:

“The (agri-food) sector operates in an environment of considerable challenge. For farmers and fishermen, the disparity between the cost of production and remuneration is a critical issue for ongoing viability. At the processor and manufacturing level, a perceived lack of scale, fierce international competition, international retail consolidation and changing consumer demands are challenges which require concerted action. In a decade that begins in extremely difficult economic circumstances, farmers and fishermen have taken the brunt of a dramatic fall in returns in many sectors. Irish food and drink exports continue to struggle with currency fluctuations and a recessionary trading environment in key markets.”

Given this context, it is useful to examine the role of the agriculture and related sectors in the Irish economy over the period of the RDP. The National Income and Expenditure (NIE) figures from the CSO indicate that the agriculture, forestry and fishing sector’s share of Gross Value Added declined post-2007. The rapid changes in Irish value-added during this period renders an interpretation of the data difficult, particularly given the statistical challenge of accurately measuring significant dislocations in economic activity over a relatively short period of time. It is important to note that the percentage increased from 2009-2011, and was approximately 2.4% of total GVA between 2012 and 2013, a similar level to that which the level witnessed at the outset of the programme in 2007.

Figure 2.2: Agriculture, Forestry and Fishing GVA as a Percentage of Total GVA (2006-2013)


Data from the CSO’s Quarterly National Household Survey also reveals that there was a fall in employment in the Agriculture, Forestry and Fishing sector in the period 2009 - 2011. Employment in the sector began to increase in late 2012 before returning to pre-crisis levels in the fourth quarter of 2013. The sector as a whole employed around 116,800 persons in the final quarter of 2013. This constituted 6.1% of total employment in the economy. This represents an increase from approximately 4.6% the second quarter of 2010, when there were circa 85,000 employed in the sector. The fact that the sector’s employment share is considerably higher than its share of GVA is indicative of the labour-intensive nature of the sector.

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

2007 2008 2009 2010 2011 2012 2013

Percentageof Total Gross Value Added(Factor Cost)




10

Figure 2.3: Employment in the Agriculture, Forestry and Fishing Sector (2007-2013)


Agricultural input and output prices were affected by a range of international and domestic factors over the period of the RDP. The CSO Agricultural Price Indices show declines in both input and output price indices in 2009. However, by 2010 both indices recorded increases, with output prices growing at a faster rate than input prices, as evidenced by the figure below.

Figure 2.4: Agricultural Input and Output Price Indices (2007-2013)


As an internationally traded sector, agriculture and fisheries are very dependent on export markets. Ireland experienced a decline in agricultural exports during the first three years of the 2007-2013 RDP. However, agri-food exports increased in 2010 and recorded year-on-year growth in the period to 2010-2013.

10

8.5

10

8.7

11

2.2

11

4.3

11

6.3

11

6

11

2.5

11

6.6

10

2

97

.5

96

.2

89

.6

80

.5 85

.1 89

.9

85

.4

83

.2

85

.7

82

.4

80

.3

80

.5 87

.1

85

.6 90 9

6.2 10

3.4

11

0.6

11

6.8

0

20

40

60

80

100

120

140

Emp

loym

en

t in

Agr

icu

ltu

re, F

ore

stry

an

d F

ish

ing

(00

0s)

020406080

100120140

2007 2008 2009 2010 2011 2012 2013

Agricultural output price index Agricultural input price index




11

Table 1.5: Summary of Exports from the Agri-Food Sector, 2007 to 2013

Sub-sector

2007 2008 2009 2010 2011 2012 2013 % Change

2007 to 2013

% Share of Agri-Food Exports in

2013 Million Million Million Million Million Million Million

Dairy Products & Ingredients

2,329 2,290 1,960 2,273 2,724 2,640 2,968 27.4% 29.5%

Beef 1,570 1,607 1,397 1,573 1,860 1,900 2,248 43.2% 22.3%

Prepared Foods

1,822 1,499 1,296 1,375 1,416 1,424 1,669 -8.4% 16.6%

Beverages 1,440 1,229 1,060 1,152 1,221 1,257 1,197 -16.9% 11.9%

Pig meat 368 343 289 371 396 510 552 50.0% 5.5%

Seafood 352 335 315 336 418 534 496 40.9% 4.9%

Edible Horticulture & Cereals

249 265 198 193 238 227 222 -10.8% 2.2%

Poultry 243 203 183 203 210 221 259 6.6% 2.6%

Sheep meat 184 167 164 163 191 212 216 17.4% 2.1%

Live Animals 170 148 213 245 205 217 245 44.1% 2.4%

Total Agri-Food

8,727 8,086 7,123 7,884 8,879 9,142 10,072 15.4% 100%

Source: Bord Bia

2.3 Summary

This section described the strategic and policy strategic context for the RDP 2007-2013. It also examined the developments in the external environment to the programme which shaped the evolving funding and activities under the programme, and also the outputs and outcomes from the programme. The key findings can be summarised as follows:

The Rural Development Programme for Ireland represents the action plan which resulted from the National Strategy Plan for rural development (2007-2013) and was formulated jointly by the former Department of Agriculture, Fisheries and Food and the former Department of Community, Rural and Gaeltacht Affairs. Importantly from the perspective of programme design, the 2007-2013 RDP was consistent with the EU strategic guidelines for rural development. It also reflected a number of national policy objectives in the area of rural development as well as the development of the farming and wider agri-food sectors.




12

At EU level, the CAP Health Check and the European Economic Recovery Plan combined with national decisions to significantly alter Ireland’s Rural Development Programme and National Strategy Plan from July 2009. The Health Check provided for additional progressive modulation of direct payments for new challenges, which included climate change; renewable energies; water management; biodiversity; innovation; and restructuring of the dairy sector. Reflecting the CAP Health Check and the EERP, additional EU funding of €146m was made available for investment under the Rural Development Programme in Ireland. These decisions had very significant implications for the composition of funding across the RDP from 2009 onwards.

Through its supports/measures under Axis 1, the RDP was designed to enhance the competitiveness of the agri-food sector. The programme also sought to complement Ireland’s overall strategy for science, technology and innovation, which ran until 2013 and which provided a major commitment for research and development in agriculture and food.

Sustainable development was encouraged through the actions under Axis 2. In the case of Axis 3, rural development actions included those targeting research/innovation and development, diversification, and culture/leisure/community facilities. In addition to promoting competitiveness, the Axis 3 measures also served the objective of contributing to the Lisbon agenda in relation to social inclusion.

The economic situation in Ireland deteriorated substantially during the programme period, notably after 2008. This impacted on the RDP, both in terms of a much more constrained budgetary environment and in relation to how the lower levels of economic activity impacted on the agriculture and agri-food sectors, and on the rural economy generally in Ireland. Nevertheless, while the Irish agriculture, forestry and fishing sectors faced major challenges over the period of the RDP, by end of 2013 a recovery set in and these sectors increased, both in absolute size and as a percentage of overall gross value added in the Irish economy.

In evaluating the RDP it is important to consider the structure of Irish agriculture, including the older age profile of farmers relative to the rest of the working population in Ireland and the low average levels of income. Also of significance is the high percentage of the Irish population living in rural areas.

3 │ Methodological Approach



13

3 Methodological Approach

3.1 Introduction

This section describes the methodological approach applied by Indecon to the completion of the ex-post evaluation. In particular, it sets out the quantitative and qualitative tools applied in the analysis and assessment of programme performance and effectiveness, and describes how the evaluation addresses the evaluation questions.

3.2 Overview of Methodological Approach to Evaluation

Reflecting the detailed terms of reference, in addition to the European Commission’s CMEF guidance, a four-phased methodological approach was applied in the completion of this evaluation. A schematic overview of the work programme and methodological tools applied is provided in the figure below. Specifically, the methodology applied was organised according to the four phases set out in the CMEF guidance. Specific components of the approach are elaborated upon overleaf.

Figure 3.1: Schematic Description of Methodological Approach to Evaluation

Source: Indecon

Phase 1: Structuring Phase 2: Observing Phase 3: AnalysingPhase 4: Judging, Evaluation

Reporting

1.1: Project inception and presentation of Inception Report

2.1: Collection and interrogation of datasets, including Teagasc National Farm Survey microdata

3.2: Detailed quantitative analysis of programme financial and output progress by axis and measure

4.1: Assessment of programme resource utilisation, and balance within the programme

1.2: Definition of key terms of evaluation questions and development of judgement criteria to assess intervention logic

2.2: Consultation programme -bilateral interviews with Government Officials, relevant agencies and other stakeholders

3.3: Analysis of qualitative findings from interviews and survey research

4.2: Assessment of programme impacts, effectiveness and efficiency

1.4: Scoping of Primary Survey Research – surveys of programme beneficiaries

3.4: Calculation of direct, indirect and induced impacts of RDPI from application of BIO Economy Input-Output Model

4.3: Assessment of common and programme specific evaluation questions (CEQs and PSEQs)

1.6: Finalisation of methodologies for answering the evaluation questions (CEQs and PSEQs)

3.5: Econometric counterfactual impact evaluation of selected measure-level impacts

4.4: Assessment of programme intervention logic, incl. factors contributing to success or failure

1.5: Finalise approach to qualitative data collection, including identification of key policy experts

2.3: Questionnaire and sample design for surveys of programme beneficiaries; dissemination of surveys

4.5: Formulate Detailed Overall Conclusions and Recommendations

2.4: National Workshop with Programme Beneficiaries and Other Stakeholders

1.3: Research review on secondary sources of data/ information

2.5: Present quality-checked evaluation questions (CEQs and PSEQs)

3.8: Estimation of net effects of RDPI at beneficiary/territory level

4.6: Complete Draft Evaluation Report

4.7: Final Evaluation Report

3.1: Review of developments in external environment, incl. contextual analysis of sectoral and national economy datasets

3.7: Completion of Case Studies on thematic issues across programme

3.6: Spatial analysis / GIS mapping of measure-level supports




14

A feature of the 2007-2013 RDP was the inclusion in the programme of measures and associated schemes that operated in various forms during previous programmes as well as under the 2007-2013 programme. This relates in particular to measures and related schemes/supports which operated in the following areas:

Supports for encouragement of young farmers;

Supports to incentivize the early retirement of farmers;

On-farm investment supports;

Support to farms operating in less-favoured areas; and

Agri-environmental supports.

In evaluating the effectiveness of such measures, a challenge relates to the identification and interpretation of outcomes in terms of results and impacts that may originate from activities, and outputs occurring during previous programming periods. It would therefore ideally be useful to consider the cumulative impacts of such measures over successive programmes. However, many of the methodological evaluation tools and datasets required to robustly disentangle impacts over specific timescales are not available.

It is also important to note that forestry was not supported under the 2007-2013 RDP, and was instead funded directly by the National Development Plan (NDP). However, indicators for forestry were nevertheless included within the 2007-2013 RDP, due to the importance of forestry in the context of biodiversity, climate change and diversification into non-agricultural activities.

In line with European Commission guidance and suggestions,12 Indecon has attempted to use a range of advanced and rigorous methods to empirically evaluate the impact of programmes and measures. We have also, where feasible, applied a ‘triangulation’ of methodologies, with the objectives of cross-confirming qualitative and quantitative measures and where possible have evaluated the counterfactual impacts. The fact that such a large percentage of farms in Ireland have received funding from the RDP or other schemes, however, makes counterfactual analysis particularly difficult. Given the fact and diversity of the programme RDP and the data constraints which exist, our methodological approach has involved the following seven methodologies to evaluate the 2007-2013 RDP:

1. Consultation Programme;

2. Extensive New Survey Evidence;

3. Detailed Analysis of Indicator Data;

4. Case Studies;

5. Bio-Economy Input-Output Model;

6. Econometric Counterfactual Models; and

7. Spatial, GIS-based Analysis.

Each of the above methodologies is discussed below. We also considered the potential use of statistical/econometric Propensity Score Matching and Inverse Probability Weighted Regression Adjustment models. Indecon has used such models to measure counterfactual impacts in other





15

programmes. However, due to the scale of farmers assisted in Ireland and constraints in relation to available data, these were not feasible within the context of the Irish RDP evaluation.

3.3 Consultation Programme

An extensive programme of consultation with a range of stakeholders was completed as part of the work programme for the evaluation. This entailed the following components/tasks:

Detailed face-to-face discussions and ongoing interaction with senior officials within the Irish Department of Agriculture, Food and the Marine, and the Department of Arts, Heritage, Regional, Rural and Gaeltacht Affairs, which oversaw individual programme measures/schemes within their remit. These discussions and subsequent ongoing interactions had the objectives of accessing relevant quantitative and qualitative data, and probing the issues/factors impacting on the performance of the RDP 2007-2013 and the programme logic for different measures.

Engagement with external stakeholder organisations and programme beneficiary representative groups, including members of the RDP Monitoring Committee, inviting each organisation/group to provide a formal written submission to the evaluation team and to meet with the team.

Detailed bilateral discussions with National Rural Network.

A National Stakeholder Workshop: This entailed a focus group workshop involving participation from a diverse of beneficiaries across the programme axes, as well as relevant agencies and other national stakeholder groups. A total of 49 individuals attended the workshop, which was held at the Hodson Bay Hotel, Athlone, on 27th September 2016. The workshop addressed the following themes:

o Modernising Irish Farms – ‘How best can the modernisation of Irish farms be achieved?’

o Agri-Environmental and Disadvantaged/Less Favoured Areas supports – ‘How has Irish farms’ impact on the environment changed over the last decade?’

o Supporting the Broader Rural Economy – ‘Do you feel that key principles of LEADER (supporting bottom up initiatives to promote rural life) were met in practice during the 2007-2013 period?’

3.4 Extensive New Survey Evidence

Extensive new primary survey research was also undertaken as part of the evaluation. This research had the following objectives:

To facilitate individual beneficiaries – including farmers and Leader Local Action Groups – to input to the evaluation in a structured manner; and

To assist the evaluation team to address the Common Evaluation Questions and Programme-specific Evaluation Questions.




16

In summary, four streams of primary research were completed, focussing in each case on the following target/programme beneficiary groups:

Axis 1: Survey of beneficiaries under Early Retirement Scheme (Measure 113);13

Axis 1: Survey of beneficiaries under Farm Improvement Scheme/Targeted Agricultural Modernisation Scheme (Measure 121);

Axis 2: Survey of beneficiaries under Disadvantaged/Less Favoured Areas Scheme and REPS/AEOS/Natura supports (Measures 212-216); and

Axes 3-4: Survey of Leader Local Action Groups (LAGs).

A total of 4,035 separate survey questionnaires were issued across the four survey streams and we had targeted a 5-10% response rate. In the event an impressive total of 1,202 responses were received across the four survey streams, implying an overall effective response rate of 29.8%. The sample detail and response achieved for each survey stream are described in the table below. It is notable in relation to survey streams 1 to 3 that the individual survey response rates were also very high, ranging between 20.1% and 35.6%. A response rate of 85.7% was attained in respect of the survey of LEADER Local Action Groups under Axes 3 and 4 of the programme.

Table 3.1: Primary Research – Details of Response Rates Achieved

Survey Stream No. of Responses Achieved

Total Target Sample

Contacted

Implied Response Rate relative to Sample

Contacted - %

(1) Early Retirement Scheme Survey 216 609 35.5%

(2) Farm Improvement Scheme and Targeted Agricultural Modernisation Scheme Survey

321 1,600 20.1%

(3) REPS/Natura, LFAs and Training Survey 638 1,791 35.6%

(4) Survey of LEADER Local Action Groups 30 35 85.7%

Total Responses across 4 Survey Streams 1,202 4,035 29.8%

Source: Indecon

In addition, to ascertain whether the samples of respondents were representative of the populations of individual measure beneficiaries, Indecon conducted a series of statistical tests to ensure validity. Specifically, this entailed applying a Chi-Squared ‘Goodness of Fit’ test on each of the different survey streams. This test compared the proportion of respondents from each region with the proportion of the overall population of measure beneficiaries in each region. We did not find evidence of a statistically significant difference between the sample and population proportions.

13 In relation to Measure 112 – Young Farmers Installation Aid – a review of the scheme was conducted by the Department of Agriculture, Food and the Marine in 2009. This included a survey of beneficiaries. For this reason, but also because expenditure on the scheme was of a much smaller magnitude, it was decided to focus resources on surveying beneficiaries under the linked Early Retirement Scheme.




17

Table 3.2: Primary Research - Tests of Validity of Samples

ERS FIS/TAMS REPS/LFAs/AEOS

Chi Squared (6) 9.6 7.5 7.81

p-value 0.1426 0.2773 0.2527


In relation to possible bias in the response received to the primary/survey research, as noted above, the survey results are based on an exceptionally large number of responses and this is likely to remove any small sample bias. There is always a possibility of potential bias among respondents but this is more likely to apply if funding for special project applications was in question rather than an assessment after the event. However, Indecon cautions against only relying on this survey evidence and we have tested where possible the findings against other methods including quantitative techniques. The results of the survey are in general consistent with other evidence examined as part of our research.

3.5 Detailed Analysis of Indicator Data

A range of EU common and other indicators were formulated within the RDP for Ireland (2007-2013). These include overall programme-level horizontal indicators, axis-level indicators and measure-level output, result and impact indicators. In the vast majority of instances, baseline position and targets for the programme period are also laid down. It was a requirement that these indicators be reported upon on annual basis as part of the ongoing reporting requirements set down by the European Commission.

A challenge for this evaluation concerned the unavailability of data on a number of indicators. This was particularly the case in respect of measure-level result and impact indicators pertaining to Axes 3 and 4 of the programme, and reflects in part the fact that activities under these axes only commenced in mid-2009. We also note a number of constraints in using existing aggregate indicator data to measure the impacts of the programme. Indecon recommends that additional resources in any new programmes are allocated to providing up-to-date, detailed, comprehensive and useful indicator data.

3.6 Case Studies

A series of case studies was also completed, with the objectives of complementing the consultation programme and primary research, and to facilitate addressing the terms of reference. This qualitative method provided supplementary evidence to the more robust quantitative methods used.




18

3.7 Bio-Economy Input-Output Model

One of the objectives of the evaluation was to consider the wider economic and social impacts at programme level. The impact of expenditures such as those supported under the 2007-2013 RDP can be assessed using the so-called Input-Output methodology, which provides an approach to identify the consequences of expenditures for production and added value throughout the whole economy.14 The main value of the use of an Input-Output model is to evaluate the following:

Multiplier Impacts of Irish Agriculture: To identify and quantify the interlinkages between agriculture sector and other sectors in the broader Irish economy;

RDP Expenditure Impact: To facilitate a high-level assessment of the direct financial impact of RDP expenditures on the overall Irish economy; and

Output Additivity Impact: To enable an indicative assessment of the overall impact on the economy of changes in rural output as a result of RDP-related expenditures.

As part of this evaluation, Indecon utilised a detailed Bio-Economy Input-Output Model of the Irish economy, which assisted in evaluating overall, economy-wide impacts of expenditures under the 2007-2013 programme.

3.8 Econometric Counterfactual Impact Evaluation

To rigorously assess the impacts of a programme measure, or group of related measures, it is necessary to consider what would have likely occurred in the absence of the supports provided (i.e., the ‘counterfactual’). As part of this evaluation, Indecon completed a formal econometric counterfactual impact evaluation of a number of measures under the 2007-2013 RDP, using best practice econometric techniques. While such modelling has limitations, it provides a level of statistical rigour which is not feasible with less quantified approaches.15

Our approach applied econometric models to study the ex post impacts of the various forms of support under the 2007-2013 RDP. Specifically, the analysis made use of the National Farm Survey (NFS) survey, which is an annual longitudinal representative sample survey of farms in Ireland, with circa 1000+ farms sampled over the period 2000-2015. The approach utilised the most up-to-date and comprehensive data available on farms in Ireland. The data was made available to Indecon for the purposes of this evaluation by Teagasc, and with the assistance of the Department of Agriculture, Food and the Marine.

The new econometric modelling involved the use of two principle models to study the impacts of supports on output and productivity. The rationale for this approach was to ensure that the model development and underlying assumptions were consistent with best practice and involving a production function-based conceptual framework adapted to agricultural economics.

Our econometric approach focused on adjusting standard regression approaches for unobserved factors. Our approach also made use of two types of regression model, namely a panel data model incorporating dummy variables for the RDP supports (‘treatments’), and secondly treatment effects-based models, which focussed on a Regression Adjustment (RA) approach.

14 See, for example, the Ex Post Evaluation of Cyprus RDP 2007-2013, An Application of Input-Output Analysis, Psaltopoulos, Lionos, D and S. Malliotis, EU Good Practice Workshop, Palermo, July 2016, Op. Cit.

15 See, for example, Counterfactual Evaluation of Farm Modernization Measure of Latvian RDP 2007-2009, Elitz Benga, Juris Házners, EU Good Practice Workshop, Palermo, July 2016. Op. Cit.




19

3.9 GIS Spatial Analysis

As part of our evaluation, Indecon examined different methodological approaches used to evaluate rural development programmes in other EU Member States. These included an interesting case study using spatial analysis presented by Slovenia at the European Commission’s workshop in Palermo in July 2016.16 Drawing in this research, Indecon obtained data on the areas of land in receipt of REPS and AEOS payments in 2013 under the 2007-2013 RDP for Ireland in tandem with data on Special Protected Areas (SPA) and Special Areas on Conservation (SAC) under Natura 2000 in Ireland, and completed a spatial analysis, which is presented in Section 7 of this report.

3.10 Summary

Reflecting the detailed terms of reference, in addition to the European Commission’s CMEF guidance, Indecon applied a four-phased methodological approach to the completion of the ex-post evaluation of the RDP for Ireland (2007-2013). In line with the CMEF guidance, this involved structuring, observing, analysing, and judging/evaluation.

In line with European Commission guidelines and suggestions,17 Indecon attempted to use a range of advanced robust methods to empirically evaluate the impact of programmes and measures. We also, where feasible, used a ‘triangulation’ of methodologies with the objective of cross-confirming qualitative and quantitative measures, and adopted the principle of proportionality in deciding on research priorities.

Given the diversity of the programme and the data constraints which existed, our methodological approach involved the following seven methods to evaluate the 2007-2013 RDP for Ireland:

Consultation Programme;

Extensive New Survey Evidence;

Detailed Analysis of Indicator Data;

Case Studies;

Bio-Economy Input-Output Model;

Econometric Counterfactual Models; and

Spatial GIS-based Analysis.

16 Use of a GIS-based method for assessment of contribution of RDP to biodiversity Mojca Hrabor, Oilos, Slovenia, EU Good Practice Workshop. Palermo, July 2016.


4 │ Description of Programme, Measures and Budget



20

4 Description of Programme, Measures and Budget

4.1 Introduction

In this section Indecon reviews the structure and composition of the 2007-2013 RDP Ireland, before discussing the level of funding across the different axes and measures of the RDP. The performance of the programme is then assessed in relation to the degree to which targets were achieved and the levels of expenditure undertaken relative to budget.

4.2 Programme Implementation and Composition

The Rural Development Programme for Ireland for the period 2007-2013 was launched in July 2007. The EU framework for rural development formed the basis for the design of the programme, with the National Strategy Plan (NSP) for rural development covering the whole of the country and a single Rural Development Programme providing the action plan operating within this framework.18 Consistent with the National Strategy, the aim of the 2007-2013 RDP was to contribute to the following overarching objectives:

Improving the competitiveness of agriculture by supporting restructuring, development and innovation (Axis 1);

Improving the environment and the countryside by supporting land management (Axis 2); and

Improving the quality of life in rural areas and encouraging diversification of economic activity (Axis 3).

The agricultural sector represented the primary focus of the first two of these axes, with the competitiveness and environmental focus of these axes reflecting the multifaceted nature of, and the particular challenges facing the sector. The measures under Axes 1 and 2 were both consistent with the NSP and with the 2006 Agri Vision 2015 Action Plan for the agri-food sector,19 which envisaged “an industry attaining optimal levels of efficiency, competitiveness and responsiveness to the market while also respecting and enhancing the physical environment.”

Quality of life in rural areas and the diversification of the rural economy represented the two main areas of focus in Axis 3 under the RDP. The measures under Axis 3 were delivered under Axis 4 through the LEADER approach, and related to all rural dwellers, including farmers (particularly given the growth in part-time farming).

The programme noted that the challenges for this area in the wider context included “the provision of alternative and suitable employment opportunities for people living in rural areas and a range of services that people now want and expect locally.”20

In the 2007-2013 RDP, actions centred on the wider rural community, such as the development of rural enterprises based on local natural resources, tourism, village enhancement and environmental initiatives, were designed to complement on-farm measures. The measures were consistent with the 1999 White Paper on Rural Development and its commitments relating to the economic and social well-being of rural communities.

18 Ireland Rural Development National Strategy Plan – 2007-2013, Op. Cit.

19 Agri Vision 2015 – Action Plan, Department of Agriculture, Fisheries and Food, 2006, Op. Cit.

20 Rural Development Programme for Ireland, 2007-2013, Page 6.




21

A summary of the priorities/axes of the 2007-2013 RDP for Ireland and the measures through which supports were provided under the programme, together with the government department responsible for their implementation, is presented in the table below. The programme was comprised of a total of 18 individual measures – four under Axis 1, three under Axis 2, eight under Axis 3 and three under Axis 4.

Table 4.1: Rural Development Programme, Ireland (2007-2013) – Summary of Programme Priorities/Axes and Measure-level Supports

Measure Code Measure (EU description and RDP Scheme) Responsible Department*

Axis 1 – Improving the Competitiveness of the Agricultural Sector

111 Vocational training and information actions – REPS Training scheme DAFM21/DAFF22

112 Setting up of young farmers – Young Farmers Installation Scheme DAFM/DAFF

113 Early retirement of farmers and farm workers – Early Retirement Scheme DAFM/DAFF

121 Modernisation of agricultural holdings – Farm Improvement Scheme DAFM/DAFF

121 Modernisation of agricultural holdings – New Targeted Agricultural Modernisation Scheme (TAMS) (from March 2010)

DAFM/DAFF

Axis 2 – Improving the Environment and the Countryside

212 Payments to farmers in areas with handicaps, other than mountain areas – Less Favoured Areas Compensatory Allowances Scheme

DAFM/DAFF

213 Natura 2000 payments and payments linked to Directive 2000/60/EC – Natura 2000 Payments scheme

DAFM/DAFF

213 New Natura 2000 Payments scheme (from 2010) DAFM/DAFF

214 Agri-Environmental payments – Rural Environmental Protection Scheme (REPS)

DAFM/DAFF

214 New Agri-environmental Options Scheme (AEOS) (from 2010) DAFM/DAFF

Axis 3 – Quality of Life in Rural Areas and Diversification of the Rural Economy

311 Diversification into non-agricultural activities DECLG23/DCRGA24

312 Business creation and development DECLG/DCRGA

313 Encouragement of tourism activities DECLG/DCRGA

321 Basic services for the economy and rural population DECLG/DCRGA

322 Village renewal and development DECLG/DCRGA

323 Conservation and upgrading of the rural heritage DECLG/DCRGA

331 Training and information for economic factors under Axis 3 DECLG/DCRGA

341 Skills-acquisition and animation measure DECLG/DCRGA

Axis 4 – Implementation of the LEADER Approach

41 Implementing local development strategies DECLG/DCRGA

421 Implementing co-operation projects DECLG/DCRGA

431 Running the Local Action Groups DECLG/DCRGA Source: DAFM - Annual Progress Reports for Rural Development Programme, 2007-2013 Note: * DAFM = Department of Agriculture, Food and the Marine; DCELG = Department of Environment, Community and Local Government.

21 Department of Agriculture, Food and the Marine

22 Department of Agriculture, Fisheries and Food

23 Department of Environment, Community and Local Government

24 Department of Community, Rural and Gaeltacht Affairs




22

Axes 1 and 2 measures were implemented through the Department of Agriculture, Food and the Marine (formerly Department of Agriculture, Fisheries and Food), while Axes 3 and 4 measures were managed by the Department of Environment, Community and Local Government (formerly Department of Community, Rural and Gaeltacht Affairs). The various measures supported under the RDP were operationalised through different schemes, a number of which were reconfigured during the programme period, with some schemes suspended or closed and new schemes introduced.

Objectives of Axis 1

The overall objective of Axis 1 of the RDP was to improve the competitiveness of the agriculture sector. The individual measures aimed to meet this through:

Providing training to beneficiaries under the Natura 2000 (measure 213) and agri-environment (measure 214) measures under Axis 2 to optimise delivery of commitments undertaken;

Achieving the transfer of land to young trained farmers better able to meet the new challenges facing Irish agriculture;

Encouraging the transfer of holdings from older farmers to younger, more educated farmers setting up in farming; and

Support for capital improvements in farm structures, ensuring that primary agriculture becomes competitive and market-oriented.


The individual measures under Axis 2 of the programme were designed to protect and enhance natural resources and landscapes in rural areas. In so doing they were designed to contribute to the EU priority areas of:

Biodiversity and the preservation and development of high nature value farming and forestry systems and traditional agricultural landscapes;

Water; and

Climate change.

The individual measures under Axis 2 were also designed to contribute to the implementation of the Natura 2000 network, to the Gotebörg commitment to reverse biodiversity decline by 2010, to the objectives laid down in Directive 2000/60/EC establishing a framework for Community action in the field of water policy, and to the Kyoto Protocol targets for climate change mitigation. The associated measures were designed to meet the Axis 2 objectives through:

Ensuring continued agricultural land use, thereby contributing to the maintenance of a viable rural society;

Promoting environmentally friendly farming practices; and

Preserving the farmed landscape.




23


The Axis 3 measures aimed at meeting the objective of improving quality of life in rural areas and promoting diversification of the rural economy, through the following channels:

Increasing economic activity and employment rates in the wider rural economy through encouraging on-farm diversification into non-agricultural activities;

Supporting the creation and development of micro-enterprises in the broader rural economy;

Encouraging rural tourism built on the sustainable development of Ireland’s natural resources, cultural and natural heritage;

Improving access to basic services by rural dwellers by, for example, addressing inadequate recreational facilities;

Regenerating villages and their surrounding areas by improving their economic prospects and the quality of life; and

Maintaining, restoring and upgrading the natural and built heritage.


As indicated previously, the rural quality of life and diversification-related measures under Axis 3 of the programme were delivered using the LEADER approach, which was incorporated in Axis 4. The objective of the LEADER approach, which represents the EU Community Initiative for rural development, was to foster the development of rural areas through the implementation of innovative, locally-based, bottom-up development strategies designed by local groups/bodies made up of a range of local actors (statutory and non-statutory).

4.2.1 Programme implementation

In relation to implementation structures, in accordance with Article 74 of Regulation (EC) No. 1698/2005, overall responsibility for implementation of the CAP Rural Development Programme for Ireland was held by the Department of Agriculture, Fisheries and Food. Responsibility since 2011 was held by the Department of Agriculture, Food and the Marine. The Department oversaw various structures designed to ensure that administrative and control systems protected the financial interests of the EU and that Ireland met its responsibilities. In particular, the Rural Development division within DAFM/DAFF performed the role of Managing Authority and was responsible for managing and implementing the programme. It also led/chaired the programme Monitoring Committee and oversaw ongoing evaluation of programme, the preparation of progress reports and retention of documentation. The Department also acted as the accredited Paying Agency in relation to Axes 1 and 2 measures within the Programme.

In the case of Axes 3 and 4 measures, the paying agency’s responsibilities were delegated to the Department of Environment, Community and Local Government and, through this Department, to




24

the LEADER Local Action Groups (36 groups), and the (former) Department of Communications, Energy and Natural Resources (involved in the Rural Broadband Reach Scheme).25,26

4.2.2 Programme monitoring and evaluation

Responsibility for the monitoring and evaluation system governing the RDP was held by the managing authority and the monitoring committee. The system reflected the guidance set out in the EU Common Monitoring and Evaluation Framework (CMEF). The framework included provision for completion of the ex-ante, mid-term and ex-post evaluations, to be undertaken by independent evaluators. However, these evaluations were also supported by ongoing monitoring and evaluation work, carried out by the implementing Departments. The scope and nature of ongoing monitoring and evaluation was informed by the CMEF requirements, the outcome of the independent evaluations and the deliberations of the monitoring committee.

A range of performance indicators and targets were contained within the Programme, both at overall axis level and at individual measure level, across the four axes of the RDP. It was required that these indicators be reported upon, with data submitted to the European Commission alongside the progress reports required on an annual basis. These indicators are discussed in respect of each axis and measure as part of the process of addressing the evaluation questions in different sections of this report. As noted elsewhere in this report, some gaps in terms of the availability of indicators were evident to the evaluators.

The National Strategy Plan outlined the different indicators and targets for each measure and each axis, with the targets for Axis 1 outlined in Table 4.2 below. In a number of cases the targets were only set in imprecise terms as an increase, which inevitably constrains the use of these indicators for programme monitoring and evaluation.

Table 4.2: Indicators and Targets for Axis 1

Indicator Measurement Baseline Target

Training and education in agriculture

Percentage of farmers with basic and full education in agriculture

Basic 17% Full 14%

17% 14%

Age structure in agriculture Ratio: farmers under 35 years of

age/farmers aged 55 years or over 0.17 0.15

Labour productivity in agriculture

Gross value added per annual work unit (GVA/AWU)

€14,057 GVA per AWU Increase

Labour productivity in food industry

Gross value added per person employed in food, drink and tobacco

industry €137,043 Increase

Labour productivity in forestry

Gross value added per employee in forestry

€39,200 Increase

Source: Ireland Rural Development National Strategy Plan 2007-2013

25 A written agreement covering compliance with accreditation criteria operates between the Department of Agriculture, Fisheries and Food and the Department of Community, Equality and Gaeltacht Affairs and there is cross-representation between the two departments on their respective Accreditation Review Groups. A similar arrangement has been entered into with the Department of Communications, Energy and Natural Resources concerning its implementation of the broadband measure under measure 321. 26 EAFRD claims are, however, also channelled through the Finance Division of the Department of Agriculture, Fisheries and Food and

the paying agency has to provide guarantees as to the validity of payments and retention of supporting documents.




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4.3 Intervention Logic

The CMEF Guidelines state that the intervention logic for the programme should be explicitly stated in the National Strategy Plan, and that its absence should be flagged as a weakness. The guidelines outline the RDP intervention logic, with the figure overleaf showing the intervention logic at a programme, axis and measure level.

Figure 4.1: RDP Specific Intervention Logic

Source: Guidelines for the Ex-Post Evaluation of RDPs

While targets for each of the axes are discussed in the NSP, the plan lacked a discussion of the intervention logic associated with the programme overall, as well as with individual axes and measures. As part of this evaluation, Indecon outlines our assessment of the intervention logic.

4.4 Budget and Programme Funding Balance

In evaluating the RDP, it is appropriate to examine the budget allocated to the Programme and to also assess the axes and their constituent measures with respect to their balance within the overall RDP.

4.4.1 Distribution of funding by axis

The allocation of funding across the axes of the RDP was designed to conform to a specific balance requirement in relation to the EU/EAFRD funding component, as follows:

Competitiveness of agricultural sector (Axis 1) – 10% of overall EAFRD funding;

Improving the environment and the countryside (Axis 2) – 80% of overall EAFRD funding; and

Diversification/quality of life – Axes 3 and 4 – 10% of overall EAFRD funding.




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Such an allocation was in line with the funding approval process of the European Commission, which required Member States to comply with a minimum allocation of 10% of EU EAFRD funding to both Axis 1 and Axes 3+4, and a minimum of 25% of EU funding to Axis 2, with approval given in 2007 on foot of Ireland’s compliance. A similar approach was agreed in March 2010 in respect of revised allocations during the programme period.27

Over and above the adherence to the EU legal minimum cross-axis requirements, the rationale for the 10:80:10 overall division of funding between Axes 1, 2 and 3+4 set within the RDP reflected the strategic priorities set out in the National Strategy Plan. In particular, the plan envisaged that the funding allocation would take into account the following aspects:28

To maximise the contribution of agriculture to the environment and to compensate farmers for the ‘public good’ aspects of farm enterprises. It was proposed to deliver results in the areas of water quality (Agri-environment) and biodiversity (Agri-environment, compensatory allowances in less favoured areas).

Sustainability was to be the underpinning principle behind development, with the European model of agriculture emphasising this as well as its multi-functional role. Ireland endorsed that view and considered that the actions under Axis 2 of the RDP underpinned those provided elsewhere in the Rural Development framework.

It was proposed to concentrate funding on measures under Axis 2.

In the case of the wider rural dimension – diversification/quality of life – priorities were designed to support on-farm diversification; rural/agri-tourism; rural enterprise; provision of cultural and leisure infrastructure; community initiatives in areas such as renewable energy and IT access; village and countryside enhancement; and conservation of rural and cultural heritage.

The “environmental” support for farmers was to be concentrated under this strategy, whereas the other priorities would benefit from policies adopted outside of the specific EU rural development remit.

From an overall perspective, the RDP was designed to be a balanced, co-ordinated programme that would promote growth, sustainable development and social equity. This was to reflect the Lisbon agenda and Ireland’s related reform programme.29 The Lisbon Reform Programme published in October 2005 identified the following priorities:

Promote, protect and enhance competitiveness;

Increase R&D investment, capacity and output;

Encourage greater innovation and entrepreneurship across the enterprise sector;

Continue to address the physical infrastructure deficit, particularly in the transport sector;

Continue to roll out regulatory reform; and

Support social inclusion and sustainable development.

27 Specifically, under Article 17 of Council Regulation 1698/2005, each Member State is obliged to allocate the EAFRD funding over the axes with a minimum of 10% to Axes 1 and to 3+4. For Axis 2 a minimum of 25% of the funds must be allocated.

28 NSP, Op. Cit. Page 22.

29 Ibid.




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The implications of adhering to the overarching strategic rationale and the requirement for a specific balance of funding across the programme are important, particularly given the impact of developments that took place following programme commencement, which are discussed below.

4.4.2 Implications of developments following commencement of programme in 2007

The economic background and context for rural development in Ireland changed markedly following the commencement of the 2007-2013 RDP. In particular, a number of important developments necessitated re-configuration of the programme during its lifetime. Some of these have been referred to previously, and further detail is provided below.

In 2009, additional funds of €146.3 million were made available under the CAP Health Check/modulation agreement and under the European Economic Recovery Plan (EERP). A number of new challenges and priorities were identified, including in relation to climate change, renewable energies, water management, and biodiversity, measures accompanying restructuring of the dairy sector, innovation and broadband infrastructure in rural areas. A consultation process was held on how best to use the new Health Check- and EERP-related funds in order to meet these new challenges/priorities and it was decided that the total Health Check modulation fund of €119.5 million and half of the EERP fund (€26.8 million) of €13.4 million should be allocated to a new Agri-Environment Options Scheme (AEOS), which would be addressed under Axis 2 of the RDP. The balance of the EERP fund of €13.4 million was allocated to a new scheme to assist the provision of broadband in rural areas. In addition, a new investment scheme, the Targeted Agricultural Modernisation Scheme (TAMS), was introduced at the same time in order to provide more targeted investment support under the Programme and to address the axis balance. The total funding for this new scheme was set at €110 million.

These developments had implications for the original budget allocations for various measures across the four axes of the Programme. The overall implications of the above developments are described in the table overleaf, which compares the original funding allocations upon programme commencement in July 2007 with the final revised budget allocations for the programme. All expenditure figures are gross figures and so include both EU and national funding.




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Table 4.3: Rural Development Programme for Ireland – Comparison of 2010 Revisions with Original Budgetary Allocations

Measure

Original Funding Allocation - 2007-

2013 (EAFRD + Matching National)

- € Million

% of Total RDP

2010 Revised Funding Allocation - 2007-2013

(EAFRD + Matching National + Health Check + EERP) - €

Million

% of Total RDP

Axis 1

Measure 111: Vocational Training (REPS) 14 0.2% 6.9 0.1%

Measure 112: Young Farmers Installation Scheme

63 1.1% 14.9 0.3%

Measure 113: Early Retirement Scheme 418 7.2% 267.2 5.2%

Measure 121: Farm Improvement Scheme 85 1.5% 84.3 1.7%

Measure 121: New Targeted Agricultural Modernisation Scheme [TAMS]

0 0.0% 110.2 2.2%

Axis 1 Total 580.0 10.0% 483.5 9.5%

Axis 2

Measure 212: Less Favoured Areas 1,799 31.1% 1,648.0 32.3%

Measure 213: Natura 2000 Payments + Measure 214: REPS

2,968 51.4% 2,249 44.1%

Measure 213: New Natura 2000 measure 0 0.0% 90.0 1.8%

Measure 214: New Agri Environment Options Scheme [AEOS]

0 0.0% 160.2 3.1%

Axis 2 Total 4,767.0 82.5% 4,147.1 81.3%

Axis 3

Measure 321: New Rural Broadband Scheme 0 0.0% 17.9 0.4%

Axis 3 measures excl. rural broadband scheme 330 5.7% 353 6.9%

Axis 3 Total 329.5 5.7% 370.9 7.3%

Axis 4

LEADER 96 1.7% 95.5 1.9%

Axis 4 Total 96 1.7% 95.5 1.9%

Programme Technical Assistance 6 0.1% 6 0.1%

RDP Total 5,778.0 100% 5,103.1 100%

Of which:

National Funding 3,439.0 59.5% 2,608.5 51.1%

EU funding 2,339.0 40.5% 2,494.5 48.9% Source: Department of Agriculture, Food and the Marine

Following agreement reached with the European Commission on 17th March 2010 on the programme revisions, the overall level of funding allocated to the RDP (EU plus national funding) was revised to €5,103.1 million, comprising €2,608.5 million in national funding and €2,494.5 million in EU funding.

The RDP Programme Complement outlined the indicative breakdown of the allocated expenditure for measures showing the balance of funding in relation to the RDP is presented in Table 4.4 overleaf. This updated the previous revisions in 2010, and reflected the reduction in overall RDP allocations from €5,103.1 million to €4,228 million when all of the expenditure out to 2015 is incorporated.




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Table 4.4: Indicative Breakdown by Rural Development Measure

Measure / Axis Public Expenditure

(€ - 000)

(111) Vocational training and information actions 7,316

(112) Setting up of young farmers 12,916

(113) Early retirement of farmers and farm workers 234,662

(121) Farm modernisation 124,009

(123) Adding value to agricultural and forestry products

Total Axis 1 378,903

(212) Payments to farmers in areas with handicaps, other than mountain areas 1,435,513

(213) Natura 2000 payments and payments linked to Directive 2000/60/EC (WFD) 100,667

(214) Agri-environmental payments 1,986,398

(216) non-productive investments 1,054

Total Axis 2 3,521,524

Axis 3 Implemented under Axis 4 -

(41) Local development strategies of which:

- 411 Competitiveness 1,945

- 413 Quality of life/diversification 248,145

421 Cooperation: 4,671

431 Running costs, skills acquisitions, animation 71,670

Total Axis 4 326,432

Total Axes 1, 2, 3 and 4 4,279,653

511 Technical Assistance 1,938

Of which the National Rural Network (approx.) 1,700

(a) running costs 400

(a) action plan 1,300

Grand Total 4,228,796 Source: RDP

It is also of note that the scarce availability of national funding, due to the rapid deterioration in the Exchequer financial position following the financial crisis in 2008/09, required a fundamental re-prioritisation of resources and a change in approach to the nature and type of activities funded under the RDP. In particular, the negative budgetary situation early in the scheme resulted in the decision to suspend some schemes to new applicants and forced reductions in support levels on other schemes, whereas in the latter half of the programme period some schemes were reopened or changed. The following outlines some of the key changes made to schemes during the RDP, in relation to closure, reopening and change of criteria:

Closure of the Farm Improvement Scheme (Measure 121) in October 2007, due to scheme being fully subscribed by October 2007 at that point;

Suspension/closure to new applicants of the Young Farmers Installation Scheme (Measure 112) and the related Early Retirement Scheme (Measure 113) in October 2008;

Reduction of the maximum hectarage limit on which payments are made available under Less Favoured Areas scheme (Measure 212) in October 2008;

Reduction in the rate of the Rural Environment Protection Scheme (REPS) (Measure 214) payments in 2009 and the subsequent closure of the third iteration of the scheme to new entrants in 2009;




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Closure of a Natura 2000 measure linked to REPS4 to new entrants in July 2009, although a new reduced-budget Natura 200 scheme was introduced linked to AEOS;

In 2012, there were a number of changes to the Disadvantaged Areas Scheme, including:

o An increase in the minimum stocking density from 0.15lu/ha to 0.3lu/ha;

o Horses being excluded from stocking density calculations;

o Land over 80 km from a farmer’s main holding was excluded;

o An increase in the minimum retention period from three to six months; and,

o A reduction in the rate of aid for applicants holding both Disadvantaged and non-Disadvantaged Lands.

There were also changes to the RDP during in 2013, which are outlined below:

o An increase in the provision for Measures 111, 112 and 113;

o An increase in the rate of aid in the BioEnergy Scheme;

o Increased retention period for LFA scheme from six to seven months, as well as a reduction in in the overall ceiling payment from 34 hectares to 30 hectares;

o Funding allocated for the Natura measure relocated to other agri-environment measures under Axis 2; and

o Closure of the Broadband Reach Scheme, and reallocation of remaining funds to REPS and BioEnergy Schemes.

4.4.3 Balance of funding across programme measures

At measure level, the implications of revised programme budget, in terms of the balance of funding across measures within the programme, were as follows:

The suspension of Young Farmers Installation Scheme and Early Retirement Scheme reduced the funding share of these measures from a combined 8.3% of overall programme funding under the original allocation to 5.5% under the revised budget. The suspension of these schemes was expected to impact on the achievement of objectives in relation to supporting mobility of holdings and structural change in farming.

The introduction of the new TAMS scheme was expected to boost the share of the programme budget allocated to on-farm investment from 1.5% to 3.9%. An important issue, however, concerns the need for ongoing focus on investments which yield value-for-money in terms of improvements in on-farm capacity, productivity and competitiveness.

Taking into account the introduction of the new Agri-Environmental Options Scheme and the Natura 2000 measure, the overall proportion of programme funding devoted to agri-environment schemes under the revised budget, at 49%, compared with an original overall allocation of 51.4%, while funding allocated to the Less Favoured Areas scheme was expected to account for 32.3% of the overall programme (versus 31.1% previously). Given the closure of REPS/Natura 2000 in 2009, the outturn in terms of actual expenditure as opposed to budgetary allocations was expected to adversely impact the balance of investment ultimately achieved in respect of the agri-environment measures within the programme.




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Axes 3 and 4 saw an increase in the proportion of overall programme funding allocated to associated measures, from a combined 7.4% in the original budget to 9.2% under the revised budget. Given the late commencement of activity under Axes 3 and 4, an issue is whether funding may have been more effectively invested if a greater time period had been available to identify and develop projects. Indecon, however, accepts that Leader is a development programme that aims to build the capacity of individuals and groups to maximise the additionality provided by the investments.

4.5 Overall Programme-level Expenditure Progress

A summary of the final expenditure outturns compared with the revised budget for each axis and for the RDP as a whole is presented in Table 4.5 below.

Table 4.5: Financial Implementation of the Rural Development Programme and National Strategy Plan – Overall Funding and Expenditure Summary (2007-2013)

Axis and Total

Revised Funding Allocation in € Million (2007-2013) (EAFRD +

Matching National +Health Check + EERP

funds)

Actual Cumulative Expenditure - 2007-2013 - €

Million

Final Expenditure as % of Final RDP Funding

Allocation

Axis 1 368.6 328.7 89.18%

Axis 2 3,590.2 3,450.8 96.12%

Axes 3/4 320.8 243.5 75.90%

Total Axes 1 to 4 4,280 4,023 94.00%


Overall RDP 4,284 4,025 93.95%


Overall cumulative expenditure over the lifetime of the RDP (2007-2013) totalled €4,025 million. This was equivalent to just below 94% of the revised final overall funding allocation for the RDP of €4,284 million. The largest component of overall programme expenditure was under Axis 2, which spent €3450.8 million, or 89.5% of the final funding allocation for this axis. Axes 1 and 3/4 spent over 75% of their budgets, spending €328.7 million and €243.5 million respectively. The low levels of expenditure compared to target for technical assistance is relevant given the importance of developing rigorous indicator data and the need for ongoing evaluation to inform evidence-based policy.

Table 4.6 expands the period in question out to 2015 to include spending on axes after 2013. When 2014 and 2015 is included the expenditure as a percentage of the revised allocation for the overall RDP is 98.2%, up from 94%. Spending on each axis was above 97% of the final funding allocations.




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Table 4.6: Financial Implementation of the Rural Development Programme and National Strategy Plan - Overall Funding and Expenditure Summary (2007-2014)

Axis and Total

Revised Funding Allocation in € Million

(2007 – 2013) (EAFRD + Matching National +Health

Check + EERP funds)

Actual Cumulative Expenditure - 2007-2014 -

€ Million

Expenditure to date as % of RDP Allocation

Axis 1 388.4 378.9 97.55%

Axis 2 3,593.2 3,521.5 98.00%

Axes 3/4 324.6 326.4 100.6%

Total Axes 1 to 4 4,306.2 4,226.8 98.16%


Overall RDP 4,308 4,228.7 98.16%


It should be noted that the indicator data used in this report is from 2007 to 2013. Payment continued for a number of measures of the 07-13 RDP in 2014 and 2015, though this data had not been approved at the time this ex-post evaluation began. The 2014 report and data were only approved in October 2016 while the 2015 report has not yet been approved. To ensure that the evaluation was completed on time, it was decided to base the report on the data from 2007 to 2013. However, all of the indicators data in this report should be viewed in light of this limitation. This may impact on the Leader element of the Programme more than other areas given the nature of expenditure. As a result, Indecon understands that only 75% of the caseload would be processed by the end of 2013.

4.6 Summary

This section described the structure and composition of the 2007-2013 RDP Ireland, and also examined the level of funding across the different Axes and Measures of the RDP, including changes that occurred during the programme period. We also examined the performance of the programme in terms of actual programme- and axis-level expenditure relative to budgeted levels of funding. The main findings were as follows:

The Rural Development Programme for Ireland for the period 2007-2013 was launched in July 2007. The EU framework for rural development formed the basis for the programme, with the National Strategy Plan for rural development covering the whole of the country and a single Rural Development Programme providing the action plan operating within this framework. Consistent with National Strategy, it was the aim of the programme to contribute to the following overarching objectives:

o Improving the competitiveness of agriculture by supporting restructuring, development and innovation (Axis 1);

o Improving the environment and the countryside by supporting land management (Axis 2); and

o Improving the quality of life in rural areas and encouraging diversification of economic activity (Axes 3 and 4).




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While targets for each of the axes were included in the National Strategy Plan, the plan did not include a Programme intervention logic model. As part of this evaluation report, Indecon outlines our assessment of the intervention logic.

The National Strategy Plan outlined the different indicators and targets for each measure and each axis. However, in a number of cases the targets were only set in imprecise terms or in terms of an increase, which inevitably constrains the use of these indicators for Programme monitoring and evaluation.

The suspension of the Young Farmers Installation Scheme and Early Retirement Scheme reduced the funding share of these measures from a combined 8.3% of overall programme funding under the original allocation to 5.5% under the revised budget.

The introduction of a new TAMS scheme boosted the share of the programme budget allocated to on-farm investment from 1.5% to 3.9%.

Taking into account the introduction of the new Agri-Environmental Options Scheme and Natura 2000 measure, the overall proportion of programme funding devoted to agri-environment schemes under the revised budget, at 49%, compared with an original overall allocation of 51.4%, while funding allocated to the Less Favoured Areas scheme was expected to account for 32.3% of the overall programme (versus 31.1% previously).

Axes 3 and 4 saw an increase in the proportion of overall programme funding allocated to associated measures, from a combined 7.4% to 9.2% under the revised budget.

Overall cumulative expenditure over the lifetime of the RDP totalled €4,228.7 million, which includes expenditure out to 2015. This was equivalent to 98% of the revised overall funding allocation for the programme of €4,308 million. The largest individual axis was Axis 2, which spent 98% of its final revised funding allocation. Axes 1 and 3/4 spent over 97% of their budgets, spending €78.9 million and €326.4 million respectively. The low levels of expenditure compared to the original target for technical assistance is relevant given the importance of developing rigorous indicator data and the need for ongoing evaluation to inform evidence based policy.

5 │ Answers to Evaluation Questions: Programme Level



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5 Answers to Evaluation Questions: Programme Level

5.1 Introduction

As part of the overall evaluation, we have attempted to address the following Common Evaluation Questions:

Question 1: To what extent has the RDP contributed to the growth of the whole rural economy?

Question 2: To what extent has the RDP contributed to employment creation?

Question 9: To what extent has the RDP contributed to improving the quality of life in rural areas and encouraging diversification of the rural economy?

Insights to these questions can be gleaned from the evaluation of specific measures, but it is also important to examine programme-wide impacts. In evaluating overall programme-level impacts, it is instructive to consider the expenditure impacts of the programme. To assist in this, Indecon applied a quantitative methodology, which involved the use of a bio-economy input-output model of the Irish economy.

5.2 Measuring Wider Social and Economic Impacts

RDP expenditures have a number of broader socio-economic impacts on the rural and national economy. The expenditure directly benefits those farms, businesses and communities that are direct beneficiaries of funds, but there are also indirect benefits on the economy through increased consumption and employment.

5.2.1 BIO-ECONOMY Input-Output Database

The ‘BIO-ECONOMY’ input-output model30 was utilised by Indecon to assess the impacts of the RDP on the broader Irish economy. This model was developed in a collaborative research project between Teagasc, NUI Galway in association with the Marine Institute and funded by a Beaufort Marine Research Award and the Teagasc Research Programme. In the standard published CSO Input-Output tables, the primary resource sectors, Agriculture, Forestry and Fisheries are grouped together in one sector, as are the Food Processing industries and most of the other Marine based sectors. Utilising data collected by Teagasc in their National Farm Survey and other sectoral information, the BIO-ECONOMY Model decomposes these sectors into a finer sectoral resolution. The model has been specifically developed to allow a greater understanding of the flows and interactions between and within the bio-economy sectors, and as such merits consideration as an input to the impact of the RDP programme. It builds upon earlier work focusing on the Irish Agri-Food sector by O’Toole and Matthews (2002) and Miller et al. (2014).

5.2.2 Multiplier Impacts of Irish Agriculture

In evaluating the programme-level impacts it is useful to examine the linkages between the agricultural sector and the rest of the economy, in particular how direct and indirect impacts of agricultural output impact on the rest of the economy through activity multipliers.

30 “The Bio-Economy Input Output Model: Development and Uses”, Grealish et al., 2015.




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The table below reports on three sets of multipliers, namely, output multipliers, value-added multipliers and wage multipliers. These are reported for nine sectors, with a weighted average of the economy-wide multipliers also quoted. The figures should be interpreted as follows. An output multiplier of (say) 1.4 indicates that for an additional output of €1 of (say) dairy produce results in an additional output of €1.4 in the economy overall, which includes the original increase in demand of €1. As such, the indirect effect of inter-industry linkages in this case is €0.4. A similar interpretation is put on the value-added multipliers and the wage multipliers.

Table 5.1: Direct + Indirect Multiplier Impacts of Primary Agriculture Sectors, 2010

Output Multiplier Value added Multiplier Wage Multiplier

Forestry 1.5 0.4 0.2

Horticulture & Potatoes 1.2 0.7 0.2

Dairy 1.4 0.6 0.2

Cattle 1.8 0.4 0.1

Sheep 1.5 0.5 0.2

Horses 1.5 0.5 0.2

Pigs 1.4 0.3 0.1

Poultry 1.5 0.2 0.1

Deer and Goats 1.3 0.7 0.2

Economy Average 1.4 0.6 0.3 Source: Indecon analysis of BIO-ECONOMY Input-Output Model

Turning first to the output multipliers, the greatest impact on output comes from an increase in demand for cattle production, with a multiplier value of 1.8. More generally, the output multiplier values reported in the table are in line with, or exceed, the national average multipliers in all but two of the sub-sectors.

The extent to which value-added is generated by an additional sale of €1 of each good is also shown in the table. Again, agricultural sectors are generally seen to have similar levels of multipliers to the national average. One element of value-added is wages. While the table shows that generally wage multipliers are lower in agricultural sectors, this in part reflects the nature of the structure of Irish agriculture which is typified by small owner-producers. In examining the socio-economic impact of the RDP it is particularly useful to consider the impact on value-added.

5.2.3 RDP Expenditure Impacts

In estimating the direct socio-economic impact of RDP expenditures on the broader economy, the main challenge in utilising the BIO-ECONOMY model, as with any Input-Output model, is to develop appropriate vectors of sectoral demand corresponding to the aggregate expenditure of the RDP. Two structures of economy-wide demand are available, namely:

Gross Fixed Capital Formation: This captures the structure of investment in the economy. The breakdown of this is used in the model to estimate the sectoral-level demand structure for expenditures relating to on-farm investment (Measure 121).

Household consumption: This is relevant for measuring the direct plus indirect effect of RDP expenditures which raise farm/non-farm household incomes through direct payments.

The results reported in this section are aimed at measuring the impact of the expenditures as a result of the RDP.




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The results of the new quantified analysis are shown in the table below. They show the annual average of a number of measures of economic activity. When the direct and indirect impact of this expenditure is taken into account, the total impact in terms of expenditure/output on the Irish economy was €3,773m over the course of the 2007-2013 RDP. Similar interpretations can be put on the measures of Value Added and Wages.

Table 5.2: Estimated RDP Expenditure Impacts, 2007-2013

Direct Impacts Direct + Indirect Impacts

Output (over the 2007-2013 period) €2,646m €3,773m

Value Added (over the 2007-2013 period) €1,364m €1,910m

Employee Wages (over the 2007-2013 period) €670m €933m


The above expenditure impacts represent the direct and indirect impacts as measured by Type 1 multipliers but excludes the wider impacts arising from consumption related to the additional incomes generated. These are measured by Type 2 multipliers which are not available from the calculated BIO-ECONOMY model. Indecon’s approach to deal with this deficiency has been to utilise wider Type 2 multipliers for the agriculture sector in an Input-Output model which doesn’t break-out this sector as is done in the BIO-ECONOMY model. In table 5.3 we present estimates of the overall expenditure impacts and output and value added of the RDP spend.

Table 5.3: Estimated Overall RDP Expenditure, Direct, Indirect and Induced Impacts, 2007-2013

€ Million

Impact on Output €4,184m

Impact on Value Added €2,337m

Impact on Employee Wages €1,272m


An estimate of the impact of this spend on employment using economy wide employment multipliers is presented in Table 5.4. This suggests that annual employment of 6,466 was related to the expenditure impacts of the RDP. This is an important measure of the wider socio-economic benefits of the Programme.

Table 5.4: Estimated Overall Employment Impacts of RDP Expenditure Direct, Indirect and Induced Impacts, 2007-2013

Employment Annually






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5.2.4 Regional Impacts of Programme Expenditure

In addition to considering the broader economic and social impact of the spend we examined the impact on the regional economy. As part of this evaluation Indecon has addressed this by considering the regional impact using survey data. An approximation of an Input-Output method was also completed to give an indication of the direct, indirect and induced impact of RDP expenditures, based on a regional model of Ireland completed which separated Ireland on a NUTS 2 basis31.

In terms of survey evidence, respondents to the survey on Axis 2 measures, which constitute 80% of the Irish budget, were asked about the extent to which each of their household expenditure and their purchase of farm inputs, are done in the local area (with local being defined as within 35kms). The results show that a large majority of expenditure on both household goods as well as farm inputs was estimated as being spent within 35km of their farm, with nine out of ten farm households reporting that virtually all of their expenditures for household and farm needs are conducted locally. Most of the remainder reported that around half of expenditures were local. This is likely to understate spending in the broader rural economy, as a portion of the spending outside of a 35km radius of farms is likely to have been in the rural economy.

These survey results suggest that a majority of the economy-wide impact as reported by the Input-Output model are felt locally. While the first-round effects are almost entirely local and contained within the local economy, second- and further round effects are likely to be more dispersed throughout the country. The survey results would suggest that the impact of RDP is likely to have significant effect in supporting employment, incomes and value added in the rural economy.

An approximation of the regional impacts was completed by Indecon using a Regional Input-Table for Ireland.32 This utilised a set of symmetric Supply and Use and domestic Input-Output tables compiled for the NUTS 2 regions in Ireland: the Border, Midlands and Western region and the Southern and Eastern region. For the purposes of this section, it is assumed that the structure of the Border, Midland West region is a reasonable approximation for the aggregate rural economy, in particular given that it has a much larger agricultural economy than the Southern and Eastern Region. Also of note for the analysis is that the BMW region and the aggregate rural regions supported by the RDP are approximately the same size in economic terms.

The analysis was conducted at two stages:

Apply adjusted final demand figures: Using the survey data, an adjusted vector of final demands based on the estimated spend in rural areas was applied, with the estimate that 85% of expenditure was local. This reduced vector of final demands was broken out based on average final demands locally, as the reduced-form regional Input-Output model did not contain a separate household disaggregation.

Apply to Regional Input-Output Leontief Matrix: The Leontief matrix based on the Border, Midland, West symmetric Input Output model was calculated, and the vector of final demands derived as above was applied to give an estimate of the direct plus indirect impacts of RDP expenditure.

31 The two NUTS2 regions in Ireland are the Border, Midland and Western Region, and the Southern and Eastern Region.

32 “A Study of the NUTS 2 Administrative Regions using Input-Output Analysis”, MacFeely, Moloney & Kenneally.




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The results of the analysis are shown in the table below. They indicate that the total direct and indirect impact of RDP expenditure on the rural economy is of the order of €3,532m in output, compared to the aggregate national impact of RDP expenditure of €4,184m. As such, 84% of the estimated direct plus indirect benefit of RDP expenditures is felt within the rural economy. This excludes the economic and social benefits of any wider supply-side impacts.

Table 5.5: Estimated Regional RDP Expenditure Impacts, 2007-2013

Direct Impacts



€m




Indecon’s modelling also estimates that RDP expenditure supports 4,692 jobs on an annual basis in the rural economy. This is an important Programme wide socio-economic benefit of the RDP. It should, however, be noted that this is a result of increased spending and expenditure in other programmes and would also have a demand impact on the economy. As such it is necessary to note the economic opportunity cost of all expenditure. Indecon therefore decided to consider the supply side impacts.

Table 5.6: Estimated Regional Employment Impacts of RDP Expenditure, 2007-2013

Employment Annually



5.2.5 Supply-side Impacts

Apart from expenditure impacts the most important potential benefits of the RDP relates to the supply-side consequences for the agricultural, forestry and fishing sectors. These were examined where feasible in the evaluation of the individual measures. They were also described in our analysis in this report of the Programme Logic.

In order to consider potential supply-side impacts, it is useful to highlight some of the results of our econometric modelling of the counterfactual impacts reported later in this evaluation. The counterfactual modelling undertaken in Section 6 and 7 examined the impact of RDP funding under REPS/AEOS and under Measure 121 funding via land improvement and building grants. These models found a positive and significant impact of RDP funding on farm output for REPS and building grants but no impact of land improvement grants. Taking a weighted average based on the level of RDP funding given the REPS and Measure 121, our econometric evidence suggests that, on average, output increases by 2.1% for every 10% increase in funding.




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Based on the findings of the econometric analysis and assumptions regarding the number of farmers in receipt of RDP funding, Indecon has estimated the likely supply-side impact of RDP expenditure. We would note that the estimates below are net of deadweight and attempt to identify only the additionality attributable to RDP expenditure. It should be noted that there is significant uncertainty regarding any estimates of the long term supply impacts at Programme level and the estimates should be viewed as indicative.

Table 5.7: Supply-side Impacts of RDP

Supply-side Impact Metric

Output Impact €481.5m

GVA Impact €163.5m

Employee Wage Impact €58.6m

Employment (Annual basis) 643


Indecon’s findings suggest that RDP expenditure has made a contribution to the supply-side of the economy, net of deadweight, of the order of €481.5 million in output terms and €163.5 million in contribution to GVA. We also estimate that RDP expenditure supports around 643 additional jobs on an annual basis.

5.3 Technical Assistance

A budget was allocated in the 2007-2013 RDP for a programme of Technical Assistance (TA) to support the Managing Authority in implementation of the RDP. Of the budget of €1.9m, approximately €1.7m was spent on the National Rural Network, with the remainder being spent on other forms of technical assistance. A review of the National Rural Network is conducted in this evaluation as Case Study 5. Given that the remainder of the TA programme constituted just €200,000 (or less than 0.005% of the total RDP expenditure), and given the principle of proportionality to be applied in this study based on CMEF guidelines, no separate evaluation of these monies was conducted. Indecon, however, notes the importance of enhancing monitoring and indicator data.




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5.4 Summary

This section has examined a number of metrics for assessing the wider economic impacts of RDP expenditure on the Irish economy. The key findings of this section include:

Indecon’s analysis of the wider impact of RDP funding is based on inputs from the BIO-ECONOMY Input-Output model of the Irish economy as well as additional inputs from Indecon’s own model of the Irish economy.

Indecon estimates that the overall impact of RDP expenditure on the Irish economy, including the direct, indirect and induced impacts of this spending, amounts to:

o €4,184 million in output;

o €2,337 million in Gross Value Added (GVA);

o €1,272 million in employee income; and

o 6,466 jobs on an annual basis between 2007 and 2013.

In regional terms, Indecon has estimated that 84% of the estimated direct plus indirect benefit of RDP expenditures was felt within the rural economy.

On the supply-side, Indecon has estimated that the contribution of RDP spending net of deadweight amounted to:

o €481.5 million in output;

o €163.5 million in Gross Value Added (GVA);

o €58.6 million in employee income; and

o 643 jobs on an annual basis between 2007 and 2013.

6 │ Answers to Evaluation Questions: Axis 1



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6 Answers to Evaluation Questions: Axis 1

6.1 Introduction

This section examines expenditures which fall under Axis 1 of the RDP, which was aimed at enhancing the competitiveness of the agri-food sector. This will examine the allocation of funding and outcomes from expenditures, both from an axis-level and a measure-level perspective. The following measures under Axis 1 are included for the purposes of this analysis:

Measure 112 – Young Farmers Installation Aid;

Measure 113 – Early Retirement Scheme; and

Measure 121 – Farm investment (FIS & TAMS).

It should be noted that Measure 111, which relates to Vocational Training, is covered in Section 7 concerning Axis 2 of the programme, given the close link between this measure and implementation of the agri-environmental schemes.

Before discussing the effectiveness of each measure, it is important to assess the use of funds from an axis level. This section then discusses the two complementary measures aimed at reducing the age profile of Irish farming, namely Young Farmers Installation Aid (Measure 112) and the Early Retirement Scheme (Measure 113). We also examine the two schemes aimed at the modernisation of agricultural holdings (Measure 121).

6.2 Implementation and Composition of Axis 1

The rationale for Axis 1 expenditure measures was set out in Chapter 2 of the National Strategy Plan for the RDP 2007-2013. The plan stressed the link between the RDP and the Lisbon Reform Programme. In particular, Axis 1 expenditures were to be aimed at enhancing the competitiveness of the agri-food sector and supporting Ireland’s strategy for science, technology and innovation, which included a major commitment for research and development in agriculture and food.

In the early period of the programme’s implementation, the focus of expenditure within Axis 1 was largely on three measures out of a total of 18 possible measures, namely Measures 112, 113 and 121. The substantial contraction in the Irish economy from 2008 and the associated very challenging budgetary situation led to the suspension of the measures relating to the setting up of young farmers and early retirement from farming. Subsequent expenditure in the programme was focussed on a new agricultural investment scheme, on the basis that it was believed to provide a more targeted, sector-specific focus on market orientation and competitiveness for Axis 1. The reformed investment measures were aimed at addressing the need for capital investment at farm level, focusing in particular on improved animal welfare standards, increased efficiencies in the dairy and sheep sectors, water conservation and the promotion of renewable energies.

Figure 6.1 overleaf compares the expenditure on the different measures as a percentage of overall RDP spending within Axis 1 between Ireland and EU countries overall. This covers the entire period of the RDP from 2007-2013. It shows that the proportion of expenditure on the Early Retirement Scheme (Measure 113) in Ireland was twice that of the overall EU27 spending, suggesting a greater importance put on this area in respect of Ireland compared with the EU as a whole. It is also noticeable that while 12.3% of EU-wide expenditure went towards modernisation of agricultural buildings, less than 3% of Ireland’s RDP expenditure was targeted at this measure.




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Figure 6.1: RDP Expenditure on Measures in Axis 1 - Ireland v EU27 (As a Percentage of Overall RDP Expenditure)


The analysis presented above is influenced by the fact that a relatively small portion (8.5%) of total public expenditure in Ireland’s RDP related to Axis 1 measures, compared to the EU average (30.5%). The budget shares of each measure relative to the aggregate of Axis 1 expenditure (as opposed to overall RDP expenditure) are shown in Figure 6.2 overleaf. While the proportion of overall expenditure on Measure 121 was less than one quarter that of the EU27, when taking as a proportion of aggregate Axis 1 expenditure the two were of similar scale. Measure 121 accounted for almost one-third of Ireland’s expenditure in Axis 1, compared to approximately 40% of EU27 expenditure. The figure also illustrates the relatively large budget share dedicated to the Early Retirement Scheme compared to elsewhere in Europe, accounting for approximately 60% of Ireland’s expenditure on Axis 1.




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Figure 6.2: RDP Expenditure on Measures in Axis 1 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure)


Having compared the percentage of expenditure on each measure in Ireland against EU27 countries, it is important to understand how the level of expenditure compared to the budget allocated to each measure. This is done below, with the data being updated to include expenditure out to 2015. As can be seen in the table overleaf, in each of the Measures actual expenditure was very close to budgeted expenditure. Overall Axis 1 expenditure (€378.9m) was close to the amount allocated (€388.4m).




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Table 6.1: Actual v Financial Plan Expenditure (Axis 1)

Actual Expenditure

(000)

Financial Plan (000)

Actual Expenditure as a

% of Budget

M111-Vocational training and information actions

7,316 7,316 100.0%

M112-Setting up of young farmers 12,915 12,892 99.8%

M113-Early retirement 234,662 241,173 97.3%

M121-Modernisation of agricultural holdings 124,009 126,978 97.7%

Total Axis 1 378,903 388,361 97.6%

Source: DAFM.

6.3 Axis 1 – Indicators

The table below provides an overview of the position with regard to the Axis 1 monitoring indicators. They show that the percentage of farming with agricultural education rose to 44% by 2011 (the latest year for which data was available), which was ahead of the target of 41%. However, the age structure of farming continued to deteriorate relative to both the baseline and the target, with the ratio of farmers under 35 years of age to the number of farmers aged 55 years or over falling to 0.11. In addition, indicators of farm productivity, as measured by the value of output, generally showed improvement.

In using the indicators to measure the performance of the programme, of concern is the fact that three of the indicators are only set in terms of an increase and no specific targets were set. Another issue of relevance is that the aggregate nature of the targets is such as to raise issues regarding whether the scale of funding and the nature of the measures implemented are likely to be sufficient to have an impact at this aggregate level. Another important issue in using the indicators to evaluate performance is the need to take account of a counterfactual position, as other determinants are likely to influence such aggregate outcomes.

Table 6.2: Rural Development Programme – Axis 1 Indicators

Indicator Measurement Baseline Target Closing Position

Training and education in agriculture

Percentage of farmers with basic and full education in agriculture

Total: 41% Basic 17% Full 14%

Total: 41% Basic 17% Full 14%

% farmers with some agricultural

education = 44% (2011)*

Age structure in agriculture

Ratio: farmers under 35 years of age/farmers aged 55 years or over

0.17 0.15 0.11 (2013)**

Labour productivity in agriculture

GVA per annual work unit (GVA/AWU)

€14,057 GVA per AWU Increase +40.2% (2007-2013)***

Labour productivity in food industry

GVA per person employed in food, drink and tobacco industry

€137,043 Increase €142,242 (2011)****

Labour productivity in forestry

GVA per employee in forestry

€39,200 Increase +62% (2010)*****

Sources: * www.teagasc.ie/media/website/publications/2014/Teagasc_Impact_of_Education_Report.pdf ** www.cso.ie/en/releasesandpublications/ep/p-fss/farmstructuresurvey2013/detailedanalysis/farmownershipandlabourinput/ *** Based on Gross Martin by family farm using National Farm Survey 2007 and 2013, Teagasc. **** CSO Output by Industry 2011, and Quarterly National Household Survey 2011. ***** CSO Output by Industry 2010, and Quarterly National Household Survey 2011 (2010 suppressed for confidentiality reasons).

http://www.teagasc.ie/media/website/publications/2014/Teagasc_Impact_of_Education_Report.pdf

http://www.cso.ie/en/releasesandpublications/ep/p-fss/farmstructuresurvey2013/detailedanalysis/farmownershipandlabourinput/




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6.4 Measure 112/113 – Early Retirement Scheme and Young Farmers Installation Scheme

In this sub-section we discuss two measures, namely the Young Farmers Installation Scheme (YFIS) and the Early Retirement Scheme (ERS). The Young Farmers Installation Scheme (YFIS) aimed to facilitate young educated people to enter farming. The Early Retirement Scheme (ERS) was intended to complement the Young Farmers Installation Scheme by encouraging the transfer of holdings from older farmers (transferors) to younger farmers (transferees), through the provision of a pension for transferors. Both were designed to encourage structural changes in the agricultural sector, with the objective of enhancing the competitiveness and sustainability of farming in Ireland.

Given the complementarity between the two measures, both are covered in a single analysis of the Programme Intervention Logic. This section begins with a short introduction to each of the measures, followed by a discussion of the Programme Logic Model with respect to these two schemes. The aim of this section is to help address the following Common Evaluation Questions:



Question 5: To what extent has the RDP contributed to improving the competitiveness of the agricultural and forestry sector?

Question 6: To what extent has the RDP accompanied restructuring of the dairy sector?

Question 14: How efficiently have the resources allocated to the RDP been used in relation to achieving the intended outputs?

Question 15: For each of the Axis 1 measures included in the RDP - How and to what extent has the measure contributed to improving the competitiveness of the beneficiaries?

Question 20: What other effects, including those related to other objectives/axes, are linked to the implementation of this measure (indirect, positive/negative effects on beneficiaries, non-beneficiaries, local level)?

Background to Young Farmers Installation Scheme

The Young Farmers Installation Scheme (YFIS) was designed to help address the structural issues of an older age profile, low educational attainment and a lack of land mobility within the Irish farming sector by encouraging and facilitating young, educated people to enter farming. The specific objectives of this measure were to:

Increase the amount of land transferred to young, trained farmers better able to meet the new challenges facing Irish agriculture;

Mitigate the costs faced by young people when setting up their farm; and

Provide assistance for the investments required on such farm holdings.




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The scheme provided young trained farmers between the ages of 18 and 35 who had set up in farming for the first time with a grant of €15,000. Under the rules of the scheme, the young farmer must have been set up in farming on or after the 1st January 2007 and not later than the 31st December 2013. The grant was subject to an off-farm income ceiling, as well as education and property-related requirements. The Young Farmers Installation Scheme was increased by 57% from €9,523 in the previous scheme (2000-2006 RDP) to €15,000 under the 2007-2013 RDP. The scheme included a single payment to eligible applicants, i.e. individuals between the ages of 18 and 35 who were qualified to FETAC Level 6 or equivalent and who were setting up for the first time in farming. A detailed business plan was required from each applicant. Participants were required to continue farming for five years from the date of set-up and to farm the land transferred during that period.

This scheme was suspended on 14th October 2008. While the original target was set at 4,200 beneficiaries at a total cost of €63 million, this was subsequently adjusted to 941 beneficiaries at a cost of €14.95 million to accommodate all applications received. This represented a much lower level of funding than was originally envisaged. The small scale of funding compared to the related Early Retirement Scheme is noteworthy.

Background to Early Retirement Scheme

The Early Retirement Scheme was designed to assist those farmers interested in retiring early from farming to transfer their land to younger, trained farmers who would commit to the development of these holdings. Two groups of farmers could be transferees, namely farmers under the age of 35 or farmers who succeed the retiring farmer. Farmers who were eligible and approved for payment under the Young Farmers Installation Scheme (2007–2013) were also eligible transferees under the Early Retirement Scheme.

The transferor that retired and met the conditions of the scheme could then qualify for a Farm Retirement Pension. The pension was set at a flat rate of €9,300 per annum for the first 5 hectares, with an additional €300 per hectare available for subsequent hectarage, up to a maximum of 24 hectares.33 The transferor age limit was increased compared to the previous 2000-2006 RDP, with the transferor required to be between the ages of 55 and 66. The total duration of early retirement support was not allowed exceed 10 years for the transferor and for the farm worker, or to go beyond the 66th birthday of the transferor and the normal retirement age of the farm worker. The size of the agricultural holding required was also reduced in less favoured areas to acknowledge regional differences in holding sizes.

The 2007-2013 RDP had an initial budget of €418 million for Early Retirement Scheme (Measure 113). Due to the changed economic circumstances after the 2008 financial crisis in the early years of the programme, this funding allocation was reduced to €267.2 million. The ERS was suspended for new applicants in October 2008. However, it temporarily reopened in September 2009 and accepted applications up to 30 October 2009 to accommodate previously prepared applications. The adjusted number of early retired farmers was 636, reflecting the number of applications that had already been received at the time of cancellation.

33 The amount of the Farm Retirement Pension was a flat rate plus an amount related to the number of hectares of land transferred/leased. If a transferor became eligible for a social welfare pension, this amount was reduced.




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Intervention Logic

The next table shows the Programme Logic Model for Measures 112-113. The core objective of these measures was to enhance the age profile of Irish farming, and thereby improve and modernise farming methods. The logic behind these measures assumes that grants provided to young farmers, and pensions provided to older farmers (the inputs) would at the margin facilitate a transfer of land to younger and better trained farmers earlier than it would otherwise do. The logic is based on an assumption that as the age profile decreases and the skill levels increase, this would result in an improvement in productivity and output. Specifically, the logic of these measures assumes the following:

That both schemes independently are targeted at the right age/education cohorts;

That younger farmers embrace more productive farming methods than the farmers that they replace, and that the education requirements of the schemes support them in so doing. Independent econometric evidence completed by Indecon and discussed later sheds some light on the validity of this assumption;

That these more productive farming methods are sufficient to support the younger farmer and his/her family, while the older farmer also has sufficient income to support his/her family;

That the balance of the budgetary allocation between the two schemes was likely to be effective;

That wider public policy was consistent with the aims of these measures; and

That the investment encourages a transfer of farms that would not otherwise have taken place.

In identifying the age-profile target for such schemes to promote restructuring and modernisation in farming, two opposing considerations need to be balanced. The target age for early retirement should be sufficiently old, having regard to the physical/educational attainment rates among each cohort of farmer. Targeting older farmers should achieve greater restructuring and modernisation. Conversely, the target age should be set so as reduce deadweight, in other words the extent to which farms would have been transferred anyway in the absence of the scheme. Targeting the correct cohort of farmers to retire could help reduce deadweight, while encouraging land mobility and a transfer to potentially more productive farmers.

Table 6.2: Programme Logic Model - Measure 112/113

Source: Indecon

The assessment of the measures’ inputs, activities and outputs, results and impacts is presented overleaf.

INPUTS

Exchequer Funding

EU Funding

Administrative Support

ACTIVITIES

Payments to young farmers

Pension payments to

retired farmers

Scheme Administration

OUTPUT

Establish young(er) farmers

Establish better trained farmers

RESULT

Improve age profile of farming

Improve skill level of farming

IMPACT

Improve productivity of

Irish farms




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Inputs

There are three inputs to both schemes. The first two relate to financing, including whether the scheme were funded by the Irish Exchequer or through the EU. The third is the administrative support required to implement both schemes. The next figure shows the total realised public expenditure under the RDP between the two measures, for both Ireland34 and the EU27.35 It shows the while a majority of expenditure in other EU countries focussed on the YFIS, in Ireland virtually all funds were dedicated to the ERS. It has been argued in Ireland that the balance between the two schemes reflected the need to address barriers to exit from farming rather than barriers to entry.36 This would support the relatively small share given to the YFIS.

Figure 6.3: Balance of Budget between Measures 112 and 113 for Ireland and EU27

Source: Indecon

The table below sets out the numbers of farmers for whom the commencement of payment began in each year from 2007 to 2013.

Table 6.3: Measures 112-113 – Annual Expenditure – 2007-2013

Commencement of Payments to Farmers (number)

Year Young Farmers Early Retirement

2007 15 14

2008 357 274

2009 341 158

2010 125 126

2011 24 27

2012 0 1

2013 0 0

Total 862 600

Source: DAFM

34 See: https://enrd.ec.europa.eu/sites/enrd/files/mi_financial_fiche_2015_ie_0.pdf 35 See: https://enrd.ec.europa.eu/sites/enrd/files/mi_financial_fiche_2015_eu27_0.pdf 36 See: http://www.iiea.com/blogosphere/wasting-money-on-young-farmers

https://enrd.ec.europa.eu/sites/enrd/files/mi_financial_fiche_2015_ie_0.pdf

https://enrd.ec.europa.eu/sites/enrd/files/mi_financial_fiche_2015_eu27_0.pdf

http://www.iiea.com/blogosphere/wasting-money-on-young-farmers




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In terms of the cost of administration, the Value for Money Review of the Young Farmers Installation Scheme published by the DAFM in 2009 examined the processes and activities involved in delivering the programme to identify areas where a higher quality/quantity of outputs could have been achieved with the existing level of inputs, or where fewer inputs could have been utilised to achieve the same level of outputs.37 As part of the scheme, applicants had to provide proof in relation to income, education and land transfer before payment can be made. The scheme guidance document ran to 18 pages, while the application process involved the submission of two separate formal applications on the part of the farmer, both of which had to be accompanied by a number of supplementary documents. The report estimated that the total cost of operating the scheme in 2007 and 2008 amounted to €3.6 million. These costs represented about one-fifth of the level of grants paid out during that period, which the review assessed as being ‘considerable’. Activities and Outputs

Young Farmers Installation Scheme

The output, result and impact indicators for the Young Farmers Installation Scheme under Measure 112 as set out in the RDP are shown overleaf. Given the very significant changes in the target levels in response to adjustments in the programme in 2008-2009, the revised targets were significantly different from those set initially. For example, initially it was proposed that 4,200 farmers would benefit from the scheme, which would suggest that just 21% of the target was achieved. As with other programmes, these mid-programme changes in targets raises difficulties in tracking and commenting on success over the 2007-2013 lifetime of the programme. Furthermore, the result and impact measures were not tracked at farm level and, as such, cannot be used to assess the achievement of the programme either in absolute terms or against the percentage of target. A broader issue with the indicators is that the results and impact targets were set at a very aggregate level and it is questionable whether these are likely to be the best indicators of the measures introduced.

Table 6.4: Output Targets and Indicators for Measure 112 under the RDP 2007-2013

Type of Indicator

Indicator Revised Target -

2007-2013

Achievement 2007-2013

Percentage (%) of Target

Output Number of assisted young farmers 941 862 92%

Result Increase in agricultural gross value added in supported farms

€10.3 million NA NA

Impact

Net additional value added expressed in PPS

€1.5 million per annum

NA NA

Change in gross value added per annual work unit

€1,020 per annual mwu

NA NA

Source: DAFM Indicator Data

The YFIS measure was introduced in June 2007 and due to the small number of applicants that developed to payment stage that year, expenditure did not become evident until 2008, during which a total of 357 young farmers were supported involving expenditure under the scheme of €5.45 million. A total of 941 applications for grant-aid were received under this scheme before its suspension and, up to the end of 2013, 862 applications had been paid, totalling just under €12.9 million.

37 http://www.agriculture.gov.ie/media/migration/publications/2009/VFMReviewofYoungFarmersInstallationScheme.pdf




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Early Retirement Scheme

The output, result and impact indicators for the Early Retirement Scheme (Measure 112) as set out in the RDP are shown below. As with the YFIS, these reflect the revised targets following the closure of the programme in 2008, and as such do not represent meaningful indicators of success over the life of the programme. In addition, the result and impact measures for the scheme were also not tracked at farm level, and as such, cannot be used to assess the achievement of the programme. Notably, the targets set for gross value added per full-time equivalent were lower than that set under the YFIS, even though much lower funding was allocated to the YFIS.

Table 6.5: Output, Impact and Result Targets and Indicators for Measure 113 under the RDP 2007-2013

Type of Indicator Indicator Revised Target 2007-2013



Output

Number of farmers early retired 636 (cumulative) 600 94%

Number of farm workers early retired

7 in total 0 0%

Number of hectares released 21,000 in total 19,808 94%

Result Increase in agricultural gross value added in supported farms

€6.36m €6.00m 94%

Impact

Net additional value expressed in PPS

€3,664,632 NA NA

Change in gross value added per full-time equivalent

€8,480 (cumulative)

NA NA


In 2007 the Early Retirement Scheme paid out €63.1 million, which equated to almost 24% of the total revised allocation under the RDP. Expenditure in 2008 was over €46 million, followed by over €40 million in 2009. ERS was suspended for new applications on 14th October, 2008. By that date, 467 applications (139 in 2007 and 328 in 2008) had been received. However, it became apparent that there was a certain number of farmers who had their preparations to apply for the scheme completed, or close to completion, at the time the scheme was closed. Therefore, the scheme was temporarily re-opened on 23rd September 2009 with limited additional funding, with a view to accepting as many as possible of the applications that fell into this category. The Managing Authority received a further 175 applications up to the new closing date of 30th October 2009. While the number of farmers who retired early as part of the scheme increased substantially in 2008, the outturn was below the target of 500 retirements set in the RDP. The suspension of the scheme for new applications in October 2008 would not have impacted on actual transfers in 2008, due to the delay between application and the finalisation of contracts.

In total, only 600 farms participated in the ERS scheme over the 2007-2013 period. Of note is the relatively small number of recipients compared to the total number of farms. There are approximately 139,860 family farms in Ireland with an average size of 32.7 hectares per holding (CSO Census of Agriculture 2011). Even assuming the scheme had zero deadweight, this would have the effect of reducing the average age of Irish farming by 0.09 of a year. In contrast, the average age of Irish farms has increased by around 0.37 of a year, every year, from 2000 to 2010. As such, the scheme was not large enough to have had a material impact on the overall aggregate position in relation to the age structure of Irish farming. However, we believe such a measure in principle is appropriate and targets a particular challenge concerning the age profile of farmers in Irish agriculture. Later in this report we consider some analysis of the likely impact of such measures.




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Dual Take-up of YFIS and ERS

YFIS and the ERS are considered by the DAFM to be complementary in relation to attempting to achieve structural changes in primary agricultural production and younger, more demographically viable primary producers. A number of beneficiaries of the YFIS were also transferees in the ERS. The benefit of dual take-up of these two measures was that with the YFIS there was certainty that the ERS transferees are of a certain age and educational attainment. However, of the 611 beneficiaries under YFIS, only 253 (or 41%) were ERS transferees, far below the original target of 65%.

Impact on gender

The RDP also makes provision for the promotion of gender equality in farming. The impact of the YFIS and ERS on gender can be reviewed by examining the gender split in each of the schemes. This is shown in the figure overleaf. This indicates a relatively small number of entrants (7%) under the YFIS being women, while a large number of the exits (35%) under the ERS were women. This may be explained by a large number of joint applications for the ERS scheme where a farm was run by a couple. In such circumstances, if one spouse retires, then the other spouse must also retire. The effective age distribution of male retirees as a result of the scheme might therefore be older than the scheme average age of 58. However, in terms of the promotion of gender equality, the very small number of women entrants receiving funding under the YFIS under the 2007-2013 RDP is disappointing.

Figure 6.4: Gender Impact of YFIS and ERS

Source: DAFM Annual Progress Reports

93%

7%

Farm Entrants Under YFIS

Male Female

65%

35%

Farm Exits Under ERS

Male Female




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The Indecon survey of beneficiaries under the ERS scheme asked how many successors were daughters. Only 1.4% said that their daughter was their successor, compared to 62.5% who said it was their son. Of all the farm beneficiaries surveyed, 28.4% reported that they sold, transferred or leased the farm to a non-family member. As such, the schemes appear to have contributed very little to the promotion of greater gender balance within farming.

Results

The ERS scheme was aimed at securing an improvement in the age profile of farming and an improvement in the skill level of farming, with a related impact on output and productivity. It is therefore useful to consider the extent to which there was a difference between the age of transferees and transferors; and the skill difference level between transferees and transferors. It is also necessary to consider the likely levels of deadweight (i.e., the extent to which the transfer of farms would have happened in the absence of the support).

Age Difference between Transferees and Transferors

The two tables presented overleaf show the change in ages of farmers, from those who had previously owned the farm to the successor of the respondent. The majority of respondents to Indecon’s research were aged between 65 and 69 (55.4%) at the time of the survey (2016), with a further 35.7% between 60 and 64.

Table 6.6: Current Age of Retired Farmers Who Participated in ERS Scheme

Percentage

55 - 59 0.0%

60 - 64 35.7%

65 - 69 55.4%

70 - 74 8.5%

75 - 79 0.5%

Over 80 0.0%

Total 100%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 1 – ERS Measure)

Table 6.7 table below shows that there has been a shift in the age of farmers on the farms covered by the survey. 1.4% of successors were over the age of 54 at the time of the survey (2016). Over half were between 36 and 54 years old, with 38.9% younger than 36.

Table 6.7: Current Age of Successor to Farmers Who Participated in ERS Scheme

Percentage

18 – 35 years 38.9%

36 – 54 years 59.7%

55 – 66 years 0.9%

Over 66 years 0.5%

Total 100%





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Recipients were also asked to indicate whether they believed the scheme was targeted at the right age group. The majority of respondents (70.6%) felt that the scheme was targeted at the right age group, as shown in Table 6.8 below. There were some (15.2%) who believe it should have been targeted at farmers older than 65, with 7.4% believing it should have been targeted at farmers under 55.

Table 6.8: Views on Targeting of Early Retirement Scheme

Percentage

The scheme was targeted at the right age group 70.6%

The scheme should have been aimed more at encouraging farmers older than 65 to retire 15.2%

The scheme should have been aimed more at farmers under 55 to retire early 7.4%

Don't know 6.9%

Total 100%


Overall, it appears that there was a significant (approximately 30-year) difference between the typical age of transferees and transferors under the ERS. When asked what relation the successor to the farm was to the respondent, almost two-thirds (64%) of respondents stated that it was their son or daughter who was the successor.

Skill/Education Difference between Transferees and Transferors

As well as attempting to reduce the age of farmers, the ERS aimed at increasing the level of education of those farming. The evidence from Indecon’s survey research, presented in Figure 6.5 below, suggests that a larger proportion of those who succeeded from the respondent had completed upper second level or third level education. It was found that 30.3% of respondents had no formal education or were educated to a primary level, compared to only 1% among successors to the farm. As such, the ERS scheme appears to have been correlated with a significant upskilling, as measured by formal education levels.

Figure 6.5: Level of Education of Respondent and Successor to Farm for ERS Beneficiaries


0.0%5.0%

10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%50.0%

No formal education orprimary level education

Lower secondary(Junior Certificate)

Upper Secondary(Leaving Certificate) or

PLC course

Third level or above

Respondent Successor to Farm




54

Indecon’s primary survey analysis of participants in the ERS scheme also examined evidence on the reasoning behind the decision to retire. A vast majority (82%) of respondents said that the financial incentives of the scheme made it worthwhile to retire. 63.7% stated that they believed that their farm could be better managed by someone younger than them. Some also felt that their general health was not good enough (30.2%) or that the person who took over would have left farming otherwise (40.6%).

Table 6.9: Main Factors Behind Farmers’ Decision to Retire

Agree Neither

Agree nor Disagree

Disagree

My general health was no longer good enough to run the farm 30.2% 17.8% 52.1%

The farm could be better managed by someone younger than me 63.7% 22.8% 13.5%

I wanted to get a job outside of farming 14.6% 20.5% 64.9%

The financial incentives made it worthwhile to retire when I did 82.0% 9.9% 8.1%

The person who took over might have left farming if I had not handed the farm over when I did

40.6% 24.2% 35.2%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 1 - ERS Measure)

Finally, beneficiaries of the ERS were asked whether or not taking up the ERS had an effect in how the farm was run (see findings in table below). Over one-third of respondents stated that the farm is run in a very similar manner to how it was previously run. Over half of respondents said that the farm had modernised significantly and that it was being run more efficiently than it had been under their management. However, caution should be exercised in interpreting such qualitative perceptions and in this report we later examine more rigorous quantitative modelling of the impact of the age of farmers on output and productivity.

Table 6.10: Views on the Change in the Management of the Farm

Percentage

The farm is run in much the same way as I had run it 33.8%

The farm has modernised significantly since I retired and is now more efficient 55.4%

The farm doesn’t operate as efficiently as when I operated it 3.8%

Don’t know 7.0%

Total 100%





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Deadweight

One of the challenges in any scheme such as the YFIS and the ERS was to minimise the level of deadweight that is inevitable in almost all such programmes. In particular, it is likely that a number of those who would have taken over a farm or retired would have done so without the support of the YFIS and the ERS respectively.38 The Department’s 2009 Value for Money Review survey of grant recipients was utilised to provide one estimate the level of deadweight for the YFIS by asking what would have happened if the recipients had not received the grant aid. The results are shown in the figure overleaf. These suggest that a majority of transfers relating to the YFIS would have taken place at the same time regardless (59%), though in 31% of cases it was suggested that the transfer was brought forward, by more than three years in 22% of the cases. This suggests a high level of deadweight for the scheme.

Figure 6.6: Outcome of YFIS without Installation Aid

Source: DAFM VFM Study. Figures exclude ‘don’t knows’.

The possible levels of deadweight under the ERS programme can also be estimated from the primary survey analysis conducted by Indecon for the purposes of this ex-post evaluation. Table 6.11 provides an indication of the level of deadweight in the scheme. 11.7% of respondents said that they would have retired anyway, suggesting that the scheme was not necessary for them to retire. Almost half of respondents said that they probably would not have retired for the foreseeable future, suggesting the scheme incentivised some people to retire who would not have retired. On top of this, 15.5% said it brought their retirement forward by up to three years.

38 One other element of deadweight relates to training. The DAFM value for money review argued that since seven out of eight recipients said they would have completed training anyway may point to deadweight. However, it is more likely that the educational requirement operates more as a screening device to ensure that the young farmer in question actually does bring more modern techniques to the farm, and not necessarily to get that particular farmer to avail of education. Ideally Indecon would have liked to empirically test deadweight using an econometric base counterfactual analysis involving propensity score matching or other techniques but data to utilise such an approach was not available.

Taken over the farm at the same time as you did?,

58.7%

Taken over the farm at least 1 year later than you did?,

8.7%

Taken over the farm at least 3 years later than you did?,

22.1%

Not taken over the farm and worked on a farm

ownedby somebody else?, 5.8%

Not taken over the farm and chosen a different

career?, 4.8%




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Table 6.11: Counterfactual Scenario In Absence of ERS

Percentage

Retired at the same time as you did? 11.7%

Retired within three years anyway? 15.5%

Not retired for the foreseeable future? 46.6%

Don’t know 26.2%

Total 100%


The two sets of survey results would appear to suggest that the level of deadweight was significant for the YFIS scheme, but more limited for the ERS scheme. While this might support a view that policy should focus on encouraging older farmers to retire, rather than incentivising younger farmers to join farming,39 Indecon believes there is merit in measures which ensure that younger individuals are attracted to a career in farming. In addition, we would caution that the qualitative survey results for the relatively small number of YFIS beneficiaries may not be representative of the potential of such measures, and a possible explanation for the results may also be the small levels of funding provided under this measure.

6.4.1 Impacts

In evaluating the likely impacts of the ERS and YFIS measures, it is useful to examine the progression of the average age of farmers in the Irish farming sector. As indicated by the figure below, the average age of Irish farmers has been progressively getting older between 2000 and 2010. This appears to relate to a combination of two factors. The first factor is the apparent long-run decline in the numbers of young farmers in Ireland. From 2000-2010 the number of farmers under the age of 35 more than halved, while the number of farmers over the age of 65 – which is the normal retirement age in most other industries – increased by 31%. The second factor relates to the very sharp rise in employment in Ireland up to 2007/8, and the subsequent rise in unemployment. In the immediate aftermath of the financial and economic crisis there was an increase in on-farm employment, which might have increased the number of younger farm workers. The overall structure of Irish farming remained the same, despite these short-term shifts. By 2010, there were more farmers over the age of 65 than under the age of 45 in Ireland.

39 See: http://capreform.eu/wasting-money-on-young-farmers/

http://capreform.eu/wasting-money-on-young-farmers/




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Figure 6.7: Average Age of Irish Farmers, 2000-201040

Source: DAFM Compendium of Irish Agricultural Statistics 2013

A study by Teagasc published in 2014 showed that in the period 2000 to 2011, the percentage of farmers with formal agricultural education increased from 24% to 44%, with a greater increase evident in the proportion of farmers achieving an agricultural certificate, going to agricultural college or attending short courses, compared to those achieving university-level agricultural training.41 The study also suggests a high private return to investment in agricultural education (8.8%). In addition, there is a high social return to investment in agricultural education at farm level (13.4%), which rises to 24.5% when wider supply chain impacts are factored in.

While the aggregate results do not show an impact on the overall age structure of Irish agriculture, of note is that there was a marked difference in the age of beneficiaries under YFIS and the age of previous owners.

Econometric Evidence on Impact on Output of Farmers Age in Irish Agriculture

While both the YFIS and ERS measures are based on an assumption that younger farmers will be more productive and will enhance output, this is an empirical question, which should be formally tested in any evaluation.

Previous detailed econometric research undertaken by Indecon examined the impact on farm output levels resulting from a transfer of farms to a younger generation. Many older farmers have expertise and experience, which is of real value. However, in most walks of life, particularly where significant manual work may be required, there can be an impact on productivity after a certain age. The impact of retirement and land transfers on productivity, output and the implementation of new environmentally sustainable methods will of course vary significantly by individual. However, the previous research undertaken by Indecon econometrically tested the impact of age on output and productivity.

40 Note that the data cited here is just to 2010 given that the schemes in question had been closed by this time. 41 http://www.teagasc.ie/publications/2014/3374/Teagasc_Impact_of_Education_Report.pdf

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2000 2001 2002 2003 2005 2007 2010

< 35 35-44 45-54 55-64 > 65




58

The results from our different econometric models were all statistically significant and indicate that older farmers (over 65) have lower levels of output relative to all farmers under 65. The econometric estimates presented below for Irish agriculture suggest that reducing the number of farmers who are over 65 would increase overall agricultural output by between 4.0% and 7.1%. In other words, farmers over 65 typically have output that is between 4-7.1% lower than farmers who are under 65. Overall, our results are consistent across a number of different econometric model specifications and indicate that farmers who are over 65 have lower levels of productivity than younger farmers.

Table 6.12: Percentage Estimates of relationship between Output and being over 65

Econometric Model % estimate

Cobb-Douglas Production Function -4.6%

Translog Production Function -4.0%

Olley-Pakes Production Function -7.1%

Source: Indecon analysis for Review of Agricultural Tax Incentives for Department of Finance/Department of Agriculture, Food and the Marine

In addition to the above analysis, new econometric modelling undertaken by Indecon for this evaluation involved further research on the impact of the age of farmers on output, using updated data from the Teagasc National Farm Survey database. This indicates that the statistical evidence supports the idea that older age has a negative impact on output and productivity; that is to say, a negative relationship between being older as a farmer and output, or between a farmer’s age and his/her productivity, was found to exist.

Previously, we modelled age as a variable of over-65 and 65 and under (e.g., 1 if over 65). In this new modelling, we modelled age as a continuous variable, and also allowed for the possibility of age having a non-linear effect. In this case, in all of our panel data models, the age variable was significant and negative. The linear term was negative. The quadratic term was often positive and significant, but the coefficient was relatively small, so the impact of age on output and productivity was in general negative over the relevant range of farmers’ ages (e.g., 20-80 years of age).

The new data utilises a different dataset in the form of the full Teagasc National Farm Survey microdata and updated (more recent) data provided to Indecon by Teagasc for the purposes of this evaluation. We also included a more parsimonious form of the production functions underlying the models tested, and a number of different model specifications. Furthermore, we included dummy variables for the various interventions, including Disadvantaged Areas Payment and agri-environmental (AEOS) supports, in addition to land grants and building grants. We attempted to model young farmer grants as a separate ‘treatment’, but this proved impossible as only a very small number of farmers (e.g., on the order of 50) in the whole sample received such grants, and thus the regression procedure did not have sufficient data on those farmers who received a grant versus those who did not to estimate any kind of meaningful counterfactual treatment model (for the dummy variable models, the variable was simply insignificant, whereas for the Regression Adjustment treatment models, the regression would not converge). The results of this modelling are presented in the table overleaf.




59

Table 6.13: Impact of Farmer Age on Output – Econometric Panel Data Models

Output random effects

fixed effects random effects

fixed effects

random effects

fixed effects

Payment type Land

Improvement Land

Improvement Building Grants

Building Grants

Disadvantaged Disadvantaged

ln_lab 0.22 0.124 0.219 0.123 0.221 0.126

(17.75)** (9.73)** (17.74)** (9.72)** (17.84)** (9.94)**

ln_size 1.238 0.71 1.242 0.714 1.237 0.709

(20.90)** (10.40)** (20.97)** (10.46)** (20.88)** (10.39)**

ln_size_2 -0.115 -0.065 -0.116 -0.066 -0.115 -0.065

(16.01)** (8.04)** (16.04)** (8.08)** (16.01)** (8.07)**

YE_AR 0.011 0.014 0.012 0.014 0.011 0.013

(19.30)** (24.14)** (19.66)** (24.41)** (18.40)** (22.72)**

FARM_MD_AGE -0.004 -0.002 -0.004 -0.002 -0.004 -0.002

(10.60)** (5.26)** (10.67)** (5.31)** (10.79)** (5.48)**

farm_age2 0 0 0 0 0.000 0.000

(9.51)** (4.72)** (9.57)** (4.76)** (9.68)** (4.92)**

ln_cap 0.258 0.179 0.255 0.176 0.26 0.181

(31.78)** (21.66)** (31.26)** (21.22)** (32.03)** (21.94)**

ln_fuel 0.095 0.061 0.095 0.061 0.095 0.06

(22.87)** (14.47)** (22.86)** (14.46)** (22.92)** (14.48)**

N 13,648 13,648 13,648 13,648 13,648 13,648

R2 0.25 0.25 0.25 Source: Indecon **: Signifies economic significance at a 1% level.

The models results presented above show the impact of farmers’ age when accounting for the different payment/support types. The dependent variable in this case is gross farm output and the models shown are fixed effects and random effects, which are standard panel models. The impact of farmer manager age is highlighted in bold. The farmer’s age variable has an impact on farm output estimated in the range of -.002 to -.004. A quadratic (non-linear) variable was included but its actual coefficient is sufficiently small that it can be omitted, i.e., it has a negligible impact on the actual predicted output. The age variable is in units and the dependent variable is in logs. So the interpretation is a % change for a given number of units change. So for a farmer of age 40 versus a farmer of age 50, meaning a 10-year increase, that would mean a 4% reduction in output at the higher coefficient.

The next table shows the impact of farmers’ age on productivity, as measured by farm output per unit of labour input. The coefficients on age are again shown in bold type. The remainder of the reported figures relate to the various other factors which are included in the model, to ensure that the impact of farmer age is accurately isolated. The range shown is about -.003 to -.004 across a variety of assumptions regarding how productivity is measured and the type of payment involved. The purpose of running many different model types is to ensure that the results are robust, and that the reported impact is not sensitive to the nature of the economic assumptions which underpin these models. These are in age units, but the dependent variable is in logs, so the interpretation is that a 10 years (units on age) increase would reduce productivity by about 0.04 or 4%.




60

Table 6.14: Impact of age on productivity panel models

Productivity random effects


fixed effects

random effects

fixed effects

Payment type Land

Improvement Land


Building Grants


ln_size 1.139 0.654 1.141 0.656 1.138 0.653

(19.04)** (9.07)** (19.07)** (9.09)** (19.03)** (9.08)**

ln_size_2 -0.118 -0.074 -0.118 -0.074 -0.118 -0.074

(16.11)** (8.60)** (16.14)** (8.62)** (16.11)** (8.63)**

year 0.011 0.012 0.011 0.012 0.01 0.011

(17.81)** (19.24)** (18.03)** (19.33)** (16.62)** (17.60)**

FARM_MD_AGE -0.004 -0.003 -0.004 -0.003 -0.004 -0.003

(12.03)** (7.15)** (12.11)** (7.22)** (12.22)** (7.40)**

ln_cap_lab 0 0 0 0 0 0

(10.82)** (6.42)** (10.89)** (6.48)** (10.99)** (6.65)**

ln_fuel_lab 0.342 0.314 0.341 0.314 0.343 0.315

(45.19)** (40.11)** (44.82)** (39.83)** (45.39)** (40.33)**

2bn.d_soil_group 0.102 0.079 0.102 0.079 0.102 0.079

(23.91)** (18.08)** (23.91)** (18.09)** (23.94)** (18.03)**

N 13,646 13,646 13,646 13,646 13,646 13,646

R2 0.17 0.17 0.18 Source: Indecon **: Signifies economic significance at a 1% level.

6.4.2 Discussion

A notable feature of the YFIS and ERS schemes during the programme period was the relatively low level of take-up prior to the schemes’ closure. There are a number of potential reasons for this. An issue that may have affected take-up was that many farms may not have created sufficient income to support two families. This issue was raised by a number of stakeholders as part of the evaluation consultation process. As part of the Expenditure Review of the scheme in 2004, stakeholders identified the fixed level of pension to be a concern, as a result of which the maximum pension was increased to €15,000 in the new RDP compared to €13,515 prior to this. Even at this level, the ability of an existing farm to expand with the increased supply of labour available may have been limited.

Another issue relates to the fact that the effect of the Single Farm Payment may provide a financial incentive for farmers to remain in farming. Under the previous CAP regimes, a farmer would have had to produce in order to receive support. Under the Single Payment Scheme, all that is required of a farmer is to comply with cross-compliance conditions. This may have allowed some farmers approaching the age of retirement to rationalise their farming activity, while still maintaining their single payment.42

42 See: http://capreform.eu/wasting-money-on-young-farmers/





61

The other potential reason why uptake was not greater concerned the target age group. The ERS applied to farmers between the ages of 55 and 65. It provided for a pension up to the age of 66, and therefore was of most benefit to those farmers at the younger age of this 55-65 range, who had the most years to run before the payment ceased. Assuming a uniform age distribution and ignoring mortality, the average target age of this scheme, weighted by the age-specific benefits, was 58. Perhaps unsurprisingly, the average age of scheme take-up in 2008 was 58.43 This was very close to the average age of the Irish farmer, at 57,44 indicating that the target group for the scheme was not ‘older farmers’ per se, but rather holders at the middle of the age-distribution of Irish farming.

Given the difficulty of persuading farmers to retire, it might not be considered surprising that it proved difficult to persuade farmers who are 55-65 to do so. Farmers, like the rest of the population, are living longer, are physically healthier at each age level, and are more capable of continuing to manage a farm enterprise. But unlike the rest of the population, a farmer’s place of residence is also likely to be his or her place of work.45 Many older farmers choose to remain in agriculture because they like the lifestyle and have an attachment to a home which may have been in the family for many generations, as well as other cultural factors. This is often coupled with a lack of affordable and suitable housing in rural areas for farmers who may want to retire. The consequence is that successors must wait longer to take over the farm. And in some Member States, rural areas have become more attractive for elderly people who retire or start a part-time farming activity in agriculture.42 This would suggest that early retirement schemes are likely to have relatively little overall aggregate effect, which is also supported by a review of evidence from other European countries.46 However, our new econometric modelling shows the validity of such measures in increasing output and productivity, if sufficient take-up can be incentivised.

Stakeholder consultations also suggested that young people are not sufficiently attracted to a career in farming. Some indication of the level of interest in farming as a career can be sought by looking at the number of higher education CAO applications for agricultural-related courses, whether at degree, diploma or certificate levels. This is shown overleaf for the period 2000-2016. The figure suggests that demand for farming courses is highly cyclical, increasing at a time when the overall economy is performing poorly. Many national policy interventions also affect the willingness or otherwise of young people to take up a career in farming, for example the payment of Stamp Duty on farm transfers.

43 See: DAFM Annual Progress Report of the Rural Development Programme – Year 2008. 44 See: http://ec.europa.eu/ireland/key-eu-policy-areas/agriculture/index_en.htm 45 See: http://capreform.eu/wasting-money-on-young-farmers/ 46 Study on Employment in Rural Areas (SERA), study commissioned by the European Commission Directorate General for Agriculture,

2006.

http://ec.europa.eu/ireland/key-eu-policy-areas/agriculture/index_en.htm





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Figure 6.8: CAO applications for Agriculture/Horticulture, 2000-2016

Source: CAO

The National Workshop undertaken as part of this ex post evaluation also highlighted a wide range of challenges associated with attracting younger people into farming. The administrative burden in applying for certain grants can reduce the incentive to take them up. In addition, potential young farmers are often credit-constrained and may decide to move into other careers. The small scale of incentives provided under YFIS in this context is also of note.

6.5 Measure 121: Modernisation of Agricultural Holdings

In this section, the RDP’s on-farm investment schemes under Axis 1 are evaluated. These are, namely, the Farm Improvement Scheme (FIS) and the Targeted Agricultural Modernisation Scheme (TAMS). The evaluation commences with a short introduction of the measures, followed by a discussion of the Programme Logic Model with respect to these two schemes. The aim of this section is to help address the following Common Evaluation Questions:



Question 5: To what extent has the RDP contributed to improving the competitiveness of the agricultural and forestry sector?

Question 6: To what extent has the RDP accompanied restructuring of the dairy sector?

Question 10: To what extent has the RDP contributed to introduction of innovative approaches?

Question 14: How efficiently have the resources allocated to the RDP been used in relation to achieving the intended outputs?

Question 15: For each of the Axis 1 measures included in the RDP - How and to what extent has the measure contributed to improving the competitiveness of the beneficiaries?

Question 20: What other effects, including those related to other objectives/axes, are linked to the implementation of this measure (indirect, positive/negative effects on beneficiaries, non-beneficiaries, local level)?

-

1,000

2,000

3,000

4,000

5,000

6,000

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

Degree Level Dip/Cert Level




63

Background to Measure 121

The Farm Improvement Scheme (FIS) was designed to help Irish farms to be competitive through an increase in capacity. This scheme provided grant aid for investments that encourage the development and use of modern, highly specialised, cost-efficient and labour-saving facilities and equipment. The objectives of the original scheme are as follows:

(i) To ensure that the agriculture sector in Ireland becomes more competitive and market-oriented;

(ii) To promote higher quality and greater efficiency in production on Irish farms;

(iii) To promote diversification of activities, for example horse breeding, on Irish farms, thereby providing other sources of agricultural income;

(iv) To promote higher standards of animal welfare and protection of health and safety on Irish farms; and

(v) To ensure higher environmental standards on Irish farms and reduce overall greenhouse and transboundary gas emissions from the agriculture sector.

The conditions of the scheme were typically that a portion of the cost (e.g., 40%) in eligible investment projects was covered by a grant subject to a maximum eligible investment ceiling. Payments were made only when the outcome of the investment met the conditions of the scheme. Payment was then administered on the basis of receipts and invoices submitted by the farmer subject to compliance with the Department’s Standard Costings. The RDP outlined the following areas which qualified for investments:47

Animal housing, handling and related facilities; Sheep handling and weighing facilities;

Investments in regard to diversification of farm enterprises, including handling facilities, exercise arenas and fencing for horse/deer breeding and production;

Investments relating to improvement of dairy hygiene;

Investments which improve animal welfare standards including the conversion of sow housing to meet new EU animal welfare standards, the installation of rubber mats on slats/cubicle beds, etc.;

The installation of water storage equipment on farms for the recycling of rainwater;

The installation of equipment designed to improve occupational safety;

On-farm grain storage; and

New and developing technology for the processing of manure.

The Farm Improvement Scheme was suspended to new applicants on October 31st 2007, five months after it had been launched, as the financial ceiling for the scheme was reached due to the large number of applicants. In place of the FIS, the Targeted Agricultural Modernisation Scheme (TAMS) was introduced in 2010. It was co-funded under the Health Check agreement and the European Economic Recovery Plan (EERP). Its aim was to provide a more targeted investment scheme and to maintain the balance of EAFRD funding across the Programme axes. Whilst the broad objectives TAMS were the same as under FIS, market orientation and competitiveness were the primary focus of the new scheme. Four of the key areas which TAMS was designed specifically to address were

47http://www.environ.ie/sites/default/files/migrated-files/en/Publications/Community/RuralDevelopment/FileDownLoad,26522,en.pdf




64

dairy restructuring, animal welfare, renewable energies and water management. This can be seen in Table 6.15 which outlines the funding allocated to support six incentives under this scheme.

Table 6.15: Targeted Agricultural Modernisation Scheme (TAMS) – 2010-2013

Scheme EAFRD Fund National Funding

Total Funding Scheme Launched for Applications – Yes/No

Dairy Enterprises €22.5m €22.5m €45m Yes (March 2011)

Sheep Enterprises €4m €4m €8m Yes (November 2010)

Pig Welfare €6.5m €6.5m €13m Yes (June 2010)

Poultry Welfare €8m €8m €16m Yes (June 2010)

Water Conservation €4m €4m €8m Yes (March 2011)

Bio-energy €10m €10m €20m Yes (8 Feb 2010)

Total Investment: €55m €55m €110m - Source: Rural Development Programme, 2007-2013 (inclusive of budget revisions agreed on 17 March 2010)

Intervention Logic

The table overleaf sets out the Programme Logic Model for Measure 121. The core objective of this measure was to ensure that Ireland’s agricultural sector became more market-oriented and more competitive thereby increasing output and productivity. The logic behind the measure was that by providing subsidies for capital investment (inputs), farms would be incentivised to make investments in building and equipment which they would not otherwise make (outputs). These investments would help to modernise the farm, as evidenced by the introduction of new techniques/products, resulting in higher farm productivity (results). These would have a broader impact in terms of an increase economic activity in rural areas, while there would also be benefits from these investments in terms of health and safety, animal welfare and the environment (impacts). The logic of this measure assumes the following:

Capital investments have the potential to increase farm productivity, output and promotion of higher environmental standards. Econometric evidence undertaken by Indecon sheds some light on the validity of parts of this logic;

There exists a so-called ‘market failure’ whereby on-farm investment would not have taken place anyway by rational farmers based on private self-interest, or that the extent of public benefit was such that, where the private benefits were not sufficient to justify investment, that the public and private benefits combined would give these investments an overall positive cost/benefit profile. This could also be influenced by potential credit restrictions to fund viable projects; and

That the level of support was proportionate given the objective, and that a similar outcome could not have been achieved with a lower subsidy for each investment.




65

Table 6.16: Programme Logic Model – Measure 121 – On-Farm Investment

Source: Indecon

The assessment of the measures inputs, activities and outputs, and finally results and impacts are discussed below.

Inputs

There was a substantial interval between the date of issue of approval and the date of payment. In the first year of the scheme only €46,000 was provided by the grant scheme for investment in the modernisation of farms, in comparison to 2008 when a total of €13.3 million was invested in 2,516 farm holdings. Investment increased in 2009 to €28.2 million, and a further €13.2 million invested in 2010, when the new Targeted Agricultural Modernisation Scheme was introduced.

Table 6.17 outlines the levels of expenditure in each year of FIS originally and TAMS in the later years of the programme. The year following the introduction of TAMS saw a drop in expenditure from €13.24 million to €4.71 million. A total of €35.44 million was spent in the years following the introduction of TAMS (2011, 2012 and 2013), of 39.4% of the total spend over the full life of the RDP.

Table 6.17: Annual On-Farm Investment (Measure 121) Expenditure – 2007-2013

Year Expenditure

(€ - millions) % of Total

2007 0.1 0.1%

2008 13.3 14.7%

2009 28.2 31.3%

2010 13.2 14.7%

2011 4.7 5.2%

2012 18.8 20.8%

2013 12.0 13.3%

Total 90.2 100%

Source: Indecon analysis of DAFF Annual Progress Report data. This table does not include expenditure in 2014 and 2015.

INPUTS

Exchequer Funding

EU Funding

Administrative support

ACTIVITIES

Payments to approved applicants

Scheme administration

Farm inspections

OUTPUT

Capital investments made by farmers

Number of payments made to

eligible farmers

RESULT

Increased farmer productivity

Introduction of new farming techniques

Introduction of new products

IMPACT

Increase economic activity in rural

areas

Improvement in health & safelty,

animal welfare and environment.




66

The table below presents the level of expenditure under Measure 121 between 2007 and 2013. Out of the original budget of €194.5 million, €90.2 million (46.4%) was invested in the modernisation of Irish farms through the grant scheme.

Table 6.18: On-Farm Investment (Measure 121) Expenditure – Actual versus Budgeted

Total – 2007-2013

Actual expenditure €124.0 million

Budgeted expenditure €127.0 million

Actual expenditure as % of budget 97.7%

Source: Indecon analysis of DAFF Annual Progress Report data. This include expenditure in 2014 and 2015.

The European Court of Auditors48 criticized some Member States for the retroactive approval of investments, which ran the risk of scheme deadweight (i.e., that the project would have gone ahead without the support). The fact that the investments/drawdowns in Ireland did not take place until typically one to two years after grant approval illustrates that this retrospective aspect was not a feature of the implementation of the farm modernization schemes in Ireland. The National Workshop completed as part of the ex post evaluation highlighted the challenge some farmers faced to proceed with investments before the deadline for funding expired, while a number of farmers in the survey of beneficiaries conducted by Indecon suggested that suppliers increased their prices, negating the beneficial impact of the support.

Activities & Outputs

The combined targets were set for FIS and TAMS are shown in the table below. According to the output indicators provided by the Department,49 7,603 holdings were supported over the course of the programme, representing 109% of the revised target of 7,000. The number of holdings introducing new products or techniques was just under half of the target. A number of other result and impact indicators were set by the Department, though data was not provided on outcomes.

Table 6.19: Output, Impact and Result Targets and Indicators for the Combined Measure 121 under the RDP 2007-2013

Type of Indicator Indicator Revised Target 2007-2013



Output

Number of farm holdings supported

7,000* 7,603 109%

Total volume of investment €227 million €225 million 99%

Result

Number of holdings introducing new products or techniques

6,600 3,020 46%

Increase in gross value added in supported holdings

€164.2m €12.5m 7.6%

Impact

Net additional value expressed in PPS

€74.7 million NA NA

Change in gross value added per annual work unit

€1,500 per annum

NA NA

Source: Indecon analysis of DAFF Annual Progress Report data * The target set out I the indicator data differs from that set out in the published RDP document.

48 Targeting of Aid for the Modernisation of Agricultural Holdings, Special Report Number 8, 2012.

49 O121(2)




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Box 6.1: Case Study 2: Implementation of Measure 121 in England and Ireland – Key Findings

Introduction and Rationale

In this case study, we review and contrast the implementation of Measure 121 in Ireland and England, which was aimed at increasing on-farm investment. The allocation of funding to this measure under the RDPs was remarkably similar (around €150m) in both cases, although in a context where there are more than twice as many commercial farms in England as in Ireland, managing 8.9 m ha of farmland, as against 4.5 m ha in Ireland. As such, the allocation was roughly twice as big in Ireland per hectare as in the UK. In the Irish RDP, the rationale for this measure was cast specifically in the context of increasing global competition in agriculture and the need to improve performance across the sector, but particularly among the most intensive and efficient farms in the south-east of the country. In the RDP for England the rationale was to address market failures in respect of investment.

Delivery approaches

The Irish RDP offered this measure in two open calls: the first (FIS) was made available as soon as the programme launched but was heavily oversubscribed against the available budget, and was subsequently closed in October 2007 as the money was fully committed. The second and much more targeted version of the scheme opened in 2012 with a closely prescribed range of possible investments. This ran until the RDP closed, and did not spend all of its budget. Nevertheless, the total spend for this measure was around €90m.

Concerns about variation in delivery arrangements hindering overall efficiency were noted in the English RDP. The English RDP delivered Measure 121 initially mainly through the Regional Development Agencies (RDAs) and subsequently Defra’s centrally-administered Rural Economy Grant (REG) scheme and Farming & Forestry Improvement Scheme (FFIS). After the abolition of RDAs and the launch of FFIS and REG schemes in 2012, the measure was offered through specific ‘calls’ with different priorities and scoring to rank applications.

These different approaches between Ireland and England are partly explained by the smaller and simpler nature of policy structures in Ireland as compared to England. Further, the existence of a single agency (Teagasc) which advises farmers also helps reinforce the relative simplicity of Irish programme design relative to that which prevailed in England. However, the greater variety of approaches used in the English RDP have enabled lessons to be learned concerning how best to seek maximum cost-effectiveness with investment aid of this kind.

Deadweight

Although a small minority of beneficiaries in England surveyed reported that projects would not have proceeded at all without support, the majority indicated that their project would have proceeded to some extent, typically at a slower pace and/or smaller scale. This confirms earlier findings of significant deadweight effects generally in the range of 25% - 50%. Caution is necessary in interpreting these figures. Even if a beneficiary reports that a project would have been done anyway, this might incorrectly lead evaluators to conclude that this represents deadweight for a number of reasons. Firstly, the grant’s existence encourages beneficiaries to consider investment plans, and secondly, the process required to get the grant can sometimes ensure that projects are better planned.

The financial crisis also affected Ireland more severely than England. The deadweight in the Irish case was likely lower after the crash because private finance would be less available. In England, the crisis had less effect in terms of on-farm investment, though public match funding was harder to come by after 2010 due to austerity measures.

Application/Administrative Processes

Stakeholder interviewees in England expressed concerns about the transaction costs of application processes which imposed burdens on administrators, third-part delivery agents and applicants. Changes to schemes and delivery arrangements required (re)familiarisation with processes and imposed additional burdens, although continuity of staff was reported to have eased transition problems in some cases. Similarly, the National Workshop in Ireland expressed issues with administrative processes, in particular that many seemed to have common closing dates which impacted the ability to apply in a timely manner, while the same information required had to be inputted numerous times.

Conclusion

The conclusion is that in both England and Ireland, measure 121 contributed to the competitiveness of beneficiaries, although a degree of deadweight was incurred. The major difference between the two implementation programmes was the relative simplicity of the structures in Ireland (i.e. Central Government and Teagasc) relative to the English RDP. Further, the financial crisis might have impacted measures of deadweight differently in each of the two countries.




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Table 6.20 below outlines a breakdown of output indicators such as the number of applications approved and the level of investment made in different areas of intervention. Of the areas with available data for the period of the scheme the largest degree of investment was in ‘Other’, with €27m invested in 666 applications overall.

Table 6.20: Output Indicators for Measure 121 under the RDP, 2013

Area of Intervention

No. of applications approved Public expenditure Total volume of investment (‘000

EUR) Organic production

Other Production

Total EAFRD Total

Areas with handicaps other than mountain areas

6 191 197 348 410 1,025

Natura 2000 areas 2 125 127 596 702 1,755

Other 4 662 666 9,228 10,937 27,342

Total 12 978 990 10,172 12,049 30,122

Source: Indecon analysis of DAFM Annual Progress Report data

Data provided by DAFM shows that 2,971 holdings introduced new products following the introduction of the scheme, as well as 49 enterprises who introduced new techniques. Thus, over 40% of holdings which had applications approved introduced either new products or new techniques. The GVA of the support holdings/enterprises was estimated by the DAFM to be €12.521 million, as can be seen in Table 6.21.

Table 6.21: Results from Measure 121

Measure

Number of holdings/enterprises introducing new products and/or new

techniques

GVA in support holdings/enterprises (‘000

EUR)

New technique New product Agricultural sector

Modernisation of Farms 49 2,971 12,521

Source: DAFM Annual Indicator Data

The production of indicators for ‘new products or techniques’ may be related to other factors. The European Court of Auditors suggested,50 whilst the Measure 121 “was achieving its nominal objective of modernisation, this was almost inevitable as any investment or purchase of new equipment results in some degree of modernisation.” This may also apply to new techniques. The introduction of more modern machinery may be associated with new techniques, and may not be an independent indicator of the effectiveness of the measure. However, the new products developed may be a more useful indicator.

50 Special Report No. 8, Targeting of Support for the Modernisation of Agricultural Holdings, 2012.




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The table below shows the results of the Indecon survey of beneficiaries of the FIS/TAMs measures. More respondents to the survey stated that they availed of the Farm Improvement Scheme (42.5%), compared to the Targeted Agricultural Modernisation Scheme (27.1%). Almost one tenth of respondents availed of both schemes.

Table 6.22: Scheme Used by Farmer

Percentage

FIS 42.5%

TAMS 27.1%

Both schemes 9.9%

Neither Scheme 31.2%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 1 – FIS/TAMS Measure) Note: Percentages do not add up to 100% due to respondents selecting more than one response

Table 6.23 shows the different farming activities of respondents to this survey. The largest category were dairy farmers, with 40% of respondents stating that they were mainly dairy farmers. Suckler farming was the next most popular farming activity, mirroring the results of the other surveys.

Table 6.23: Type of Farming Activity Practiced by Farmer

Percentage

Mainly Dairying 40.0%

Mixed Livestock 14.0%

Beef 17.0%

Sheep 13.7%

Tillage 3.3%

Suckler 20.7%

Mixed Crops and Livestock 4.0%

Dairy and Mixed Livestock 8.7%

Other 4.7%


When asked about the nature of the investment supported by the schemes, the majority of respondents stated that they used the support from the scheme to invest in new buildings (59.4%), as shown in the table below. 17.1% invested in new machinery, with a further 13.4% repairing existing buildings.




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Table 6.24: Nature of Investment Supported by the Scheme

Percentage

Investment in new machinery 17.1%

Investment in new buildings 59.4%

Repair of buildings 13.4%

Investment in mix of projects 13.8%

Other 16.6%


Results

Each of the main result of the programme logic model are discussed below. In particular, this assesses whether capital employed and capital investments increased farm output and/or productivity; and assesses the extent to which farm investment would not have taken place anyway in the absence of the grants.

The first element of the programme intervention logic is that the capital investment increased farm productivity and output. Econometric evidence presented later in this section suggests that increasing the level of capital was likely to increase agricultural output and productivity. A crucial element of the intervention logic for Measure 121 is that the support increases the amount of investment that would have otherwise taken place. If the investment merely replaced private funds (so-called ‘deadweight’), then the grant would have no added benefit in terms of the increased competitiveness of the agricultural sector from the running of the scheme. There are a number of ways that the existence of deadweight can potentially be assessed. To do this we have considered a formal quantified approach to considering the counterfactual analysis. This is in line with the European Commission’s guidelines to attempt to cross-check qualitative evidence with more formal quantitative analysis. Specifically, we employed econometric methods capable of measuring/ estimating the likely counterfactual using a “regression adjustment” (RA) model. In the RA model, the model predicts what a farmer ‘would have been like’ in terms of output and productivity, holding the independent variables constant, with and without the ‘treatment’ effects. In the case of the ‘treatment’, here they are the various forms of support. We are particularly interested in the Building Grants, and Land Improvement Grants and later in this chapter we examine the results of our modelling in terms of net impacts. It is useful, however, to first examine the supply and demand for credit over the course of the programme period from 2007-2013.

The absence of a sufficient supply of credit could lead to credit constraints amongst farmers, leading to otherwise viable investments not being made. The figure overleaf shows the aggregate level of loans outstanding to Irish commercial banks (column graph, left hand axis) from 2007-2010 to the agricultural sector. It shows that the aggregate level of loans outstanding rose and reached a peak in late 2008, before subsequently falling. Also of note is the change in credit conditions for SMEs in Ireland,51 as illustrated by the line graph, right-hand axis. This showed that credit constraints started to tighten in Ireland in mid-2007, and continued to do so until mid-2009. Lending did not start to ease until 2014, as measured by the Central Bank’s lending survey.

51 The data is not available to specifically identify farmers or the agriculture sector.




71

Figure 6.9: Supply of Credit and Changes in Bank Lending Conditions, 2007-2010

Source: Central Bank of Ireland

The National Workshop completed by Indecon also revealed a consensus among farmers that following the economic and financial crisis, there was a sharp decline in both the supply and demand for credit, which reduced the levels of on-farm investment. Farmers lacked the confidence in the future to invest in their farms due to the state of the overall economy. There was reduced aid from schemes and reduced credit from banks. It is suggested that the lack of continuity and the administration involved with applying for schemes further undermined confidence and made farmers even more unwilling to borrow money for investment.

The scheme may have had the unintended benefit of overcoming credit constraints on farmers who wished to invest in on-farm capital projects which emerged following the onset of the recession, even though this was not considered in the original programme design.

Another potential reason for market failure is that young farmers in particular may have found it particularly difficult to access credit, and may have less able to raise sufficient capital to modernise their farms. If this was the case, then the scheme would likely be targeted at younger farmers and younger farmers would tend to consist of a higher percentage of approved applicants than is presented in the figure below. While not surprisingly 75% of approved applicants were over the age of 40 the profile of recipient is somewhat younger than the national farm age profile.

1

2

3

4

5

€ -

€ 1,000

€ 2,000

€ 3,000

€ 4,000

€ 5,000

€ 6,000

Mar

-07

Jun

-07

Sep

-07

Dec

-07

Mar

-08

Jun

-08

Sep

-08

Dec

-08

Mar

-09

Jun

-09

Sep

-09

Dec

-09

Mar

-10

Jun

-10

Sep

-10

Exp

ect

ed

Ch

ange

in C

red

it C

On

dit

ion

s fo

r le

nd

ing

to S

MEs

Agg

rega

te L

en

din

g to

Agr

icu

ltu

ral S

ect

or,

€m

Forestry and logging

Other agricultural activities

Dairy Farming

Farming of cattle and other animals

Expected Change in Credit Standards on Loans or Credit Lines to Enterprises

RHS-Axis

LHS-Axis eased

considerably

eased somewhat

no change

tightened somewhat

tightened

considerably




72

Figure 6.10: Breakdown of Supported Holdings by Age of Approved Applicants

Source: Indecon analysis of DAFF Annual Progress Report data

The next table shows that the majority of respondents indicated they would have had to borrow money from a bank or credit union to fund the project, should financial assistance not have been available through either scheme. Whilst some respondents said that they would have funded the project through a family loan (5.9%) or through the sale of assets (3.3%), the second largest group of respondents was those who said that the projects would have been funded using their own savings. Participants in the National Workshop said that, in the absence of the schemes, the lack of access to credit would lead led to people leaving the farming sector via emigration or simply choosing a different career path and also acted as a disincentive for potential new entrants to enter. This in turn would have reduced the level of investment in farms and facilities, and led to reduced expansion of existing farms.

Table 6.25: Counterfactual Scenario - Funding in Absence of TAM/FIS Supports Percentage

Borrowed additional money from a bank/credit union 69.5%

Family loan 5.9%

Own savings 17.6%

Sale of assets 3.3%

Other 3.8%

Total 100%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 1 – FIS/TAMS Measure)

When asked for their assessment of what would have happened in the absence of the scheme, over one-third said that they believed the project or investment would not have been done. A further 25% of respondents said that the project would still have been done but at a later date, suggesting that the scheme brought forward the investment. 20.8% of people said that the project would still have been done but at a smaller scale, with the majority of these saying that the project would have been done at smaller than half the scale originally planned. A minority (18.8%) who said that the project(s) would have been done anyway, suggesting an element of deadweight in the scheme.




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Table 6.26: Counterfactual Scenario - Activities in Absence of TAM/FIS Supports Percentage

Yes, the project(s) would have been done anyway 18.8%

No, the project(s) would not have been done 35.4%

The project(s) would have been done, but at a later date 25.0%

The project(s) would have been done, but at a smaller than half the scale originally planned

17.3%

The project(s) would have been done, at a larger than half the scale originally planned 3.5%

Total 100%


In order to try and capture potential impacts, beneficiaries of the FIS and TAMS schemes were surveyed to understand the impact that they believe these investments had. One of the findings in the survey is that 64.2% of respondents felt that the investment had a significant effect on the efficiency and competitiveness of their farm, with a further 27% saying it had a moderate impact. Similar levels of respondents said that the investment had a significant or moderate impact on improving the welfare of animals (89.2%), protecting the environment (85.3%), improving the safety on the farm (91.7%) and improving the quality of farm produce (81.5%). This would suggest that in the opinion of survey respondents the scheme led to a number of positive benefits. However, caution must be exercised in this, given that beneficiaries’ opinions on positive externalities may or may not be aligned with outcomes. Therefore in line with EU guidelines we test the validity of evidence from the qualitative survey methods with other more formalised quantitative methods.

Table 6.27: Impact of Investment on Farm

Significant

Impact Moderate

Impact No

Impact Don't Know

Improved the efficiency and competitiveness of my farm 64.2% 27.0% 7.9% 0.9%

Helped me improve the quality of my farm produce 39.5% 42.0% 16.6% 2.0%

Allowed me to move into different types of farming 8.2% 13.1% 73.8% 4.9%

Helped improve the welfare of animals 63.8% 25.4% 10.3% 0.5%

Helped protect the environment 61.1% 24.2% 14.2% 0.5%

Helped improve the safety on my farm 65.0% 26.7% 7.8% 0.5%


Econometric Evidence on the Impact of Investment on Output

In evaluating the likely impact of the investments it is useful to consider whether measures which incentivise increased investment in agriculture would be likely to have beneficial impacts in terms of output and productivity. Previous econometric evidence undertaken by Indecon sheds some light on the regression results of the translog model shown in the next figure indicate a statistically significant result between capital investment and agricultural output. We use this production function model to estimate the impact of capital investment on agricultural output. In other words, we examine how much agricultural output changes relative to changes in capital investment, i.e., capital elasticity of output. We also examine the impact of capital investment on productivity. These outcomes are important in establishing the broad rationale for RDP measures which aim to increase capital investment.




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Table 6.28: Econometric results - Impact of Capital input on output (Translog model)

Note: We also include variables for the different farm types. Source: Indecon analysis

A summary of the various output elasticities is shown in the next table and indicate that increasing the level of capital input increases the agricultural output of the farm. This is relevant as any RDP measures which result in increased investment could potentially have benefits in terms of increased agricultural output and employment, but that this is an empirical question.

The results vary depending on the choice of econometric specification but all results are statistically significant and indicate a positive relationship between investment and increased output. The results indicate that for a 10% increase in capital inputs, annual agricultural output is likely to increase by between 1.6% and 4.2%. Our preferred specification is the translog model which captures second order and combined impacts of the input variables and indicates that for a 10% increase in capital inputs, agricultural output is likely to increase by around 2%, but we accept that the impacts may be higher.

Table 6.29: Summary of Capital Elasticity of Output

Econometric Model Capital Elasticity of Output

Cobb-Douglas Production Function 0.423

Translog Production Function 0.205

Olley-Pakes Production Function 0.162

Note: These output elasticities refer to the % change in output as a result of a % in capital investment Source: Indecon analysis

New econometric evidence undertaken by Indecon for this RDP evaluation study also shows a positive and significant impact of investment on output.

lnlab_size -.0675306 .0224973 -3.00 0.003 -.1116244 -.0234368

lnkap_size .0408435 .0138143 2.96 0.003 .013768 .0679191

lnkap_t -.0076736 .0016708 -4.59 0.000 -.0109483 -.0043989

lnlab_kap .0595327 .0123292 4.83 0.000 .0353678 .0836976

lnkap_2 .0209044 .0071456 2.93 0.003 .0068993 .0349094

lnkap -.1719336 .0686638 -2.50 0.012 -.3065121 -.0373551

lnc_labhrs .0172823 .0012969 13.33 0.000 .0147404 .0198241

lnc_size -.0748544 .0146749 -5.10 0.000 -.1036167 -.0460921

d_o70 -.0570463 .0163725 -3.48 0.000 -.0891358 -.0249569

t_2 -.0215255 .0027993 -7.69 0.000 -.027012 -.0160389

t .1055691 .0204497 5.16 0.000 .0654885 .1456497

lnc_farm_2 .0950058 .0085124 11.16 0.000 .0783219 .1116898

lnc_farm -.4288638 .0665476 -6.44 0.000 -.5592947 -.2984329

lnsize_2 -.0997451 .0223335 -4.47 0.000 -.143518 -.0559722

lnsize .9363953 .1155266 8.11 0.000 .7099674 1.162823

lnlab_2 .0140551 .0140924 1.00 0.319 -.0135655 .0416757

lnlab -.3661927 .1139571 -3.21 0.001 -.5895444 -.142841

lnq_farm Coef. Std. Err. z P>|z| [95% Conf. Interval]

corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000

Wald chi2(23) = 21219.07

overall = 0.9171 max = 5

between = 0.9337 avg = 3.9

R-sq: within = 0.2169 Obs per group: min = 1

Group variable: farm_idx Number of groups = 1479

Random-effects GLS regression Number of obs = 5726




75

The first table below shows the impact of a number of explanatory variables on output (output as the dependent variable). The ln_cap variable is the capital variable. The fact that it is has a positive value suggests that an increase of capital investment increases farm output. A more detailed explanation is provided below.

Table 6.30: Impact of investment on output panel models

Output random effects


fixed effects

random effects

fixed effects

Payment type Land

Improvement Land


Building Grants


ln_lab 0.22 0.124 0.219 0.123 0.221 0.126

(17.75)** (9.73)** (17.74)** (9.72)** (17.84)** (9.94)**

ln_size 1.238 0.71 1.242 0.714 1.237 0.709

(20.90)** (10.40)** (20.97)** (10.46)** (20.88)** (10.39)**

ln_size_2 -0.115 -0.065 -0.116 -0.066 -0.115 -0.065

(16.01)** (8.04)** (16.04)** (8.08)** (16.01)** (8.07)**

YE_AR 0.011 0.014 0.012 0.014 0.011 0.013

(19.30)** (24.14)** (19.66)** (24.41)** (18.40)** (22.72)**

FARM_MD_AGE -0.004 -0.002 -0.004 -0.002 -0.004 -0.002

(10.60)** (5.26)** (10.67)** (5.31)** (10.79)** (5.48)**

farm_age2 0 0 0 0 0.000 0.000

(9.51)** (4.72)** (9.57)** (4.76)** (9.68)** (4.92)**

ln_cap 0.258 0.179 0.255 0.176 0.26 0.181

(31.78)** (21.66)** (31.26)** (21.22)** (32.03)** (21.94)**

ln_fuel 0.095 0.061 0.095 0.061 0.095 0.06

(22.87)** (14.47)** (22.86)** (14.46)** (22.92)** (14.48)**

N 13,648 13,648 13,648 13,648 13,648 13,648

R2 0.25 0.25 0.25 Source: Indecon

This variable was calculated as the sum of capital employed for various types of capital, machinery, building, land, and also included an imputed rental value of land, and land rented in, as well as depreciation. The interpretation of the coefficient is that a change in the coefficient (change in capital is a net investment) gives a change in the dependent variable, so for the coefficient of about .2, then a 10% change in capital would give a 2% change in output. Note that this is an aggregate capital effect, and the change is interpretable as a weighted average change in the typical profile of capital. The coefficient estimates are significant and not sensitive to the types of grant or support.

Counterfactual Impact on Output

Because we are interested in the level of investment that would have occurred otherwise, we include a variable for ‘capital investment’ in the list of explanatory variables in the equations of our econometric modelling as well as capital employed (the latter of which would include rented land and equipment, whereas for the former is the change in end of year value on buildings, machinery, and livestock as per the definition of investment in these variables in the NFS). We ran the models for Building Grants, and Land Improvement Grants as the ‘treatment’, and for each of ‘output’ and ‘productivity’ as the dependent variable. The results are in the tables below.




76

In general, Building Grants have small and positive significant impacts on output and productivity, while land improvement grants have an insignificant impact. The estimated impact is the ATET or average treatment effect on the treated, so the interpretation is that farm output or farm productivity for the ‘average’ farmer who received the grant, is higher than it otherwise would have been, had they not received the grant, and controlling for the explanatory factors including, labour, capital, fuel, age, soil type, size and year.

Table 6.31: New Econometric Evidence of Impact of Building Grants and Land Improvement Grants on Output

Output variable Building Grants

Land Improv. Grants

OME0 ln_lab 0.248*** 0.347***

(0.031) (0.046)

ln_size 0.204*** 0.184***

(0.018) (0.036)

YE_AR 0.00591*** 0.0164***

(0.001) (0.003)

FARM_MD_AGE -0.00428*** -0.00542***

(0.001) (0.001)

lndinv 0.701*** 0.475***

(0.021) (0.157)

ln_cap -0.020 0.194

(0.022) (0.151)

ln_fuel 0.0574*** 0.000

(0.009) 0.000

2bn.d_soil_group -0.0696*** -0.143***

(0.012) (0.033)

3.d_soil_group -0.179*** -0.276***

(0.024) (0.086)

Constant -9.740*** -29.59***

(2.774) (5.746)

OME1 ln_lab 0.216*** 0.355***

(0.020) (0.026)

ln_size 0.254*** 0.223***

(0.015) (0.016)

YE_AR -0.001 0.0138***

(0.001) (0.001)

FARM_MD_AGE -0.001 -0.003

(0.001) (0.002)

lndinv 0.527*** 0.119***

(0.049) (0.022)

ln_cap 0.045 0.528***

(0.040) (0.025)

ln_fuel 0.122*** 0.000

(0.009) 0.000

2bn.d_soil_group -0.131*** -0.222***

(0.010) (0.010)

3.d_soil_group -0.211*** -0.483***

(0.025) (0.020)

ATET r1vs0.d_building_grants 0.0340***

(0.009)

POmean 0.d_building_grants 11.03***

(0.012)

ATET r1vs0.d_land_improve_grant -0.030

(0.020)

POmean 0.d_land_improve_grant 11.14***

(0.021)

Constant 5.418** -23.50***

(2.504) (2.804)

N 13,648 13,648

* p<0.10; ** p<0.05; *** p<0.01

Source: Indecon Modelling for this RDP Evaluation




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The results of the counterfactual modelling on output as the dependent variable above, suggest Building Grants increased output about 3.4%, holding all other factors equal; that is to say, a 10% increase in the grant increases output by 3.4%. The impact of Land Improvement grants was insignificant. This is the average impact on the treated, so for the typical farmers who received the grant. Interpretation of the investment variable should be exercised with caution, as our main goal of this analysis was to test the treatment effect, so we included both a capital and an investment variable (ln_cap and lndinv in the table). Nonetheless, the coefficients on the investment variables are of plausible signs and magnitudes, showing positive and significant impacts of investment on output of the order of .12 to .52. These are log-log models, so the interpretation is an elasticity, i.e., a 10% change in investment is associated with a 5.2% change in output. Counterfactual Impact on Farm Productivity

We next repeated the same analysis as the above but with productivity as the dependent variable. These results are presented in the next table.

Table 6.32: New Econometric Evidence of Impact of Building Grants and Land Improvement Grants on Productivity

Productivity Variable Building Grants Land Improv. Grants OME0 ln_size -0.002 -0.031

(0.016) (0.022)

YE_AR 0.0128*** 0.0132***

(0.001) (0.002)

FARM_MD_AGE -0.00622*** -0.00594***

(0.001) (0.001)

lndinv 0.386*** 0.373***

(0.013) (0.020)

ln_cap_lab 0.342*** 0.343***

(0.016) (0.022)

ln_fuel_lab 0.0668*** 0.0849***

(0.010) (0.012)

2bn.d_soil_group -0.0875*** -0.111***

(0.013) (0.017)

3.d_soil_group -0.224*** -0.206***

(0.025) (0.034)

Constant -22.44*** -23.23***

(2.834) (3.563)

OME1 ln_size 0.0588*** 0.0519***

(0.015) (0.014)

YE_AR 0.00306** 0.00406***

(0.001) (0.001)

FARM_MD_AGE -0.002 -0.002

(0.001) (0.001)

lndinv 0.346*** 0.348***

(0.024) (0.021)

ln_cap_lab 0.310*** 0.319***

(0.017) (0.015)

ln_fuel_lab 0.119*** 0.110***

(0.008) (0.008)

2bn.d_soil_group -0.135*** -0.124***

(0.010) (0.009)

3.d_soil_group -0.230*** -0.229***

(0.021) (0.018)

ATET r1vs0.d_building_grants 0.0173*

(0.009)

POmean 0.d_building_grants 10.73***

(0.011)

ATET r1vs0.d_land_improve_grant -0.0317***

(0.011)

POmean 0.d_land_improve_grant 10.83***

(0.012)

Constant -3.052 -5.058**

(2.459) (2.419)

N 13,646 13,646

* p<0.10; ** p<0.05; *** p<0.01

Source: Indecon Modelling for this RDP Evaluation




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Overall, the models of productivity show that receiving the building grants increases productivity by about 0.17% in the model of Building Grants; that is to say, a 10% increase in the grant increases output per unit of labour by 1.7%. These are the average treatment effects on the treated, so are for the typical farmer who received the grant relative to similarly matched (regression adjustment matching) counterfactual groups of farmers. We however find a statistically significant negative impact of land improvement grants on productivity.

6.6 Summary

This section examined expenditures which fall under Axis 1 of the RDP, which is aimed at enhancing the competitiveness of the agri-food sector. The main findings were as follows:

The balance of the Axis measures was changed significantly due to the budgetary constraints brought about by the financial crisis. Rather than reduce each measure proportionally, the decision was made to abolish Measures 112 and 113, and focus instead on supporting on-farm investment. Further, the FIS programme was replaced with TAMS, as the former was fully subscribed after just five months in 2007.

Given the pressure on resources and the possibility of potential deadweight, it is understandable why the YFIS was closed. However, the validity of measures to reduce the age profile on farmers is clear given the econometric evidence on the impact on output and productivity.

Economic evidence suggests that increased investments in agriculture are likely to have enhanced output and productivity. This does not suggest that all investments will have had a positive impact and there is a need to ensure all individual capital projects are carefully evaluated for both the likely impact and the likely level of deadweight.

Due to their small size, the YFIS and the ERS are unlikely to have had any overall impact on the age profile of Irish farming. The age distribution of Irish farming became progressively older from 2000-2010, and it does not appear that the schemes materially altered this trend. However, Indecon believes the objective of these measures to reduce the age of farmers should be a key target of the RDP.

The balance of the expenditure in Ireland between the two schemes shows that 5% of the budget was spent on incentives to get young farmers established in farming, while 95% was spent on promoting farmers to retire early. The evidence presented in this section suggests that deadweight may be greater with the YFIS scheme than the ERS scheme. This balance which favoured the ERS scheme over the YFIS scheme is consistent with the view that the primary problem in reducing the age profile of Irish farming is the dearth of exits. However, Indecon would stress the need for measures to incentivise new entrants as well as exits from Irish agriculture.

The fact that YFIS was so small to begin with, though involving significant administrative costs, would question whether sufficient resources were allocated to this programme. Programmes such as these have economies of scale, and the introduction of small programmes increases the risk of an inefficient use of public money and is likely to be associated with higher levels of deadweight.




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There is evidence from previous Indecon econometric findings that farm efficiency and output is affected by age. Further, many ERS beneficiaries in the survey analysis reported that their farms had significantly modernised. Additional new econometric modelling undertaken for this RDP evaluation confirms that reducing the age of farmers adjusting for other factors is likely to have a beneficial impact on farm output and productivity.

The fact that the FIS measure was fully subscribed after five months in 2007 raises the issue of whether the incentives were set at the right level. While many of the changes in the RDP in 2008-2009 were brought about as a result of the financial crisis and could not reasonably have been foreseen, the excess demand for FIS is of note. Where demand for a measure is much greater than funds allocated this raises the issue of whether alternative criteria or a different screening of applications could have helped spread aggregate expenditure, and increased the quality of supported projects.

As TAMS operated from 2010-2013, it is likely to have played a role in easing credit constraints for farmers wishing to invest in their farm enterprises. There is evidence that financing constraints occurred in Irish agriculture became much more acute following the financial crisis, especially in 2007, 2008 and 2009.52 Therefore, the replacement of the scheme with TAMS represented an important response to this market development.

A survey of beneficiaries suggested that their view was that the supported investment had a significant or moderate impact on improving the welfare of animals (89.2%), protecting the environment (85.3%), improving the safety on the farm (91.7%) and improving the quality of farm produce (81.5%).

The largest category of recipients, as shown by the survey of beneficiaries, was dairy farmers, with 40% of respondents stating that they were mainly dairy farmers. The fact that participation in the scheme had such a strong take-up among dairy farmers supports the contention that the scheme helped support restructuring in the dairy sector over the programme period.

New econometric evidence undertaken for this study shows a positive and significant impact of investment on output.

Econometric counterfactual analysis suggests that Building Grants increased output above 3.4%, holding other factors equal. The impact of Land Improvement Grants was found to be statistically insignificant.

52 O’Toole, C., Newman, C. and Hennessy, T., (2014) ‘The Role of Financing Constraints in Agricultural Investment Decisions Since the Irish Financial Crisis.’ Journal of Agricultural Economics, 65(1), pp. 152-176.




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7 Answers to Evaluation Questions: Axis 2

7.1 Introduction

This section examines expenditures which fall under Axis 2 of the RDP, which is aimed at enhancing the competitiveness of the agri-food sector. This will examine the allocation and outcomes of these both from an axis level and a measure level perspective. The following measures are included for the purposes of this analysis:

Measure 212 – Least Favoured Area Scheme;

Measure 213 – Natura 2000;

Measure 214/216 – REPS/AEOS/Non-productive investments; and

Measure 111 - Vocational Training.

Note that while Measure 111 (vocational training for agri-environmental supports) comes under Axis 1, it is covered in this section given the close link between this measure and implementation of the agri-environmental schemes.

The section is arranged as follows. Before discussing the effectiveness of each measure, it is important to assess the extent to which individual measures were targeted in the context of the overall RDP and axis-level budget, and the extent to which the axis-level indicators were met. The budget allocation is discussed in Section 7.2, while Section 7.3 sets out the indicator data. Section 7.4 discusses the Least Favoured Area scheme which aims to contribute to maintaining the countryside by promoting sustainable farming systems in marginal areas where farming activity may not be otherwise viable. Section 7.5 discusses the agri-environment schemes, which constitute a large share of the overall budget of the RDP. Section 7.6 discusses the vocational training which farmers must attend to receive supports under Axis 2 measures, while Section 7.7 focusses on the Organic Farming Scheme. Finally, Section 7.8 concludes on the overall axis-level performance and allocation.

7.2 Implementation and Composition of Axis 2

Measures under Axis 2 were designed to protect and enhance natural resources and landscapes in rural areas. In so doing they have the potential to contribute to the EU priority areas of:

Biodiversity and the preservation and development of high nature value farming and forestry systems and traditional agricultural landscapes;

Water; and

Climate change.

The next figure compares the expenditure on the different measures as a percentage of overall RDP spending between Ireland and the EU27. It shows that the proportion of expenditure on Measure 212 (Less Favoured Areas) in Ireland was relatively high, even when taking account of the fact that Measure 211 expenditure in Europe includes the Mountain Areas for which there is no expenditure in Ireland. It is also noticeable that a relatively high proportion of expenditure was dedicated to agri-environmental measures (Measure 214). Axis 2 measures did not face the same inter-measure switch of priority that occurred in Axis 1, with both of the main measures (Measure 212 and Measure 214) continuing to receive substantial support.




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Figure 7.1: RDP Expenditure on Measures in Axis 2 - Ireland v EU27 (As a Percentage of Overall RDP Expenditure)


The analysis presented above is affected by the fact that a relatively large portion (84%) of total public expenditure in Ireland’s RDP was undertaken in Axis 2 measures compared to the EU average as a whole (52.6%). The budget shares of each measure compared with the aggregate of Axis 2 expenditure as opposed to overall RDP expenditure are shown overleaf. The figure illustrates that the budgetary share allocated to each measure in Ireland closely matched the distribution in the EU, when Measure 211 and Measure 212 are considered as de-facto a single measure.









M223-First afforestation of non-agricultural land





0% 20% 40% 60%

EU27 Ireland




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Figure 7.2: RDP Expenditure on Measures in Axis 2 - Ireland v EU27 (As a Percentage of Axis 1 Expenditure)


Having compared the percentage of expenditure on each measure in Ireland against EU27 countries, it is important to understand how the level of expenditure compared to the budget allocated to each measure. As can be seen in the table below, the measures were delivered broadly in line with the final budget allocation, and 98% of the aggregate budget was spent.

Table 7.1: Actual v Budgeted Expenditure (Axis 2)

Actual Expenditure (m)

Budgeted Expenditure

(000)

Actual Expenditure as a % of Budget

M212-Payments to farmers in areas with handicaps €1,436 €1,441 99.7%

M213-Natura 2000 €101 €95.7m 105.5%

M214-Agri-environmental (REPS/AEOS) €1,986 €2,041 97.3%

M216 – Non-Productive Investments -€1 €16 -

Total Axis 2 €3,521 €3,593 98.0%

Source: DAFM. Data has been updated to include data from 2014 and 2015.





M223- First afforestation of non-agricultural land









0% 10% 20% 30% 40% 50% 60%

EU27 Ireland




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7.3 Axis 2 - Indicators

The table below provides an overview of the performance against target based on the Axis 2 monitoring indicators.53 Generally, the indicator data showed an under-performance relative to targets, with some exceptions. The Gross Nutrient Balance between 2007 and 2013 in terms of tonnes of nitrogen was very similar in 2013 to the level in 2007, though was generally far lower in the intervening period. The target set was for an 8.5% reduction, albeit based on a differently defined indicator. The figures also show that while the change in primary production from biomass and renewable waste from 2007-2013 was 26.7%, this fell far short of the target which envisaged a more than 100-fold increase. It should be noted that the figures quoted for HNV Farmland shows the potential extent of HNV rather than actual environmental quality, given the absence of adequate data. Finally, the very ambitious targets for organic farming were missed by a large margin, though there was an increase in the Utilised Agricultural Area (UAA) organically farmed. More positively, the Farmland Bird Index was higher in 2013 than targeted originally.

Table 7.2: Rural Development Programme - Axis 2 Indicators Indicator Measurement Baseline EU Average Target Final Position

Biodiversity: population of farmland birds

Trend of index of population of

farmland birds

93.5 Index

2000=100

EU15 = 96.2 (2003)

95 100*

Biodiversity: high nature value farmland areas

UAA of high nature value farmland areas

1.1m ha (i.e. 26% of UAA)

EU25 (ex. CY, MT) = 30.8

(1999/2000)

1.1m ha (i.e. 26% of UAA)

1.1m ha**

Water quality: Gross nutrient balance

Surplus of nitrogen in kg/ha

82kg/ha EU15 Nitrogen 83kg/ha Phosphorus 10kg/ha

(2002-2004)

75kg/ha -1.7% (2007-2013)***

Climate change: Production of renewable energy from agriculture and forestry

Production of renewable energy

from biomass

3 kToe EU27=7,940.6 kToe EU27 (excluding

MT)=68,218 kToe (2007)

370 kToe +26.7% (2007-

2013)****

Afforestation: area determined under forestry

Hectares of trees planted

10.29% of land area

10.75% of land area

10% of land area

(2012)*****

Soil: Areas at risk of soil erosion

Ton/ha/year 0.16 0.16 N.A.

Soil: Organic farming

UAA under organic farming (thousand ha)

38 EU27 = 7,134,778 ha (2007)

220 62.6 (28.5%)******

Climate change: GHG emissions from agriculture

Emissions of methane and nitrous oxide from

agriculture and measured in 1000t of

CO2 equivalent

18,435 EU27 = 462,217 (2007) Methane: 9,791

Nitrous Oxide: 6,625

i.e. 16,416

18,905 (2013)*******

Source: * http://indicators.biodiversityireland.ie/index.php?qt=si&id=9 ** http://ec.europa.eu/environment/agriculture/pdf/High%20Nature%20Value%20farming.pdf *** Change of Gross Nutrient Balance between 2007 and 2013, tonnes of nitrogen: http://ec.europa.eu/eurostat/en/web/products-datasets/-/AEI_PR_GNB **** % Change in Primary Production of biomass from Biomass and renewable waste, 2007-2013: ec.europa.eu/eurostat/web/environmental-data-centre-on-natural-resources/natural-resources/energy-resources/energy-from-biomass ***** Figures are only given to one decimal place. CSO Environmental Indicators Ireland 2014. ****** DAFM Indicator Data ******* http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=aei_pr_ghg&lang=en

53 It was not possible to access matching data for some of the indicators, so close alternatives were used in some instances.

http://indicators.biodiversityireland.ie/index.php?qt=si&id=9




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7.4 Measure 212 – Less Favoured Areas Scheme

7.4.1 Background to Measure

The Less Favoured Areas (LFA) scheme aimed to contribute to maintaining the countryside by promoting sustainable farming systems in marginal areas (so-called Natural Handicap/ Disadvantaged Areas) where farming activity may not be otherwise viable.54 It appears to Indecon that the implicit intervention logic has undergone a significant evolution since its inception in the 1970s: instead of explicitly addressing rural depopulation, LFA payments now have a stronger focus on land management to contribute to the delivery of public goods, such as valuable landscapes, biodiversity, soil conservation in addition to abating the risk of abandonment of agricultural land.55 Natural handicap payments compensate for farmers' additional production costs related to the handicap for agricultural production in the area.

Support under the scheme is intended to contribute to:

Ensuring continued agricultural land use, thereby contributing to the maintenance of a viable rural society;

Maintaining the countryside; and

Maintaining and promoting sustainable farming systems, which in particular take account of environmental protection requirements.

The target group was individual farm enterprises in LFAs. An annual compensation was paid to those farming in LFAs to encourage sustainable use of their agricultural land and, in so doing, to contribute to maintaining the countryside. Levels of payment were based on eligible forage area declared in the Department of Agriculture and Food’s Integrated Administration and Control System (IACS). Aid was differentiated to reflect the differing levels of severity of handicap experienced within the LFAs. LFA land was sub-divided into: a) More severely handicapped (lowland); b) Less severely handicapped (lowland); and c) Mountain-type land. The key requirements for this scheme were as follows:

Farmers must agree to comply with environmental protection requirements consistent with their statutory obligations;

Farmers must farm in the LFA (at least three hectares) for five years from the first payment of a compensatory allowance;

Adhere to the requirements on cross-compliance, relating to the environment; public, animal and plant health; notification of diseases; and animal welfare; and

With effect from 2012 scheme year, applicants had to meet a minimum stocking density of 0.15 livestock units per hectare, having already attained a stocking rate in 2011 of 0.3 or received a derogation from same.

The expected key result areas include biodiversity; water quality; climate change; soil quality; and avoidance of marginalization and land abandonment. Payments under the scheme were also provided in respect of land under energy crops subject to certain conditions, although 2009 was the last year of the EU Energy Crops Scheme.

54 Guidance note E – Measure Fiches

55 Review of the Less Favoured Areas Scheme, Public Consultation Document for Impact Assessment, EU Commission (2008).




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7.4.2 Intervention Logic

The table below shows Indecon’s analysis of the Programme Logic Model for Measure 212. It shows the inputs, activities and output. These in turn could potentially lead to changes on direct beneficiaries, covering both the income of the farmer and changes in the way the land is farmed (results). The ‘impacts’ assess the broader changes brought about by the programme other than on direct beneficiaries, which include economic activity in rural areas more generally, as well as the supporting of the countryside/environment.

Figure 7.3: Programme Logic Model - Measure 212

Source: Indecon

The logic of this measure assumes the following:

Appropriate land management (in particular by farming at specific levels of intensity/farm systems) yielded environmental and related public goods that are of value to the public;

The scheme rules set appropriate restrictions on land-use which resulted in environmental benefits, and that benefitting farmers comply with these restrictions;

There was an income gap arising from the natural handicap attached to land;

Land abandonment in identified areas was happening or was a credible threat, because of the income gap mentioned above;

Those farms/regions where land abandonment was most likely have been correctly identified; and

The amount of public subsidy/income used to prevent land abandonment was both sufficient and not excessive.

A value for money study56 conducted by the Department highlighted possible unintended consequences which may run counter to the stated policy aims. For example, the report suggested that the payment through the LFA scheme could have in certain instances disincentivised the transfer of holdings from parents to their children, or could have led to holdings being fragmented in order to attract more than one LFA payment given the 34/30-hectare restriction57. Such unintended consequences would run counter to the stated aims in Food Harvest 2020 of increasing the scale of holdings, addressing the rate of fragmentation, and removing impediments to land mobility.

56 https://www.agriculture.gov.ie/media/migration/publications/2014/VFMReviewDisadvantagedAreaSchemeFinalpdf140314.pdf 57 The 34-hectare limit replaced the old 45 hectare limit from the 2009 Scheme onwards in response to the need to reduce the budget

for the Scheme. In Budget 2013 this limit was reduced to 30 hectares.

INPUTS

Exchequer Funding

EU Funding


ACTIVITIES



Farm inspections

OUTPUT


eligible farmers

RESULT

Increased farmer income

Promote sustainable

agricultural land use

IMPACT

Increase economic activity in rural

areas

Maintain countryside/ environment




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The assessment of the measures inputs, activities and outputs, and finally results and impacts are discussed below.

7.4.3 Inputs

The main input required to operationalise the Programme is financial support from the EU and from the Irish State. The RDP for 2007-2013 had an original allocation of €1,799 million for this scheme. However, in 2008, this allocation was revised down to €1,648 million due to the financial pressure on the state at the time. This reduction was implemented through a reduction in the maximum hectare limit of payments from 45 hectares to 34/30 hectares depending on the type of area farmed. No changes were made to the stocking density requirements at that time. In 2012 technical adjustments were made to the scheme in a further effort to reduce the cost of the measure. In particular, from year 2012 scheme applicants had to have met a minimum stocking density of 0.3 livestock units in scheme year 2011 in order to be considered eligible, with the aim of concentrating support on more active farmers.

As well as the cost of income supports, significant administration resources were required to operate the scheme. In order to examine the cost of processing applications under the LFA scheme, the value for money review surveyed the relevant divisions within DAFM to ascertain the level of administrative burden. The survey estimated that the total representative year staff cost for administering the LFA scheme was €1.1m. As the review noted, intuitively this would appear low in the context of processing circa-100,000 payments annually with a value in excess of €220m, giving administrative costs a value of 0.5% of grant expenditure. This compares with a rate of 2.4% in the previous expenditure review in 2005. This may have been due to the introduction of the online application process in 2007, efficiencies achieved from the ongoing reorganisation of the Department, and the redesign of the LFA scheme as an area based scheme from a headage based scheme.

7.4.4 Activities & Outputs

The number of holdings supported via this measure was 102,414 by 2013, 2.4% over the target. As can be seen from the figure below, the number of beneficiaries was lower in the latter years of the Programme due to the changes in the Programme which were aimed to achieve budgetary savings, and which resulted in approximately 5,000 fewer beneficiaries than in earlier years. However, a more gradual trend of a falling number of beneficiaries is also evident, as farms were amalgamated and average farm size increased.

Figure 7.4: Number of beneficiaries of Measure 212

Source: DAFM Annual Progress Reports

90,000

92,000

94,000

96,000

98,000

100,000

102,000

104,000

2007 2008 2009 2010 2011 2012 2013

Nu

mb

er o

f b

enef

icia

ries




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The table below outlines the targets and indicators for Measure 212. The indicator data shows that 3.28m ha were supported under this measure, representing just 63.6% of the target level. This same aggregate area is repeated for each of the different environmental results (3.28m ha). While the results target for areas under successful land management contribute to specific environmental objectives differed from the output target for agricultural land supported, the same results measure was used. Indecon believes that more refinement in the ‘result’ indictors are required to differentiate these from the general output indicator. As they stand, the figures relate to the potential or expected impact rather than actual environmental impacts. For future programmes there is merit in additional indicators to measure the specific contribution to biodiversity water quality, climate change and improvement in soil quality.


Type of Indicator

Indicator Revised Target 2007-2013

Programmed 2007-2013


Input

Amount of public expenditure realised:

Total

EAFRD

€1,153.0m €634.1m

€1,439.7m €791.8m

124.9% 124.9%

Output

Number of supported holdings 100,000 102,414 102.4%

Agricultural land area supported:

More severely handicapped

Less severely handicapped No. of LFA farmers in REPS

5.155m ha 4.075m ha 1.080 m ha

50,000

3.28m ha

NA

63.6%

Results

Area under successful land management contributing to:

Biodiversity

Water Quality

Climate change

Improvement in soil quality

Avoidance of marginalisation and land abandonment

4.00m ha

3.28m ha 82.0%

Impact

Reversing biodiversity decline Preserving high amenity

value countryside into the future

NA

Maintenance of high nature value farming and forestry areas

Farmers being able to survive in farming while preserving biodiversity

NA

Source: Indecon analysis of DAFF Annual Progress Report data

7.4.5 Results Each of the main result/impact elements of the programme logic model are discussed below.

Land Management as a Public Good

The core objective of the LFA was based on the contention that the environmental and related public goods that are of value in the countryside stem from appropriate land management, and specifically agricultural management over large areas. These are difficult to assess given the nature of the results and impact indicators available. However, it is of note that a Eurobarometer survey conducted in 201558 suggested that the majority of Europeans consider investing in rural areas to stimulate economic growth and job creation (47%), and strengthening the farmer’s role in the food chain (45%) to be “very important”.

58 Published in 2016.




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The next figure shows that for Irish respondents, the figures were 63% and 59% respectively, suggesting strong support for the contention that stimulating economic life in areas which might otherwise suffer land abandonment are indeed public goods of value.

Figure 7.5: Survey Reponse on Importance of CAP to Stimulate Growth/Jobs in Rural Areas

Source: Eurobarometer (2016)

Given the limited value of the existing indicators in evaluating results or impacts Indecon has considered a range of aspects of these measures in more detail as outlined below.

Level of Income Support

The Value for Money exercise conducted by DAFM showed that, in general, there was an income gap (as measured by Family Farm Income/FFI) between participants in the LFA scheme and other farmers. This is illustrated in the figure below. This is consistent with the underlying rationale of the scheme whereby a system which sought to compensate farmers for the higher costs and income foregone arising out of the natural handicaps of the land they farmed.

Figure 7.6: Family Farm Income, Broken down by LFA/DAS recipients and non-recipients, 2010

Source: DAFM

€-00

€200

€400

€600

€800

Non-LFA Farms LFA Farms

An

nu

al In

com

e p

er

ha

Non-LFA Income LFA Payment




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The income gap, however, was not stable across years or across different types or sizes of farms. Also, the relative importance of payment under the LFA scheme as a component of FFI varied. In particular:

Difference by Farm Size: The pre-support income gap of 43% between LFA scheme recipients versus non-recipients was smaller for large farms. For example, it was 62% for farms between 10 and 20 ha, double the gap witnessed of 31% for farms >100ha;

Difference over time: The income gap between recipients and non-recipients was smaller in 2009, which was a particularly poor year for farm incomes generally. Because the absolute amount of the LFA payment was virtually identical in the two years, the gap between these categories farms was relatively small in 2009; and

Difference by farm system: In 2010, all the individual farm systems in designated disadvantaged areas show an income gap before LFA payment except for the ‘mixed livestock’ category. After the LFA payment is factored in ‘cattle rearing’ also reversed the negative income gap. The largest income gap was noted in the ‘dairy’ category at €315/ha before the LFA payment.

As the figure above shows, and notwithstanding the difference in the income gap over time, family farm income including LFA support was below that of non-LFA farms. To support the intervention logic, the payment should have been sufficient but not exceed the subsidy required to prevent land abandonment and to compensate farmers for adhering to the measures designed to promote the environment. The finding that post-LFA payment income was lower than for non-LFA farms would provide support for the contention that the level of the payment to LFA farms was consistent with one of the programme’s aims.

LFA Payment and Farm-Level Viability

A question arises as to whether total income for LFA farms resulted in ‘viable’ farms. Farms that are judged not to be viable are likely to be at more risk of land abandonment. Analysis undertaken by Teagasc for the Value for Money review of Measure 212 examined the role of payments under the LFA scheme in supporting the viability of recipient farms. A farm is deemed by Teagasc to be viable if “it generates enough income from farming to exceed the minimum Agricultural Wage and to achieve a 5% return on assets. It can be argued that a return lower than this means that a farmer would be better off spending their time working as an Agricultural worker or investing their assets elsewhere, rather than working on their own farm.”59 (Given the age profile of farmers such alternative jobs may however not be available. Indecon would also note the fact that farm assets may not be easily divisible from family homes.)

Teagasc calculated a viability improvement efficiency (VIE), defined as the proportion of payments going to farmers that were not viable, without bringing them over the viability line. The Value for Money study reports that the proportion of payments under the LFA scheme going to farmers that were not viable before the payment is accounted for was just under 80% in 2011. It concludes that “payment under the Scheme is successfully targeted for the most part at farms that would not otherwise be viable.”

Teagasc also calculate a viability gap efficiency (VGE), as the proportion of the pre-transfer viability gap that was closed via the payment under the LF scheme. Payments under the LFA scheme can be seen to have made a contribution to reducing the viability gap, though this contribution fell from a peak of nearly 40% in 1996 and the early 2000s to about 14% in 2010.

59 Teagasc, as cited in the Value for Money Review.




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Given the number of farms still not viable as defined above after the payment, this may impact on the portion of LFA farms that remain at some risk from land abandonment. However, the estimated number of non-viable farms will depend critically on the definition of what constitutes viability as defined by Teagasc.

It is important to note that the LFA payment is just one of many payments that beneficiary farmers receive. For example, an individual farmer could have received a single farm payment, a LFA scheme payment and a REPS/AEOS payment among others. The figure below shows that well over a half of all Irish farm income was in the form of subsidies. While farms assisted in disadvantaged areas might not be commercially viable the assistance is likely to reduce the risk of land abandonment. This is discussed further below. In addition, new empirical survey evidence undertaken by Indecon for this study and presented later indicates that most respondents felt that LFA payment had an impact on viability.

Figure 7.7: Share of direct payments & total subsidies in agri factor income (2010-4 average)

Source: EU Commission

Threat of Future Land Abandonment

At the core of the intervention logic for this measure is the contention that, in the absence of this payment, land abandonment would have occurred. Given the earlier mentioned environmental and related public goods linked to agricultural management over large areas of land, this could create negative externalities which would justify public intervention of some form.

The principle determinants of farmland abandonment can be classified into three blocks.60 The first is poor environmental/biophysical suitability for agricultural activity; the second is low farm stability and viability (farmland is typically abandoned as an economic resource when it ceases to generate an income); and other factors which encourage land abandonment, for example, an increase in income in urban areas can draw labour out of farming. An EU study in 2013 identified a number of metrics based on these to assess the threat of land abandonment by region:

Weak Land Market (rent paid per hectare)

60 http://ec.europa.eu/agriculture/external-studies/2013/farmland-abandonment/fulltext_en.pdf




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Low Farm Income (measured as Farm Income per AWU/National GDP per cap)

Low investment level in the farm (measured as farm investment per hectare of UAA)

Age of farm holder (measured as share of farmers above 65 years)

Remoteness/low population density (measured as Share UAA in remote rural areas)

From this, the EU study produced a composite risk indicator of ‘farmland abandonment’, the results of which are shown in the figure overleaf. This shows that the threat of land abandonment is at the highest level (>74%) in the NUTS2 Border, Midland and West region in Ireland, though is moderate in the Southern and Eastern region. The level of threat in the BMW region is shared with a small number of regions in Europe, in particular on the Iberian Peninsula, Sweden and in Italy. The LFA region for Ireland (inset) also covers south-eastern regions in Ireland. The EU analysis is consistent with the designation of disadvantaged regions in Ireland for the 2007-2013 RDP which targets those areas where the threat of land abandonment was greatest.

Figure 7.8: Map of Areas of Highest Threat of Farm Abomdonment (main)

LFA Scheme Regions in Ireland in 2007-2013 (inset)

Source: EU Commission (main), DAFM (inset)




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In contrast to the results reported above, a separate study61 reviewed a number of models and studies which have been developed to forecast future land abandonment, and concluded that Ireland was not one of the areas most at risk of land abandonment. If EU supports were not available this could change as the analysis does not suggest that there is no risk particularly for lower income farmers in disadvantaged areas.

Stakeholder consultations run by Indecon supported the view that there was a threat of land abandonment, which matched the outcome of stakeholder consultations run as part of the Value for Money exercise. In particular, stakeholder groups suggested that within hill/mountain areas and some lowland areas, land abandonment was a real threat and it may be the case that there are certain categories of land in particular that are ‘extremely sub-economic’, i.e. the land quality is of such a low level that it would be abandoned if the farmer currently using that land were to exit farming. Similar views in relation to the threat of land abandonment have been expressed by a number of bodies in observations received in relation to proposed changes to the LFA scheme terms and conditions in 2012.62

It should also be noted that there is asymmetry regarding land abandonment. Land which has been abandoned, even for just one or two years, would be very expensive to return to agricultural use. As such, any policy which seeks to maintain land in agricultural use should reflect this asymmetry in its design.

Evidence of Actual Land Abandonment

In evaluating whether the LFA scheme has contributed to continued agricultural land usage, it is useful to consider the extent of land abandonment. The figure below shows the evolution of land use in Ireland from 1990 to 2012. This shows some differences by activity in the quantum of land used for agricultural purposes (i.e., cropland and grassland at 5% and 61%, respectively) over the period which most closely overlaps with the RDP (2005-2012). This measure covers all of Ireland, not just disadvantaged areas and disadvantaged areas by their nature represent ‘marginal’ land.

Separately, the VFM undertook a separation into three ‘bands’ of counties based on the level of take-up of LFA payments. It showed a pattern of continued usage across all counties, with the positive trend being slightly more pronounced in counties which are more likely to be recipients of LFA payments.

Figure 7.9: Land use in Ireland, 1990-2012

Source: CSO Environmental Indicators Ireland 2014

61 Keenleyside, C. And Tucker. G., Farmland Abandonment in the EU: an Assessment of Trends and Prospects, Institute for European Environmental Policy, 2010, p. 4.

62 Smith et al “Case Studies on High Nature Value Farming in Ireland; North Connemara and the Aran Islands”, the Heritage Council, 2010, p 4.

0%

20%

40%

60%

80%

100%

1990 1995 2000 2005 2010 2012

% o

f La

nd

by

Use

OtherLandSettlementWetland




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It was not, however, possible to easily separate out the effect the LFA scheme might be having on retaining land in agriculture use, given the range of other supports and factors which influence the rate of agriculture use. In interpreting the evidence, it should be noted that an increase in land being farmed does not necessarily mean that there is no threat of land abandonment. For example, one study of land abandonment reported that land abandonment and an increase in land being farmed were observed simultaneously in Spain.63

Some other insights to the threat of land abandonment can be gleaned by reviewing land prices in Ireland. According to the Society of Chartered Surveyors/Teagasc Land Market Review and Outlook, land price per acre (without residence) is approximately €10,000 in Leinster and Munster, and €7,000 in Connaught and Ulster. The report states that Ireland is typically found to have some of the most expensive agricultural land in Europe, despite the fact that many other countries offered support on a per-hectare basis. The level of different EU supports can directly impact on underlying land prices, which at least partially reflect the capitalised value of anticipated future grant payments. Other things equal, a hectare of land without an entitlement should sell for less than a hectare of land with a subsidy entitlement.64

It should, however, be noted that land abandonment might manifest itself initially in under use before progressing to more severe case. The ‘land-use’ figures as presented above represent a simple assessment as to whether land is being used or not, and does not take into account changes in the intensity of land-use. Further, the increasing age-profile of Irish farming and associated lower productivity would increase the vulnerability of Irish farmland to abandonment.

Region covered by LFA Payments

As discussed above, the eligible region for LFA payments covered a large swathe of Irish agricultural land, which broadly reflects poorer land quality, lower value-added farming systems and lower farm income. However, within this region, there will be sub-regions and sub- categories of farms with very different characteristics, and the risk remains that the level of targeting of support is sub-optimal. The choice of region covered by LFA payments appears to have developed in an incremental manner, as opposed to having strict criteria for which sub-regions should be included.

The EU Commission is currently conducting a review of the coverage of LFA payments across the Member States. The new approach, which is to be in place by 2018, represents a move away from designation of Less Favoured Areas based on socio-economic factors, (declining rural population, low productivity and low farm incomes), to a methodology favouring designation based on physical characteristics, (soil type, poor climate, slope and altitude of land). The outcome of this review should impact upon the targeting of any future LFA payments.

7.4.6 Impacts

There are two main objectives of this measure, namely to increase economic activity in rural areas, and to maintain the countryside/environment. The broader socio-economic impact of the RDP expenditures was analysed using an Input-Output model in Section 5 which suggests that the RDP Programme is likely to have had a significant impact in increasing economic activity in rural areas.

63 As cited in the DAFM Value for Money study, Pointrea et al 2008 as referenced in Keenleyside, C. And Tucker. G., Farmland Abandonment in the EU: an Assessment of Trends and Prospects, Institute for European Environmental Policy, 2010.

64 Society of Chartered Surveyors/Teagasc Land Market Review and Outlook 2015




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In terms of protecting the environment, Indecon considered the extent to which the Department conducted checks that farmers were complying with the conditions of these measures. There were two types of checks carried out for the purpose of implementing the Single Payment/ Disadvantaged Areas’ Compensatory Allowance Scheme: eligibility checks and cross-compliance checks. These checks were carried out to verify that the area declared corresponds with the area farmed to ensure there are no overlapping or duplicate claims, and that land declared for various purposes (e.g., set aside or permanent pasture) were being used accordingly. In addition, a stocking rate of 0.15 livestock unit/hectare with reference to achievement of 0.3 in 2011 or derogation from same, was required to be eligible for the LFA payment unless a derogation had been accepted.

There was a requirement to check 5% of farmers (about 6,750 annually) for both the Single Payment Scheme and Disadvantaged Areas Schemes. The checks for both schemes were generally carried out during the same inspection. About two-thirds of these checks were carried out by way of remote sensing. Remote sensing was done through the use of satellite imagery to identify farms the area of land claimed for LFA payments. If a question arose regarding the validity of a claim via this remote sensing, a follow up on-site inspection was conducted. The Department used a risk-weighted approach to selecting farms for inspection, with around 80% of inspections being on farms where significant changes in circumstances had occurred which might affect the validity of a claim, while the remaining 20% are random. Finally, the Department conducted administrative checks in addition to the above, while also linking data on movements in livestock with claims made. Given the extent of checks, the fact that many farms are long-term recipients, and the access to data available to the Department, the evidence suggests a high degree of compliance at approximately 98.5%. While this is supportive that the scheme is being implemented correctly, additional evidence is needed to consider the impacts, if any, on farming methods and on the environment.

Assessing Changes in Farming Methods

Indecon’s survey of beneficiaries under the scheme assessed the extent to which the scheme requirements impacted on the way they farmed. The results are shown in the table below. They show that a similar proportion of farmers who indicated that the LFA scheme had a significant or moderate impact on their farming methods and those who indicated that the scheme had no effect on this aspect. This suggests that the LFA scheme had positive impacts but also suggests the likelihood of a degree of deadweight in the programme.

Table 7.4: Extent of Impact of LFA Scheme Requirements on Farming Methods

Significant impact 7.5%

Moderate impact 39.6%

No impact 44.3%

Don't know 9.4%

Total 100%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 2 Measures)




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The table below presents the views of respondents on the level of compensation taking into account the limits placed on the farmer’s farming. Again, a similar proportion of respondents felt that the compensation levels of the LFA scheme were adequate (41.9%) as felt they were inadequate (44.8%). The potential for survey bias on this question, however, should be noted.

Table 7.5: Views on Adequacy of Levels of Compensation in LFA Scheme

Percentage

Yes - adequate 41.9%

No - inadequate 44.8%

Don't know 13.3%

Total 100%


Farmers were also asked the impact of the support on a number of aspects relating to their farming enterprise. It showed that the perceived impact of the scheme was significant. In particular, 78.1% felt that LFA payments had had an impact on the viability of the farm, 79.2% felt that it had helped protect the environment, 86.5% felt that it had impacted on water management, and a lower portion (56.7%) felt that it had impacted on biodiversity on the farm.

Table 7.6: Views on Effects of LFA Payments on Farm Outcomes

Viability of Farm Protection of the Environment

Impact on Water Management

Impact on Biodiversity on Farm

Significant Impact 21.9% 26.7% 31.6% 10.3%

Moderate Impact 56.2% 52.5% 54.9% 46.4%

No Impact 16.2% 13.9% 10.3% 33.0%

Don't Know 5.7% 6.9% 3.2% 10.3%

Total 100.0% 100.0% 100.0% 100.0%

Source: Indecon survey of farmers in the Rural Development Programme.

7.4.7 Conclusions on measure

The LFA scheme is one of the most long-standing of the agriculture supports in Europe. These payments aimed to contribute to maintaining the countryside by promoting sustainable farming systems in marginal areas where farming activity may not otherwise have been viable.

The farms covered by LFA payments typically had lower value-added farm systems and lower family farm incomes than in the rest of the country. Land was generally of a much poorer quality, which rendered full-scale commercial farming difficult or, in many regions, impossible. However, the evolution of the area covered by these payments since the 1970’s were based on socio-economic criteria and, as such, a stricter approach based on scientific criteria relating to land quality may have resulted in an even better targeting of support.

The high level of compliance with the terms of the scheme suggests that the maintenance of the countryside environment through farmland management was aligned with Programme requirements.




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The evidence regarding the potential for land abandonment is mixed. In the absence of a counterfactual, it is not possible to definitely determine the likelihood of land abandonment in the absence of these supports. Such a counterfactual analysis is not feasible given that up 75% of Irish agricultural land was eligible for the support.

The importance of aggregate Common Agricultural subsidies as a proportion of family farm income suggests that in the absence of the CAP, some additional land abandonment may have been likely. While the payments under the LFA scheme were unlikely on their own to determine the levels of land abandonment, recipients of scheme payments had lower family farm income, and the LFA would have been likely to play a part in preventing land abandonment.

Land abandonment does not appear to be an imminent threat, based on the stability of the aggregate national quantum of land being farmed, coupled with the relatively high price of farm land in Ireland, even in less favoured areas.

The evidence from survey results suggests that the LFA scheme was perceived as having positive impacts on viability and on environmental objectives. However, the absence of rigorous results and impact indicators makes it difficult to be definitive on this issue.

7.5 Measures 213, 214 and 216 – Agri-Environmental Measures

7.5.1 Introduction

There are three Measures (213, 214, 216) which represented targeted agri-environmental components of the RDP. Of particular importance is Measure 214 which constituted a majority of the expenditure of the agri-environmental schemes. Since 2000, agri-environment payments have been part of the EU’s rural development policy, and are mandatory for member states.

There are three main ‘layers’ of environmental protection built into the Common Agricultural Policy, as illustrated in the figure below. The most common payment, illustrated at the base of the pyramid, are Pillar I supports through a Single Farm Payment which requires adhesion to cross-compliance restrictions. These require farmers to comply with 18 Statutory Management Requirements (SMRs) set down in EU legislation on the environment, food safety, public, animal and plant health and animal welfare; and a requirement to maintain the farm in good agricultural and environmental condition (GAEC).65

Managed by member states, and co-funded by the European Agricultural Fund for Rural Development, RDP’s encompass a range of environmentally beneficial measures. Some 30% of EU funds are required to be linked to measures for agri-environment and climate practices, organic farming and payments for areas facing natural constraints. The voluntary REPS/AEOS schemes require that farmers adhere to the cross-compliance restrictions. Farmers in particularly environmentally sensitive areas can also benefit from additional payments under Natura 2000.

65www.agriculture.gov.ie/media/migration/farmingschemesandpayments/crosscompliance/Mostcommonnoncompliances2009.doc




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Figure 7.10: Hierarchy of Environmental Requirements/Supports

Source: Indecon66

7.5.2 Background to Natura 2000

Natura 2000 sites are important ecological areas which were selected and designated by the National Parks and Wildlife Service (NPWS) of the Department of Arts, Heritage, Regional, Rural and Gaeltacht Affairs. These sites form part of a network of protected areas throughout the European Union. The network comprised of Special Protection Areas (SPA’s) and Special Areas of Conservation (SAC’s). The total land and freshwater area within the Natura 2000 network in Ireland was some 11,644km2, which includes some 2,300km2 of designated marine areas.

The Natura 2000 measure was designed to provide support to farmers to deal with specific disadvantages concerned with the conservation of natural habitats and wild fauna and flora in the effective management of Natura 2000 sites. The objective of this scheme under the 2007-2013 RDP is to contribute to the positive environmental management of farmed Natura 2000 sites and river catchments in the implementation of the Birds Directive, the Habitats Directive and the Water Framework Directive.

The Natura 2000 measure was replaced by a new scheme in 2010. A budget of €90 million was allocated for the last three years of the RDP. The levels of support under the old and replacement scheme are compared below:

Old Natura 2000 measure - €242 per hectare up to 40 hectares, €24 per hectare on next 40 hectares. €18 per hectare on next 40 hectares and €5 per hectare for each hectare above 120 hectares.

66 Additional information from: http://ec.europa.eu/agriculture/cap-in-your-country/pdf/ie_en.pdf

Natura

2000

REPS/AEOS

Single Farm Payment

Cross-Compliance

Entry-level scheme. Compliance is required to receive the Single Farm Payment.

# of famers supported: 122,540 Total area supported: 5m ha

Voluntary scheme. Cross-compliance is a prerequisite for REPS/AEOS.

# of famers supported: 42,444 Total area supported: 2.22m ha Number of contracts: 92,664

REPS/AEOS is a prerequisite for Natura 2000. Number of holdings supported: 10,924 Total area supported: 0.29m ha

Par

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ura

l Dev

elo

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Pro

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New Natura 2000 measure - €75 per hectare up to 40 hectare (including costs incurred in preparation and implementation of Sustainable Management Plan), €314 per hectare for conservation of priority wild bird habitats.

7.5.3 Background to REPS/AEOS

The Agri-environmental measure (REPS 4) was introduced in August 2007 aimed at improving the environmental impact of farming. The continuation from past REPS (1, 2 and 3) programmes was designed to ensure that previous environmental improvements to structures, processes and practices in rural Ireland were sustained and built upon. REPS 4 also expanded further to include enhanced biodiversity and supplementary measures. This scheme provided farmers with financial support for farming in an environmentally friendly manner and improving the environmental state of existing farms. The stated objectives of the measure were:

To promote:

o Ways of using agricultural land which are compatible with the protection and improvement of the environment, biodiversity, the landscape and its features, climate change, natural resources, water quality, the soil and genetic diversity;

o Environmentally-favourable farming systems;

o Conservation of high nature value farmed environments that are under threat;

o Upkeep of historical features on agricultural land;

o Use of environmental planning in farming practice.

To protect against land abandonment; and

To sustain the social fabric in rural communities.67

As such, the REPS 4 scheme contained both environmental and social goals, though the importance of these goals was not ranked.

Following the closure of REPS 4 to new applicants from July 2009 and the additional funding available through the Health Check agreement and under the European Economic Recovery Plan, a total modulation fund of €119.5 million and half of the EERP fund of €13.4 million was allocated to a new Agri-Environment Options Scheme (AEOS). The AEOS was a further iteration of REPS 1 – 4, though the opportunity that the closure of REPS created was to further progress the design of the scheme to have much more targeted environmental impact.

The objectives of Agri-Environment Options Scheme (AEOS) were to meet the challenges of preserving and promoting biodiversity, encouraging water management and water quality measures and to a lesser extent, combating climate change. This scheme marked a significant change away from the ‘whole farm’ approach adopted by its predecessor, REPS, to a more ‘targeted’ approach allowing farmers to select specific environmental options through a menu-type approach that were deemed as being most appropriate to their individual farms.

67 The measure formally includes The Organic Farming Scheme (OFS), with the promotion of organic farming identified as one of its objectives. This is discussed separately in Section 7.7.




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7.5.4 Background to Non-Productive Investments

Measure 216 was aimed at supporting non-productive investments, in order to achieve the commitments undertaken under agri-environmental schemes. Non-productive investments were investments that did not lead to any significant increase in the value or profitability of the agricultural holding. Examples include:

Establishment and maintenance of habitats;

Tree planting and management;

Hedgerow planting; and

Provision of alternative water source for bovines.

Actions classified under Measure 216 were integrated within REPS and AEOS and were funded under Measure 214 as the dominant measure.


The next figure outlines Indecon’s analysis of the Programme Logic Model for the agri-environmental measures. It shows the inputs that results in financial payments to eligible farmers (the output). These in turn had the potential to alter incomes of the farmer and changed the way the land was farmed (results). The ‘impacts’ assess the broader changes brought about by the programme other than on direct beneficiaries, which include economic activity in rural areas more generally, as well as the supporting of the countryside/environment. The logic of this measure assumes the following:

Appropriate levels of farming from managing land as opposed to abandoning it yielded environmental and related public ‘goods’ that are of value to the general public;

Conversely, farming can also simultaneously result in negative environmental impacts which should be curtailed through appropriate incentives/restrictions;

Farms/regions where the benefits were the greatest were correctly identified;

Scheme rules set appropriate restrictions on land-use while promoting continued land management;

Amount of public subsidy/income used to promote sustainable use of land is both sufficient and not excessive;

Farmers were in compliance with restrictions;

Land abandonment in identified areas was actually happening or was a credible threat; and

Cumulative benefit of these measures was an improvement in various measures of environmental and social impact, such as in terms of climate-change, biodiversity and avoiding land abandonment.




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Figure 7.11: Programme Logic Model – Agri-Environmental Measures

Source: Indecon

7.5.6 Inputs

Agri-environment payments were implemented through contracts between the Managing Authority and a beneficiary (farmer or land manager). These contracts, which normally cover five to seven years, detail the commitments that the beneficiary was required to enter into, which covered a wide range of farming practices. Participation is voluntary on the part of the farmer. The REPS 4 scheme closed to new entrants in 2009, although many of the farmers who were participating in REPS at the beginning of 2010 still had the majority of their five-year contracts to complete.68

7.5.7 Activities and Outputs

Indicators – Natura 2000

The table below illustrates the output, impact and result targets and indicators for the Natura 2000 measure. By the end of 2013 a total of 10,924 holdings had been supported under Natura 2000. The total UAA supported under this measure up until the end of 2013 was 285,473 hectares, which is equivalent to 75% of the revised target of 381,000 hectares. The fact that the same indicator was used for both output and results highlight the need for further enhancement of indicators.

68 www.agriculture.gov.ie/farmerschemespayments/ruralenvironmentprotectionschemereps/repsfactsheets/

INPUTS

Exchequer Funding

EU Funding


ACTIVITIES



Farm inspections

OUTPUT


eligible farmers

RESULT

Enhanced farmer income

Promote sustainable

agricultural land use

IMPACT

Enhance economic activity in rural

areas

Maintain countryside/ environment




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Type of Indicator

Indicator Revised Target 2007-2013

New and old variants of Natura 2000

Measure



Output Number of supported holdings in Natura 2000 areas/under WFD

14,625 10,924 75%

Supported agricultural land under Natura 2000/under WFD

439,000 ha 285,473 ha 65%

Result Areas under successful land management:

Biodiversity

Water Quality

Climate Change

439,000 ha

439,000 ha

439,000 ha

285,473 ha

285,473 ha

285,473 ha

65%

65%

65%

Impact Reversal in biodiversity decline Decline halted NA 100* (Baseline = 93.5)

Maintenance of High nature value farmland

439,000 ha 285,473 ha 65%

Improvement in water quality 78 Kg N NA -1.7%

(2007-2013)**

Contribution to combating climate change

N.A. N.A. 18,905 (2013)***

Source: * Index of population of farmland birds. Source: http://indicators.biodiversityireland.ie/index.php?qt=si&id=9 ** Change of Gross Nutrient Balance between 2007 and 20913, tonnes of nitrogen: http://ec.europa.eu/eurostat/en/web/products-datasets/-/AEI_PR_GNB *** Emissions of methane and nitrous oxide from agriculture and measured in 1000t of CO2 equivalent http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=aei_pr_ghg&lang=en

Indicators – REPS/AEOS

The indicators for Measure 214 are presented in Table 7.8. To the end of 2013, a total area of 2,187,525 hectares had been supported under agri-environment schemes, which is an average of around 48.7 hectares per farm holding, for each of the 44,853 participants. More than 2 million hectares has therefore been farmed to agri- environment standards. As with Natura 2000 land it contributed to biodiversity, water quality, climate change, soil quality and the avoidance of land abandonment. Participation in agri- environment schemes was particularly significant in the West and North West of Ireland, including counties such as Galway, Mayo and Donegal. Results indicators on progress in achieving a number of detailed targets were not available and similar issues arose with some of the impact indicators.

http://ec.europa.eu/eurostat/en/web/products-datasets/-/AEI_PR_GNB




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Table 7.8: Overall Output, Impact and Result Targets and Indicators for Measure 214 under the RDP 2007-2013

Type of Indicator

Indicator Revised Target 2007-2013 (REPS/AEOS Combined)


Output

# of farm holdings & holdings of other land managers receiving support

79,000 42,444 (57%)

Total area under agri-environmental support

2.48 m ha 2.22 m ha (93%)

Total number of contracts 79,000 92,664 (125%)

Physical area under agri-environmental support

2.48 m hectares

2.22 m ha (93%)

Number of actions related to genetic resources

11 actions N.A.69

Result Areas under successful land management

2.48 m hectares 2.22 m ha (93%)

Impact

Reversal in biodiversity decline

Increase in farmland bird index

Increase in unpolluted length of rivers

Average no. of habitats on non-target area

Reversal in biodiversity decline - Biodiversity Decline halted

Increase in farmland bird index (100)

Increase in unpolluted length of rivers (72 per cent of length)

Average no. of habitats on non-target area (maintain 1 per farm)

Farmland Bird Index = 100 (2013)

Unpolluted length of rivers 2010-2012: 72.9% (+1%)**

Maintenance of high nature value farmland and forestry

Maintenance of quality farm buildings

Protection of archaeological features

No. of new features discovered

Likert landscape assessment

Maintenance of high nature value farmland and forestry (0.75m ha)

Maintenance of quality farm buildings (1 per farm)

Protection of archaeological features (1 per farm)

No. of new features discovered (10% increase)

Landscape assessment (N.A.)

N.A.

Improvement in water quality:

Increase in unpolluted length of rivers

Decrease of slightly/moderately polluted length

Soil P index

Fertiliser P use

Reduced Chemical N use


Increase in unpolluted length of rivers (72% of length)

Decrease of slightly/ moderately polluted length (31% of length)

Change in gross nutrient balance:

Soil P index (75 per cent of samples @ 2/3)

Fertiliser P use (5kg/ha)

Reduced Chemical N use ( 20 per cent compared to non-REPS)


Unpolluted length of rivers 2010-2012: 72.9% (+1%)**

Slightly/ moderately polluted length: 27.1% (-13%)**

Contribution to combating climate change

Increase in production of renewable energy

+26.7% (2007-2013)***

Source:* McMahon, Sheridan, et al. 2013 ** Environmental Protection Agency Water Quality Report 2010-2012 *** % Change in Primary Production of biomass from Biomass and renewable waste, 2007-2013: ec.europa.eu/eurostat/web/environmental-data-centre-on-natural-resources/natural-resources/energy-resources/energy-from-biomass

69 The number of actions delivered is not explicitly expressed in the indicator data.




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Profile of Recipient Farmers

One of the stated objectives of REPS was to protect against land abandonment. Therefore, an investigation of farm income can help in understanding whether REPS was targeted at those farms which were most likely to abandon land, which it can be taken to be those farms with the lowest income levels before direct payments were received. The table below shows family incomes for various types of farming for both those participating in REPS and not participating in REPS. Examination of the income and farm size of REPS farms and non-REPS farms is useful as a first step in considering the impact this scheme had on the sustainability of farming in Ireland. The results for all farms shows that average income is greater for REPS farms than for non-REPS farms, but is relatively low at €14,455 but this might hide other differences.

The results also show significant divergence by sector and in some sectors such as dairying and tillage, REPS beneficiaries had smaller farm size but this was not evident in the case of cattle rearing and sheep. In considering the impacts of REPS it is also important to review the geographical location of beneficiaries. This is discussed further below.

Table 7.9: Family Farm Income and Direct Payments for REPS and Non REPS Farms by Type of Farming, 2009

REPS

Non- REPS REPS

Non- REPS REPS

Non- REPS REPS

Non- REPS REPS

Non- REPS

Dairying Cattle Rearing Sheep Tillage All

Family Farm Income

25,432 22,504 9,708 3,894 11,659 6,552 16,085 14,501 14,455 9,695

Direct Payments

23,256 19,083 17,517 9,131 18,451 10,738 24,395 25,024 20,234 13,894

REPS contribution

6,329

5,406 6,161 6,110 5,577

Farm Size (Ha)

44.4 49.5 32.4 27.4 36.7 31.6 47.3 65.3 37.5 36.7

FFI per Ha 573 455 300 142 318 207 340 222 385 264

Source: Adapted from the Annual Progress Report of the Rural Development Programme, Ireland, 2007 – 2013, 2009

GIS Spatial Analysis

As part of our evaluation of REPS, Indecon has examined a number of different methodological approaches to evaluate environmental and other aspects. These include an interesting case study using spatial analysis presented by Slovenia at the European Commission’s workshop in 2016.70 Indecon obtained data on the areas of land in receipt of REPS and AEOS payments in 2013 and completed a spatial analysis in tandem with data on Special Protected Areas (SPA) and Special Areas on Conservation (SAC) under Natura 2000 in Ireland. This spatial analysis seeks to provide an insight into the extent to which the REPS and AEOS payments are being disbursed in areas of the most environmental and ecological significance in Ireland. The table overleaf outlines the square kilometres of land in receipt of REPS funding by county.

70 Use of a GIS-based method for assessment of contribution of RDP to biodiversity Mojca Hrabor, Oilos, Slovenia, EU Good Practice Workshop. Palermo July 2016




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Table 7.10: Square Kilometres of land in receipt of REPS funding by County

Carlow County 148.6

Cavan County 389.0

Clare County 628.6

Cork City 0.0

Cork County 1,549.1

Donegal County 1,042.0

Dublin City -

Dun Laoghaire-Rathdown 5.6

Fingal 11.7

Galway City 0.7

Galway County 1,328.5

Kerry County 1,343.5

Kildare County 177.8

Kilkenny County 436.8

Laois County 348.2

Leitrim County 362.9

Limerick City 0.7

Limerick County 645.0

Longford County 227.8

Louth County 103.1

Mayo County 1,514.4

Meath County 263.1

Monaghan County 253.4

North Tipperary 452.1

Offaly County 319.8

Roscommon County 494.3

Sligo County 395.8

South Dublin 8.4

South Tipperary 566.7

Waterford City 3.4

Waterford County 433.0

Westmeath County 333.9

Wexford County 392.3

Wicklow County 338.0

Source: Indecon analysis of data from Dept. of Agriculture

The spatial data provided to Indecon by the Department allowed us to undertake a mapping exercise to illustrate the geographic spread of REPS funding relative to areas of particular environmental importance in Ireland. Indecon obtained spatial data on the designated Natura 2000 sites around Ireland from the National Parks and Wildlife Service. Nature 2000 sites are split between SPAs and SACs. Ireland is required under the terms of the EU Birds Directive (2009/147/EC) to designate Special Protection Areas (SPAs) for the protection of endangered species of wild birds:

Listed rare and vulnerable species.

Regularly occurring migratory species, such as ducks, geese and waders.

Wetlands, especially those of international importance, which attract large numbers of migratory birds each year.




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Ireland’s SPA Network encompasses over 570,000 hectares of marine and terrestrial habitats. The marine areas include some of the productive intertidal zones of our bays and estuaries that provide vital food resources for several wintering wader species including Dunlin, Knot and Bar-tailed Godwit. Marine waters adjacent to the breeding seabird colonies and other important areas for sea ducks, divers and grebes are also included in the network. The remaining areas of the SPA network include inland wetland sites important for wintering water birds and extensive areas of blanket bog and upland habitats that provide breeding and foraging resources for species including Merlin and Golden Plover.

SACs are prime wildlife conservation areas in the country, considered to be important on a European as well as Irish level. Most SACs are in the countryside, although a few sites reach into town or city landscapes, such as Dublin Bay and Cork Harbour. The areas chosen as SAC in Ireland cover an area of approximately 13,500 sq. km. Roughly 53% is land, the remainder being marine or large lakes.

Figure 7.12: REPS Funded Land and Natura 2000 SPA in 2013

Source: Indecon analysis of Dept. of Agriculture data

The map above displays the degree of overlap between Natura 2000 SPAs and square kilometres in receipt of REPS funding by county in 2013 as a percentage of the total land area in each county. The darker the shade of blue, the greater the amount of land in kilometres squared that was in receipt of REPS funding. This map illustrates that those counties which contain or partially contain large areas designated as SPAs generally contained larger areas of land in receipt of REPS funding than other counties. It can be observed that the western, south-western and north-western counties which contain the majority of SPAs are also those containing some of the highest percentages of land which were in receipt of REPS funding.




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The map below contains similar data as that displayed above but in this case the map is overlaid by the Natura 2000 designated SACs in Ireland. As with the previous map, it can be observed that those counties which contained the largest areas designated as SACs are also largely those which were counties with the highest percentage of land in receipt of REPS funding.

Figure 7.13: REPS Funded Land and Natura 2000 SACs in 2013


This spatial analysis suggests that the distribution of REPS funding in Ireland, while spread across the country, is particularly focused in those regions of the country which contain the largest areas designated as being of particular environmental or ecological significance. This is important in considering the counterfactual impact analysis of these measures.




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The next table continues this spatial analysis in a similar vein by examining the number of land holdings in receipt of REPS funding on a county-by-county basis with both the SACs and SPAs overlaid. As with the previous maps examining the amount of land as a proportion of total land in receipt of REPS funding, the number of land holdings in receipt of funding also appears to accord with the national distribution of Natura 2000 sites.

Figure 7.14: REPS Funded Land Holdings and Natura 2000 SACs in 2013

Special Areas of Conservation (SACs) Special Protected Areas (SPAs)





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Box 7.1: Case Study 4: Implementation of AES in England and Ireland – Key Findings

Introduction and background

In the 2007-2013 period, both England and Ireland chose to allocate the majority of RDP funding to agri-environmental measures. This case study compares the implementation of the agri-environmental schemes in the two countries. It begins with a discussion of the schemes as introduced in England. A detailed description of these schemes in Ireland is included elsewhere in this report.

Environmental Stewardship Scheme

In England, investment supported the all-England Environmental Stewardship (ES) Scheme which was designed and launched during the previous programme period in 2005. It had two key components:

A ‘broad and shallow’ element which was made available to all those with registered agricultural land that was in receipt of the Basic farm support under Pillar 1 of CAP - the so-called ‘Entry Level Scheme’ (ELS), on condition that they contracted to undertake a range of management practices designed to benefit the environment on their holding;

A ‘narrow and deep’ element which required the beneficiary to have an initial ‘Farm Environment Plan’ (FEP) prepared for all the land entered into the scheme, which detailed its environmental features and the potential for enhanced management to benefit the environment, and identified a range of more ambitious management prescriptions to be undertaken on specific plots of land designated on the FEP, for which individual payments would be made.

In the evaluation of these measures the conclusion of the evaluators in England, based largely on secondary literature, was that both schemes had delivered some environmental gains over the period. In respect of design and delivery aspects, the ex-post team noted certain design features linked to specific issues around performance of the scheme. In particular, early evaluation of the ELS component indicated very high deadweight arising from the automatic acceptance of applications that met the pre-determined threshold score. In addition, it suggested that the uptake of options was sub-optimal from an environmental perspective because farmers were not thinking about which management might be most beneficial in particular places or situations, from an environmental perspective, even when such management might be relatively simple for them to adopt.

Beneficiary opinion concerning the performance of the HLS was generally very positive, reflecting the deeper level of farmer engagement and related higher level of financial rewards that entry into this more ambitious scheme entailed. However, the financial austerity in public finances after 2010 meant that it became progressively more challenging to secure HLS agreements as the budget for HLS advisory support and for new agreements was reduced.

Comparison with Ireland

Comparing the English experience with the two schemes which operated in Ireland, we can note important similarities in respect of lessons learned and design/delivery attributes. The Irish REPS4 scheme already incorporated an element of compulsory training for all scheme entrants, and as a result REPS may have avoided some of the deadweight issues that affected England’s ELS. Like the situation in England, the economic crisis led to significant restrictions in the available budget for these environmental management measures, after mid-term. In Ireland, the decision to close REPS4 and to replace it with a more targeted scheme (AEOS) can be seen as a rational response to these budgetary restrictions, so as to seek to achieve greater value for money from the remaining available funding for the measures.

The Irish beneficiary survey of agri-environment agreement holders indicated few differences in experience between recipients of REPs and AEOS, with both schemes appearing to attract a similar range of beneficiaries by age and by farm type. A slightly higher proportion of beneficiaries of both REPS and AEOS (95%) as opposed to those with only AEOS (87%) said that in future they would avail themselves of a similar scheme if it were offered. These results suggest that the transition to the new scheme has been relatively positively received by beneficiaries. The output indicators show that for the Rural Development Programme as a whole, the targets for total area of land under agreement were nearly met (at 93%); whereas that for numbers of holdings assisted was significantly under target (57%) while that for numbers of contracts was exceeded (125%). The new AEOS scheme had a significantly smaller reach than REPS. However, even though AEOS was a more environmentally ambitious scheme, because of the absence of comprehensive monitoring data it is not possible to fully assess how this change did/will affect specific environmental impacts. It is noted, however, that research to enhance evidence on environmental impact is underway. A range of other methodologies were used in the current evaluation to measure potential impacts.

Conclusion

The common finding in both England and Ireland schemes is that the merits of additional evidence on environmental benefits.




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7.5.8 Results

A significant question relating to the intervention logic is whether the environmental impacts on participant farms were likely to have been appropriately targeted. In Ireland, the REPS scheme required that farmers choose at least two biodiversity undertakings from a menu as part of their contract. Participating farmers should ideally choose undertakings based on the habitat types found on their farms, though in reality a variety of economic, demographic, farm and farmer characteristics are likely to influence this decision. A study by Murphy et al (2011)71 assessed the match between the undertakings chosen by farmers, and those which would have been chosen based purely on environmental groups. The results indicate that farmers’ choices only sometimes equated with the optimal ecological choices. While certain habitats, namely wetlands and reclaimed peatlands, were relatively well protected, the most ecologically optimal choice for peatlands and marginal grasslands (maintain and enhance grazing) had the lowest probability of being chosen by farmers. As such, the freedom given to farmers under REPS may have been an issue but this may have impacted also on levels of uptake.

7.5.9 Impacts

One of the challenges faced during this evaluation of the RDP was that Ireland had not implemented a national-scale, comprehensive monitoring programme to measure the environmental impacts of the agri-environment schemes. Comprehensive monitoring is needed to fully demonstrate the environmental effectiveness (and especially biodiversity benefits) of agri-environment schemes.72 In light of this, the DAFM awarded a contract to evaluate the GLAS scheme (the successor to REPS/AEOS under the 2014-2020 RDP), which will extend over the life of the GLAS scheme with a final report expected in 2020. The contract is to undertake a study of the effectiveness of the agri-environmental measures on selected farms with a view to assessing their effectiveness. All of the principal measures within the scheme will be assessed but the greatest priority is to be given to Farmland Habitats, Farmland Birds and Commonages in that order.

The major task of the evaluation of GLAS will be to undertake a longitudinal field-based evaluation of the GLAS actions contributing to biodiversity, climate and water quality objectives.73 The overall evaluation will incorporate both quantitative and a qualitative assessment of the impact of each GLAS action. A longitudinal survey on the impact of GLAS actions will be conducted, including the collection of initial baseline data on a representative sample of farms for each action, with further monitoring/data collection on the same individual farms periodically to track the impact of the actions implemented over time. The field assessments will consider the impacts on the objectives of individual actions, as well as the indirect impacts, for example impacts on non-target species or indirect environmental benefits for multifunctional actions. The results of this analysis will be available for the evaluation of the 2014-2020 RDP, and preliminary results may also be available for the mid-term evaluation.

However, in the absence of a similar farm-level, scientifically based analysis for the 2007-2013, it is not possible to quantify with any precision some of the environmental impacts of RDP measures. However, we have utilised a range of methods including GIS/spatial modelling and survey evidence to shed light on this.

71 “Do farmers in Agri-Environmental schemes make appropriate ecological choices for the habitats on their farms?”

72 “Monitoring the environmental impacts of the Rural Environmental Protection Scheme: a scoping study”, Teagasc, 2010.

73 Request for Tenders for the Evaluation of GLAS, DAFM, July 2015.




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In Phase I of the GLAS project, a literature review of existing studies was completed. It concluded that:

Lower Carbon Emissions: There is some limited evidence that emissions from dairy and suckler beef farms in the REPS scheme were lower than non-REPS farms. Cover crops, minimum tillage and the use of a trailing shoe injector for slurry application could also reduce emissions, though all three measures are uneconomic given the traded price of carbon.

Nitrate Leaching: Strong evidence has emerged to suggest a significantly lower nitrate leaching rate in REPS versus non-REPS intensive beef suckler systems. REPS uptake may also explain the decrease in phosphorus enrichment observed in some catchments over the previous decade, though these declines may have had more to do with the implementation of the Nitrates Action Programme which made certain nutrient management measures mandatory nationwide.

Biodiversity: Higher level indicators of biodiversity (bird abundances, bird species richness and vegetation species richness) generally show little or no difference between REPS and non-REPS measures. However, functional indicators of biodiversity such as invertebrate and below-ground species richness, generally show that REPS had a positive effect.

The review also examined other agri-environment measures such as the Burren Farming for Conservation Programme. The numbering system used to assess the scheme showed consistent improvements over the past decade. It was also found that the annual public goods delivered (€2.3 million) outweighed the annual cost (€1.4million), partially due to lower than average administration costs. ADAS state that the FPS (Farm Plan Scheme) in relation to hen harriers was the most popular in terms of both numbers and funding, with GLAS continuing the initiative.

Survey Evidence

Indecon’s survey of beneficiaries under the REPS/AEOS schemes asked the extent to which the scheme requirements impacted on the way they farmed. The results are shown in the table below. They show that a large proportion of farmers said that the schemes had had a moderate or significant impact on their farming methods (70.2%), while 27.9% said it had no effect.

Table 7.11: Extent of Impact of REPS/AEOS Scheme Requirements on Farming Methods

Significant impact 12.4%

Moderate impact 57.8%

No impact 27.9%

Don't know 1.9%

Total 100%


The next table presents the views of respondents on the level of compensation taking into account the restrictions placed by the scheme. A majority of respondents felt that the compensation levels of the REPS/AEOS scheme were adequate (57.3%). This is of interest given that there may be an incentive for beneficiaries to suggest the levels of comparison were not adequate and indeed 33% expressed this view.




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Table 7.12: Views on Adequacy of Levels of Compensation in REPS/AEOS Schemes

Percentage

Yes - adequate 57.3%

No - inadequate 33.1%

Don't know 9.6%

Total 100%


The survey of beneficiaries also asked farmers on the impact of the REPS/AEOS supports on a number of aspects relating to their farming enterprise. It showed that the perceived impact of the REPS/AEOS schemes were significant. In particular, 86.5% felt that the payments had had an impact on the viability of the farm (31.6% of which reported that this was a significant impact), 93.6% felt that it had helped protect the environment (45.8% reported a significant impact), 77.3% felt that it had impacted on water management (41.3% reported a significant impact), while 77.1% felt that it had impacted on biodiversity on the farm.

Table 7.13: Views on Effects of REPS/AEOS Payments on Farm Outcomes

Viability of Farm Protection of the Environment

Impact on Water Management

Impact on Biodiversity on Farm

Significant Impact 31.6% 45.8% 41.3% 30.2%

Moderate Impact 54.9% 47.8% 36.0% 46.9%

No Impact 10.3% 4.4% 19.4% 11.0%

Don't Know 3.2% 2.0% 3.3% 11.8%

Total 100.0% 100.0% 100.0% 100.0% Source: Indecon survey of farmers in the Rural Development Programme.

7.5.10 Counterfactual Impact of REPS/AEOS Grants on Output

Indecon has undertaken a counterfactual econometric model to assess the impact of REPS and AEOS funding similar to that undertaken in Section 6 of this report for land improvement grants and buildings grants. The following table outlines the impact74 on those farms that receipt of REPS and AEOS funding had in terms of farm output levels.

The model result shows the impact of various factors on farm output. It is necessary to control for these factors, to ensure that the impact of participation in REPS/AEOS is correctly identified. This detail can be ignored by the reader in interpreting the results. The most important figure (0.0213) is highlighted in bold and can be interpreted as follows. The models specified here are log-log models. The models suggest that REPS and AEOS grants increase output by 2.1%, holding all other factors equal, for every 10% increase in the level of grant funding received. This is the average impact on the treated, so for the typical farmers who received the grant. Such an increase in output is likely to have potential environmental benefits if it results in reducing the risk of land abandonment.

74 As measured by the Average Treated Effect on the Treated (ATET)




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Table 7.14: Impact on farms of receipt of REPS and AEOS funding in terms of farm output levels

Output variable Reps and AEOS

ATET r1vs0.d_reps_aeos 0.0213***

(0.007)

POmean 0.d_reps_aeos 11.09***

(0.012)

OME0 ln_lab 0.217***

(0.023)

ln_size 0.213***

(0.015)

YE_AR 0.000

(0.001)

FARM_MD_AGE -0.001

(0.001)

lndinv 0.575***

(0.061)

ln_cap 0.060

(0.051)

ln_fuel 0.110***

(0.011)

2bn.d_soil_group -0.114***

(0.011)

3.d_soil_group -0.235***

(0.026)

Constant 3.226

(2.590)

OME1 ln_lab 0.245***

(0.021)

ln_size 0.268***

(0.018)

YE_AR 0.00664***

(0.002)

FARM_MD_AGE -0.00386***

(0.001)

lndinv 0.519***

(0.020)

ln_cap -0.007

(0.022)

ln_fuel 0.104***

(0.008)


(0.011)


(0.020)

Constant -9.776***

(2.986)

N 13,648 Source: Indecon




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7.5.11 Counterfactual Impact on Productivity

Indecon has carried out a similar analysis looking at the impact of REPS and AEOS funding on farm productivity. The findings are outlined below. As before, the model result contains detail on the impact of various factors on farm productivity, though these are not of primary interest in this analysis so can be ignored. The most important output of the model (0.0406) is again shown in bold and can be interpreted as follows. The model suggests that receipt of REPS/AEOS funding results in a 0.4% increase in farm productivity, holding all other factors equal. As these are log-log models, that is to say, a 10% increase in the grant increases output per unit of labour by 4%.

Table 7.15: Impact on farms of receipt of REPS and AEOS funding in terms of farm productivity

Productivity Variable Reps and AEOS

ATET r1vs0.d_reps_aeos 0.0406***

(0.008)

POmean 0.d_reps_aeos 10.79***

(0.010)

OME0 ln_size 0.012

(0.016)

YE_AR 0.00405***

(0.001)

FARM_MD_AGE -0.002

(0.001)

lndinv 0.371***

(0.027)

ln_cap_lab 0.344***

(0.017)

ln_fuel_lab 0.109***

(0.009)


(0.010)


(0.022)

Constant -5.391**

(2.507)

OME1 ln_size 0.0826***

(0.018)

YE_AR 0.0105***

(0.002)

FARM_MD_AGE -0.00550***

(0.001)

lndinv 0.316***

(0.016)

ln_cap_lab 0.270***

(0.018)

ln_fuel_lab 0.106***

(0.009)


(0.012)


(0.021)

Constant -16.95***

(3.169)

N 13,646 Source: Indecon




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The below table outlines Indecon’s estimate of the impact of investment on output using a range of different economic models using panel data. By using different forms of economic model to test results, the analysis can show that a result is independent of the economic methodology chosen, and that the findings are robust. These findings are similar to those reported in Section 6 for those farms in receipt of other forms of grant aid. The interpretation of the coefficient is that a change in the coefficient (change in capital is a net investment) gives a change in the dependent variable, so for the coefficient of (say) 0.254, then a 10% change in capital would give a 2.54% change in output. The models for those farmers in receipt of REPS/AEOS funding suggest that investment leads to an increase in output of between 1.75% (as per the highlighted text in bold under the ‘fixed effects’ model) and 2.54% (as per the highlighted text in bold under the ‘random effects’ model).

Table 7.16: Impact of investment on output panel models

Output random effects fixed effects

Payment type AEOS/REPS AEOS/REPS

ln_lab 0.229 0.134

(18.66)** (10.73)**

ln_size 1.216 0.704

(20.69)** (10.48)**

ln_size_2 -0.112 -0.064

(15.72)** (8.01)**

YE_AR 0.012 0.014

(20.08)** (25.19)**

FARM_MD_AGE -0.004 -0.002

(10.94)** (5.72)**

farm_age2 0.000 0.000

(9.83)** (5.14)**

ln_cap 0.254 0.175

(31.64)** (21.47)**

ln_fuel 0.093 0.058

(22.59)** (14.06)**

N 13,648 13,648

R2 0.27 Source: Indecon

The table above also contains results which can provide insight into the impact of farmer age on output. The FARM_MD_AGE variable suggests that, for those farms in receipt of REPS/AEOS funding there is a negative coefficient on output of between -0.002 and -0.004. The interpretation is a % change for a given number of units change. Thus, for a farmer of age 40 versus a farmer of age 50, meaning a 10 year increase, that would mean a 4% reduction in output at the higher coefficient.

Indecon has run a similar model looking at the impact of age on farm productivity. The findings of this model are outlined in the table overleaf. Again, the results of a random effects model and a fixed effects model are both tested, to make sure that any finding is independent of the economic assumptions which underpin these models, and that therefore the model results are robust. The most relevant results of the analysis are again highlighted in bold. We find similar coefficients of between -0.003 (the fixed effects model) and -0.004 (random effects model). Again, this suggests that for a farmer of age 40 versus a farmer of age 50, meaning a 10 years increase, that would mean a 4% reduction in productivity at the higher coefficient.




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We note that the findings for these metrics are in line with those reported in Section 6 for farmers in receipt of other forms of grant assistance.

Table 7.17: Impact of age on productivity panel models

Productivity random effects fixed effects

Payment type AEOS/REPS AEOS/REPS

ln_size 1.117 0.649

(18.83)** (9.14)**

ln_size_2 -0.114 -0.072

(15.79)** (8.57)**

year 0.011 0.012

(18.57)** (20.24)**

FARM_MD_AGE -0.004 -0.003

(12.37)** (7.62)**

ln_cap_lab 0 0

(11.14)** (6.85)**

ln_fuel_lab 0.336 0.308

(44.95)** (39.92)**

2bn.d_soil_group 0.099 0.076

(23.63)** (17.65)**

N 13,646 13,646

R2 0.22 Source: Indecon

7.5.12 Discussion

The REPS scheme contained both environmental and social goals, though the importance of these goals was not ranked. This existence of multiple – and possibly conflicting – goals in one measure makes a full evaluation difficult. The optimal number of instruments in policy design, as suggested in the so-called Tinbergen rule, is that each policy instrument should address one specific policy objective, i.e. the number of tools used should be equal to the number of policy aims. However, REPS 4 had two classes of objectives, one environmental, the other social. It has been previously suggested that REPS had been more about income support to farm families than on delivering environmental goods.75

A challenge of managing these inter-related schemes is to ensure that they deliver net additional environmental benefits, while also that they are sufficiently attractive to farmers to achieve adequate take-up. Over time, cross compliance requirements placed on farmers in receipt of the Single Farm Payment had been extended,76 which in turn required an extension of the requirements under REPS/AEOS if a significant degree of deadweight was to be avoided.

Further, at the core of the logic of REPS/AEOS is the contention that traditional farming practices have produced a landscape that is heavy in biodiversity but particular forms of farming can produce environmental negatives. The decoupling of direct payments from production and the ending of the milk quota could result in a decline in farming activity in more marginal lands (particularly in the West of Ireland) with an accompanying loss of biodiversity, while simultaneously increasing the scale of more intensive farms in other parts of the country (particularly in the East and South).

75 http://www.tcd.ie/Economics/TEP/2003_papers/TEPNo13AM23.pdf

76www.ieep.eu/assets/1188/Allen_and_Hart_2013_Meeting_the_EUs_environmental_challenges_through_the_CAP_how_do_the_reforms_measure_up.pdf




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An issue also issue relates to the ‘stop-start’ effect of changes in policy in the middle of the programme, brought about largely by the onset of the financial crisis. Attendees at the National Workshop run by Indecon as part of this evaluation raised the problems caused by a lack of continuity of agri-environmental schemes during the programme period. Delegates pointed to the fact that many protected areas, such as meadowlands, required continuity if they were to deliver on benefits such as greater bio-diversity.

7.5.13 Conclusions on the Measures

The agri-environmental schemes represent around half of total RDP expenditure, and as such are very important elements of the overall programme.

The stated objectives of the REPS scheme contained both environmental and social goals, though the importance of these goals was not ranked. This existence of multiple – and possibly conflicting – goals in one measure makes a full evaluation difficult.

On average the family income is greater for REPS farms, compared to non-REPS farms but remains at reliably low levels. In terms of farm size there were significant differences by sector.

Indecon’s survey of beneficiaries under the REPS/AEOS schemes assessed the extent to which the scheme requirements impacted on the way they farmed. The results show that a large proportion of farmers suggested that the schemes had an impact on their farming methods (70.2%).

The survey of beneficiaries also asked farmers on the impact of the REPS/AEOS supports on a number of aspects relating to their farming enterprise. It showed that 86.5% suggested that the payments had had an impact on the viability of the farm, 93.6% felt that it had helped protect the environment, 77.3% felt that it had impacted on water management, while 77.1% felt that it had impacted on biodiversity on the farm.

The stop-start nature of the various schemes available to farmers was identified by beneficiaries as not only a hindrance to farmers, but also having the effect of greatly undermining the ability of these schemes to address real environmental issues.

Indecon has undertaken a counterfactual econometric model to assess the impact of REPS and AEOS funding. The model suggests that REPS and AEOS grants increase output and productivity and this may have longer-term impacts on land abandonment.

A new innovative special mapping analysis undertaken by Indecon for this study showed that the distribution of REPS funding was focussed on regions which contained the largest areas of environmental or ecological significance.

7.6 Measure 111 – Agri-Environmental Training


The objective of Measure 111 was to provide participants with information on environmental benefits arising from the Agri-environment and Natura 2000 Measures, and to equip farmers with the knowledge and skills necessary to implement comprehensive environment actions. While the measure appears as an Axis 1 Measure, it is more appropriately included here given that it is linked directly to the major Axis 2 schemes.




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Under the scheme, beneficiaries under the Axis 2 Agri-environment and Natura 2000 Measures were required to attend approved education courses. An integral part of the training was a visit to an approved REPS demonstration farm. Beneficiaries who had attended a training course in the 2000 to 2006 programming period were only obliged to attend an appreciation Training module. The appreciation module was required to meet a standard set of criteria, including a minimum of 10 hours’ duration.

7.6.2 Programme Logic Model

The figure below shows the Programme Logic Model for Measure 111. It shows the inputs, mostly in terms of funding. The results are seen in terms of an improvement in the way farms are managed, with the ‘impact’ of an improvement in the countryside environment.

Figure 7.15: Programme Logic Model – Measure 111

Source: Indecon

The logic of this measure assumes the following:

There is a significant amount of knowledge required to appropriately understand implement on-farm changes which benefit the environment;

This knowledge can be passed on through training; and

A sufficient number of farmers availed of training.

7.6.3 Indicator Data

The table overleaf outlines the output targets and indicators for Measure 111 over the course of the full programme period. Due to the transitioning of REPS programmes, training within 2007 did not occur. Further, the closure of two new entrants to the REPS 4 scheme would have resulted in a decrease of participants for the remaining years of the programme. However, a total of 30,234 participants received 54,999 days of training, which is an average of almost two days training per participant. Thus, by 2013, 61.5% of the targeted number of participants had received training.

INPUTS

Exchequer Funding

EU Funding


ACTIVITIES

Training activity


OUTPUT

Farmers who attend courses being

eligible for other supports

RESULT

Improvement in the way farms are

managed

IMPACT

Improvements in environment




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Type of Indicator Indicator Revised Target

2007-2013



Output Number of participants to training 49,200 30,234 61.5%

Number of training days received 147,600 54,999 37.3%

Result Number of farmers or forest holders that successfully ended a training activity

49,200 30,234 61.5%

Impact Change in gross value added per annual work unit

NA NA NA


7.6.4 Survey Results

Indecon outlines the views of respondents in relation to the training they received. Just under 50% of farmers felt that the training that they attended was useful, whilst only 9.5% said that it was not useful. Almost one-third of respondents say they did not attend training, though as it was compulsory under REPS, it is likely that many who did attend did not recall it when completing the survey. A further 8.3% saying that they wished that there had been more training available. It should be noted that recipients of AEOS were also included in this survey but there was no associated training programme in AEOS as there was in REPS.

Table 7.19: Views on Usefulness of Training

Percentage

I didn't attend training 29.9%

The training I attended was not useful 9.5%

The training I attended was useful 49.9%

I would have liked to have had more training available to me 8.3%

Don't know 5.8%

Source: Indecon survey of farmers in the Rural Development Programme (Axis 2 Measures) Note: Percentages do not add up to 100% due to respondents selecting more than one response

When broken down by scheme, a large majority of attendees found the training useful. Of total survey recipients under the REPS scheme, 61.9% out of the total attendees of 83.6% found the training useful, with 14.9% finding it not useful and 5.2% expressing a wish that more training would be available. Similar figures of satisfaction are observed for both AEOS and LFA, though under both of these schemes the attendance was lower.

Table 7.20: Views on Usefulness of Training by Type of Scheme

All

Respondents LFA REPS AEOS

I didn't attend training 29.9% 57.7% 16.4% 36.8%

The training I attended was not useful 9.5% 7.7% 14.9% 5.7%

The training I attended was useful 49.9% 22.1% 61.9% 50.6%

I would have liked to have had more training available to me

8.3% 6.7% 5.2% 6.9%

Don't know 5.8% 6.7% 3.7% 3.4%

Source: Indecon survey of farmers in the Rural Development Programme




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7.6.5 Conclusions on the Measure

This section has outlined the key findings regarding Measure 111. Beneficiaries suggested that this measure has significantly contributed to the growth in knowledge and skills available within the farming sector in Ireland. A total of 30,234 participants received 54,999 days of training, which is an average of almost two days training per participant. Over 83% of respondents who attended courses across schemes stated that this training/information was useful.

7.7 Organic Farming Scheme


Organic farming is recognized by a number of national and international agricultural groups, including the European Initiative for Sustainable Development in Agriculture (EISA) as a primary method of producing high quality products, with significant added value for both farmers and consumers.

The Organic Farming Scheme (OFS) is an Agri-environment measure covered under the RDP, providing funding to farmers targeting full organic status. Payments of up to €283 per hectare per annum were provided during the period in which a farm converts from nonorganic to organic farming methods, while up to €142 per hectare per annum would have been received once the farm had achieved full organic status. Following a review in 2009, the scheme rules were tightened to focus resources on farms where organic production was more likely to be economically viable. The specific objective of the measure was as follows:

To encourage producers to respond to the market demand for organically produced food; and

To deliver enhanced environmental and animal welfare benefits.


The figure below shows the Programme Logic Model for the OFS. It shows the inputs, mostly in terms of funding. The results are seen in terms of an increase in area being farmed originally. The ‘impacts’ are the improvement in the environment and in animal welfare.

Figure 7.16: Programme Logic Model – Organic Farming Scheme

Source: Indecon

INPUTS

Exchequer Funding

EU Funding


ACTIVITIES



Farm inspections

OUTPUT

Payments to farmers converting to organic methods

Payments to farmers to maintain

organic methods

RESULT

Increase in area being farmed

organically

IMPACT

Improvements in environment/ animal welfare

Meet market demand




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The logic of the Organic Farming measure assumes the following:

There is a market failure which leads to an unmet market demand, domestically or overseas, for organic produce;

The same result could not have been achieved through a lower/no subsidy; and

The scheme delivers environmental and animal welfare benefits which constitute public goods which, if not subsidised, would not be under produced in a free market.

7.7.3 Inputs

As with other measures, the two inputs required to operationalise the programme is the financial support and staff/other costs relating to the administration of the scheme. The table below shows the number of farmers who availed of the scheme, the total land area covered, and the aggregate cost of the scheme. It should be noted that the extent of organic farming relative to the size of the overall farming sector in Ireland is small, at around 1% of the total number of farmers and land being farmed.

Table 7.21: Expenditure on Organic Farming Scheme (2007-2013)

Year Number

of Farmers

Total Farmed Area (ha)

Total Annual Payment €m

2007 6 311 -

2008 179 6,252 -

2009 527 18,956 €0.4

2010 907 34,445 €2.0

2011 1,188 46,018 €4.3

2012 1,383 53,789 €3.3

2013 1,146 57,724 €4.6

Total - - €14.6 Source: DAFM Data

The Value for Money Review conducted by the DAFM found that the overall administration cost of the OFS represented 23.7% of the total value of payments in 2012, which represents a ‘staff cost per participant’ of €568 in 2012. The significant costs of the scheme compare with an average cost of five other schemes of 7.2%, which range from as low as 0.5% for the LFA scheme, to 18% for the Installation Aid scheme. The relatively high cost of the OFS can is likely to be due to the fact that the OFS payments system was not computerised, the schemes relatively small size, the fact that the scheme had a high number of new entrants, and the fact that the scheme could not easily ‘piggy-back’ on other on-farm inspections, such as the LFS scheme does.

7.7.4 Activities and Outputs

An important question in the evaluation is to judge the extent to which the OFS induced more farmers to enter into organic farming than would otherwise have been the case. Also of relevance is how the level of subsidy compared with the level of financial cost incurred by farming organically versus farming by some other means, including the value of getting subsidies for participating in other RDP schemes. The extent to which there was an overlap between the numbers of farmers entering into organic farming, and the numbers who participated in the OFS scheme is also examined.




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Level of subsidy – versus other RDP supports

An evaluative question is whether the level of subsidy in the OFS scheme compared with the level of financial cost incurred by farming organically versus farming by some other means. If the subsidy was too high, then farmers would be overcompensated for the costs induced by farming in an organic manner, and that the same effect could have been achieved with a lower subsidy. If on the other hand the subsidy was too low, then farmers would have been undercompensated, and the scheme might have been undersubscribed.

The next table compares the OFS subsidy with the subsidies for participating in other RDP schemes. It shows that the OFS subsidy for when a farmer had achieved full organic status with an area of between 6 and 55ha is €106 per hectare. This compares with triple that amount for maintaining Traditional Hay Meadows and Species Rich Grasslands under AEOS. Given that organic farming is generally thought to have imposed greater restrictions on farming than under REPS/AEOS, this might be suggestive that the level of subsidy under the OFS was low77. However, account should be taken of a range of factors but we note the relatively low take-up of the scheme.

Table 7.22: Payments applicatiable under the OFS/AEOS (2007-2013)

Year Area

OFS - Horticulture-only In conversion Full organic status

<= 6 ha €283/ha €142/ha

6 ha - 55 ha €212/ha €106ha

> 55 ha €30/ha €15/ha

All other Farmers In conversion Full organic status

3 ha – 55 ha €212/ha €106ha

> 55 ha €30/ha €15/ha

AEOS78 Traditional Hay Meadows Species Rich Grasslands Wild bird clover Commonage Land79

€314/ha €314/ha €869/ha €75/ha

Source: DAFM

Level of subsidy – versus additional cost of production

Farmers incur additional costs by farming organically versus farming by some other means. If the level of subsidy was in excess of this cost, then farmers are overcompensated, and over-production was likely. If the level of subsidy was lower than this cost, then farmers are under-compensated, and under-production was likely. Based primarily on Teagasc baseline farm output figures, on average the difference in margins per hectare between producers in conversion to organic farming and their conventional counterparts was calculated as minus €750/ha/yr.80 This is a multiple of the rates paid to organic farming. However, given the small number of organic farming in Ireland it is difficult to be definitive on this issue.

77 With respect to AEOS, it should be noted that AEOS payments were only paid on specific actions/parcels of land and not on a whole farm basis.

78 Payment rates for a selection of AEOS schemes are shown for illustrative purposes.

79 Commonage Land outside Natura network

80 Teagasc National Farm Survey Results 1996, cited in the Value for Money Review, p13.




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Level of subsidy – international comparison

With the exception of the Netherlands and France, all EU Member States had implemented specific area payments for organic farming. Generally, the rates of subsidy in Ireland were lower than in other European countries:81

Ireland ranked in 8th place out of 22 member states for grassland maintenance. Irish farmers received €106 per hectare after conversion up to 55 hectares, compared to €450 per hectare in Cyprus;

Ireland ranked 2nd lowest out of 24 countries with respect to the per hectare payments for arable land, with the per hectare payment of €106; and

Per hectare payment for vegetables in Ireland is €142 per hectare which is the lowest in the EU. Per hectare payment for perennials, orchards and fruits also saw Ireland in the lowest position for supports in this sector.

Extent of deadweight

In considering deadweight it is useful to examine the extent of overlap between the numbers of farmers entering into organic farming, and the numbers who participated in the OFS scheme. The OFS involves additional controls, oversight and administration burden on the farmer, which might lead farmers to decide not to participate in OFS even though they intend to farm organically.

The figures suggest a high level of overlap between the OFS and the decision to farm organically. Of the 904 new organic operators who registered with the DAFM since 2007,82 636 joined the OFS. Over the period 2007 to 2013, 1,488 joined OFS although 584 were already registered organic operators prior to joining OFS. Of these 584 operators, 423 were originally in the organic supplementary measure under REPS. As such, there is a very close association between the numbers who engage in organic farming, and the numbers who participate in the OFS.

7.7.5 Results & Impacts

In this section, the results and impacts of subsidising organic production is discussed.

While there is evidence of consumer demand for organic produce, the fact that existing market demand is not being met does domestically not, in itself, constitute a market failure. While there may be a market demand, the value of alternative production (e.g., conventional production methods) might be of more commercial benefit to the farmer, who might then rationally make the choice to produce conventionally. In addition, other countries may have a comparative advantage in the production of organic farming, and the importation of organic food may reflect an optimal international division of labour.83

The stage of development of the Irish organic sector suggests that the sector might benefit from ‘increasing returns to adoption.’ Nascent industries often do not have the economies of scale that their more established competitors from other countries have, and may need support until they can attain similar economies of scale. In the case of organic farming in Ireland of note is the following:

81 Value for Money Review.

82 An organic licence is a mandatory requirement in order to be registered as an organic operator.

83 There is a large economic literature on the factors which help countries acquire a comparative advantage in the production of a good or service.




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The extent of organic farming in Ireland (at around 1% of total UAA), is still very low compared to other European countries. The figure below shows the share of organic area in total utilized agricultural area (UAA) at regional level in 2010. It shows that organic farming was particularly significant in regions with extensive livestock production systems, based on permanent grassland. The importance of the organic sector was generally lower in the regions of plains where more intensive production systems prevail.84

There are a small number of processors who handle particular lines of farm-level organic output. The small number of processors may in turn influenced by the small volumes and a lack of continuity of supply for processors or organic produce.

A study by Teagasc in 2011 showed that farmers had a cultural reluctance to engage in organic farming, and did not have a good level of knowledge about the sector.

In conclusion, given Ireland’s extensive livestock production systems based on permanent grassland, there was a reasonable basis to suppose that Ireland could have some comparative advantages in this sector, though that this will be difficult to achieve in the absence of Government intervention. The main weaknesses Ireland had in the area of organic farming was the relatively high cost of feedstuffs because of a lack of protein crops, and the fact that labour is more expensive in Ireland compared to other regions in Europe where relatively high rates of organic production are observed. With respect to the latter, it should also be noted that a number of countries like Sweden and Austria show high levels of organic production despite also being ‘high wage’ countries, so higher labour costs may not prevent Ireland establishing a sizable, competitive organic industry.

Figure 7.17: Extent of Organic Farming in Europe

Source: EU Commission

84 EU Agricultural Markets Briefs No 3 | July 2014, The rapid growth of EU organic farming.




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The Value for Money study illustrated the potential market for organic produce. In 2012, Bord Bia estimated the Irish Organic Market to be worth almost €98 million which compares with an estimated €66 million in 2006. This represented a decrease from a Bord Bia estimate of €124 million in 2009, likely due to changing consumer demand as a result of the recession. Bord Bia’s research, as cited in the VFM report, suggested that Ireland is self-sufficient in the production of organic red meat for the home market and that there is scope for a large increase in exports, particularly for organic beef.

Intervention could also be justified based on an ‘imperfect information’ of producers of the market potential that is there. A recent study of the organic sector in Ireland points to an information deficit amongst farmers and a general lack of knowledge and awareness of organic farming.85 The study concluded that policy makers may wish to consider modifying the means by which they communicate with famers on issues associated with organic farming. The Department also provides funding to facilitate the development and promotion of the organic sector through two elements, namely:

Payments to the five Organic Control Bodies (OCBs) that carry out inspection and certification of organic operators on behalf of the DAFM. The OCB’s must carry out at least one inspection per year on all organic operators. The OCBs receive a subvention of €121 per farm/processor inspected from the DAFM.

Payments for initiatives to develop the organic sector in Ireland include National Organic Week, National Organic Awards, an Organic Demonstration Farm Programme, a marketing conference, and at international level, Biofach (world's largest trade fair for organic products, held annually in Germany).

It should be noted, however, that outputs are more volatile from organic farming, which may counteract any premium on the price for risk-averse farmers.

Environmental Benefit

An environmental comparison review86 indicated from international experience that organic farming delivers enhanced environmental benefits. It concluded that there are three significant areas where organic farming was found to deliver enhanced environmental benefits due to the following:

Significant difference in pesticide use between conventional and organic farming: In terms of environmental impact, pesticides can impact on surface and ground water and on air and soil contamination. Pesticide use in organic farming is very restricted, while synthetic pesticides are completely banned;

Soil conservation: Soil care is expressed in higher levels of soil organic matter, the active promotion of soil organic matter, the active promotion of soil biological activity, more balanced nutrient cycles and in many cases enhanced soil structure; and

Biodiversity: Enhanced biodiversity deemed to be delivered through enhanced richness of flora and fauna.

85 Meeting national targets for organic farming in Ireland, Teagasc, 2012.

86 “Organic Farming versus Conventional Farming” (Clavin, 2008)




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7.7.6 Conclusions on Measure

The Organic Farming Scheme (OFS) provides funding to farmers targeting full organic status.

There was likely to have been market failure which justified the existence of the OFS, in particular regarding the environmental and animal welfare benefits of organic farming.

The organic sector in Ireland was characterised by a lack of coordination and demonstration effects due to the small size of the industry. It may have proved difficult for the industry to develop to a sufficient scale in a reasonable time period without public support.

The level of subsidy would appear to have been low in comparison with differences in production costs compared to conventional farming, the level of support for a number of supports provided under AEOS87, and relative to the subsidy rates in other countries. It is not surprising, therefore, that the level of take-up of the support, and by extension the increase in area under organic farming to 55,000 ha, fell far short of its target of 220,000 ha.

While it is not possible to put a monetary value on the various benefits that arise from organic farming, the information available is supportive of the contention that the subsidy provided under the OFS may have been insufficient, and that organic produce was under-provided relative to a societal optimal level in the period under question.

7.8 Summary

The following are the key findings from this section, which focussed on the implementation of Axis 2 measures in the Irish RDP for the 2007-2013 period:

The overall conclusion is that the LFA scheme achieves its primary goal of increasing economic activity in rural areas. The farms covered by LFA payments typically have lower value-added farm systems and lower family farm incomes than in the rest of the country. However, a stricter approach based on scientific criteria relating to land quality may result in a better targeting of support;

The evidence regarding the potential for land abandonment is mixed. The importance of aggregate Common Agricultural subsidies as a proportion of family farm income means that it is likely that in the absence of the CAP, more significant levels of land abandonment would result, and the LFA is likely to play a role in preventing land abandonment. However, with existing EU supports and with measures implemented as part of RDP land abandonment does not appear to be an imminent threat, based on the stability of the aggregate national quantum of land being farmed, coupled with the price of farm land in Ireland, even in less favoured areas.

The stated objective of the REPS scheme contained both environmental and social goals, though the importance of these goals was not ranked. This existence of multiple – and possibly conflicting – goals in one measure makes a full evaluation difficult.

A majority of farmers suggested that the agri-environmental schemes had a moderate or significant impact on their farming methods (70.2%).

87 AEOS payments were only paid on specific actions/parcels of land and not on a whole farm basis.




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The survey of beneficiaries also asked farmers on the impact of the REPS/AEOS supports on a number of aspects relating to their farming enterprise. It showed that 86.5% felt that the payments had had an impact on the viability of the farm, 93.6% felt that it had helped protect the environment, 77.3% felt that it had impacted on water management, while 77.1% felt that it had impacted on biodiversity on the farm.

Indecon has undertaken a counterfactual econometric model to assess in a more quantitative way the impact of REPS and AEOS funding. The model suggests that REPS and AEOS grants increase output by 2.1%, holding all other factors equal, for every 10% increase in the grant funding received. If this enhances farm viability it is likely to result in a reduction in the risk of land abandonment. This could have significant environmental benefits.

Beneficiaries of the vocational training measure which accompanied the agri-environmental measure felt that the training had significantly contributed to the growth in knowledge and skills available within the farming sector in Ireland. Given the relatively modest cost of the scheme, this training appears to have been a justified use of public monies.

There is likely to be failure which justifies the existence of the Organic Farming Scheme, in particular regarding the environmental and animal welfare benefits of organic farming. The level of subsidy provided under the OFS would appear to be very low and take-up of the support fell far short of its target.

8 │ Answers to Evaluation Questions: Axis 3/4



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8 Answers to Evaluation Questions: Axis 3/4

8.1 Introduction

This section examines expenditures which fall under Axis 3 and 4 of the RDP, which were concerned with ‘the quality of life in rural areas and diversification of the rural economy’. As such, Axis 3 measures sought to address problems relevant to all rural dwellers, not just those with a direct or indirect link to farming. This reflects goals of the RDP in terms of contributing to the growth of the whole rural economy, not just the farming industry. RDP actions centred on the development of rural enterprises based on local natural resources, tourism, village enhancement and environmental initiatives, which were complement on-farm measures. The measures were developed to be consistent with the 1999 White Paper on Rural Development and its commitments relating to the economic and social well-being of rural communities.

The aim of this section is to help address the Common Evaluation Questions. It should be noted that some of the insights on certain questions such as the extent to which the RDP contributed to employment creation were examined in a quantified manner in previous sectors. Further it should be noted that the indicator data employed in this Section were as provided by the Managing Authority for the period until the end of 2013. Subsequently there have been further updates to this indicator data, and as such differences between the indicator data presented here and the most up to date versions available are likely. While this is true of other indicator data employed in this report, given the later start for much of the activity under Axis 3 and 4 the data for these may be more affected by differences in indicator data than for programmes under Axis 1 or Axis 2.

8.2 Implementation and Composition of Axis 3 and 4

Background

Axis 3 measures were implemented using the LEADER approach (Axis 4) that emphasised a ‘bottom up’ approach to project design, with area-based local development strategies. Since its launch in 1991, LEADER provided rural communities in the EU with the means to directly shape policy interventions. The LEADER approach has by its nature higher costs and risks, given that more control of EU budget is given to a multitude of local partnerships called Local Action Groups (LAGs). However, the approach has largely been seen as having been a success, with the result that it was in effect mainstreamed into the RDP for the first time under the 2007-2013 RDP.

Axis 3 measures had the objective of improving the quality of life in rural areas and diversification of the rural economy through the following:

Increasing economic activity and employment rates in the wider rural economy through encouraging on-farm diversification into non-agricultural activities;

Supporting the creation and development of micro-enterprises in the broader rural economy;

Encouraging rural tourism built on the sustainable development of Ireland’s natural resources, cultural and natural heritage;

Improving access to basic services by rural dwellers by, for example, addressing inadequate recreational facilities;

Regenerating villages and their surrounding areas by improving their economic prospects and the quality of life; and

Maintaining, restoring and upgrading the natural and built heritage.




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Intervention Logic

The next table shows the Programme Logic Model for the LEADER approach. LEADER works by local communities developing project proposals, and submitting them to their Local Action Group. Projects can cover a wide range of areas, such as in encouraging farm diversification, supporting small businesses, investing in villages and the natural/built heritage both to improve local services and to improve tourism. As such, the inputs are the public financing available, the administrative processes involved in overseeing the schemes, and training/support provided to LAGs to enable them to operate efficiently.

These inputs give rise to the following activities: communities develop and submit proposals, which are then either supported or declined. They must then, if successful, comply with the administrative requirements of the scheme. A further activity is interaction between LAGs to promote best practice, and to ensure that the operation of the LAGs can best support the communities they work in while ensuring value for money in the use of public funds (the output). The result is the objectives of the EU’s rural development programme, while an additional impact relates to the strengthening of community ties through the LEADER approach which results in greater local cohesiveness than would otherwise be the case.

Specifically, the logic of these measures assumes the following:

That local communities are sufficiently active to provide a supply of suitable community-based projects;

That these communities have the capacity, knowledge and resources to develop strong applications;

That the Managing Authority is able to adequately assess the quality of each proposal;

That administrative requirements are sufficient to protect the interest of the taxpayer while not being dissuasively complex; and

That projects deliver on the goals they set out which form a basis for their funding.

Table 8.1: Programme Logic Model - Measure 112/113

Source: Indecon

INPUTS

Exchequer Funding

EU Funding

Administrative Support

Training Support and Advice

ACTIVITIES

Communities/ individuals/ enterprises

develop proposals

LAGs to award grants to best

projects

LAGs to share information &

experience

Compliance with scheme

administration

OUTPUT

Achievement of specific project

results

RESULT

Achieve EU’s rural development

objectives

IMPACT

Other local activities being

done better




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Inputs

There are four major inputs to operationalise the various strands which were included under the LEADER approach. The first two relate to financing, including whether the scheme were funded by the Irish Exchequer or through the EU. The third is the administrative support required to implement the schemes, while the fourth relates to the training support provided to LAGs.

Funding Provision

It had been originally expected that Axes 3 and 4 of the RDP would commence early in 2008, slightly later than measures under Axis 1 and 2. However, a complaint lodged with the EU Commission regarding Ireland’s ‘cohesion process’ led to a delay. Consequently, the process for selecting LEADER Local Action Groups (LAGs) to deliver the Axis 3 measures was postponed until 2008. Having then undertaken a selection process, a total of 36 LAGs were selected and announced in November 2008, and contracts were subsequently signed in January 2009. The effect of the late start of the programme resulted in the main activity occurring in the 2010-2013 period. For example, the number of projects involving diversification into non-agricultural activities by year is shown below, with the impact of the late start of the programme clearly evident.

Figure 8.1: Number of Projects under Measure M311 - Diversification into non-agricultural activities, by year, 2007-2013


The level of expenditure on each programme element differed across implementing Local Action Groups and across the variety of measures under which projects could be funded. The figure below shows the spread of investment across the Local Action Groups by measure over the entire programme period.




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Figure 8.2: Maximum, Minimum and Average Expenditure Across Measures by Local Action Groups, 2007-2013


It is important to understand how the level of expenditure compared to the budget allocated to each measure. As Ireland delivered the Axis 3 Measures (Quality of life in Rural areas and Diversification of the Rural Economy) using the Axis 4 approach, this part of the RDP is reported using measure 413 (Implementing Local Development Strategies). This is the sum of the expenditure amounts claimed under individual Axis 3 measures. It shows that the budget was spent despite the late start in programme implementation, with a large portion of this expenditure occurring in 2014 and 2015.

Table 8.2: Actual v Budgeted Expenditure (Axis 3 and 4)

Code Measure Public Expenditure

Programmed Public

Expenditure

Financial execution of

the RDP

411-3 Implementing local development strategies

250,090 246,975 101.3%

421 Implementing cooperation projects 4,671 5,166 90.4%

431 Running the local action group, acquiring skills & animating the territory

71,669 72,490 98.9%

Source: DAFM 2013 Output Indicators. Data has been updated to include data from 2014 and 2015.




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The process for dividing the budget between different LAGs was based on an independent review of the business plans of each of the LAGs. As part of this review, the consultants were required to:

advise the Department regarding the process around the selection of Groups; undertake an evaluation of the Business Plans for the Rural Development Programme; assess the relative merits of the Business Plans of the applicants with reference to a series

of criteria; and recommend on the basis of their assessment and ranking of the plans, the Groups that

should be selected to implement the programme in Ireland and the amount of public funding that should be allocated to each selected Group.

The allocations were subsequently amended in 2012, following a change to the EU co-financing rate arising from the financial crisis. This resulted in a decrease in the overall programme allocation, though at this point some of the LAGs had already spent significant amounts of their original budgets.

Scheme Administration

The third input required for LAGs to operate was administrative support. This was both an input (from the Managing Authorities perspective) or an activity (from the individual LAG’s perspective). The LEADER initiative, which had been in existence for three programming periods prior to the 2007-2013 RDP, was mainstreamed under the 2007-2013. Many LAGs felt that the weight of the regulations which this entailed were excessive. The vast majority (88.5%) of the LAGs who responded stated that they felt there were excessively onerous administrative and reporting requirements involving the LEADER programme. The appropriateness of the level of administration and oversight for schemes delivered using a community development approach is an issue and raises the difficult balance between appropriate monitoring and compliance and ease of administration.

Table 8.3: Views on Administration of the Scheme

Percentage of Respondents

Excessively onerous 88.5%

Moderate 11.5%

Light 0.0%

Don't know 0.0%

Total 100%

Source: Indecon survey of Local Action Groups

Participants at the National Workshop also felt that the bureaucracy and overly rigorous inspections meant that requirements were too strict under the LEADER programme. However, this view was challenged by the Managing Authority. This was thought to be a particular problem in more disadvantaged communities. These barriers were viewed to have impeded investment and prevented developmental work in rural communities. Participants also reported that the administrative burden required that a lot of work had to be done “behind the desk”, which was viewed to be a potential issue for the future. Despite the administrative requirements, participants felt that there were not enough qualitative indicators/requirements such as an understanding of the effect of the investment/grant on the community as a whole.

The feedback suggests that ways of easing administrative requirements should be considered, although Indecon would caution that this should not be achieved at the expense of appropriate rigorous evaluation and compliance.




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Training and Support

The final input required was an adequate level of training and support to LAGs to allow them to operate efficiently. Whilst not many respondents felt that they received a lot of support and advice in running their LAG (3.8%), half did say that they received some support. A further 38.5% stated that they received little support.

Table 8.4: Views on Level of Support and Advice Provided Whilst Running the LAG


A lot 3.8%

Some 50.0%

Little 38.5%

None 7.7%

Don't know 0.0%

Total 100%


When asked about areas for potential training, the majority of respondents believed that training in the area of procurement and the related requirements could be provided to support running the LAG. Others felt that operating rule requirements (14.8%) would be an area in which additional training could be provided.

Table 8.5: Views on Potential Additional Training


No additional training is necessary 3.7%

Governance and conflict of interest 0.0%

Operating rule requirements 14.8%

Procurement requirement 55.6%

File management 3.7%

Project cases studies 0.0%

Animation activity - best practice examples 0.0%

Other 22.2%

Total 100%


Activities

The next step in the programme logic model is that the inputs dedicated to Axis 3 and 4 resulted in a series of activities. The activities of the LAGs are dependent on the pipeline of suitable projects from the communities in which they serve. The LEADER approach in Ireland differs from that in many other EU countries which represent straightforward grants for investment or other projects. In Ireland the level of pro-activism is notable, in particular through the appointment of ‘development officers’ who actively search for and develop project ideas that would help achieve the strategy objectives88.

88 http://www.eca.europa.eu/Lists/ECADocuments/SR10_05/SR10_05_EN.PDF




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The level of activity depends on:

The level of community activism in each region, and the level of community participation in the development of proposals;

The obstacles faced by communities in proposing projects;

The quality of grant applications received; and

The need and supply of training opportunities available to members of community.

Each of these are now discussed in turn, reporting the outputs of Indecon’s survey of LAGs. When asked about the level of community participation involved in the development of proposals, the vast majority of respondents (74.1%) said that there was very broad participation and knowledge of proposals and projects across the community. This reinforces the findings on the level of community activism in the region, showing that there was a high degree of high quality community engagement.

Table 8.6: Views on Level of Community Participation in the Development of Proposals


Very broad participation/knowledge of proposals/projects across the community 74.1%

Proposals/projects were generally dominated by a small number of individuals 25.9%

Don't know 0.0%

Total 100%


Table 8.7 presents the main obstacles faced by applicants for grants. Over half stated that the complexity of the application process was the main obstacle that was faced, which is in line with the findings of surveys of farmers regarding measures such as TAMS, REPS and ERS.

Table 8.7: Views on Main Obstacle Faced by Applicants


Identifying the right project 0.0%

Securing community interest and involvement 0.0%

Finding matching funding 3.8%

Restrictions and delays in planning regulations 0.0%

Complexity of the application process 53.8%

Lack of sufficient information/guidance 3.8%

Time delays 0.0%

Uncertainty regarding success or otherwise of proposal 3.8%

Other 34.6%

Total 100%


Almost half of respondents (48.1%) believed that it was either easy or very easy to attract good quality, well developed grant application from the communities in their area. However, there were 18.5% who had difficulties in attracting quality applications, with a further third of respondents finding it neither easy nor difficult.




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Participants at the National Workshop felt that better developed communities had a significant advantage when it came to the application process, and thus funding may have favoured advantaged communities compared to less advantaged areas. The view of some LAGs was that there should have been a focus on developing less-developed communities. However, this focus would be required at local level by the LAGs themselves.

Table 8.8: Views on Quality of Grant Applications


Very easy 14.8%

Easy 33.3%

Neither easy nor difficult 33.3%

Difficult 14.8%

Very difficult 3.7%

Don't know 0.0%

Total 100%


Interaction with other LAGs

Another activity conducted by LAGs is an on-going engagement with other LAGs to try and identify and promote best practice. Table 8.9 shows that the majority of respondents had a lot of interaction with other LAGs, with 57.7% stating this to be the case. Over a third (34.6%) stated that their LAG had some interaction with other LAGS, with the remaining 7.7% saying that they only had little interaction with other LAGs. These findings suggest a high degree of cooperation amongst LAGs.

Table 8.9: Level of Interaction with Other LAGs


A lot 57.7%

Some 34.6%

Little 7.7%

None 0.0%

Don't know 0.0%

Total 100%


Result/Output

The final stage of the programme logic model is an assessment of some of the results and outputs. In particular, the Axis-level indicators for Axis 3 are shown below. They suggest that the percentage of the population in rural areas increased to 73%. Alternative census data suggests that population in rural regions was 38% in 2011. This may reflect the fact that the definition of what constitutes a rural region differs between the EU and the Irish statistical agencies.

In considering the evidence on off-farm employment it is relevant that fluctuations in trends in off-farm-income during the programme period are likely to have been dominated by the sharp deterioration in the labour market with the onset of the financial crisis89, rather than a change in the potential willingness or ability of farmers to work off-farm. The proportion of farms where either the farm holder or the spouse had off-farm employment, as measured by the Irish National Farm

89 http://www.farmersjournal.ie/WEBFILES/61396-158420.pdf




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Survey, had until 2013 declined from a peak of 59% in 2006 to a low of 50% in 2012. In 2013, the proportion of farm holdings where the farmer or his/her spouse with an off-farm job increased to 51.2%. The EU indicator for 2010 as reported in the table below showed a figure of 45.8%, which was below the target of 50%. Further, employment in secondary and tertiary sectors was around 93.3% in 2010, which again would have been impacted by the financial crisis. Probably the most dramatic impact of the financial crisis, however, lies in the net migration figure, which at the outset of the programme was strongly positive though had turned negative following the crisis.

In terms of other indicators, there was a sharp increase in tourism beds in rural areas from 2005-2012, rising by 32%. Rural areas also saw a very strong increase in take-up of broadband over the period to 2012. The tertiary sector had risen to 62.6% of economic output in rural areas by 2010, well above the target level of 60%. There was a fall in the participating in life-long learning in rural areas.

Table 8.10: Rural Development Programme - Axis 3 Indicators - Summary of Progress versus Target

Indicator Measurement Baseline Target Latest Position

Importance of rural areas

Per cent of population in rural areas 72 % 72% 73%

Farmers with other gainful activity

Sole holders-managers with other gainful activity as a % of total number of farm holders (sole

holders-managers)

44% (2005) 50% 45.8% (2010)

Employment development of non-agricultural sector

Employment in secondary and tertiary sectors (000s)

National 1,956.5; In Rural Areas 1,373 (2006)

96% 93.3%

Economic development of non-agricultural sector

GVA in secondary and tertiary sectors (€m)

National 153,955

In Rural Areas 92,296 (2006)

98% 97.6%90

Self-employment development Self-employed persons

National 322; In Rural Areas 262

(2006) 20%

14.5% (2012)

Tourism infrastructure in rural area

Number of bed places

National 206,831; In Rural Areas

166,859 (2005)

Sustain In rural areas

219,874 (2012)

Internet take-up in rural areas Persons having subscribed to DSL

internet as a % of total population

National 13%; In Rural Areas 5%

(2006) 20%

Increase in broadband of

34.7% p.p. from 2008-2010

Development of services sector

GVA in services as a percentage of total GVA


(2006) 60% 62.6% (2010)

Net migration Net migration into the state (per

1000 inhabitants)

National 16.9; In Rural Areas 17.8

(2006/2007) Sustain -6.0 (2011)

Life-long learning in rural areas

Per cent of adults (25 to 64 years) participating in education and

training


12% 5.1% in rural areas (2012)

90 http://ec.europa.eu/agriculture/statistics/rural-development/2013/full-text_en.pdf




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Impact

The impact of the LEADER approach was also assessed through the Indecon survey of LAGs. Each of the respondents to the Indecon survey of LAGs were also asked their views on the achievement of LEADER principles. 66.7% expressed a view which strongly agreed that the key principles of LEADER were met in practice in the region. It should be noted that LAGs would be likely to report that the overall LEADER process – and by extension their own performance – was impactful, and the results of this survey analysis must be considered in this light.

Table 8.11: Views on Achievement of Key LEADER Principles


Strongly Agree 66.7%

Agree 33.3%

Neither Agree/Disagree 0.0%

Disagree 0.0%

Strongly Disagree 0.0%

Don't know 0.0%

Total 100%


At least half of respondents stated that the LEADER programme had a significant impact in each of the areas contained in the question, as shown in Table 8.12. 89.9% said that LAGs significantly contributed to achieving the objectives of the local strategy and the RDP. 77.8% believed that LEADER had a significant impact in building local capacities for employment and diversification, with a further 22.2% saying it had a moderate impact. Half of respondents stated that the implementation of the LEADER approach had a significant impact in relation to improving local governance, with 42.3% saying that there was a moderate impact from the LEADER approach.

Table 8.12: Views on Overall Impact of LEADER Programme on Rural Development

Significant Impact

Moderate Impact

No Impact

Don't Know

To what extent has the RDP contributed to building local capacities for employment and diversification through LEADER?

77.8% 22.2% 0.0% 0.0%

To what extent have LAGs contributed to achieving the objectives of the local strategy and the RDP?

88.9% 11.1% 0.0% 0.0%

To what extent has the Leader approach been implemented? 81.5% 14.8% 0.0% 3.7%

To what extent has the implementation of the Leader approach contributed to improving local governance?

50.0% 42.3% 3.8% 3.8%


8.3 Axis 3 and 4 - Indicators

In the following section, we analyse the indicator and other data at measure level, focussing on outputs, results and impacts insofar as the data is available.

8.3.1 Measure 311 - Diversification into Non-Agricultural Activities

The objective of Measure 311 is to increase the percentage of holdings where a member of the farm household profits from utilising the fixed assets of the farm for non-agricultural activity.




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Analysis of indicator data

The quantified targets for the output, result and impact indicators specified in the RDP in respect of Measure 311 - Diversification into Non-Agricultural Activities – are set out in the table below. All Axis 3 measures delivered by LEADER are evaluated under Axis 4 of the programme; as such indicators under Axis 3 are additional indicators only. The targets set for the indicators represent significant revisions on the original targets as set out originally. For example, the target for the total number of beneficiaries was reduced from the original 800 to 507 in the revised version.

Table 8.13: Measure 311 - Diversification into Non-Agricultural Activities – Quantified Targets for EU Common Indicators

Type of indicator Indicator Target 2007—2013

Output Number of beneficiaries

507 (Total) (380 Male, 127 Female)

Age: < 25 years – 32; > 25 years – 475

Type of non-agricultural activity:

– Tourism Activity – 158 – Craft Activity – 126 – Trade/Retail Activity – 32 – Other – 190

Total volume of investment supported in assisted projects

€19.1 million

Result

Increase in non-agricultural GVA in supported businesses

N.A.

Gross number of jobs created 791 Full-Time Jobs (126 on-farm, 665 off-farm)

Impact Net additional value expressed in PPS €3.4 million

Net additional full-time equivalent jobs created

950 Full-Time Equivalents (158 on-farm, 792 off-farm)

By the end of 2013 a total of 283 applications for project funding under the measure were approved, relating to 2,494 beneficiaries of which 2,446 were natural persons and the remainder were legal entities. This is equivalent to 482% of the revised overall target of 507 beneficiaries by 2013. The overall volume of investment that took place in these projects amounted to €13.5m or 70.7% of the revised programme target of €19 million.

Table 8.14: Measure 311 - Diversification into Non-Agricultural Activities - Output Indicators

Type of rural non-agricultural activity

Number of applications

approved 2007-2013

Number and gender of beneficiaries 2007-2013 Total Volume of Investment in

Supported Projects – 2009-

2013 ('000 €)

Natural persons

Male Female Total

< 25 >=25 < 25 >=25

Tourism 117 257 588 254 549 1647 6,860

Craft activities 14 0 10 0 6 16 187

Retail activities 33 3 29 3 14 49 1,771

Renewable energy production 38 0 56 0 1 57 1,624

Other (childcare, etc.) 81 206 230 202 39 677 3,022

TOTAL 283 466 913 459 609 2446 13,464 Source: RDP Annual Progress Report for 2009 -2013 – Output Indicators




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Box 8.1: Case Study 4: Implementation of LEADER in England and Ireland – Key Findings

Ireland England

Background

All Axis 3 measures were implemented through Axis 4. Irish central government played a strong role in establishing the boundaries of LAGs and make-up of LAG Boards.

Number of LEADER groups in England increased from 25 to 64 LAGs, but with a smaller budget. In most cases LAGs had very limited funding levels and limits on what they could deliver. For many LAGs the time available for action was considerably shorter due to the delayed start.

Similarities

Delivery Processes

Majority of Irish LAGs found the administrative processes were ‘onerous’.

Grant applications

In Ireland, half of survey respondents reported that it had been ‘very easy’ or ‘easy’ to get good quality grant applications submitted. .

Evaluating impacts

The Maye and Simpson (2009) report suggested that LAG personnel in Ireland were concerned over the failure to adequately measure all outcomes from the Leader programme. However Indecon’s analysis suggests the need to balance administration requirements and evaluation. For this evaluation Indecon research shows that most LAGs had positive views on achievement of projects.

Delivery Processes

There is evidence in England to suggest applications were less than anticipated, or withdrawn, due to difficulties such as staffing changes within LAGs and paperwork required even for very small projects.

Grant applications

In England, the nature and quality of applications varied. There is evidence that LAG chairmen had a high degree of control on the direction of activity and the types of projects funded.

Evaluating impacts

In England a survey carried out as part of the 2016 Ex-post Evaluation of the England RDP of LAG managers highlighted the challenge of measuring outputs.

Differences

Cohesion

The ‘cohesive process’ linked LEADER in Ireland with other locally delivered programmes. There was a delay in starting and slowing down of expenditure in the early part of the programme, while the process was bedding in.


In Ireland over half of LAGs indicated they had a lot of interaction with other LAGS. The nature of the interaction appears to be significantly different from the experience in England where relatively few LAGs interacted together, and there were significant obstacles to any form of transnational activity.

Achievement of Leader principles

In Ireland, Indecon’s survey results reported that Leader principles had been implemented. There was also strong support for the role of Leader with more than three-quarters of the sample indicating that in each case LAGs have had a significant impact on rural development in their area.

Cohesion

In England there was no attempt at cohesion with other rural funding streams though the make-up of the LAG Boards helped in coordination. Delivery was heavily influenced by previous experience of LAG members and the support of local authorities.


In England, the ‘implementation of cooperation projects’ was intended to be a key element of Axis 4, and to. encourage LAGs to undertake joint actions. Interaction with other LAGs in practice, however, was limited to informal interaction. LAGs chose not to engage in international collaboration.

Achievement of Leader principles

In England programme implementation was considerably delayed, leaving little opportunity to implement truly integrated local development strategies. For new LAGs, the LDS had already been prepared before the LAG itself was constituted.




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8.3.2 Measure 312 - Support for Business Creation and Development

The overall objective of Measure 312 was to provide support to rural communities to increase their economic sustainability into the future. The measure provided funding for the development of innovative and sustainable enterprises and was designed to provide local people with an opportunity to develop employment and business locally which would in turn increase the appeal and sustainability of these communities.


The quantified targets for the output, result and impact indicators specified in the RDP in respect of Measure 312 - Support for Business Creation and Development – are set out in the table below.

Table 8.15: Measure 312 - Support for Business Creation and Development – Quantified Targets for EU Common Indicators


Output Number of micro-enterprises supported

Total – 4,47991 New – 1,568 Existing – 2,911

Result Gross number of jobs created Total: 4,355 (Male 2,613, Female: 1,742) Age: < 25 years—623, > 25 years—3,732 On-farm: 435; off-farm: 3,920

Increase in non-agricultural GVA in supported businesses

Economic growth expressed in non-agricultural GVA by region, from baseline 2006

Impact Net additional value expressed in PPS €10 million


Total: 4,977 (Male: 2,986, Female: 1,991)

Age: < 25 years—746 > 25 years—4,231 On-farm: 498; off-farm: 4,479

Source: Rural Development Programme, Ireland, 2007-2013

In relation to results, a total of 2,219 enterprises were supported during the programme period, which was around half of the adjusted target of 4,479. In terms of the employment creation within projects supported under the business creation and development measure, a total of 1,859 full-time equivalent jobs were supported in projects funded under the measure, only 43% of the measure target. However, this should be seen in the context of the economic downturn.

Table 8.16: Summary of Result Indicators by Measure – Measure 312: Support for Business Creation and Development

Measure

Number of micro-enterprises supported 2009-2013

Male Female Legal Bodies

Total

< 25 ≥ 25 < 25 ≥ 25

Micro-Enterprise Creation 90.5 320 182 177 190 959.5

Micro Enterprise Development 98.2 426 80.5 223.5 431 1259.2

Total 188.7 746 262.5 400.5 621 2218.7 Source: Indecon analysis of DAFM Indicator Data

91 RDP Plan




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8.3.3 Measure 313 - Encouragement of Tourism Activity

The objective of Measure 313 is to realise the potential for tourism within rural areas in a sustainable manner. The aim in particular was to tackle a lack of regional balance in tourist activity, which was identified as a challenge to the future viability of rural tourism. Environmental awareness and protection had to be an intrinsic feature of this measure.


The quantified targets for the EU Common Indicators in respect of Measure 313 are set out in the table below.

Table 8.17: Measure 313 – Encouragement of Tourism Activity – Quantified Targets for EU Common Indicators


Output Number of supported actions Small-Scale Infrastructure - 355 Recreational Infrastructure - 355 Development/marketing - 870

Total volume of investment €49.1 million

Result Additional number of tourist visits Overnight Stays – 3,551 Number of day visitors – 10,653

Gross number of jobs created 1,065

Impact Net additional value expressed in PPS €11 million

Net additional full-time equivalent jobs created 355

The achievements by the end of the programme based on available data in relation to the quantitative indicators for measure 313 is described in the table overleaf. In relation to outputs, a total of 1,718 new tourism actions were supported and total investment amounted to over €59.3 million under the scheme was recorded. These output indicators are equivalent to 115% and 121% of the programme targets respectively. In terms of results, data was available on additional tourism visitors which showed very high levels of increases. However, Indecon did not believe that this indicator data was an accurate measure of additional tourism visits related to the counterfactual impact of Measure 313 and we have excluded this as it does not represent a useful input into this evaluation.

Table 8.18: Summary of Output and Result Indicators – Measure 313: Encouragement of Tourism Activities

Indicator Outcome 2007-2013

Target 2007-2013

Output as a % of Target

Output Number of supported actions 1,822 1,580 115%

Total volume of investment (€) €60.9m €49.1 124%

Result: Gross number of jobs created 877 1,065 82%

Impact: Net additional value expressed in PPS N.A. €11m N.A.

Net additional FTE jobs created N.A. 355 N.A.




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8.3.4 Measure 321 - Basic Services for the Economy and Rural Population

The main objective of this measure is to determine the needs of rural communities and provide appropriate leisure and cultural facilities not otherwise available to them. The rationale for this measure is that quality of life issues including the availability of services and living conditions significantly influence the extent to which people are willing to return or re-locate to rural areas to live and work.


Details in relation to the EU Common Indicators agreed in respect of measure 321 are shown in the table below.

Table 8.19: Measure 321 – Basic Services for the Economy and Rural Population – Quantified Targets for EU Common Indicators


Output Number of supported actions Amenity/Leisure Facilities – 206

Arts/Cultural Facilities – 206

Recreational Infrastructure – 206

Total volume of investment €50.1 million

Result Population in rural areas benefiting from improved services

2,500,000

Increase in internet penetration in rural areas Not supported under this measure



514

The position at the end of the year was that 1,290 actions had been supported under the scheme, representing a total volume of investment which was 24% ahead of target.

Table 8.20: Summary of Output and Result Indicators – Measure 321: Basic Services for the Economy and Rural Population


Target 2007-2013


Output Number of supported actions 1,438 618 233%

Total volume of investment €66.2m €50.1 132%

Result: Population in rural areas benefiting from improved services

2,493,28392 2,500,000 100%

Increase in internet penetration in rural areas N.A. N.A. 82%

Impact: Net additional value expressed in PPS N.A. N.A. N.A.


N.A. N.A. N.A.

92 This refers to population years, in other words the total population benefiting is summed over the programme.




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8.3.5 Measure 322 - Village Renewal and Development

The objective of the village renewal and development measure is to enhance the economic and social attractiveness of villages, small towns and the surrounding countryside. Actions were to be aimed at enhancing the environmental, amenity and surface structural aspects of these communities and to complement measures to support tourism and conservation of local heritage. Analysis of indicator data

The quantified targets for the EU Common Indicators in respect of Measure 322 are set out in the table below. Indecon would note that the same indicator for results targets and outcomes in terms of population in rural areas benefiting from improved services is used as was applied to Measure 321 and this is also used subsequently for Measure 322. This suggests that the indicator is not appropriately targeted on this particular measure and suggests the need for future refinement of indicators. Also of concern is that no target was set for the increase in internet penetration in rural areas although this would appear to be a well-defined indicator.

Table 8.21: Measure 322 – Village Renewal and Development – Quantified Targets for EU Common Indicators

Type of indicator

Indicator Target 2007—2013

Output Number of villages where actions took place 1,789, of which: Renovation of buildings - 441 Environmental upgrading - 441 Farmers’ markets - 126 Surface and amenity improvements – 441 Other small-scale infrastructure – 340

Total volume of investments €49.82 million


2,500,000 Small towns – 906,894 Villages – 365,275 Countryside – 125,95693

Increase in internet penetration in rural areas N/a


Net additional full-time equivalent jobs created 1630

The position at the end of the programme period in 2013 is shown overleaf, though very limited indicator data is available. It shows that the total volume of investments was in line with target, though that the geographical dispersion of the aid, based on the number of villages and the benefiting population, were around half what was targeted.

93 These figure represent the sum for each region type across specific enhancement actions, and does not sum to the total target, which (2.5m) represents over half the population of Ireland.




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Table 8.22: Summary of Output and Result Indicators – Measure 322: Village Renewal and Development


Target 2007-2013


Output Number of villages where actions took place

912 1,789 51%

Total volume of investments €49.6m €49.82m 100%


1,310,66794 2,500,000 52%

Increase in internet penetration in rural areas

N.A. N.A. N.A.

Impact: Net additional value expressed in PPS N.A. €11.64 m N.A.


N.A. 1,630 N.A.

8.3.6 Measure 323 - Conservation and Upgrading of the Rural Heritage

The rationale for this measure is based on the premise that rural heritage resources – whether natural, built or cultural - must be developed and utilised in a sustainable manner. Under this measure, conservation actions were aimed to include not just conservation and protection actions for the natural, cultural, social and vernacular heritage but to also encompass pro-active initiatives in relation to the utilisation of local resources to provide sustainable and renewable energy options for local communities.


The quantified targets for the EU Common Indicators in respect of Measure 323 are set below.

Table 8.23: Measure 323 – Conservation and Upgrading of the Rural Heritage – Quantified Targets for EU Common Indicators

Type of indicator

Indicator Target 2007—2013

Output Number of supported actions Natural/Vernacular Heritage – 452

Cultural Heritage – 452

Environmental Initiatives – 452

Renewable Energy - 452

Total volume of investment €52 million (+€5.75 million under M214)


2,500,000

Increase in internet penetration in rural areas Not supported under this measure



474





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The position at the end of the programme period in 2013 is shown below, though very limited indicator data is available. It shows that the total volume of investments was 40% of target.

Table 8.24: Summary of Output and Result Indicators – Measure 323: Conservation and Upgrading of the Rural Heritage


Target 2007-2013


Output Number of supported actions 1,115 1,808 62%

Total volume of investment €22.95m €57.75m 40%


3,074,08495 2,500,000 123%

Increase in internet penetration in rural areas N.A. N.A. N.A.

Impact: Net additional value expressed in PPS N.A. €11.64 m N.A.

Net additional full-time equivalent jobs created N.A. 1,630 N.A.

8.3.7 Measure 331 - Training and Information

The rationale for this measure is that the successful implementation of Axis 3 measures requires training in adapted and new skills for all rural dwellers and communities.


The quantified targets for the EU Common Indicators in respect of Measure 331 are set out in the table overleaf.

Table 8.25: Measure 331: Training and Information – Quantified Targets for EU Common Indicators


Output Number of economic actors supported by activity

Male - 11,972

Female - 11,962

<25 years – 4,771

25 – 44 years – 11,972

Over 44 years – 7.156

Social Group: Those prioritized in National Training Strategy

Number of days of training receive by participants

47,707

Result Number of participants that successfully ended a training activity

Male – 11,043

Female - 11,043

<25 years – 4,417

25 – 44 years – 11,043

Over 44 years – 6,626





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The position at the end of the programme period in 2013 is shown below for Measure 331. It shows that almost 57,000 persons received training in the programme period, over double the target level, though that the number of training days received was slightly lower. Indecon would note that the results and output indicators do not measure the levels of satisfaction of participants and that impact indicators were not set.

Table 8.26: Summary of Output and Result Indicators – Measure 331: Training and Information


Target 2007-2013


Output Number of economic actors supported by activity

56,960 23,934 238%

Number of days of training receive by participants

43,128 47,707 90%

Result: Number of participants that successfully ended a training activity

34,558 22,086 156%

Survey Results

As can be seen in Table 8.27 almost two-thirds of respondents felt that there were some training opportunities available for members of the community who were interested in proposing a project. A further 33.3% stated that there were a lot of training opportunities.

Table 8.27: Views on Training Opportunities Available to Members of Community


A lot 33.3%

Some 63.0%

Little 3.7%

None 0.0%

Don't know 0.0%

Total 100%


8.3.8 Measure 341 – Skills acquisition, animation and implementation

The rationale for this measure that is that as Axis 3 measures will be delivered through the LEADER methodology by Local Action Groups, the animation and capacity building needs of the rural territory are central to a successful uptake of the programme in all rural areas.




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The quantified targets for the EU Common Indicators in respect of Measure 341 are set out in the table below.

Table 8.28: Measure 341: A Skills-Acquisition and Animation Measure– Quantified Targets for EU Common Indicators


Output

Number of skill acquisition and animation actions

883

Number of participants in actions Male – 11,043

Female - 11,043

<25 years – 4,417

25 – 44 years – 11,043


Social Group: Those identified in LAG business plans

Number of supported public/private partnerships

No PPP involved at official delivery level. Delivered entirely by LAG

Result Number of participants that successfully ended a training activity

Male – 18,405

Female – 18,405

<25 years – 7,362

25 – 44 years – 18,405


The position at the end of the programme period in 2013 is shown below for Measure 341. It shows that there was six-times the number of actions as originally targeted. The very high number for ‘participants in actions’ stems from the provision of information and promotional events.

Table 8.29: Summary of Output and Result Indicators – Measure 341: Skills acquisition, animation and implementation


Target 2007-2013


Output Number of skill acquisition and animation actions

5,450 883 617%

Number of participants in actions 702,829 22,086 3182%

Number of supported public/private partnerships

N.A. N.A. N.A.

Result: Number of participants that successfully ended a training activity

31,122 36,810 85%




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Survey Results

The next table shows high levels of community activism within the respondent’s region, as reported by respondents to Indecon’s survey of LAGs. Over 70% of LAGs believed the community that they served to be very active, with the remaining 29.6% stating that their community was moderately active.

Table 8.30: Views on Level of Community Activism in the Region


Very active 70.4%

Moderately active 29.6%

Largely inactive 0.0%

Don't know 0.0%

Total 100%


Respondents to the survey of LAGs were also asked to indicate what type of activities they conducted in their areas. Examples of the responses include:

Appointment of specific animators to work on the ground;

Workshops and Information sessions;

Training programmes;

Supplements in local press;

Signage outside projects;

Information roadshows;

Sponsor groups; and

LEADER Newsletter.




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Box 8.2: Case Study 5: National Rural Network – Key Findings

This case study examined the contribution of the National Rural Network (NRN) to the delivery of the RDP 20007-2013. The NRN was established in 2008 and was facilitated through the Rural Development Support Unit within the Tipperary Institute. The purpose of the NRN was to facilitate all actors, stakeholders, beneficiaries and interested groups in the achievement of better outcomes across the entire suite of measures under the RDP, and to assist the efficient and effective implementation of the Rural Development Programme across all axes; promote synergies across measures; and have regard to the different delivery methods.

The key findings from the analysis of the NRN are as follows:

The intervention logic of this measure assumes that the problems/challenges that the NRN sought to address were best approached using network-type approaches/activities. This in turn comprises of three questions: were the problems/challenges that the NRN sought to address best approached using a network approach; were the approaches/activates conducted by the NRN sufficiently targeted at solving these problems; and did the NRN apply network type approaches/activities.

One activity conducted by the NRN which achieved an overall ‘high’ rating in terms of its network properties were the NRN Fore, though the Annual Conference also fared well. This is in particular because of the manner in which the NRN For a collected ‘best practice’ using a bottom-up approach, which in turn provided input to both policy formation, and could be used to inform communication to other interested stakeholders. The Annual Conference also brought different stakeholders together, though attendance was not sufficiently broad to say that a network approach was being adopted.

Two of the other activities were by their nature research in nature, namely the Strategic Issues Working Groups and the Case Studies. Both of these achieved a ‘Medium’ overall ranking as while they provided useful information to relevant stakeholders, by their nature the communication was not interactive. Similarly, the main communication devices used, i.e. the website and Quarterly Newsletter, were primarily a form of one-way communication. Overall, while many of the NRN’s activities may have been useful, it is not clear why they could not have been run centrally from the DAFM (or other agency), and why a network approach per se was felt necessary/optimal.

In an effort to assess the impact of the NRN, primary survey research of LAGs was also completed. In terms of the amount of interaction and support LAGs felt they had received from the NRN, 63% reported ‘little’, 20% reported no interaction or support, while only 17% reported ‘some’. None of the respondents reported that they had received a lot of support. When asked what the benefits of the NRN were to their LAG, a majority of respondents reported that it was of no particular benefit, though one in six LAGs reported that it produced useful material on its website, while one in four said that it arranged opportunities to network with other groups.

The overall assessment of NRNs is that many useful projects were completed on a relatively small budget. However, the intervention logic of NRNs is that a networking approach is most useful, and that creating synergies across different aspects of the RDP and different regions is of use. From an examination of the activities of the NRN during the 2010-2013 period, it is not clear that a networking approach was universally applied, nor that a number of activities of the NRN could not have been completed centrally instead.




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8.3.9 Axis 4 Measures

Axis-level indicators

The baseline position and targets for indicator formulated in respect of Axis 4 are set out in the table below. These indicators are referenced to the Census of Population.

Table 8.31: Measure 41 (inclusive of Measures 411 and 413): Implementing Local Development Strategies – Quantified Targets for EU Common Indicators

Type of indicator


Target 2007—2013


Output

Number of local action groups supported 36 36 100%

Total size of LAGs area (km2) 69,357 69,476 100%

Number of projects financed by LAGs 8,743 12,602 69%

Total population in LAG area 2,734,855 2,734,855 100%

Number of beneficiaries 270,416 4,194 6,447%

Result

Gross number of jobs created (FT + PT) 4542 (FT+PT)

Number of successful training results Courses – 879

Persons – 23,441

Impact

Net additional value expressed in PPS €2.3 million

Net additional FTE jobs created 4,688

All 36 Local Action Groups, covering 69k square kilometres were supported to implement 8,743 local development projects during the period of the RDP from 2007 to 20013. In terms of participation, 100% of the LAGs and all of the area covered by these LAGs have been involved in the projects undertaken in Axes 3 and 4. In terms of the number of projects, the outcome saw 69% of the target being met.

8.3.10 Measure 421: Implementing Co-Operation Projects.

275 co-operation projects were supported under measure 421 in the programme period which involved all 36 Local Action Groups.

Table 8.32: Measure 421: Implementing Co-Operation Projects – Quantified Targets for EU Common Indicators

Type of indicator Indicator Outcome 2007-2013 Target 2007—2013

Output

Number of supported cooperation projects 275 265

Number of cooperating LAGs 36 36

Result Gross number of jobs created N.A. 147

Impact Net additional FTE jobs created N.A> 74




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8.4 Summary

Axis 3 measures were implemented using the LEADER approach (Axis 4) that emphasised a ‘bottom up’ approach to project design, with area-based local development strategies. In Ireland, implementation covered the entire rural economy, and focussed on a broad range of outputs. However, there were a number of salient issues relating to the implementation of the LEADER approach over the period concerned:

It had been originally expected that Axes 3 and 4 of the RDP would commence early in 2008, slightly later than measures under Axis 1 and 2. However, a complaint lodged with the EU Commission regarding Ireland’s ‘cohesion process’ led to a delay. Consequently, the process for selecting LEADER Local Action Groups (LAGs) to deliver the Axis 3 measures was postponed, and the first year of full implementation was 2010;

The process for dividing the budget between different LAGs was based on an independent review of the business plans of each of the LAGs. The allocations were subsequently amended in 2012;

Many LAGs felt that what they viewed as overly rigorous inspections meant that requirements were too strict under the LEADER programme, which was linked to the mainstreaming of LEADER in the 2007-2013 RDP for the first time. This view was challenged by the Managing Authority. Indecon’s judgement is that there is a balance to be achieved between ensuring sufficient information for analysis of compliance with requirements and the need for evaluation while minimising administration burden. The research suggests that consideration should be given to adjustments to administration but to do this in a way which does not damage effective control mechanisms and the achievement of necessary compliance;

When asked about the level of community participation involved in the development of proposals, the vast majority of respondents to Indecon’s survey (74.1%) said that there was very broad participation and knowledge of proposals and projects across the community. This reinforces the findings on the level of community activism in the region, showing that there was a high degree of community engagement;

Each of the respondents to the Indecon survey of LAGs were asked their views on the achievement of LEADER principles. 66.7% of respondents suggested that they strongly agreed that the key principles of LEADER were met in practice in their region; and

The analysis of the available indicators suggests much progress on the measures supported. The specification of the Programme Logic Model also confirms that the measures rationale were appropriate. However, the gaps in results and impact indicators has hindered a comprehensive evaluation and Indecon recommends that further resources are allocated in future programmes to the development and data collection for indicators. A smaller number of targeted indicators would have been more appropriate and Indecon understands that this approach has been followed in the current RDP.

9 │ Conclusions and Recommendations



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9 Conclusions and Recommendations

9.1 Introduction

This section brings together the various analyses and assessment presented in the preceding sections to develop overall conclusions from the ex-post evaluation of the 2007-2013 Rural Development Programme Ireland. These are presented in Section 9.2 and include a discussion of the conclusions from the analysis at a programme, axis and measure level. Based on these conclusions, an integrated set of recommendations is presented which are also broken down as appropriate at a programme, axis and measure level. These recommendations aim to draw out the key lessons from the experience of the 2007-2013 programme, both to inform the on-going 2014-2020 programme, while also addressing issues for longer-term policy regarding the broader rural economy, particularly in terms of the agriculture sector.

9.2 Detailed Conclusions from Evaluation

The overall objective of this ex-post evaluation was to achieve a holistic, strategic and robust evaluation of the RDP programme in Ireland, as experienced during the period 2007-2013. The evaluation was based on the rural policy objectives established at EU and national levels, which are at the core of the programme’s intervention logic. These objectives were to improve the competitiveness of the agricultural and forestry sector; to improve the environment and the countryside; to improve the quality of life in rural areas and to encourage diversification of the rural economy; to build local capacity for employment and diversification; to ensure consistency in programming (maximising synergies between axes); and finally to achieve complementarity between Community instruments.

Indecon has used a range of advanced and rigorous methods to empirically evaluate the impact of measures/supports under the Programme. We have also, where feasible, applied a ‘triangulation’ of methodologies, with the objectives of cross-confirming qualitative and quantitative measures and to evaluate counterfactual impacts. Finally, we have set research priorities on the basis of the principle of proportionality, devoting more resources to those elements of the programme which constitute the largest expenditure shares. Our methodological approach has involved the following seven methodologies to evaluate the 2007-2013 RDP: a detailed consultation programme; extensive new survey evidence; detailed analysis of indicator data; case studies; Bio-Economy Input-Output Model; econometric counterfactual models; and spatial, GIS-based analysis. The conclusions as set out below draw on the output of these various forms of analyses as presented in this report.

9.2.1 Programme Level Conclusions

Absence of detailed ‘intervention logic’ associated with programme, axes and measures

The first conclusion relates to the rationale set out by the Managing Authority in designing the programme. CMEF Guidelines state that the intervention logic for the programme should be explicitly stated in the National Strategy Plan. While targets for each of the axes are discussed in the NSP, the plan lacked a detailed explicit intervention logic.

However, as part of our analysis we have completed a detailed explicit Programme Logic model and this highlights the rationale for the model. Such an approach should be used in any subsequent RDPs as it is aligned with EU requirements and would help in identifying any trade-offs or conflicts between measures.




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Budgeted and outturn of Expenditure

Taking into account the introduction of the new Agri-Environmental Options Scheme and Natura 2000 measure, the overall proportion of programme funding devoted to agri-environment schemes under the revised budget, at 49%, compared with an original overall allocation of 51.4%, while funding allocated to the Less Favoured Areas scheme was expected to account for 32.3% of the overall programme (versus 31.1% previously).

Cumulative expenditure over the lifetime of the RDP totalled €4,228.7 million, which includes expenditure out to 2015. This was equivalent to 98% of the revised overall funding allocation for the programme of €4,308 million. The largest individual axis was Axis 2, which spent 98% of its final revised funding allocation. Axes 1 and 3/4 spent over 97% of their budgets, spending €78.9 million and €326.4 million respectively. The low levels of expenditure compared to the original target for technical assistance is relevant given the importance of developing rigorous indicator data and the need for ongoing evaluation to inform evidence based policy.

Programme-level socio-economic impacts

In terms of programme level impacts and addressing the common evaluation questions 1 and 2, it is clear that RDP expenditure had a very significant impact on the level of economic activity in the broader rural economy, which in turn has contributed significantly to employment creation. Indecon estimates that the overall impact of RDP expenditure on the Irish economy, including the direct, indirect and induced impacts of this spending, amounted to €4,184 million in output and 6,466 jobs96 on an annual basis between 2007 and 2013. In regional terms, 84% of the estimated direct plus indirect benefit of RDP expenditures was felt within the rural economy. While beyond the scope of this study, this may have had an impact in reducing the rate of outward migration from rural areas and supporting a wide range of rural businesses. Overall, the evidence suggested the economic impact of the supports in promoting the quality of life in rural areas (common evaluation question 9).

Indicators

The National Strategy Plan outlined the different indicators and targets for each measure and each axis. However, in a number of cases the targets were only set in imprecise terms or in terms of an increase, which inevitably constrains the use of these indicators for Programme monitoring and evaluation.

9.2.2 Axis 1 - Axis- and Measure-level conclusions

The aim of Axis 1 of the 2007-2013 RDP was to contribute to improving the competitiveness of agriculture by supporting restructuring, development and innovation. This was achieved through two policy streams – addressing the age profile of Irish farming (namely through Measures 112 and 113) and promoting on-farm investment (Measure 121). At the outset of the programme, the Early Retirement Scheme (Measure 113) was the largest scheme within this axis, accounting for around two-thirds of total budgeted expenditure, with the Farm Improvement Scheme (Measure 121) constituting a large majority of the remainder, and relatively limited expenditure on the Young Farmers Installation Scheme (Measure 112).

96 Full Time Equivalents




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The balance of funding across the Axis 1 measures was changed significantly in 2008/2009, due to the budgetary constraints brought about by the financial crisis which was unfolding in Ireland at this time. Rather than reduce each of the measures proportionally, the decision was made to abolish Measures 112 and 113, and focus instead on supporting on-farm investment. Indecon believes that the validity of measures to reduce the age profile of farmers is clear given the econometric evidence on the impact of farmer age on output and productivity. This may also have some environmental benefits. However, there are a variety ways this can be achieved, whether by directly instituting measures which focus on the age of the farmer (such as the Young Farmers Installation Scheme/Early Retirement Scheme), or indirectly by supporting on-farm investment measures.

Young Farmers Installation Scheme (YFIS)/Early Retirement Scheme (ERS)97

The Young Farmers Installation Scheme (YFIS) aimed to facilitate young educated people to enter farming. The Early Retirement Scheme (ERS) was intended to complement the Young Farmers Installation Scheme by encouraging the transfer of holdings from older farmers (transferors) to younger farmers (transferees), through the provision of a pension for transferors. Both were designed to encourage structural changes in the agricultural sector, with the objective of enhancing the competitiveness and sustainability of farming in Ireland. The average age of Irish farmers has been getting progressively older since 2000, with the average age now standing at 57 years.

There is evidence from previous Indecon econometric findings that farm efficiency and output is affected by age. Further, many ERS beneficiaries in the survey analysis reported that their farms had significantly modernised. Additional new econometric modelling undertaken for this RDP evaluation confirms that reducing the age of farmers adjusting for other factors is likely to have a beneficial impact on farm output and productivity. While increases in output will have direct environmental impacts, such increases particularly when combined with productivity improvements and the introduction of new methods, can reduce land abandonment and assist in enhancing the environment. Reducing the age of farmers is also likely to impact on the willingness of farmers to implement environmentally sensitive methods.

Indecon believes that the overall policy aim of these supports, namely to arrest the structural shift towards an older age profile in Irish farming, is appropriate. Further, sustaining and developing rural communities will require the creation of attractive employment opportunities for young families, including on-farm employment.

As discussed above, Indecon believes that there are a number of possible policy interventions which may have the effect of improving the age-structure of Irish farming, and that policy-makers do not have to rely solely on schemes which directly target the age of the farmer. For example, many stakeholders in the consultation phase of this evaluation commented that encouraging young people into farming could only be achieved by creating a farm income that could play an important role in supporting two households and not just one. Therefore, schemes which promote on-farm investment may have a positive impact on the age distribution of farming, even if they don’t explicitly target any particular age group. Many national policy interventions also affect the willingness or otherwise of young people to take up a career in farming. In this context it is important to recognise that the Irish Government have introduced significant taxation measures to support young farmers.98

97 Given the complementarity between Measure 112 and Measure 113, and noting that they both were suspended mid-way through the programme, these were analysed using a single, integrated presentation of the programme logic model.

98 For a further discussion on these measures including the international context see Indecon Report for the Agri-Taxation Working Group to the Minister for Finance and the Minister for Agriculture, Food and the Marine. See Budget 2015 - http://www.budget.gov.ie/Budgets/2015/Documents/Agritaxation_%20Review%20_Final_web-pub.pdf.

http://www.budget.gov.ie/Budgets/2015/Documents/Agritaxation_%20Review%20_Final_web-pub.pdf




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Finally, neither of these schemes were of a sufficient scale to have a material impact on the age distribution of Irish farming. It should be further noted that the establishment, rollout and administration of such schemes involve significant economies of scale, and the introduction of small schemes increases the risk of an inefficient use of public money because of the administration costs involved. However, strategically measures which assist in reducing the age of farmers and encouraging new entrants are likely to have significant impacts on competitiveness and on the environment.

On-Farm Investment (FIS/TAMS)

The Farm Improvement Scheme (FIS) – introduced in 2007 – was designed to help Irish farms to be competitive through an increase in productive capacity. This scheme provided grant aid for investments that encouraged the development and use of modern, highly specialised, cost-efficient and labour-saving facilities and equipment.

Econometric modelling suggests that increased investment in agriculture is likely to enhance output and productivity. Econometric counterfactual analysis undertaken as part of this evaluation suggests that Building Grants increased output above 3.4%, holding other factors equal. The impact of Land Improvement Grants was found to be statistically insignificant.

However, this does not imply that all investments will have had a positive impact, nor does it imply that all publicly-funded schemes which aim to promote on-farm investment are equally efficient in identifying and supporting projects which meet social and economic goals. Of note in this regard during the 2007-2013 programming period was the rapid take-up and excess demand for FIS in 2007, to the point where the scheme had to be closed to new applications after a number of weeks. This raises the question as to whether the screening process that was in place was adequate both to ensure that investments were of a sufficiently high quality to merit public support, and to minimise project deadweight.

The introduction of the new TAMS scheme was designed to address many of the perceived weaknesses of the FIS, and was expected to boost the share of the programme budget allocated to on-farm investment from 1.5% to 3.9%. As TAMS operated from 2010-2013, it is likely to have played a role in easing credit constraints for farmers wishing to invest in their farm enterprises. There is evidence that financing constraints in Irish agriculture became much more acute following the financial crisis. The Indecon survey responses indicated that the most positive impact of investment scheme participation was reported by those farmers who had availed of both FIS and TAMS, with a higher impact reported by those farmers who availed of FIS only compared to those who availed of TAMS only. This reflects the lower amount of public expenditure involved which resulted in farmers reporting a lower impact on their farm competitiveness.

The largest category of recipients, as shown by the survey of beneficiaries, was dairy farmers, with 40% of respondents stating that they were mainly dairy farmers. The fact that participation in the scheme had such a strong take-up among dairy farmers suggests the contention that the scheme helped support restructuring in the dairy sector over the programme period.

Overall, in addressing common evaluation question 5, 6 and 10, the evidence available suggest that the schemes put in place supported competitiveness on farm, and allowed farmers to restructure to new market opportunities, particularly in the dairy sector.




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9.2.3 Axis 2 – Axis- and Measure-level conclusions

The aim of Axis 2 was to improve the environment and the countryside by supporting land management. The axis accounted for a large majority of total RDP spend. Taking into account the introduction of the new Agri-Environmental Options Scheme and the Natura 2000 measure, half of the overall proportion of overall programme funding was devoted to agri-environment schemes, while funding allocated to the Less Favoured Areas scheme accounted for just under a third of total programme expenditures.

Overall, the evidence suggests it is likely that the impact of the Axis 2 measures was to reduce the possibility of land abandonment in rural Ireland, and to support the economic viability of many rural communities. We, however, note that land abandonment in Ireland is limited. It is harder to assess with any certainty some of the other environmental impacts of the Axis 2 measures, given the absence of detailed data to enable identification and assessment of such impacts. However, the available evidence indicates that the schemes did have an effect in protecting the environment, contributing to climate change mitigation and improving water management, which are relevant to the common evaluation questions 3, 4, 7 and 8. Indecon believes that more resources should be allocated to establishing rigorous indicator data which would facilitate enhanced monitoring and evaluation of the environmental impacts and we understand that research on this is underway as discussed below in our analysis of REPS/AEOS.

Less Favoured Areas

The Less Favoured Areas (LFA) scheme aimed to contribute to maintaining the countryside by promoting sustainable farming systems in marginal areas where farming activity may not otherwise be viable. Indecon believes that the LFA scheme achieved its primary goal of increasing economic activity in rural areas, based on the Input-Output analysis. The farms covered by LFA payments typically have lower value-added farm systems and lower family farm incomes than in the rest of the country. However, a stricter approach based on scientific criteria relating to land quality may have resulted in a more effective targeting of support.

As noted above the evidence presented in this study also suggests that the threat of land abandonment in Ireland is limited, though real. This is particularly based on the stability of the aggregate are of land being farmed nationally since the turn of the millennium. Further, the strong price of farm land in Ireland suggests that there is not an imminent threat of wide scale land abandonment, even in less favoured areas. The importance of aggregate Common Agricultural subsidies as a proportion of family farm income suggests that in the absence of the CAP, some additional land abandonment may have been likely. While the payments under the LFA scheme were unlikely on their own to determine the levels of land abandonment, recipients of scheme payments had lower family farm income, and the LFA would have been likely to play a part in preventing land abandonment. There has also been very significant other policy measures introduced at national level including taxation measures, which are likely to improve the productivity of Irish farming99.

99 For a further discussion on these measures including the international context see Indecon Report for the Agri-Taxation Working Group to the Minister for Finance and the Minister for Agriculture, Food and the Marine. See Budget 2015 - http://www.budget.gov.ie/Budgets/2015/Documents/Agritaxation_%20Review%20_Final_web-pub.pdf.

http://www.budget.gov.ie/Budgets/2015/Documents/Agritaxation_%20Review%20_Final_web-pub.pdf




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A further conclusion from the evaluation of the LFA scheme is that the administration costs of the support were very low relative to the size of the budget, while the rates of compliance achieved were high. The high level of compliance with the terms of the scheme suggests that the maintenance of the countryside environment through farmland management was aligned with Programme requirements.

The evidence from survey results suggests that the LFA scheme was perceived as having positive impacts on viability and on environmental objectives. However, the absence of rigorous results and impact indicators makes it difficult to be definitive on this issue.

REPS/AEOS

Three measures within the 2007-2013 RDP related to agri-environmental supports, namely Measures 213, 214 and 216. Of particular importance was Measure 214, the Rural Environment Protection Scheme (REPS), which constituted the majority of expenditure across the agri-environmental schemes. The stated objective of the REPS scheme contained both environmental and social goals, though the importance of these goals was not ranked. The existence of multiple – and possibly conflicting – goals in one measure should be explicitly recognised and where possible quantified to better inform policy making.

We understand that a more comprehensive environmental monitoring system (which is being undertaken as part of the present GLAS programme covering the period of the 2014-2020 RDP), will assist in assessing the extent to which specific environmental benefits ascribed to the schemes were achieved. However, Indecon’s research indicated that a large proportion of farmers suggested that the schemes had an impact on their farming methods (70.2%). The survey of beneficiaries also asked farmers on the impact of the REPS/AEOS supports on a number of aspects relating to their farming enterprise. It showed that 86.5% suggested that the payments had had an impact on the viability of the farm, 93.6% felt that it had helped protect the environment, 77.3% felt that it had impacted on water management, while 77.1% felt that it had impacted on biodiversity on the farm. A large proportion of farmers reported that the schemes had an impact on their farming methods (70.2%).

An important feature of the 2007-2013 programme was the ‘stop-start’ nature of funding. This to a large extent was a result of the financial crisis which emerged shortly after the start of the programme, which was unforeseeable when the programme was being designed. However, the operation of agri-environmental programmes such as REPS/AEOS targets the development of environmental ‘goods,’ which are long term in nature and require a consistency of approach across programming periods. For example, the emergence of greater bio-diversity in specific locations may take decades to emerge.

Indecon believes that the balance of available evidence suggests agri-environmental payments played a role in protecting against land abandonment and in sustaining the economic viability of rural communities. The importance of aggregate Common Agricultural Policy subsidies as a proportion of family farm income suggests that in the absence of the CAP, some additional land abandonment may have occurred.

A new innovative special mapping analysis undertaken by Indecon for this study showed that the distribution of REPS funding was focussed on regions which contained the largest areas of environmental or ecological significance.




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The Organic Farming Scheme

Ireland may have some comparative advantages in the organic production sector. However, the extent of organic farming in Ireland (at around 1% of total UAA), is still very low compared to other European countries. Further, there are only a small number of processors who handle particular lines of farm-level organic output, while there is evidence that farmers have a cultural reluctance to engage in organic farming. Organic farming can also lead environmental benefits which, if not compensated for, may be underprovided in a free market. These points suggest a market failure in this sector which justifies Government intervention.

The Organic Farming Scheme (OFS) was an agri-environmental measure covered under the 2007-2013 RDP which provided funding to farmers targeting full organic status. The level of subsidy available under the scheme was low compared when variations in production costs compared to conventional farming; the levels of support under AEOS; or relative to the subsidy rates in other countries. It is not surprising, therefore, that the level of take-up of the support, and by extension the increase in area under organic farming to 55,000 ha, fell 71.5% short of target. As a result this measure only had a very limited impact.

While it is not possible to put a monetary value on the various benefits that arise from organic farming, the information available is supportive of the contention that the subsidy provided under the OFS may have been insufficient, and that organic produce was under-provided relative to a societal optimal level in the period under question.

Vocational Training

The objective of Measure 111 was to provide participants with information on environmental benefits arising from the agri-environmental and Natura 2000 Measures, and to equip farmers with the knowledge and skills necessary to implement comprehensive environmental actions. According to Indecon’s research, beneficiaries of the vocational training measure which accompanied the agri-environmental measure felt that the training had contributed to the growth in knowledge and skills available within the farming sector in Ireland.

Given the relatively modest cost of the scheme of €7 million when set against the commitment to agri-environmental schemes of almost €2 Billion, Indecon believes that this training was a prudent use of public monies and indeed more intensive training may have been worthwhile. Further, the positive impacts as reported through the survey was achieved despite the low level of expenditure on this programme.

9.2.4 Axis 3 and 4 Level Conclusions and 4 Measures

The aim of Axis 3 and 4 of the RDP was to improve the quality of life in rural areas and to encourage the diversification of economic activity. It had been originally expected that Axes 3 and 4 would commence early in 2008, though the process for selecting LEADER Local Action Groups (LAGs) to deliver the Axis 3 measures had to be postponed, and the first year of full implementation was 2010.

The process for dividing the budget between different LAGs was based on an independent review of the business plans of each of the groups.

Indecon believes that the existence of the LEADER approach over four programme cycles is likely to have had created a local competence and resource, and encouraged communities to self-identify projects which can improve the quality of life and economic resilience of many rural towns and countryside areas. The results of our analysis address the common evaluation questions 17-24. In general, the view expressed in Indecon’s survey research was that a high degree of community




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engagement took place through the LAGs, with 89.9% of respondents indicating that LAGs significantly contributed to achieving the objectives of the local strategy and the RDP (evaluation question 22). 77.8% believed that LEADER had a significant impact in building local capacities for employment and diversification (evaluation questions 17 and 21), with a further 22.2% saying it had a moderate impact. Half of respondents stated that the implementation of the LEADER approach had a significant impact in relation to improving local governance, with 42.3% saying that there was a moderate impact from the LEADER approach.

The available indicator data are not on their own sufficient to undertake a comprehensive examination of outputs against. Many of the indicators were not directly related to the target, and in some cases it was unclear what the underlying data was capturing, and what interpretation it should be given. Indecon would support use of a smaller number of targeted indicators and we understand this has been incorporated into the latest RDP.

Many LAGs felt that the bureaucracy and “overly rigorous” inspections were too strict under the LEADER programme, which was linked to the mainstreaming of LEADER in the 2007-2013 RDP for the first time. Indecon, however, believes that while the administrative requirements merits review it is essential that sufficient information is collated to ensure adequate evaluation and compliance with EU objectives, as well as ensuring continued compliance with regulatory requirements.

The Health check of the RDP also included a measure relating to the access to broadband in rural areas. This is addressed in the common evaluation question 11, which asks the extent to which the RDP has contributed to creation of access to broadband internet. The Government launched the ‘Rural Broadband Reach Scheme’ which was ultimately closed with no public expenditure due to a lack of applications from service providers. As such, RDP did not contribute to the access to broadband internet.

9.2.5 Assessment of suitability of indicators

The procedure for tracking the progress and achievements of the RDP as employed in this study, following EU guidelines, involved two principle elements, namely the collation, reporting and analysis of indicator data, and the setting out the intervention logic which underpinned each of the various schemes. As set out by the EU Commission100, indicators should be linked to the programme strategies and actions, and enable answering of the evaluation questions. Further, the Commission emphasised that understanding the intervention logic as clearly as possible would help in the identification of key results and impacts.

In writing this report, Indecon found that the indicator data did not in a number of cases adequately facilitate the rigorous evaluation of the success or otherwise of the programme. While useful in measuring inputs and activities, indicators intended to measure output, result and impact were of more limited use. This was for a number of reasons:

The underlying reporting data was not available in a timely fashion or in many cases at all;

Many of the indicators were very high level and the success, or otherwise, of individual schemes could not reasonably have been ascribed to the scheme in question;

Some indicators added no new real information; and

Some indicators lacked credibility.

100 Good Practice Workshop in Methods for Assessing Impacts of Rural Development Programmes, Palermo, July 2016.




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Data requirements required to inform each step of the programme logic model were accessed either through the Managing Authority, the Irish Central Statistics Office, Teagasc, other third-party providers, or were gleaned from Indecon’s primary survey research which was conducted to support this evaluation. While data was not always available, this approach of first identifying the intervention logic, and then reviewing data sources to assess the programme logic, was a fruitful approach but it was clear to Indecon that further enhancement of indicator data is required for future Programmes. We attempted to overcome this problem by using other methods but this was not always feasible.

9.2.6 Overall Conclusions

The overall objective of this ex-post evaluation was to achieve a holistic, strategic and robust evaluation of the RDP programme in Ireland, as experienced during the period 2007-2013. The evaluation was based on the rural policy objectives established at EU and national levels, which are at the core of the programme’s intervention logic. The programme was implemented at a time of crisis in the Irish economy which had a very large impact on programme measures, and the nature and scale of the challenges the RDP was intended to address. The RDP objectives were to improve the competitiveness of the agricultural and forestry sector; to improve the environment and the countryside; to improve the quality of life in rural areas and to encourage diversification of the rural economy; to build local capacity for employment and diversification; to ensure consistency in programming (maximising synergies between axes); and finally to achieve complementarity between Community instruments.

The following are the key findings from this section, which summarised the conclusion on the overall impact of the Irish RDP for the 2007-2013 period:

Indecon has used a range of advanced and rigorous methods to empirically evaluate the impact of measures/supports under the Programme. We have applied a ‘triangulation’ of methodologies, and devoted more resources to those elements of the programme which constitute the largest expenditure shares. Our methodological approach has involved seven qualitative and quantitative methodologies to evaluate the 2007-2013 RDP;

Cumulative expenditure over the lifetime of the RDP totalled €4,228.7 million, which includes expenditure out to 2015. This was equivalent to 98% of the revised overall funding allocation for the programme of €4,308 million. The largest individual axis was Axis 2, which spent 98% of its final revised funding allocation. Axes 1 and 3/4 spent over 97% of their budgets, spending €78.9 million and €326.4 million respectively. The low levels of expenditure compared to the original target for technical assistance is relevant given the importance of developing rigorous indicator data and the need for ongoing evaluation to inform evidence based policy;

Our modelling results including the application of a bio-economy input-output model as well as econometric counterfactual estimates suggests that the RDP expenditure had a significant impact on the level of economic activity in the broader rural economy. Expenditures resulted in significant benefits to farmers and the rural communities within which they live.

The results of the analysis are shown in the table below. They indicate that the total direct and indirect impact of RDP expenditure on the rural economy is of the order of €3,532m in output, compared to the aggregate national impact of RDP expenditure of €4,184m. As such, 84% of the estimated direct plus indirect benefit of RDP expenditures is felt within the rural economy. This excludes the economic and social benefits of any wider supply-side impacts.




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Table 9.1: Estimated Regional RDP Expenditure Impacts, 2007-2013

Direct Impacts






RDP expenditure had a significant impact on the level of economic activity in the broader rural economy. Expenditures resulted in significant benefits to farmers and the rural communities within which they live;

These two schemes aimed at promoting a structural improvement in the age profile of Irish farming, namely the Early Retirement Scheme and the Young Farmers Installation Scheme, were not of a sufficient scale to have a material impact on overall farmer’s age distribution. Econometric evidence presented in this report, however, shows that older farmers have lower levels of output relative to other farmers, which supports the rationale for implementing policies designed to deliver a structural improvement in the age profile. Younger farmers may also be more open to implementing measures to enhance the environmental impact of the agri sector.

The Indecon survey responses indicated a positive perception among beneficiaries of both variants of the on-farm investment schemes (FIS and TAMS) regarding their impact on the competitiveness of their farms. Further, economic evidence suggests that increased investment in agriculture is likely to enhance output and productivity;

The amount of change brought about by the financial crisis caused significant disruption to the operation of the programme, though the extent of the financial crisis could not reasonably have been predicted in advance by the designers of the programmes. Some of the measures, in particular the FIS/TAMS measure, may directly have helped to mitigate some of the effects of the financial crisis on the farming community;

Overall, Axis 1 measures are believed to have contributed to the competitiveness of beneficiaries (common evaluation question 15), though mainly through the on-farm investment schemes as the two age-related schemes were too small in aggregate to have had a significant impact;

The importance of aggregate Common Agricultural subsidies as a proportion of family farm income means that it is likely that in the absence of the CAP, more significant levels of land abandonment would result;

The evidence regarding environmental impact suggests that the impact on the environment is likely to have been positive. A majority of farmers suggested that the agri-environmental schemes had a moderate or significant impact on their farming methods (70.2%). It also showed that 93.6% felt that it had helped protect the environment, 77.3% felt that it had impacted on water management, while 77.1% felt that it had impacted on biodiversity on the farm;

Overall, Axis 2 measures are believed to have contributed to improving the environmental situation in Irish rural areas (common evaluation question 16). However, Indecon believes that additional monitoring data on environmental impacts would be required to complete a definitive evaluation;




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Programme design across the RDP was generally good with monitoring arrangements in place, which is of relevance to common evaluation question 14 which asks the extent to which the resources allocated were used efficiently. However, the Farm Improvement Scheme is likely to have benefited from a more rigorous screening process to ensure that investments were of a sufficiently high quality to merit public support, while the small size of the Young Farmers Installation Scheme meant it was unable to take advantage of economies of scale in scheme implementation. In addition, enhanced indicator data on outputs results and impacts would have been desirable;

Generally, the cost and weight of administration on beneficiaries was reasonable, with the exception of the Axis 3 and 4 measures, where the burden of administration appeared to be heavy for a community-lead programme. However, we would caution against any specific changes which would hinder obtaining key data, in particular compliance data or information required to undertake rigorous evaluation;

Indecon found that the indicator data in many cases did not strongly contribute to an understanding of the success or otherwise of the programme. While useful in measuring inputs and activities, indicators intended to measure output, result and impact were of more limited use. In contrast, applying a programme logic model as a means of assessing the intervention logic allowed for the development of a clear set of steps as to how the RDP measures were supposed to work.

9.3 Recommendations

A number of recommendations based on the findings of the ex-post evaluation have been formulated with the objective of informing the design of future policy to support agriculture and rural communities. These recommendations are summarised in the table overleaf. We elaborate upon each recommendation below.

Table 9.2: Recommended Actions

Recommended Action(s) Suggested Responsibility

Design and administration

1. Set out the programmes intervention logic in detail; 2. Allow all scheme administration requirements to be conducted

online; 3. The impact of administrative costs should be considered when

evaluating new small schemes; 4. Improve the indicators to facilitate RDP evaluations;

DAFM

Improving the competitiveness of Irish farms

5. Address the structural issues within Irish farming; 6. Ensure sufficient finance for viable of capital projects;

DAFM

Protecting the rural environment

7. Maintain targeted payments to farmers in disadvantaged areas; 8. Improve measurement of the environmental impacts of supports; 9. Review the level of support for Organic Farming;

DAFM

Supporting rural communities

10. Streamline the administration burden on beneficiaries/project promoters while ensuring essential data is collated;

DAHRRG

Recommendation 1: Set out the programmes intervention logic in detail

CMEF Guidelines state that the intervention logic for the programme should be explicitly stated in the National Strategy Plan. It is important that in designing multi-faceted programmes of the complexity of the RDP, that the intervention logic is clearly stated, and that tensions in such programmes which aim at a number of policy goals should be adequately acknowledged and, where possible, quantified. This will give rise to better, more transparent, decision making, and better overall policy.




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Recommendation 2: Allow all scheme administration requirements to be conducted online

Adequate levels of administration of individual schemes are an important input to ensure compliance with the goals of the RDP, to minimise fraud, to inform evaluations, and to support the development of future policy. Ultimately, adequate administrative checks are necessary to ensure that scarce public money is put to good effect. On the negative side, scheme administration requirements often place a burden on recipients. To minimise this while ensuring that the Management Authority had adequate information on the implementation of the programme, all application systems should be put on-line. This would have the effect of reducing the burden on beneficiaries allow for the development of databases in relation to scheme actions, help improve compliance and reduce the need for compliance checks.

Recommendation 3: The impact of administrative costs should be considered when evaluating new small schemes

Indecon believe that it is important to consider the administration costs in small schemes. However, Indecon accepts that in certain circumstances small targeted schemes to address specific issues or to pilot an innovative approach or project may be appropriate.

Recommendation 4: Improve the indicators to facilitate RDP evaluations

The procedure for tracking indicator data in this evaluation often did not strongly contribute to an understanding of the success or otherwise of the programme. While useful in measuring inputs and activities, indicators intended to measure output, result and impact were of more limited use. In future programmes additional resources should be allocated to ensure the availability of relevant and rigorous indicator data.

9.3.1 Axis 1 Recommendations

Recommendation 5: Address the Structural Issues within Irish Farming

Irish farming has a major structural problem of ageing, which has not yet been adequately addressed. This has a significant impact on the productivity and output and therefore future viability, of farming. This also has potential environmental benefits. There are a number of elements influenced by policy which have a bearing on the decision of a farmer to retire or not. Ultimately, improvements in longevity mean that older farmers are less likely to retire than in the past, so attracting and retaining younger farmers will require the creation of a sufficient farm income to support two households rather than one. This, in turn, will require the diversification of farmers into new on-farm enterprises. Indecon recommends that a focus is retained on addressing the structural problem of age in Irish farming.

Recommendation 6: Ensure Sufficient Finance for Viable Capital Projects

Indecon believes that there is a need for ongoing focus on promoting investments which yield value-for-money in terms of improvements in productivity, competitiveness and adoption of environmental best practice. Meeting the ambitious output figures as contained in Food Harvest 2020 and its successor Food Wise 2025 will require significant increases in on-farm investment, which in turn are likely to require supporting measures through the Rural Development Programme. Indecon recommends that all sources of potential financial support for viable capital investment should be investigated, including use of Financial Instruments.




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9.3.2 Axis 2 Recommendations

Recommendation 7: Maintain targeted payments to farmers in disadvantaged areas

Indecon believes that targeted support to farmers in disadvantaged areas is appropriate in order if the policy is to retain farming levels, given the evidence that the farms covered by LFA payments typically have lower value-added farm systems and lower family farm incomes than in the rest of the country. Further, it should be noted that there is an asymmetry in land abandonment – land, once abandoned, might be very difficult to bring back into agriculture use, while it may also be very difficult to attract young farmers in to so do. However, Indecon recommends that a stricter approach based on scientific criteria relating to land quality be implemented, to better target support at the farm land most at risk of abandonment.

Recommendation 8: Improve measurement of the environmental impacts of supports

The motivation for the agri-environmental schemes is built on the contention that certain restrictions or practices which impose costs on farmers have a significant environmental benefit. Indecon recommends that continued efforts are needed to measure the environmental impacts of funding to ensure that public funds are being appropriately used.

Recommendation 9: Review the level of support for Organic Farming

Ireland may have some comparative advantages in the organic production sector. The level of subsidy available under the Organic Farming Scheme during 2007-2013 was low compared to measures of the difference in production costs compared to conventional farming. Indecon recommends that the rate of support should be reviewed if Ireland is to become a major source of organic food.

9.3.3 Axis 3 & 4 Recommendations

Recommendation 10: Streamline the administration burden on beneficiaries/project promoters

The aim of Axis 3 and 4 of the RDP was to improve the quality of life in rural areas and encouraging diversification of economic activity. The use of the bottom-up approach represents a very useful addition to the broader RDP, by creating a means to communities to develop their own projects. These measures were also important as they were the only part of the RDP which allows for the support of elements of the rural community other than farmers. The future vision of a vibrant rural Ireland will require primary, secondary and tertiary industries, and non-farming projects should continue to be funded through the RDP. Ways to reduce administrative burdens on beneficiaries/project promoters should be considered. There are a number of ways in which these could be applied in the RDP 2014 – 2020. For example, the introduction of a small number of targeted indicator data would reduce administration. In addition we recommend greater use of online systems as standard for meeting administrative requirements. However, Indecon strongly supports ensuring that sufficient information is obtained in order to facilitate evaluation and full regulatory compliance.

Date post:	22-Apr-2020
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