Comparison of farmers' incomes in the EU Member States

DIRECTORATE-GENERAL FOR INTERNAL POLICIES

POLICY DEPARTMENT B: STRUCTURAL AND COHESION POLICIES

AGRICULTURE AND RURAL DEVELOPMENT

COMPARISON OF FARMERS’ INCOMES

IN THE EU MEMBER STATES

STUDY

This document was requested by the European Parliament's Committee on Agriculture and

Rural Development.

AUTHORS

University of London: Professor Berkeley Hill, Emeritus Professor of Policy Analysis

Agra CEAS Consulting: Dr B. Dylan Bradley

RESPONSIBLE ADMINISTRATOR

Albert Massot

Policy Department B: Structural and Cohesion Policies

European Parliament

B-1047 Brussels

E-mail: poldep-cohesi[email protected].eu

EDITORIAL ASSISTANCE

Catherine Morvan

LINGUISTIC VERSIONS

Original: EN

ABOUT THE PUBLISHER

To contact the Policy Department or to subscribe to its monthly newsletter please write to:

poldep-cohesion@europarl.europa.eu

Manuscript completed in June, 2015.

This document is available on the Internet at:

http://www.europarl.europa.eu/studies

DISCLAIMER

The opinions expressed in this document are the sole responsibility of the author and do

not necessarily represent the official position of the European Parliament.

Reproduction and translation for non-commercial purposes are authorized, provided the

source is acknowledged and the publisher is given prior notice and sent a copy.

Acknowledgements: Most of our analysis has made use of public databases. However, the authors gratefully

acknowledge the assistance provided by the DG AGRI EU-FADN unit which provided special analysis where

access to raw data was needed and for the construction of maps. The authors also gratefully acknowledge the

input of Professor Sophia Davidova, University of Kent.

DIRECTORATE-GENERAL FOR INTERNAL POLICIES

POLICY DEPARTMENT B: STRUCTURAL AND COHESION POLICIES

AGRICULTURE AND RURAL DEVELOPMENT

COMPARISON OF FARMERS’ INCOMES

IN THE EU MEMBER STATES

STUDY

Abstract

With the main stated objectives of the CAP in mind, relevant comparisons

that involve the incomes of farmers are made. EU official data sources

are used to describe income differences between holdings of different

sizes and types and between Member States. Comparisons between the

incomes of farmer household and other groups in society have to rely on

ad hoc information. Recommendations relate to the support of small

farms, actions to mitigate instability and to fill the important gap in farm

household income information.

IP/B/AGRI/IC/2014-68 June 2015

PE 540.374 EN

Comparison of farmers’ incomes in the EU Member States

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CONTENTS

LIST OF ABBREVIATIONS 5

LIST OF TABLES 7

LIST OF MAPS 7

LIST OF FIGURES 7

LIST OF BOXES 9

EXECUTIVE SUMMARY 11

1. INTRODUCTION 17

1.1. The economic function of profit from farming 18

1.2. Characteristics of incomes in agriculture 18

1.3. Accounting systems and agricultural incomes 21

1.4. Policy aims and appropriate measures of income 24

2. DATA SOURCES AND METHODOLOGICAL EXPLANATION 29

2.1. Data sources on the incomes of agricultural households 30

2.2. Data sources on the rewards from agricultural production 31

3. OVERVIEW OF THE INCOME DEVELOPMENT OF EU AGRICULTURE 35

3.1. Incomes of farm households 36

3.2. Incomes from agricultural activity 40

4. THE DYNAMICS OF FARM INCOMES AND THE KEY DRIVERS 65

4.1. Farm household income 66

4.2. Income from agricultural activity 67

5. DIFFERENCES BETWEEN MEMBER STATES 83

5.1. Differences in income levels 84

5.2. Differences in direction of change 88

5.3. Comparisons between Member State incomes for each main farm type

(FADN data) 91

5.4. Comparisons between Member States of farms by economic size group 94

5.5. Agricultural wages in Member States 96

6. RECOMMENDATIONS FOR FUTURE INCOME SUPPORT UNDER THE

CAP 101

6.1. The need for reliable statistics on agricultural household incomes 101

6.2. Statistics based on people rather than production 104

6.3. Income stabilisation 105

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

6.4. Support for small farms 108

6.5. Balance between support and market orientation 109

REFERENCES 111

LEGAL REFERENCES 115

ANNEX : Data sources on the rewards from Agricultural production 117

Comparison of farmers’ incomes in the EU Member States

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LIST OF ABBREVIATIONS

ARMS

AWU

Agricultural Resource Management Survey

Agricultural work unit

CAP

Common Agricultural Policy

CMO

Common market organisation

DG AGRI

Directorate-General for Agriculture and Rural Development

EAA

Economic Accounts for Agriculture

ECA

European Court of Auditors

ECU

European Currency Unit

ERS

Economic Research Service (of the United States Department of

Agriculture)

ESA

European System of Accounts

European Union

EU-15

Grouping of Austria, Belgium, Denmark, Finland, France, Germany,

Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain,

Sweden and the UK.

EU-27

Grouping of the EU-15, EU-N10 and EU-N2

EU-28

Grouping of the EU-15, EU-N10, EU-N2 and Croatia

EU-N2

Grouping of Bulgaria and Romania

EU-N10

Grouping of Cyprus, Czech Republic, Estonia, Hungary, Latvia,

Lithuania, Malta, Poland, Slovakia, Slovenia

EU-SILC

European Union Statistics on Income and Living Conditions

FADN

Farm Accountancy Data Network

FAO

Food and Agriculture Organisation of the United Nations

Policy Department B: Structural and Cohesion Policies

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FFI

Farm Family Income

FNVA

Farm Net Value Added

FSS

Farm Structural Survey

FWU

Family Work Unit

GATT

General Agreement on Tariffs and Trade

IAHS

Income of the Agricultural Households Sector

JRC

Joint Reserarch Centre (of the European Commission)

LFA

Less Favoured Area

LKAU

Local Kind of Activity Unit

NVA

Net Value Added

OECD

Organisation for Economic Co-operation and Development

OGA

Other Gainful Activity

SFS

Small Farmers Scheme

SNA

System of National Accounts

Standard Output

TFEU

Treaty on the Functioning of the European Union

United Nations

United Kingdom

US(A)

United States (of America)

Comparison of farmers’ incomes in the EU Member States

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LIST OF TABLES

Table 1:

Economic Accounts for Agriculture: current transactions accounts from 1999 118

Table 2:

FADN field of observation 121

LIST OF MAPS

Map 1:

FNVA in Euro per AWU by FADN region, 2010-2012 average 87

Map 2:

FFI in Euro per FWU by FADN region, 2010-2012 average 88

Map 3:

Average nominal wages paid by FADN region, 2010-12 average 98

LIST OF FIGURES

Figure 1:

The relationship between agricultural activity and the institutional units that generate it 23

Figure 2:

Evolution of index of real income of factors in agricultural activity per annual work unit

(Eurostat Indicator A) and index of real net agricultural entrepreneurial income per

unpaid work unit (Eurostat Indicator B) (2005=100) 41

Figure 3:

Comparison of FADN FNVA/AWU against Eurostat Indicator A and FFI/FWU against

Eurostat Indicator B, EU-25/EU-27 (2007=100, real terms) 42

Figure 4:

Distribution of farm size by farm type in the FADN sample, 2010-2012 average 44

Figure 5:

Indicators of farm income, EU-25 2000-06, EU-27 2007-12, 2004-2012 45

Figure 6:

Evolution of FFI/FWU by EU groupings, 2004-12 46

Figure 7:

Indicators of farm income by farm size, 2010-2012 average 47

Figure 8:

Evolution of FFI/FWU by farm size, 2004-2012 48

Figure 9:

Indicators of farm income by farm type, 2010-2012 average 49

Figure 10:

Evolution of FFI/FWU by farm type, 2004-2012 50

Figure 11:

FFI/FWU by type of farm and size class, 2004-2012 51

Figure 12:

Indicators of farm income by age, EU-27 2010-2012 53

Figure 13:

Indicators of farm income by ownership structure and EU sub-group, 2010-2012 average 54

Figure 14:

Indicators of farm income by Less Favoured Area status, EU-27 2010-2012 55

Figure 15:

Annual year-on-year change in farm income indicators 56

Figure 16:

Coefficient of variation of income indicators by farm size, 2004-2012 57

Figure 17:

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Coefficient of variation by farm type, 2004-2012 57

Figure 18:

Farm level volatility, 1998-2007 58

Figure 19:

Lorenz curve of the distribution of FNVA and FFI, EU-27, 2010-2012 average 59

Figure 20:

Development of the Gini coefficient of FNVA per AWU 60

Figure 21:

Paid labour (

€/hour), 2004

-2012 61

Figure 22:

Paid labour (

€/hour) by farm type, 2010

-2012 average 62

Figure 23:

Annual year-on-year change in paid agricultural wages per hour 63

Figure 24:

Income components per farm by EU group, 2010-12 average 68

Figure 25:

Income components per farm by EU farm type, 2010-12 average 70

Figure 26:

Income components per farm by economic size, 2010-12 average 71

Figure 27:

Change in value of income components 2004-06 average compared to 2010-12 average

by EU sub-group 72

Figure 28:

Change in value of income components 2004-06 average compared to 2010-12 average

by farm type 73

Figure 29:

Evolution of the components of Total Output per farm, EU-25 2004-2006, EU-27 2007-

2012 74

Figure 30:

Evolution of crop and livestock prices, EU-27, 2005 = 100 75

Figure 31:

Evolution of yield per unit of output, EU-25 2004-06, EU-27 2007-12 76

Figure 32:

Evolution of subsidies, EU-25 2004-06, EU-27 2007-12 77

Figure 33:

Evolution of specific crop and livestock costs and total farming overheads, EU-25 2004-

16, EU27 2007-12 78

Figure 34:

Evolution of specific crop and livestock costs per farm, EU-25 2004-06, EU-27 2007-12 79

Figure 35:

Evolution of the elements of total farm overheads, EU-25 2004-06, EU-27 2007-12 80

Figure 36:

Evolution of value of outstanding loans and annual interest per farm, EU-25 2004-2006,

EU-27 2007-2012 81

Figure 37:

Evolution of labour use and wages paid per farm, EU-25 2004-2006, EU-27 2007-2012 82

Figure 38:

FNVA/AWU and FFI/FWU by Member State (2010-2012 average) 85

Figure 39:

FADN coverage of economic farm size (ES) by Member State, 2010-2012 86

Figure 40:

Change in FFI/FWU, average 2010-2012 vs average 2004-2006 89

Figure 41:

Annual change in FFI/FWU, 2010-11 and 2011-12 90

Figure 42:

Coefficient of variation of farm income indicators by Member State, 2004-12 91

Figure 43:

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

FFI/FWU by farm type and Member State, 2010-2012 average, EU-27 = 100 92

Figure 44:

FFI/FWU by Economic Size and Member State, 2010-2012 average, EU-27 = 100 95

Figure 45:

Paid wages per hour (2010-12 average) 97

Figure 46:

Coefficient of variation in paid wages by Member State, 2004-2012 99

Figure 47:

The calculation of Economic Indicators in the FADN 124

LIST OF BOXES

Box 1:

The economic functions of profit 18

Box 2:

The Treaty statement of the objectives of the Common Agricultural Policy 24

Box 3:

CAP aims as articulated in Agenda 2000 (European Commission, 1997) 25

Box 4:

Reasons for non-adoption of household statistics 27

Box 5:

Definition of indicators used in the Economic Accounts for Agriculture 32

Box 6:

Definition of indicators used in the Farm Accountancy Data Network 33

Box 7:

Statements by the Commission on the relative position of incomes in agriculture 37

Box 8:

Pluriactive farm operators in the EU-27 39

Box 9:

Safety net for farm households (based on Gundersen et al., 2000) 103

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

EXECUTIVE SUMMARY

Introduction

The purpose of this study for the European Parliament, as set out in the Terms of

Reference, is to:

 Provide an overview of the income developments of EU agriculture.

 Examine the different dynamics of farming incomes (changes, amplitudes of

movements, stability) and their main drivers.

 Analyse the disparities across Member States and aggregates.

 Provide recommendations in order to adjust the CAP income support and national

policies to counteract current trends.

This purpose has to be achieved within the context of what the Terms of Reference describe

as the central aim of the Common Agricultural Policy ‘to ensure a fair standard of living for

the agricultural community, in particular by increasing the individual earnings of persons

engaged in agriculture’.

The Terms of Reference also make it clear that data sources and methodologies for making

the comparative analysis are the responsibility of the authors of the briefing note. With that

in mind, the chosen staring point is a review of the incomes of agricultural households and

in particular the incomes they receive from independent activity in agriculture (their self-

employment income from farming).

The profit from running a business (which may be called entrepreneurial income) has a

number of economic functions which make it a very important concept in the context of

farmers and agriculture. In particular, it represents both funds generated within the farm

that can be used for consumption, investment and saving and the rewards to the resources

owned by the farmer (including the unpaid labour on the farm).

Profits from agriculture in developed countries such as those of the EU generally suffer from

a long-term downward pressure that help explain structural change and from shorter-term

instability. Furthermore, there are geographical and circumstantial differences between

groups within agriculture.

There are two alternative approaches to measuring entrepreneurial incomes in agriculture:

aggregate accounting as used by the Economic Accounts for Agriculture (EAA) drawn

up by Eurostat and microeconomic accounting as used by the EU’s Farm Accountancy

Data Network (FADN). Both have important limitations, and there are also

methodological differences between them that have relevance for their use in the context of

this brief.

However, profit from agriculture is only part of the income picture for many farm

households and a focus on their returns from agriculture will therefore present only a

partial picture of the farm household’s income, which is a main determinant of the farmer’s

standard of living.

Data sources and methodological explanations

Literature has been drawn on to establish the main types of comparison relevant to this

study. This has been followed by an in-depth analysis of the statistical systems that

generate income data in the EU, and a detailed and independent analysis of what the data

show (presented in Chapters 3 to 5).

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

For statistics on the incomes of agricultural households key definitions for use in the

monitoring and guidance of agricultural policy have been worked out by Eurostat and at

international level by the FAO. The most appropriate indicator is considered to be the net

disposable income of households (covering income from farming and other gainful

activities, from property, pensions and other transfers, and after the deduction of personal

taxes and other non-optional payments). Possible data sources to furnish these statistics

are considered; these vary between Member States.

For income that arises from agricultural activity indicators based on the Economic Accounts

for Agriculture are calculated by Eurostat, but these are only available at the national level.

However, the Farm Accountancy Data Network (FADN) calculates indicators at the level of

the farm business and these can be used to illustrate detailed patterns in the agricultural

industry.

Two FADN indicators are appropriate in the present context. Farm Net Value Added

(FNVA) represents the rewards to all the fixed factors used in the farm business,

irrespective of their ownership. Farm Family Income (FFI) is after the further deduction

of the costs of hired labour, interest paid and rent paid and is the return to the farmer for

the use of his own labour, own land and own capital; it represents the amount generated

by the farm business that is available for consumption, investment and saving.

FFI expressed per business or per work unit of family (unpaid) labour (FFI/FWU) is the

preferred income concept for this analysis because it corresponds most closely to the

concept of the profit from farming that is available to support the living standards of

farmers. Because incomes are subject to much short-term instability, where possible,

averages are taken across three adjacent years; the main study period is 2010-2012.

Overview of the income development of EU agriculture

There is currently no working statistical system at EU level for agricultural household

incomes. Structural statistics for EU agriculture make it clear that many farmers (at least a

third, and more if other members of their household are included) also have other gainful

activities. National results where available show that other incomes not only raise the

household income levels of farm families, but also add to its stability.

Furthermore, the evidence points to farmers NOT being a particularly low-income sector of

society in most Member States judged on the basis of their household disposable incomes.

This is of obvious importance to the CAP’s aim to ensure a fair standard of living of the

agricultural community.

In terms of incomes from agricultural activity, the focus of this report, it is clear that the

income indicators at aggregate level (Eurostat) and farm level (FADN), where they share

similar concepts, tend to move in similar fashion. The two FADN indicators (FNVA/AWU

and FFI/FWU) are also closely aligned in their directions of change over time.

Among the various groups of Member States in common usage, in absolute terms FFI/FWU

is highest in the EU-15, then the EU-N10 and lowest in the EU-N2. FFI/FWU increased over

the 2004 to 2012 period with a substantial decline between 2007 and 2009 in all groupings

with the exception of EU-N2.

For the EU-27, a strong relationship exists between the economic size of farm business and

the average levels of income generated. This applies not only to FFI per farm (as might be

expected) but, more importantly, income per unit of family labour (FFI/FWU). Care has to

be exercised in interpreting results for small farms because only some Member States are

represented because of the application of different thresholds for inclusion in FADN; only

for size classes with Standard Output of

€25

,000 and over are all countries represented.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

That said, in each farming type the smallest farms have the lowest incomes, and absolute

incomes per FWU increase with farm size.

Incomes differ between the various types of farming, granivores having the highest

incomes, and mixed farms the lowest. Granivores also tend to dominate in the largest size

groups.

This relationship between farm size and income levels permeates other differences, such as

between farms of different legal status and age of farmer, with the observed patterns

largely explainable by differences in farm size.

Incomes of farms in Less Favoured Areas were lower than those in non-Less Favoured

Areas, even after including the special payments that the former receive.

It is clear that the variability of income over time in FADN results at the group level is much

greater in the smallest size class of farms, though it should be recalled that this omits data

from many Member States because of the differing size thresholds applied. Beyond that,

variation increases with farm size.

‘Granivore’ and ‘Fieldcrop’ farms have the greatest volatility of income. The most stable

incomes are found in the ‘Horticulture’ and ‘Other permanent crops’ sectors.

When income volatility is measured at the level of the individual farm 55% of large farms

and 38% of small farms experienced income volatility of ±30% from the previous three

year average.

The distribution of income at the farm level is very unequal; 20% of the labour force

generates 78% of the FFI. Furthermore, incomes averaged over three years 2010-2012

were negative for large parts of the farm labour force, suggesting that additional factors,

such as income from other gainful activities, is important in explaining the ability of such

farms to survive.

For the dependent (paid) section of the labour force, agricultural worker income (wages)

increased steadily (in nominal terms) over the 2004-12 period with only the EU-N2 group

experiencing a decline in 2008 and the EU-N10 one in 2009. The pay of agricultural

workers in the EU-N10 converged with that in the EU-15 over the period, but pay in the EU-

N2 did not. Agricultural wages per hour differ across farming type, being highest in the

wine sector and lowest in ‘Other grazing livestock’ and ‘Fieldcrops’ farm types.

The dynamics of farm incomes and the key drivers

For agricultural households with income from other gainful activities, earnings from

property and/or pensions and transfers, the drivers of this non-farm income are largely

those that shape the general economy. Some 12% of EU-27 farms also draw income from

on-farm diversified activities, and these increase with farm scale; this income is also driven

by general economic factors, although some will be related to the agricultural economy.

The most important component of agricultural revenue is returns from the market

which account for 86% of FADN Total Output for the EU-27.

Market returns are driven by quantity of output and price. Yields have been relatively

stable, but prices, especially for crops, have fluctuated considerably over the 2005 to 2012

period.

Subsidies make up the balance of Total Output; there is no suggestion that changes in

subsidies have played a major role in the evolution of income.

Policy Department B: Structural and Cohesion Policies

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The most important cost element is total intermediate consumption which accounts for two-

thirds of total expenses for the EU-27. Depreciation accounts for 15% of total costs, wages

paid 9%, rent 5% and interest payments 3%.

Total intermediate consumption is made up of total specific costs (crop and livestock) and

overheads (machinery and building costs, energy, contract work and direct inputs). These

elements of intermediate consumption have all increased between 2004 and 2012, but

specific crop costs have increased the least. Within specific crop costs, fertiliser cost is the

most volatile element. Within overheads, energy costs have been the most volatile and

showed the sharpest absolute increase.

Although the use of paid labour has declined, wages paid per farm increased steadily

between 2007 and 2012.

The importance of these income components differs by farm type. Subsidies account for

a quarter of the value of total output in ‘Other grazing livestock’ farms, but less than 5% in

the horticulture, granivore and wine sectors. There is less difference in the relative

importance of costs by farm type, although paid wages are more important in the

horticulture and wine sectors.

Analysis by farm size shows that the relative importance of subsidies decreases as farm

size increases.

Differences between Member States

A Common Agricultural Policy does not appear to result in a common absolute level of

income for the average farm in different Member States. Belgium, Denmark, Germany,

France, Luxembourg, the Netherlands and the UK stand out as having high farm incomes.

Amongst the EU-N10 Member States, only in the Czech Republic, Estonia and Hungary do

farm income indicators exceed or come close to the EU-27 average.

The main reason for this is the economic size of farms; the mix of farm types also plays a

role. However, when farms of the same size and type are compared, performance is often

equivalent throughout the EU-28 and sometimes higher in the EU-N10 and EU-N2 than it is

in the EU-15.

The influence of farm structure is also important at the regional level with farm incomes

varying widely within Member States. This regional variation is especially noticeable in

France and Germany.

In terms of the growth in farm incomes between figures averaged for the 2004-06 and

2010-12 periods, EU-N10 Member States have outperformed EU-15 Member States as a

result of higher market prices, access to the single market and increased public support.

The increase in farm income per unit of labour in these Member States also reflects

decreases in total labour use. Despite these increases, farm income in the EU-N10 and

especially the EU-N2 lags behind that in the EU-15.

Within this overall trend, farm incomes are highly variable from year to year, but farm

incomes in different Member States move in different directions and by different

magnitudes, partly the result of structural difference in farm type.

Some Member States have higher levels of income variation than others. Again this is

partly structural with income in the granivore and fieldcrop sectors relatively unstable while

income in horticulture and permanent crops is relatively stable. The relatively low variability

in farm income seen in Greece, Spain and Italy reflects the substantial proportion of other

permanent crop farm types in these Member States.

Comparison of farmers’ incomes in the EU Member States

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There is a tendency for EU-N12 Member States to have higher coefficients of variation than

EU-15 Member States, but this is partly the result of the general upward trend in farm

incomes that these Member States have experienced.

Farm income levels differ between Member States within farm type, although this is partly

the result of the structure of farms within FADN. A key factor in differences between

Member States by farm type is actually farm size within the FADN sample.

As economic size increases, it becomes more common for farms from the EU-N10 to show

higher FFI/FWU than farms in the EU-15. For the largest size group, only farms in Italy and

the UK from the EU-15 have farm income higher than the EU-27 average.

Agricultural wages differ markedly between Member States. In Denmark, the Netherlands

and Sweden wage levels average more than

€15 per hour while in Bulgaria, Greece, Latvia,

Lithuania, Poland and Romania the average is €3 or less.

Agricultural wages vary little within Member States, although there are some exceptions

with wages higher in Champagne than in the rest of France and higher in the east of

Germany where the wages of company farm managers and administrators are included in

the figures.

Recommendations for future income support under the CAP

Based on our analysis the recommendations to the European Parliament are that:

 Further consideration is given to the re-establishment of EU statistics on the

incomes of agricultural households, since they are needed to assess the extent to

which the CAP is achieving this core objective of a fair standard of living.

 Data sources that relate to the entire economic activities of the households (and

other institutional units) that operate farms should be encouraged.

 A study be undertaken to assess the relative attributes of a safety net for the

incomes of farm households for the EU, including its costs, and the necessary

technical conditions that would be required for it to operate successfully.

 When considering the need for support of incomes, the wealth of agricultural

holdings should be taken into account.

 Suitable caveats should be used when FADN data are reported to make clear the

impact of the field of observation on the results.

 Consideration should be given to the need to represent people (the operators of

farm holdings) rather than production. A suitable balance needs to be struck

between the current production/land use focus of FADN and the social impact of the

CAP.

 Attention should be diverted away from interventions that attempt to combat

instability directly at the farm level and towards risk management schemes that

prepare farm operators to better anticipate and cope with instability. This could

involve further studies.

 Consideration should be given as to how the occupiers of small farms can enhance

their economic prospects by building their skills and other forms of human capital.

 We recommend that policies that increase market participation and ease the

adjustment of farm businesses and households should be further supported and that

current impediments to access be examined.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

1. INTRODUCTION

The purpose of this detailed briefing note for the European Parliament, as set out in the

Terms of Reference, is to:

 Provide an overview of the income developments of EU agriculture.

 Examine the different dynamics of farming incomes (changes, amplitudes of

movements, stability) and their main drivers.

 Analyse the disparities across Member States and aggregates.

 Provide recommendations in order to adjust the CAP income support and national

policies to counteract current trends.

This purpose has to be achieved within the context of what the Terms of Reference describe

as the central aim of the Common Agricultural Policy ‘to ensure a fair standard of living for

the agricultural community, in particular by increasing the individual earnings of persons

engaged in agriculture’.

The Terms of Reference also make it clear that data sources and methodologies for making

the comparative analysis are the responsibility of the authors of the briefing note.

KEY FINDINGS

 Entrepreneurial income (less formally called ‘business profit’) has a number of

economic functions which make it a very important concept in the context of

farmers and agriculture.

 Profits from agriculture are generally suffering from long-term downward pressure

and shorter-term instability and there are geographical and circumstantial

differences between groups within agriculture.

 However, profit from agriculture is only part of the income picture for many

farm households and a focus on returns from agriculture will therefore present only

a partial picture of farm household income.

 There are two possible approaches to measuring entrepreneurial incomes in

agriculture: aggregate accounting as used by the Economic Accounts for

Agriculture (EAA), drawn up by Eurostat, and microeconomic accounting as used

by the EU’s Farm Accountancy Data Network (FADN). Both have important

methodological limitations and there are also methodological differences between

them that have relevance for their use. Neither at present is capable of describing

the overall income situations of the households that operate farms, which represents

a major gap in the information needed to assess the performance of the CAP in

relation to its stated objectives.

The evidence on ‘Comparison of Farmers’ Incomes in the EU Member States’ and its

accompanying analysis presented in this Report needs to be put in context. This section

does so by presenting the functions of income (for farmers the essential component of

which is profits from their agricultural activity), the characteristics of incomes in

agriculture, the approaches taken to incomes within accounting systems, and the

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

relationship between policy aims and measurements of income. Further contextual

information is provided in Hill (2012), FAO (2011) and UN (2008).

1.1. The economic function of profit from farming

The large majority of EU farms are arranged as independent units (businesses operated by

households or corporations) and thus farmers receive their rewards from agriculture in the

form of entrepreneurial income, or less formally, business profit. For household firms

entrepreneurial income is a hybrid, in the sense that it is a mix of rewards for the unpaid

labour provided by the family, for using its own land and capital, and for the risk-taking

and management function. Ways in which this income is defined and measured will be

considered later, but at the outset it is worth noting why there is interest for purposes

related to the CAP in observing changes and differences in entrepreneurial incomes

(various forms of comparisons over time and place and circumstance).

In the EU’s modern competitive market economy profit performs important economic

functions as shown in the Box below.

Box 1: The economic functions of profit

 Profit is the reward from production, and is the residual remaining to the operators

of businesses (including farms) once the costs of inputs, wages paid to hired labour,

rent paid to landowners, interest paid on loans and an estimate of depreciation have

been deducted from the value of sales and other forms of revenue. Profit reflects the

risks that the farmer is taking and the use of his/her own factors of production

including labour.

 Profits signal to producers where expansion or contraction of production should take

place as they reflect changes in market prices (driven by changes in demand) and

costs.

 Profits enable the most efficient firms to expand.

 Profits provide the incentive for innovation.

 Profits are therefore key to explaining structural change, although it should be

noted that income from non-agricultural activities is also a factor here.

In addition to its economic functions, the business structure of EU agriculture, with the

numerical dominance of the small family farms

, means that profits from farming form an

important component of the personal incomes of most farmers’ households, though they

often also have other income sources (see below).

1.2. Characteristics of incomes in agriculture

The literature shows that agriculture is characterised by a number of features that have to

be understood if income comparisons over time and place and circumstance are to be

understood.

 The long-term downward pressure on incomes (comparison over time).

Historical evidence shows that agriculture in economically developed countries is

caught in a cost-price squeeze. On the one hand, the prices that farmers receive for

their output is in long-run decline because the supply of farm products has

According to the 2010 Farm Structure Survey there were 12 million farms in the EU-28, 97% of which were

single holder operations.

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expanded faster than the demand for them. Technological advances in production

processes (new varieties of crops, improved livestock, more and better machinery

and fertilisers, etc.), which it is in the interest of the individual farmer to adopt,

have led to greater volumes of production, whereas in contrast factors that affect

demand (such as the size of the market and willingness of people to spend more on

food) have changed much less. The outcome has been a fall in the real value of the

net margin between costs and revenues remaining to the sector as a whole, and

thus a fall in the relative position of average rewards to productive resources (in

particular labour) in agriculture compared with those available in the rest of the

economy. This in turn has led to structural change (such as the migration of labour

out of agriculture, the reduction in numbers of smaller farms and the absorption of

their land by larger ones). This downward pressure on incomes in agriculture is a

result of the basic economics of supply and demand and shows the competitive

market economy performing its normal role in bringing about change.

 Shorter-term income instability (comparisons over time). Superimposed on

the long-term trend are shorter-term movements in income which, mostly, reflect

the market doing its job in better matching shorter-term supply and demand. There

are medium-term diversions from the long-term trend, resulting, for example, from

natural disasters or political events that interrupt supply or demand. There will be

inter-seasonal variations caused by good or poor growing conditions that lead to

temporary over or under-supply. There are also regular seasonal price variations

and random market ones. Thus farmers face an inherently unstable income

situation. Farmers are expected to manage most of these risk factors as part of their

normal operation.

 The heterogeneous nature of agriculture (comparisons over space and

circumstance). Farms differ greatly in terms of the types of production taking

place on them (their farming type), their size (measured in terms of land area or

economic size), the diversity of natural conditions they face (climate, soil, slope,

altitude, etc.), labour force (numbers of workers and composition), and region. Even

within one type/size/region group there will be differences in income brought about

by differences in management ability, the age profile and experiences of farmers,

etc. It is worth noting that the Commission has drawn a distinction between income

disparities, income dispersion, and income distribution (CEC, 1985b). Disparities

refer to the differences in average incomes between groups (such as between

Member States or types of farming); a specific type of disparity which is of

significance to achieving the official aims of the CAP is the relative incomes of

farmers and those of the rest of the EU population. Income dispersion refers to

the deviations of the individual figures within a given group from the average for the

group. Income distribution refers to the breakdown of farmers (and/or other units

of labour) according to income classes. This in-depth analysis deals with all three,

within the constraints of available data.

Observation of the documentation, discussion and practice of policy suggests that farmers

and their households are caught up in income problems that are widespread and

characterise the agriculture industry. These income problems are as follows:

 The particularly low incomes in certain regions or sizes of farm (the poverty issue).

At the same time the occupiers of other farms may have high incomes, so that the

heterogeneity of the income situation presents a problem in describing the (income)

poverty issue in agriculture as a whole and in designing policy to address it.

Policy Department B: Structural and Cohesion Policies

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 The variations of income experienced by the individual farm over time (the

instability issue). Again this may vary between region, type and size of farm.

However, it is readily shown that instability as measured by group averages greatly

understates the degree of instability experienced at the level of the individual farm

business (for a review of this evidence see Hill (2012), Chapter 4). An implication is

that the measurement of income in a single year is unlikely to be a reliable indicator

of the income of a farm over a run of years; empirical evidence suggests that an

average over three years is preferable and this is the approach we take in this

report where possible. While incomes from agricultural activity are inherently

unstable, the presence of other income may dampen the impact on total farm

household income; this appears to be usually the situation. This means that farm

household income is usually more stable than agricultural income.

 The general levels of rewards of those engaged in farming compared with earnings

in other sectors (the parity issue). This is often expressed in terms of the incomes

of people working in agriculture compared with those in other groups in society or

the national average. However, for self-employed farmers these incomes are a mix

of rewards to labour, capital and land and the issue of parity includes the return to

investments in land and capital assets as well as to labour. A major factor in

explaining the apparently low reward to land is that its value is determined in a

market, typically very small in relation to the total stock that is often dominated, on

the demand side, by existing farmers trying to expand to reap the benefits of

spreading fixed costs and technical advances that require larger-scale production.

However, expanding farmers typically bid up land prices to levels that are

determined by their margins over variable costs, not by total costs, and thus land

appears very expensive in relation to average profits.

 Partly as a result of this last point, and because in market economies public support

of farm incomes tends to be capitalised into higher land prices

, income problems

are often seen among farm occupiers that are often also owners of substantial

amounts of wealth. Wealth is even more unequally distributed than are incomes,

and farmers who own land are likely to have a markedly different economic status

from those who are tenants or where land rights are poorly defined. It is worth

noting that the wealth of farm households is usually ignored when discussing the

need for policy intervention to tackle income problems.

The first three of these points are the same trio of central components of ‘the farm

problem’ that have been identified in the United States and summarised by Gardner

(1992).

Parity and poverty are concerned essentially with the welfare of farmers and their

dependants. Instability is somewhat different. A low farm income in a single year may not

immediately throw the recipients into the poverty category. Reserves will be drawn on or

borrowings made to maintain living standards through times of temporary financial

setback. Thus in industrialised countries it is important to distinguish between those farm

households that have to contend with occasional periods of low income and those that

suffer hardship from incomes that are persistently low. However, when year-to-year

fluctuations are anticipated, the level of consumption by farmers and their households may

have to be curtailed in order to set aside reserves for years of low incomes or to pay for

past borrowing in lean years. Farmers may have to be content with generating a safer but

See, for example, European Parliament (2013b); Swinnen, et al. (2008); and the Framework 7 project Factor

Markets, Grant agreement N°: 245123-FP7-KBBE-2009-3 http://www.factormarkets.eu/content/rural-land-

market

Comparison of farmers’ incomes in the EU Member States

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lower income, with consequences both for consumption possibilities and the potential for

the business to grow.

A further characteristic of agriculture in the EU that must be borne in mind is the business

structure of farms. As noted above, the large majority of EU farms, in terms of numbers,

are arranged as unincorporated businesses that are operated by households (the relevance

of this for income accounting is covered below). In EU structural statistics these are

returned as farms operated by ‘natural persons’, in contrast with farms arranged as

companies or similar forms which have their own legal status (‘legal persons’). In practice

this means that:

 On farms operated by households no clear distinction can be drawn between the

business income and assets of the farm and the personal income and wealth of the

farmer and his immediate household. This is of importance when assessing the sums

that are available to support the living standards of the farm household.

 Because many farm households have additional sources beyond what they receive

from farming, the income obtained from farming activity is not a reliable guide to

the total or disposable income of the household, usually taken as an important

determinant of potential consumption spending and thus of the standard of living of

the household.

 Because in international accounting systems households are seen as being engaged

in both consumption and (as in agriculture) production activities, great care has to

be taken not to confuse and misuse indicators of one function for the other. As will

be seen below, in reality indicators of the rewards from farm production have often

been used as proxies for household disposable income, leading to importance

misunderstandings of the need for and effectiveness of spending under the

CAP.

1.3. Accounting systems and agricultural incomes

Accounting systems allow for the possibility of basing the measurement of incomes on

institutional units (e.g. family farms) or activities (e.g. agricultural production). Within this

structure, each approach can be taken at the level of the aggregate (industry/sector) or of

the individual unit (farm or household). Within the EU’s statistical system aggregate

accounting is represented by the Economic Accounts for Agriculture (EAA) (based in

national accounts) which are drawn up by Eurostat for the EU and Member States.

Microeconomic accounting, built up from individual units, is used to produce the EU’s

Farm Accountancy Data Network (EU-FADN) and household accounts, such as in the

EU Statistics on Income and Living Conditions (EU-SILC). For historic reasons,

accounting systems and income measurement in agriculture have been based on farming

activities and not the more appropriate farm household unit (when measuring incomes that

relate to the standards of living). This has resulted in misunderstandings and potentially

inappropriate policies.

The UN’s System of National Accounts (SNA) is probably the most universally accepted

set of international accounting conventions and is the basis of the European System of

Accounts (ESA). With roots going back some fifty years, the SNA has formed the basis of

much of the economic statistics that already exist for agriculture in countries at all levels of

economic development. The SNA, though aggregate in nature, also commonly acts as a

benchmark for micro-economic accounting.

Policy Department B: Structural and Cohesion Policies

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Two main approaches towards accounting for agriculture can be found within the SNA

accounting framework:

 accounts for the activity of producing commodities (goods and services) deemed

to be agricultural according to agreed international classification, together with their

residual ‘income’ concepts;

 accounts for institutional units that engage in agricultural production; these

form three main types:

 households, in their role as units of production (household-firms), and for

which agricultural activity is one (possibly the only) form of independent activity

(self-employment) that the household members engage in. The household may

also engage in dependent activity (its members work as employees) and may

also receive resources in other ways (for example, from welfare transfers,

property income, etc.). The independent agricultural activity may account for

various shares of the total resources available to the household;

 corporations, at least part of whose activity involves agricultural production;

and,

 other types (including government and Non-Profit Institutions).

Of course, as these are part of a single system, they relate to each other (see Hill, 2003).

Figure 1 illustrates this relationship in an agricultural context. It shows that agricultural

activity is divided between the various types of institutional units that are involved

in entrepreneurial activity.

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Figure 1: The relationship between agricultural activity and the institutional units

that generate it

REAL INSTITUTIONAL UNITS

Mixed income

(Operating

surplus of

agricultural Local

Kind of Activity

Units (LKAUs)

HOUSEHOLDS-AGRICULTURAL

OTHER

HOUSEHOLDS

CORPORATIONS

OTHER

Entrepreneurial income from

agricultural

activity

Other income

from independent

and dependent

activity transfers

etc.

Other

Kitchen

gardens

Source: Hill (2003).

Activity accounts which cover the value of production of agricultural commodities and the

associated costs can only, strictly, be taken to the level of Operating Surplus (value

added minus the cost of paid labour). To go further to estimate Entrepreneurial Income by

the further deduction of interest and rent payments means attributing these to specific

activities. This requires assumptions about the extent to which the farm household is

involved in other (non-agricultural) activities and how these payments should be allocated.

For example, the extent to which any of the interest payment relate to non-farming

activities or consumption goods. However, such assumptions are often made by the array

of indicators commonly in use. Both aggregate income indicators developed by Eurostat

from the EAA and microeconomic indicators within FADN make such assumptions.

The nature of what constitutes an agricultural household (or an agricultural corporation)

is critical to the generation of statistics and can affect both the numbers of households and

the income levels and compositions relating to them. The concept of a household (which

may take a variety of forms) and the basis used to classify them as agricultural or non-

agricultural (for which several possibilities exist) is discussed in Chapter 3.1.

Also used in Hill and Platt (2003) and FAO (2011). An agricultural Local Kind of Activity Unit (LKAU) is the

fictional basic statistical unit concerned with agricultural production and for which accounting for output,

intermediate consumption, etc. is possible. It may form part of an institutional unit (such as a farm business

operated by a household), but does not include any non-agricultural activities in which the farm may engage

other than those that are inseparable in the data sources (such as minor farm-gate sales). See Eurostat

(2000).

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1.4. Policy aims and appropriate measures of income

A major issue that has to be confronted when reviewing the information on incomes in EU

agriculture is that there is a mismatch between the declared aims of the CAP and the

indicators that are available to monitor the policy’s performance. As will become clear, in

reality accounts drawn up on the basis of institutions (such as farm households) are

relatively poorly developed, whether at sector or microeconomic levels. In contrast,

accounts for the activity of agricultural production are well established at both levels

and the indicators are in common use.

One source of the aims of policy is what appears in official statements. On the one hand,

the Treaty is clear that a central concern is with the living standards of the agricultural

community, though Hill (2012) points out that this rather general objective has not been

articulated in a more precise and testable form. First seen in the 1957 Treaty of Rome

(Article 39), the wording has been carried forward into subsequent Treaties, including the

2012 Consolidated Version of the Treaty on the Functioning of the European Union (Official

Journal of the European Union, C326, 26 October, 2012). The implication is that the 1957

wording has been the basis of giving legal validity to any proposed policy measures since

the start of the CAP and continues to do so.

Box 2: The Treaty statement of the objectives of the Common Agricultural Policy

The Treaty states that ‘The common agricultural policy shall have as its objectives:

a) To increase agricultural productivity by promoting technical progress and by

ensuring the rational development of agricultural production and the optimum

utilisation of the factors of production, in particular labour.

b) Thus to ensure a fair standard of living for the agricultural community, in

particular by the increasing of the individual earnings of persons engaged

in agriculture [emphasis added].

c) To stabilise markets.

d) To assure the availability of supplies.

e) To ensure that supplies reach consumers at reasonable prices.’

The Agenda 2000 agreement, though lacking the full authority of a Treaty, also

articulated the CAP’s aims, carrying over the ‘fair standard of living’ phrase but also adding

an assurance of promoting income stability and of expanding on how farmers might be

assisted by providing alternative sources of livelihood.

Official Journal of the European Union, C326/47, Article 39, pp62-63.

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Box 3: CAP aims as articulated in Agenda 2000 (European Commission, 1997)

 [To] 'increase competitiveness internally and externally in order to ensure that

Union producers take full advantage of positive world market developments.

 Food safety and food quality, which are both fundamental obligations towards

consumers.

 Ensuring a fair standard of living for the agricultural community and contributing

to the stability of farm incomes [emphasis added].

 The integration of environmental goals into the CAP.

 Promotion of sustainable agriculture.

 The creation of alternative job and income opportunities for farmers and

their families [emphasis added].

 Simplification of Union legislation'.

 To ensure that supplies reach consumers at reasonable prices.’

Another indication of the persistence of the CAP aim of ‘ensuring a fair standard of living of

the agricultural community’ is that these words are incorporated into the Regulations that

give the legal basis for spending on agriculture from the EU budget. For example,

Regulation (EC) No 1308/2013 establishing a common organisation of the markets in

agricultural products uses these same words, following a convention demonstrated in the

superseded legislation. When referring to support of particular commodities, the aim of

ensuring the living standards of growers concerned is also mentioned. The apparent

requirement for this aim to be stated in Regulations, linking back to the fundamental

Treaties, should be noted, even if what the phrase means is far from transparent.

The need for income information relevant to the standard of living of farmers, as a major

component of the agricultural community however defined, is supported by a number of EU

and other international organisations. It was the basis of Eurostat’s establishment of its

Income of the Agricultural Households Sector (IAHS) statistics in the late 1980s (see

Eurostat 1996, 2002), was commented on by the European Court of Auditors as something

that the Commission should monitor

(ECA, 2004), was the subject of studies and a policy

brief by the OECD (OECD 2002, 2003, 2004), and was the driver for the drafting of a

Handbook covering statistics on agricultural households (in two editions, UNECE 2007 and

FAO 2011) under the auspices of the UNECE, FAO, OECD, the World Bank and Eurostat.

Agra CEAS Consulting (2007) investigated the feasibility of reintroducing a rebased IAHS

for Eurostat, although this has not been acted upon. There are many other commentators

and researchers who also interpret the income situation of farmer households as at the

centre of the purpose of the CAP (reviewed in Hill 2012).

Given that there would appear to be an obvious need to know about the standard of living

of the agricultural community for policy purposes, statisticians are faced with the task of

turning the concepts of ‘standard of living’ and ‘agricultural community’ into operational

entities (indicators) before the process of actual measurement by data collection can take

place. Indicators should be closely aligned with the policy impact that is required and be

sensitive to the extent of that impact. When attempting to devise practical indicators for

the standard of living it is conventional to use disposable income of the household or the

average per household member, as this represents their potential command over the

consumption of goods and services, though it has to be acknowledged that some factors

which may be important to farm families (such as their independence and work

The ECA (2004) noted that ‘Although this is only one of the five objectives of agricultural policy expressly stated

in the EC Treaty, the income of the agricultural community runs like a leitmotif through the CAP’.

Policy Department B: Structural and Cohesion Policies

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environment) are not captured. Farm families are typically asset-rich, and there are ways

in which the wealth of farm households can be taken into account; wealth itself provides a

potential command over goods and services, and estimates of ‘economic status’ combine

current income with an annuitized value of net worth, though this indicator has not so far

taken a significant part in EU agricultural statistics.

The agricultural community is similarly a concept that has to be made operational.

Again, alternatives approaches are possible (see Hill, 1990). The consensus is that (a) this

is made up of households, rather than individuals; (b) it is made up of the households

where income from independent activity in agriculture (that is, entrepreneurial income) is

part of the household’s total income, though various criteria can be used to, for example,

separate those households where farming is the main source of income from those where it

is a minor part. It should be noted that hired workers on farms are not treated as part of

the agricultural community according to this approach as their incomes are not residual

profits; this is not considered satisfactory in some countries where agriculture is dominated

by large corporate (and similar) units, and even where farms in other countries are

arranged as private companies; to answer such problems Eurostat proposed a series of

‘add-ons’ to the strict coverage.

As has been noted above, despite the apparent need for income statistics to be available

that relate to agricultural households and to agricultural activity, in practice there is no

working system for agricultural household income statistics in the EU. Eurostat’s

IAHS statistics, which was a pioneer in this area when it started in the late 1980s, was

terminated in 2002 for reasons that included problems with quality (especially in Member

States using national accounting methodology), lack of comparability across Member

States, low priority given to developing these statistics at a time of declining resources,

and, in some administrations, concerns with the results that showed farmers as a group to

have household incomes broadly comparable with the rest of society (with some

exceptions). Instead, indicators taken from activity accounts are dominant, though they are

incapable of answering central questions on the income of agricultural households that are

crucial to illuminating the living standards of farmers.

UNECE 2007 offers some suggestions as to why (taken from Hill, 2000), which can be

adapted to the present circumstances (see Box 4).

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Box 4: Reasons for non-adoption of household statistics

Lack of political demand. Politicians have not requested this information, perhaps

because of a too-simple perception of the agricultural industry, or a fear of the electoral

consequences of drawing attention to results that suggest that farmers are in a

relatively favourable income position.

Historical precedent. Activity accounts, at both aggregate and farm levels, and their

related “income” indicators are long-established, having been set up when there were

stronger grounds for assuming that the only source of incomes of farm households was

from farming. In the EU, the EAA adopted the ‘Branch’ concept at its outset in 1964; as

did the FADN basic legislation of 1965.

Operational requirement. The fact is that the CAP has operated apparently

successfully for many years in many countries without information on the incomes of

agricultural households. The administration of income support systems has rarely if ever

required the data (though some tests of eligibility have been applied within individual

structural schemes).

‘Rational ignorance’ among many users. There is a tendency among users,

especially non-specialists, to adopt satisficing behaviour. That is, they take the first

available indicator that appears to meet their needs, so that measure of the income

from agricultural activity may be assumed to show the income of farmers. Among some

users there may be a suspicion that the information revealed by household-firm data

could be against their political and/or bureaucratic interests.

Self-interest of bureaucracies. Government departments for agriculture have often

taken a pro-farmer stance and might therefore not wish to draw attention to anything

that might lead to a reduction in support for the industry, as might be revealed by

statistics on household income. There is also an understandable aim of wishing to

maintain continuity with long-established systems of activity accounting.

Data availability. Lack of basic data of suitable quality in some countries is a major

constraint in the development of statistics on the complete activities of farm businesses

and their households. In countries where it has not been conventional to ask questions

on non-farm income, agencies that collect data have been reluctant to ask new

questions about non-farm income for fear of harming response rates.

The importance of knowing about the income situation of farm households does not remove

the importance of knowing what is happening to the rewards from the activity of

agricultural production. For example, these would be helpful in understanding changes in

the supply of farm commodities, in explaining why farmers diversify and take steps to

reduce risk, and why structural change occurs in the industry. The indicators of the rewards

from agricultural production, though superficially more agreed upon among statisticians in

EU Member States than those relating to agricultural households, in fact are based on

concepts that are by no means self-evident. Principle among these are the following:

 In both the aggregate Economic Accounts for Agriculture and microeconomic FADN

the basic unit is not the complete farm business. Rather it is only the

agricultural activities taking place on farms and excludes (with small exceptions) any

other gainful activities in which the farm may engage. This may involve

misattribution of the costs of inputs where these are used by both the agricultural

and other activities (such as energy usage). These other activities (which may take

Policy Department B: Structural and Cohesion Policies

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place on or off the farm) may well be important in explaining the overall

performance and viability of the farm business as an economic unit

 The main indicator at both levels (Net Value Added per Annual Work Unit, in

absolute or index form), though usually labelled as income, is a concept distinctly

different from that of business profit and even further from personal or household

income. It represents the reward to all the ‘fixed’ factors of production (all the land

and all the capital irrespective of whether or not owned by the farm operator, and all

the labour whether hired or part of the farmer’s family). When looking at changes

over time the practice of dividing the NVA factor reward by the size of the factor

base has some logic, but taking account of changes in only one fixed factor (labour)

can be objected to on both theoretical grounds (such as attributing any productivity

gains to labour whereas increases in capital may be partly responsible) and practical

ones (at least in some countries statisticians have reservations about the quality of

data on labour input where most of this consists of the contribution of the self-

employed farmer and spouse) (Hill, 1991).

 While the EAA Entrepreneurial Income and FADN Family Farm Income

(both of

which involve removing the costs of paid labour, paid interest and paid rent) are

reasonable approximations of profit from agricultural production, indicators that go

further and attempt to remove costs for the farmer’s owned land, owned capital and

family (unpaid) labour, singly or together, are on weak ground because of the

difficulty of agreeing on imputed values. This was proposed by the Commission

(CEC, 1982) but soon abandoned. Nevertheless, attempts to use the same dubious

process have been repeatedly made, most recently in 2014

This problem has been behind suggestions that agricultural income statistics at both macroeconomic and

microeconomic levels should be re-engineered and based on real institutional units (in effect, households and

companies). While this would represent a hiatus in agricultural statistics, it would place agriculture on a similar

footing as other industries.

The term Farm Net Income (FNI) is used for farms that are arranged as legal entities (such as companies)

within FADN.

In EU farm economics overview (European Commission, 2014a) two indicators involving imputation are used.

The concept of ‘Remuneration of family labour’ involves imputing a charge for owned capital and land. The

concept of ‘Return on assets’ involves imputing a cost for family (unpaid) labour.

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2. DATA SOURCES AND METHODOLOGICAL

EXPLANATION

KEY FINDINGS

 For statistics on the incomes of agricultural households key definitions for use in

the monitoring and guidance of agricultural policy have been worked out by Eurostat

and at international level by the FAO. The most appropriate indicator is considered

to be the net disposable income of households (covering income from farming

and other gainful activities, from property, pensions and other transfers, and after

the deduction of personal taxes and other non-optional payments). Possible data

sources to furnish these statistics are considered; these vary between Member

States.

 For income that arises from agricultural activity the Economic Accounts for

Agriculture calculated by Eurostat are only available at the national level. However,

the Farm Accountancy Data Network (FADN) calculates indicators at the level of the

farm business and can be used to illustrate detailed patterns in the agricultural

industry.

 Two indicators are appropriate in the present context. Farm Net Value Added

(FNVA) represents the rewards to all the fixed factors used in the farm business,

irrespective of their ownership. Farm Family Income (FFI) is after the deduction of

the costs of hired labour, interest paid and rent paid and is the return to the farmer

for the use of his own labour, own land and own capital.

 FFI expressed per business or per work unit of family (unpaid) labour (FFI/FWU) is

the preferred income concept for this analysis because it corresponds most closely

to the concept of the profit from farming that is available to support the living

standards of farmers.

The evidence on the comparisons required in this report has comprised three main

components. First there was a literature review to establish the nature of the comparisons

of incomes that can be expected to be of concern to policy makers (which will include those

that have featured in regular and occasional reports by the services of the European

Commission). This has been followed by an in-depth analysis of the methodology used by

the statistical systems that generate data about EU agriculture (especially those of the

Commission). Thirdly, and potentially of greatest concern to the European Parliament,

there has been a fresh and independent analysis of the data on the incomes from farming

in the EU and a presentation of results with a commentary on the findings. This means

that, with a few exceptions, our results are not dependent on what is found in

existing publications from the European Commission.

In the light of the objectives of the CAP that appear in the Treaty on the Functioning of the

European Union (TFEU, 2012), attention is given first to data on the incomes of

agricultural households before moving to the rewards from agricultural activity.

Data are not the same as information; information implies the analysis and interpretation

of data in the context of some problem. However, data form an integral part of the

information required for agricultural policy directed at achieving the objects set. As has

already been noted, a major aim of the CAP is directed at the living standards of the

agricultural community, though there are reasons why there is also interest in the levels of

production of agricultural commodities and the way in which these are changing.

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2.1. Data sources on the incomes of agricultural households

As explained above, there is currently no EU statistical system that is capable of

providing information on the living standards of the agricultural community, either

directly or through the conventional proxy of the disposable income of agricultural

households. Despite this, a substantial amount of national information exists, much of

which is relevant to understanding the income problems faced by farmers and their

responses to policy interventions. Data come from three main types of source, each of

which has drawbacks:

 National surveys of farm accounts that contribute to FADN (see below) where

these collect information beyond the narrow requirements of FADN and extend to

questions relating to the household (such as income from other gainful activities

and from property and social transfers). However, in many Member States such

surveys do not collect this sort of data.

 Taxation and administration records where persons that are members of

agricultural households can be distinguished from those in other socio-professional

groups. Problems with this source are that, in many Member States, some or all

farmers are not taxed according to their personal incomes as shown in accounts

but by various flat rate systems (per hectare, etc.). Operators of farms arranged

as companies may escape coverage (as their directors may not have income from

self-employment in agriculture).

 National surveys of households. There are EU-wide networks of household

surveys of expenditure and income and the EU Statistics on Incomes and Living

Conditions (EU-SILC); each of these is capable of providing data on the household

incomes of agricultural households. The main limitations for both are the small

number of cases of farmer households (sometimes very small) that are found

within these surveys at national level and, for countries where numbers are

adequate, issues over the quality of the income data relating to self-employment.

Sometimes these sources are used in combination (for example, France which periodically

combines FADN and tax records, and Ireland which uses farm accounts surveys in

association with its household survey). The situation in each EU-27 Member State is

described in detail in Hill (2012), Chapter 5 and in the online edition of the Wye Group

Handbook

Though within a single data source the income of agricultural households will generally be

assessed in a consistent way compared with those of other households, care has to be

taken in interpreting results for consistency between sources and between Member

States in three key methodological issues:

 Definition of a household. The main alternatives are the single dwelling unit

(individuals under the same roof) and the single budgetary unit (individuals

sharing income and consumption expenditure). Households containing several

generations or siblings are thought to be more common among farmers than

among the general population in some Member States, and these do not

necessarily pool income and expenditure, so a single dwelling may contain several

financially independent budgetary units. Also, it is important to record the number

of individuals in the household and their ages, since income per person and per

http://www.fao.org/economic/ess/ess-capacity/wyegroup/wyehandbook/en/

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

adult-equivalent (or per consumer unit) is more relevant to potential consumption

expenditure (and hence standards of living) than income of the entire household.

Equivalence scales are used to calculate the number of consumer units.

 Definition of an agricultural household. Classification can be on the basis of

income from farming, labour input to farming, or occupation of a farm. The

Eurostat preferred ‘narrow’ definition for its IAHS statistics was where the main

source of income of the head of household (reference person) was from self-

employment in farming (independent activity in agriculture), though some

countries apply this to the composition of the entire household income. Others

have applied a definition based on the main occupation of the reference person,

which can generate rather different numbers of households and income levels.

Both approaches allow a complete and consistent breakdown of households into

socio-professional groups. A Eurostat ‘broad’ definition was to include all

households where any member of the household had some income from self-

employment in agriculture, which produces coverage close to that of all farm

occupiers. Such broad approaches include many households for which agriculture is

a very minor component of household income

 Definition of income. There are relatively few contentious issues in the definition

of household income. Total income conventionally includes income from self-

employment, from employment, property and social transfers (including pensions);

capital gains on property (which may be important to farmers in the long-run) are

not included. Disposable income is after the deduction of direct taxes and other

compulsory contributions (such as to social security schemes). FAO 2011 sets out a

definition, based on the recommendations of the Canberra Group (2001), but

slightly adapted to suit farming, that was agreed by contributing international

institutions. There remains the issue of whether income in kind provided by the

farm (such as the ability to acquire fuel for the farmhouse and food produced

directly – things that in part determine consumption possibilities) are adequately

treated within the income computation, which suggests that changes over time are

probably more robust than comparisons of disposable income with other socio-

professional groups, such as wage-earners where the role of the household as a

producer (as well as a consumer) is absent or less prominent (such issues are dealt

with extensively in Hill 2012, Chapter 3).

2.2. Data sources on the rewards from agricultural production

Two separate but related systems currently exist by which the rewards from agricultural

production are measured and monitored – the aggregate accounts for agriculture produced

by Eurostat using information supplied by statistical authorities in the Member States, and

the microeconomic approach of the Farm Accountancy Data Network (FADN) supervised by

the European Commission (DG AGRI) that gathers information from the accounts of

individual farm businesses. Each level produces an array of indicators, commonly described

as ‘income’ indicators, but in reality relating to the rewards to the owners of factors of

production used in agricultural activity. Both are described in Annex 1. The key points of

relevance to this study are set out in the sub-sections below.

In the USA a farm is defined as any place from which $1,000 or more of agricultural products were produced

and sold, or normally would have been sold, during the year. Thus statistics on farm household income has a

wide coverage of farms where agriculture is not the main income source of the operator.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

2.2.1. Economic Accounts for Agriculture (EAA) and its indicators

The EAA methodology involves three current transactional accounts which when linked

together produce net entrepreneurial income for all agricultural production as shown in the

Box below.

Box 5: Definition of indicators used in the Economic Accounts for Agriculture

Output, minus intermediate consumption, minus consumption of fixed capital = Net

Value Added

Net Value Added, minus compensation of employees, minus other taxes on

production, plus other subsidies on production, minus interest paid, minus rent paid =

Net Entrepreneurial Income

Based on these aggregates, three indicators are derived.

Indicator A: Index of the real income of factors in agriculture per annual work

unit. This is calculated by taking the Net Value Added at basic prices that appears in

the Production account and adjusting it by adding ‘other subsidies on production’ (which

includes direct payments to farmers) and deducting ‘other taxes on production’, dividing

by the labour input, and expressing in deflated and index form. NVA in this form is

referred to as being at Factor Cost.

Indicator B: Index of real net agricultural Entrepreneurial Income per unpaid

annual work unit. This is appropriate for countries where agriculture is organised

almost totally as unincorporated holdings (family farms).

Indicator C: Net Entrepreneurial Income of agriculture. This aggregate is given in

absolute terms, but may also be expressed in index form. The important point is that it

is not calculated per unit of non-hired labour and so is suitable for uses involving

countries where the output from corporate farms is an important part of the total.

It is clear that the approach embodied in each of the present Indicators is essentially one of

trying to gauge the rewards to a hybrid bundle of factors used in the production of

agricultural commodities. NVA at Factor Cost is a long way from the personal incomes of

the agricultural community (unless there is no borrowing, no renting of land, no hired

labour and no other sources of income to the household). While Entrepreneurial Income

coincides broadly with what might be seen as profit, it only relates to that originating from

agricultural activity and excludes that which might come from other activities carried on

within the farm business, unless these are very minor.

2.2.2. Farm Accountancy Data Network (FADN) and indicators

At EU level, the farm accounts surveys of all the Member States are brought together under

the co-ordination of the Commission’s Directorate-General for Agriculture and Rural

Development (DG AGRI) as the Farm Accountancy Data Network (FADN). This was

established in 1965 ‘with the specific objective of obtaining data enabling income changes

in the various classes of agricultural holding to be properly monitored’ (Commission, 1982).

The justification for FADN was rooted in policy, in that ‘...the development of the Common

Agricultural Policy requires that there should be available objective and relevant

information on incomes in the various categories of agricultural holdings and on the

business operation of holdings coming within categories which call for special attention at

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Community level’ (EEC Regulation 79/65). The FADN is therefore not a single survey but is

an amalgamation of national surveys carried out by Member States.

There is a minimum size threshold, set to capture ‘commercial farms’ that varies between

Member States, reflecting their different farm size structures as shown in the periodic EU

Farm Structure Survey. Consequently, while the overwhelming majority of farming activity

falls within the FADN field of observation, only 42% of the EU’s agricultural holdings found

in its farm structure survey are represented (2015). Figures vary widely between countries.

For example, in Slovakia only 17% of farms are covered by FADN, but these represent 96%

of the economic activity, whereas in Ireland 75% of the farms are covered, with 98% of the

activity. Though numerically important, holdings below the FADN size thresholds contribute

very little in terms of agricultural activity. In many Member States, especially more recent

additions to the Union, it is likely that the coverage of holdings within FADN is even lower

because some farms are small that they fall below the size for qualification for inclusion in

the Structure Survey. Altogether the FADN sample consists of just under 87,000 holdings

(2014), corresponding to about 1.7% of all holdings within the FADN’s field of observation.

FADN’s main income measures are Farm Net Value Added, expressed per farm or per

Annual Work Unit (FNVA/AWU) (that is, per full-time person equivalents working on the

farm) and Family Farm Income (FFI), per farm or per Family Work Unit (FFI/FWU). These

are calculated as follows:

Box 6: Definition of indicators used in the Farm Accountancy Data Network

Total Output, plus balance current subsidies and taxes, minus intermediate

consumption, minus depreciation = Farm Net Value Added (FNVA)

Farm Net Value Added, plus balance subsidies and taxes on investment, minus wages

paid, minus rent paid, minus interest paid = Farm Net Income (FNI) or Family Farm

Income (FFI) (depending on organisational structure)

FFI is often expressed per annual work unit of unpaid (family) labour (FFI/FWU), including

the farmer, in order to reflect the varying amounts of such labour used. As long as its

definition is borne in mind, FFI is a very useful measure on two counts: first, it represents

what would generally be accepted as being income derived from farming; and, second, by

excluding the hired labour force, it covers only those people whose welfare the CAP is in

practice primarily aimed – farmers and their families.

FFI is conceptually close to Eurostat’s Entrepreneurial Income and, when expressed per

unit of family labour input, to Indicator B.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

3. OVERVIEW OF THE INCOME DEVELOPMENT OF EU

AGRICULTURE

KEY FINDINGS

 It is important to be aware that farm families cannot be assumed to depend on their

incomes from farming, and that other incomes not only raise their household income

levels but also add to its stability.

 The evidence points to farmers NOT being a particularly low-income sector of

society in most Member States judged on the basis of their household disposable

incomes. This is of obvious importance to the CAP’s aim to ensure a fair standard of

living of the agricultural community.

 In terms of incomes from agricultural activity, the focus of this report, it is clear that

the income indicators at aggregate level (Eurostat) and farm level (FADN) move in

similar fashion. The two FADN indicators (FNVA/AWU and FFI/FWU) are also

closely aligned in their directions of change over time.

 Among the various groups of Member States in common usage, in absolute terms

FFI/FWU is highest in the EU-15, then the EU-N10 and lowest in the EU-N2.

FFI/FWU increased over the 2004 to 2012 period with a substantial decline between

2007 and 2009 in all groupings with the exception of EU-N2.

 For the EU-27, a strong relationship exists between the economic size of farm

business and the average levels of income generated. This applies not only to FFI

per farm (as might be expected) but, more importantly, income per unit of family

labour (FFI/FWU). This relationship permeates other differences, such as between

farms of different legal status and age of farmer, with the observed patterns largely

being explained by differences in farm size. In each farming type the smallest farms

have the lowest incomes and absolute incomes increase with farm size. Incomes

differ between the various types of farming, granivores having the highest incomes,

and mixed farms the least.

 Incomes of farms in Less Favoured Areas (LFA) were lower than those in non-Less

Favoured Areas, even after including the special payments that the former receive.

 It is clear that the variability of income over time in FADN results at the group

level is much greater in the smallest size class of farms, though it should be recalled

that this omits data from many Member States because of the differing size

thresholds applied. Beyond that, variation increases with farm size.

 ‘Granivore’ and ‘Fieldcrop’ farms have the greatest volatility of income. The most

stable incomes are found in the ‘Horticulture’ and ‘Other permanent crops’ sectors.

 When income volatility is measured at the level of the individual farm 55% of

large farms and 38% of small farms experienced income volatility of ±30% from the

previous three year average.

 The distribution of income at the farm level is very unequal; 20% of the labour

force generates 78% of the FFI. Furthermore, incomes averaged over three years

2010-2012 were negative for large parts of the farm labour force, suggesting that

additional factors, such as income from other gainful activities (OGA), is important

in explaining the ability of such farms to survive.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

 Agricultural worker income (wages) increased steadily (in nominal terms) over

the 2004-2012 period with only the EU-N2 group experiencing a decline in 2008 and

the EU-N10 one in 2009.

 The pay of agricultural workers in the EU-N10 converged with that in the EU-15

over the period, but pay in the EU-N2 did not.

 Agricultural wages per hour differ across farming type, being highest in the wine

sector and lowest in ‘Other grazing livestock’ and ‘Fieldcrops’ farm types.

3.1. Incomes of farm households

A comparison that is key to monitoring the extent to which the CAP has achieved its stated

objectives, as shown in the Treaty (TFEU) is that between the disposable incomes of

household of farmers and the households of the rest of society; this is pertinent to the ‘fair

standard of living for the agricultural community’ aim (section 1.4 – Box 2). Closely allied

to this is the proportions of farmers and other social groups that have incomes that place

them in poverty; a satisfactory group average income can nevertheless hide considerable

numbers of households whose standards of living can be taken as being less than ‘fair’.

Though the targeted agricultural community might be considered as somewhat broader

than the households of self-employed farmers, especially in some of the new Member

States, it is clear that households headed by farmers (or at least having a farmer as a

member) form the dominant sector in terms of numbers

. Furthermore, the CAP uses

intervention tools that almost exclusively impact on the entrepreneurial incomes of such

farmers; the ‘fairness’ of the wages of farm employees (dependent workers) are not an

issue addressed directly by the CAP, being left to national legislation such as minimum

wage levels and social policies on poverty alleviation.

The European Commission has, on a number of occasions, asserted that incomes in

agriculture compare unfavourable with those in the rest of the economy (see for example,

European Commission, 2010a; 2010b; 2010c; and 2009 and Box 7). Disparities of the

order of 40% are mentioned which, if taken at face value, might give cause for concern as

being unfair and the basis of continuing support to EU agriculture. However, the basis of

this claim is not information on the incomes of farm households, though this impression

may be given. Rather, it comes from estimates of the rewards to factors engaged in

agricultural production compared with those in the broader economy (indicators from the

activity approach to income accounting). Objections can be made to comparing the incomes

of self-employed farmers (their entrepreneurial rewards from the factors they use in

agricultural production) with labour earnings in the economy as a whole, which will be

dominated by wages; the economic characteristics are different, including the spread of

factors to which they relate and the role of risk. Furthermore, the CAP policy aim is not

to secure fairness of returns to factors of production but, rather, to ensure fair

standards of living, which is a concept related to the disposable incomes of farm

households (or their consumption expenditures). The Commission assertions about low

incomes in agriculture are not borne out by evidence based on the incomes of agricultural

households (that is, making measurement according the institutional units – principally

household-firms – involved in farming).

In EU-28 in 2010 the Farm Structure Survey showed that 97% of holders were natural persons (in contrast to

legal entities, such as companies and groups of natural persons). France alone accounted for more than two-

fifths of the holdings in the EU-28 that were under the control of legal entities or groups.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Box 7: Statements by the Commission on the relative position of incomes in

agriculture

2010 Consultation Document for Impact Assessment of the Reform of the CAP

towards 2020: ‘Family labour is not sufficiently remunerated and family assets do not

provide adequate returns. Farm incomes are lower than that of the rest of the

economy. In 2008, the entrepreneurial income per worker employed in agriculture in

the EU-27 was estimated to be around 58% of the average wage in the EU. The gap is

more pronounced in the EU-N12 than in the EU-15. Since the year 2000, the gap has

decreased in the EU-12, but actually increased in the EU-15’.

2010 ‘Developments in the income situation of the EU agricultural sector’:

‘...the evidence clearly points to the conclusion that agricultural incomes in the EU are

significantly lower than earnings outside the sector. In 2008 the entrepreneurial

income per worker employed in agriculture in the EU-27 was estimated at around 58%

of the average wage in the EU. The gap was more pronounced in the EU-N12 than in

the EU-15.’

November 2010 Communication from the Commission: ‘After a decade of mere

income stagnation, agricultural income dropped substantially in 2009 adding to an

already fragile situation of an agricultural income significantly lower (by an estimated

40% per working unit) than that in the rest of the economy, and income per inhabitant

in rural areas is considerably lower (by about 50%) than in urban areas’.

December 2009 ‘Why Do We Need a Common Agricultural Policy’: graphics are

given in which the relative income position of agriculture is shown as declining over the

period 2000 to 2008. Using as an indicator ‘agricultural income (not specified in detail)

per AWU unit as % of total economy income/labour unit’ the relative position of

agriculture is shown as falling from about 22% to about 20% in EU-27 over the nine

years, the decline in EU-15 being from a relative income of almost 40% down to close

to 30%. For EU-N10 the relative position of agricultural income was broadly maintained

over the period, whereas in EU-N2 it fell sharply.

This section reviews the evidence on the incomes of agricultural households, in

particular how these relate to other households, details of which are given in FAO (2011)

and Hill (2012). This is in the form, first, of national data from eight Member States using a

mix of sources (farm accounts surveys, taxation data, household surveys, etc., either singly

or in combination); countries covered are Denmark, Finland, France, Ireland, Italy, Poland,

Sweden, and the United Kingdom (England). Second, the main findings of Eurostat’s

Income of the Agricultural Household Sector statistics should be noted; though suspended

in 2002 these remain the only attempt to generate harmonised statistics on this issue, and

many of the results were not invalidated by the disparities in methodology between

countries (the weakness that led inter alia to their suspension). Third, the OECD has

published an overview taking national results (including some from Eurostat’s IAHS project)

which has relevance here (OECD, 2003). Fourth, the Luxembourg Income Study

(LIS - an

international collaboration of which Eurostat is a member) has also analysed relative

income levels, though its basic sources of data (national household surveys) are

handicapped by, in many countries, few cases of households headed by farmers in the

sample

It is well-known that many households that operate farms are also active in other sectors

of the economy. Over a third of farmer/managers are known to have an ‘Other Gainful

http://www.lisdatacenter.org/

See Hill (2012), Chapter 5 for a critique of de Frahan, et al. (2008).

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Activity’ (OGA) with earnings from outside the farm businesses (see Box 8), and this

proportion would be larger if spouses/partners were to be included. For many of these,

particularly where the farm is very small, farming is likely to be a very minor activity

Hence there is a need to draw a distinction between those where agriculture is the main

source of livelihood, which might be termed ‘agricultural households’, and the others.

The lack of a harmonised and working statistical system way of measuring the total and

disposable incomes of agricultural households in the EU is a major impediment in providing

an authoritative picture. Having said that, bringing together the evidence for the EU it is

clear that:

 The definition of what is an agricultural household is important to both the numbers

of households and their income situation. The number of agricultural households

(where the main income of the reference person comes from farming) is

substantially smaller than the number of households where there is some income

from farming, and generally smaller than the number of agricultural holdings. Where

data exist over time, absolute numbers of agricultural households have been falling,

in some instances very rapidly. The fact that results do not relate to a constant set

of households must be borne in mind when interpreting changes in incomes per

household over time.

 Agricultural households (defined as above) in all countries are recipients of

substantial amounts of income from outside agriculture. Though typically about a

half to two thirds of the total comes from farming, there are large differences

between Member States and some differences between years. Other households

with farms will have even more reliance on incomes from outside the farm business.

It follows that knowing the income that a farm operator obtains from farming is not

a reliable guide to their level of household income, so that statistics on incomes

from farming should not be used to draw conclusion relating to household

living standards of farm operators.

 The total income of agricultural households is more stable than their income

from farming alone. Non-agricultural income (taken together) is less variable from

year to year than is farming income. Disposable income seems to be less stable than

total income, but the relationship between the two depends on a variety of factors,

including the way that taxation is levied. Because of short-term variability, figures

for total and disposable household incomes in single years should be treated with

caution; this applies to an even greater extent to data on the income from farming

alone.

 The average disposable incomes of households headed by farmers (in the sense

that farming is the main income source) are generally of similar levels to those

of society in general. This is rather different from the 58% implied by the

Commission’s 2010 statements. In a few countries they are rather lower (Portugal

and Poland for example), but in a greater number of Member States they can be

substantially higher than national household averages. It seems likely that national

circumstances (farm structures, which reflect histories of adjustment, patterns of

land inheritance, pluriactivity rates, etc.) influence relative income positions.

European Commission (2013) reports that over 60% of managers of farms with less than 5 ha UAA spend less

than a quarter of their working time on farm. Over 70% of managers of farms with more than 100 ha UAA

work full-time on the farm. The CAP context indicators show the relative unimportance of agriculture as an

economic activity in most parts of the EU (European Commission, 2014a).

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

 Incomes per household member (or per Consumer Unit) are typically somewhat

lower than per household because of the larger size of the average farm household

(though this characteristic varies between countries).

Box 8: Pluriactive farm operators in the EU-27

According to the 2005 Farm Structure Survey, 36% of EU farmer/managers were

pluriactive, in the sense that they had some other gainful activity (OGAs) outside the

farm businesses. These can fall into two main types: entrepreneurial rewards from

independent activity (self-employment); and, wages and salaries from dependent

activity (as employees). The incidence of OGAs was much higher among small farms,

but even among the largest size groups at least one fifth of farmer/managers had an

OGA.

Source: 2005 FSS given in Barthomeuf (2008).

Some types of farming are particularly associated with pluriactivity, such as specialist

olive farms and grazing and fattening of livestock, while its incidence is lower in others,

for example, specialist dairying and horticulture, where the type of activity seems to

provide less opportunity to be away from the farm. Having an OGA is also more

prevalent among younger farmers than older ones.

Source: 2005 FSS given in Barthomeuf (2008).

These statistics do not cover spouses and other family members, so the percentage of

households having income from involvement with occupations off the farm is likely to be

higher.

10%

20%

30%

40%

50%

<1 ESU 1-<2 ESU 2-<4 ESU 4-<8 ESU 8-<16

ESU

16-<40

ESU

40-<100

ESU

100-<250

ESU

>=250

ESU

Share of sole holder managers with another gainful activity

% of potential gross value added of EU-27

10%

20%

30%

40%

50%

60%

<35 y.o. 35-<44 y.o. 45-<54 y.o. 55-<64 y.o. >=65 y.o. Total

2003 2005

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

If, as seems very likely, living standards of farmers as a group can be shown to be already

‘fair’ (as indicated by approximate parity of disposable incomes) in most EU countries, this

is important from the perspective of social welfare policy. It suggests that farm households

are not a particularly low-income group and points to the need to be able to spot the low

income cases that undoubtedly exist in order to target support at them. The fact that the

mean (or median) disposable incomes of some other groups (such as households headed

by other self-employed persons) are higher than those of farmers is not of much concern in

this context, though it points to the need to be careful in the choice of comparators.

Little attention has been given here to the wealth of farm households. What little

information exists at Member State level suggests that farm operators form a relatively

high net-worth group, largely because of the land assets they control. When considering

support on social grounds, some systems take wealth into account when testing eligibility

(e.g. the English approach to Social Service departments paying for care in retirement and

nursing homes). If the support of low household incomes in agriculture is seen as a

function of social policy rather than agricultural policy, the likelihood of being able to

reflect wealth would appear to be greater than if it were a function of the CAP.

3.2. Incomes from agricultural activity

Income from agricultural activity is only a contributor to what should be understood as

‘farmers’ income’, though the extent of its contribution depends on how broadly the

boundaries of an ‘agricultural household’ are drawn (see the discussion on agricultural

household income above). This will be especially true among small farms where other

gainful activities are the most prevalent, though those that are unmistakably commercial in

their farming operations will tend to be mainly dependent on their profits from agriculture.

As has been explained in Chapter 1.3, there are two approaches to establishing income

derived from agricultural activities: the aggregate approach using sector data (Eurostat)

and the farm-level approach using individual farm data (FADN). Eurostat’s approach covers

all the agricultural activity in the Member State whereas FADN only covers that on holdings

that are deemed to be ‘commercial’ by exceeding a given economic size (which varies

between Member States). The former has attracted the attention of EU policymakers

because of the speed with which results can be made available, whereas the latter contains

much of the detail that is important to CAP decisions. Income from agricultural activity is

set out using both approaches in the sub-sections below.

3.2.1. Aggregate levels (Eurostat)

Chapter 2.2.1 explained the income indicators developed by Eurostat from the Economic

Accounts for Agriculture. Indicators A (income of factors in agricultural activity per AWU)

and B (Entrepreneurial Income per AWU of unpaid labour) are relevant here; both are in

real terms and expressed as indices. Figure 2 presents the evolution of both these

indicators for the EU-27, the EU-25 and the EU-15 (no other aggregations are available).

The general trend is the same for both indicators with Indicator B showing greater

volatility; this difference results from the difference in definition (Indicator B reflects what

is left over from NVA after the further deduction of payments for rent, interest and wages

of hired workers, which tend to be quite stable from year to year). Although there were

decreases in these indicators in 2005 and, more seriously, in 2008/2009 due to declining

commodity prices and increasing input costs, both have since recovered to finish the 2000-

2014 period substantially higher (see Chapter 4 for a discussion on the drivers of income

development). The EU-27 group has outperformed the EU-25 and the EU-15 since 2009

which reveals that incomes in the EU-N10 grouping have converged with those in the EU-

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

15 while those in the EU-N2 have converged with those in the EU-25 from this point

onwards.

Figure 2: Evolution of index of real income of factors in agricultural activity per

annual work unit (Eurostat Indicator A) and index of real net agricultural

entrepreneurial income per unpaid work unit (Eurostat Indicator B) (2005=100)

Source: Eurostat.

Eurostat’s aggregate indicators cannot, by definition, be used to describe income

developments by sub-groups such as farm size and types; this analysis has to be

undertaken using farm-level data in the FADN (Chapter 3.2.3).

3.2.2. Comparing aggregate to farm level data

Before analysing the farm-level FADN data it is worth investigating how the dataset

compares to the aggregate Eurostat data. The most appropriate income indicators for this

analysis are

 FADN Farm Net Value Added per Annual Work Unit compared with Eurostat

Indicator A (index of real income of factors in agricultural activity per AWU); and,

 FADN Family Farm Income per Family Work Unit compared with Eurostat

Indicator B (real net agricultural entrepreneurial income per unpaid annual work

unit).

Figure 3 presents an index of these variables in real terms where 2007 = 100. From 2007

both series are EU-27. Prior to this date the FADN series is EU-25 only, and this helps

explain why the series only move together from 2007; Indicators A and B evolved

differently in Bulgaria and Romania prior to 2007 and this is reflected in Eurostat index for

these years. The conclusion to draw from this analysis is that the two approaches to

calculating farm income provide very similar results in terms of annual fluctuation. It

is reasonable therefore to treat them as broadly comparable.

Eurostat income indicators are expressed in real terms while FADN data are nominal. For the purposes of this

comparison we have converted FADN data into real terms.

100

120

140

160

2000 2002 2004 2006 2008 2010 2012 2014

Indicator A

100

120

140

160

2000 2002 2004 2006 2008 2010 2012 2014

Indicator B

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 3: Comparison of FADN FNVA/AWU against Eurostat Indicator A and

FFI/FWU against Eurostat Indicator B, EU-25/EU-27 (2007=100, real terms)

Source: Eurostat and DG AGRI EU-FADN.

3.2.3. Farm level data (FADN)

FADN data are available for all EU-25 Member States from 2004 to 2012; Bulgarian and

Romanian data are included from 2007 onwards. Where possible we have presented EU-25

data for 2004 to 2006 and EU-27 data for 2007 to 2012 showing a structural break

between the two. Where this is not possible (in the interests of clarity) we have used a

vertical line to divide graphs to make this structural break clear.

It is also important to understand the basis on which FADN data are compiled because this

influences the results produced. The key point is that the FADN field of observation does

not include all agricultural holdings but rather those that are above certain size thresholds

(Economic Size expressed in Standard Output terms), which vary between Member

States to reflect their agricultural structures. In practice this means that FADN covers

almost all production (around 90% or more which comes mostly from what might be

termed ‘commercial farms’) but a much smaller share of farms by number (typically nearer

50% though again there are differences between Member States (these data are presented

in Annex 1).

This means that no farms below a Standard Output (SO) size threshold of

€2,000 are

included in FADN at all and no farms below €25,000 SO are included in Belgium, Germany,

Luxembourg, Netherlands or Slovakia, or below

€8,000 in Austria, Czech Republic,

Denmark, Finland, France, Ireland, Sweden or the UK. The consequence of this is that

FADN results for farms within these lower size classes must be treated with caution

as they do not encompass farms from every Member State.

For example, in published EU-27 results, farms in the

€2,000 to €8,000 size class only

come from 14 countries

and those in the

€8,000 to €25,000 size class 22

countries

Only in results for farms with SO of

€25,000 and over are all Member States represented.

This is important in making observations about the relationship between income and farm

size using EU-level results and also when drawing comparisons between Member States.

Also there are some farmers at the smaller end of the scale for which information on

income from agricultural activities is simply not covered in FADN (see above), an omission

Bulgaria, Cyprus, Greece, Spain, Estonia, Hungary, Italy, Lithuania, Latvia, Malta, Poland, Portugal, Romania,

Slovenia.

The additional eight Member States are Czech Republic, Denmark, France, Ireland, Austria, Finland, Slovenia,

United Kingdom.

100

120

140

2005 2006 2007 2008 2009 2010 2011 2012

FNVA/AWU Indicator A

100

120

140

2005 2006 2007 2008 2009 2010 2011 2012

FFI/FWU Indicator B

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

that is important when viewing the CAP as a policy directed at the standards of living of the

persons engaged in agriculture, but of less significance when the focus of concern is on the

level of agricultural production. By definition, farmers on very small farms are likely to be

earning only small incomes from farming, although they are also likely to earn income from

other gainful activities.

FADN also classifies farms by type, using two standard breakdowns (into fourteen and eight

types: TF14 and TF8 respectively). There is considerable overlap between the two and we

have used the latter which classifies farms as (1) Fieldcrops; (2) Horticulture; (3) Wine; (4)

Other permanent crops; (5) Milk; (6) Other grazing livestock; (7) Granivores; (8) Mixed.

The relative importance (in SO terms) of the different farm enterprises is used to determine

farm typology.

Before presenting analysis at the farm level, it is worth setting out the correspondence

between farm size and type within the FADN sample because there are areas of correlation

between the two which should be kept in mind. Figure 4 shows that the smallest Economic

Size group contains a disproportionate number of mixed farms (the fact that only 14

Member States are represented should also be borne in mind) while the largest group

contains a disproportionate number of granivore enterprises. Dairy enterprises are

more likely to be between

€50,000 and €500,000 in Economic Size terms (groups 4 and 5).

Other permanent crop enterprises tend to be of small Economic Size. Horticultural

enterprises increase in proportion with scale (although here it is especially important to

note the exclusion of small farms in half the Member States; horticulture is often a small-

scale enterprise).

As a result of these relationships, when discussing farm income for granivores, for

example, there will be some correspondence with findings for the largest Economic Size

grouping and vice versa.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 4: Distribution of farm size by farm type in the FADN sample, 2010-2012

average

Source: DG AGRI EU-FADN.

3.2.3.1. Overview

As has been explained above (Chapter 2.2.2 – Box 6), the two main indicators of farm

income within the FADN dataset are Farm Net Value Added per Annual Work Unit

(FNVA/AWU) and Family Farm Income per Family Work Unit (FFI/FWU) (this only relates

to family farms, not those arranged as legal entities). Of the two, FFI is closer to the

concept of ‘farmer income’ in that is represents the profits generated by the farm business

which are available to the farm operator to help fund consumption spending, personal

taxation and saving. FFI is the reward to all the factors of production owned by the farm

operator – the land, labour and capital owned plus the physical labour and managerial input

of the farmer and any other non-hired workers; it is therefore a hybrid of all these. In

contrast, FNVA measures the reward to all the fixed factors used, irrespective of who owns

them. It should be noted that an estimate for the depreciation of capital assets is deducted

from both of these indicators, in line with the conventional approach to income

measurement (in the short-term actual spending on capital items can be delayed or

brought forward).

These two measures are compared in Figure 5 for the EU-27 where it can be seen that their

movements are closely correlated. FFI/FWU equated to 85% of FNVA/AWU in 2004,

increased to 89% in 2007 before falling to 78% in 2009, from which position it increased to

84% by 2012. On average over the 2004 to 2012 period FFI/FWU was 84% of FNVA/AWU.

The close correlation of these measures mean that analyse of FFI/FWU, the most

appropriate measure, does not need to be universally accompanied by a separate analysis

of FNVA/AWU.

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

(1) 2 000 - < 8

000 EUR

(2) 8 000 - < 25

000 EUR

(3) 25 000 - <

50 000 EUR

(4) 50 000 - <

100 000 EUR

(5) 100 000 - <

500 000 EUR

(6) >= 500 000

EUR

(1) Fieldcrops (2) Horticulture (3) Wine

(4) Other permanent crops (5) Milk (6) Other grazing livestock

(7) Granivores (8) Mixed

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 5: Indicators of farm income, EU-25 2000-06, EU-27 2007-12, 2004-2012

Source: DG AGRI EU-FADN.

Both of these indicators relate to the rewards earned by self-employed (independent)

farmers). Wages paid to the hired workers (who may include managers employed by farms

organised as legal entities) are considered later in section 3.2.3.10. The rationale is that, in

some Member States, such workers are generally considered as part of the agricultural

community and thus potential targets for support under the Common Agricultural Policy.

Within the EU there are important differences between groups of countries that were

Member States before 2004 and those that joined subsequently (the treatment of incomes

in single countries are presented separately in Chapter 5). Figure 6 disaggregates FFI/FWU

by EU-15, EU-N10 and EU-N2. The key points to note are:

 In absolute terms FFI/FWU is highest in the EU-15, then the EU-N10 and lowest in

the EU-N2; and,

 FFI/FWU increases over the 2004 to 2012 period with a substantial decline between

2007 and 2009 in all groupings with the exception of EU-N2.

The Figure shows some convergence in absolute levels of income between FFI/FWU in the

EU-15 and EU-N10. In 2004 and 2005, FFI/FWU in the EU-15 was just over four times the

magnitude of FFI/FWU in the EU-N10, but by 2012 was only 2.7 times larger. There was

similar convergence between FFI/FWU in the EU-N2 and the other groups. Although the

decline in FFI/FWU between 2007 and 2009 was greater in absolute terms in the EU-15, in

percentage terms FFI/FWU declined more in the EU-N10 (30% c.f. 25%). The EU-N2

grouping showed no such decline. The drivers behind these changes are considered later

(Chapter 4).

€0

€2.000

€4.000

€6.000

€8.000

€10.000

€12.000

€14.000

€16.000

€18.000

€20.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

FNVA/AWU FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 6: Evolution of FFI/FWU by EU groupings, 2004-12

Source: DG AGRI EU-FADN.

3.2.3.2. Farm size

When considering farm economic size it is important to bear in mind that the field of

observation of FADN does not cover any farms below

€2,000 Standard Output and that

coverage is not universal until an SO of

€25,000 is reached

With that in mind, it is nevertheless clear that a strong relationship exists between the

size of farm business and the average levels of income generated over the three year

period 2010-2012. This is evident in Figure 7 which shows both FNVA/AWU and FFI/FWU

increasing with scale. FFI/FWU edges above FNVA/AWU for the

€100,000

-€500,000 size

group and is considerably higher for farms above

€500,000 (more than double). Though

FNVA/AWU also shows a rise across the farm size spectrum, it is fairly similar between

these two largest size groups. Literature suggests that this association between farm size

and income level is mainly due to the ability of larger farms to take advantage of scale

economies, including crucially on returns to labour. The high FFI/FWU among the largest

farms reflects the large quantities of the capital and land in these businesses that are

combined with relatively small numbers of FWU of (family) labour; it should be recalled that

large farms arranged as legal entities are excluded from coverage by this indicator (though

they are covered by FNVA/AWU) so that this group will contain many large businesses that

are run as family (non-corporate) farms.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

€30.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

EU-15 EU-N10 EU-N2 EU-25 EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 7: Indicators of farm income by farm size, 2010-2012 average

Source: DG AGRI EU-FADN.

The evolution of FFI/FWU by farm size between 2004 and 2012 found in FADN results

is shown in Figure 8. The first point to note is that FFI/FWU increases with the economic

size of farms. Within each size group, the general pattern is the same as shown above in

Figure 7, but the decrease in FFI/FWU from 2007 to 2008 is not only larger in absolute

terms (as would be expected) for the largest size group than it is for the smallest, it is also

much more substantial in relative terms (28% c.f. 9%). Prior to that, the apparent

decrease in FFI/FWU for the smallest size group in 2007 was largely the result of the

accession of Bulgaria and Romania which have a large number of small farms (see Chapter

3.2.3), and the move from EU-25 to EU-27.

€0

€10.000

€20.000

€30.000

€40.000

€50.000

€60.000

€70.000

€80.000

€90.000

€100.000

2,000 - < 8,000

EUR

8,000 - <

25,000 EUR

25,000 - <

50,000 EUR

50,000 - <

100,000 EUR

100,000 - <

500,000 EUR

>= 500,000 EUR

FNVA/AWU FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 8: Evolution of FFI/FWU by farm size, 2004-2012

Source: DG AGRI EU-FADN.

3.2.3.3. Farm type

Figure 9 examines FNVA/AWU and FFI/FWU (both taking the average for 2010-2012) by

farm type using the FADN TF8 classification system

. Although the relationship between

the two indicators varies by farm type, there is no change in the order of types, with

‘Granivores’ having the highest farm income and ‘Mixed’ farms the lowest. These findings

are also influenced by scale (see section 3.2.3), with ‘Granivores’ appearing

disproportionately among large farms and ‘Mixed’ farms disproportionately among small

farms. ‘Other permanent crops’, ‘Other grazing livestock’ and ‘Mixed’ farms all had FFI/FWU

below the EU-27 average while the other farm types all reported FFI/FWU above the

average. This is also the case with respect to FNVA/AWU.

The prevalence of farm types differs across the EU Member States; it should also be noted that ‘Granivores’

are not included in the Irish sample because the total number of these types of farm is too small.

€0

€20.000

€40.000

€60.000

€80.000

€100.000

€120.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

2,000 - < 8,000 EUR 8,000 - < 25,000 EUR 25,000 - < 50,000 EUR

50,000 - < 100,000 EUR 100,000 - < 500,000 EUR >= 500,000 EUR

EU-25

EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 9: Indicators of farm income by farm type, 2010-2012 average

Source: DG AGRI EU-FADN.

The evolution of FFI/FWU for each type between 2004 and 2012 is shown in Figure 10 while

some farm types show the same evolution as noted for all farm types at the EU-27 level

(Figure 9), others do not. In making this observation it is important to bear in mind the

impact of enlargement from EU-25 to EU-27 which generally reduced FFI/FWU at the

aggregate level. The 2006-2007 decline in the ‘Horticulture’ sector is mainly due to the

accession of Bulgaria and Romania in which the horticulture sector is very fragmented.

Sectors which are less significant in Bulgaria and Romania, e.g. wine, do not show this

decrease at EU level.

The dip in FFI/FWU in the ‘Granivore’ sector in 2007 is partly influenced by the accession of

Romania and Bulgaria, but the main causes of the large decrease were a general decline in

FFI/FWU and negative FFI/FWU in Denmark and the Netherlands. Negative FFI/FWU in

Denmark in 2007 in the ‘Other grazing livestock’ and the ‘Mixed’ sectors also contributed to

the large decrease seen here (in the later cases there were also large falls in the

Netherlands). The developments in these two countries, and in the other Member States,

are considered in more detail in Chapter 5.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

€30.000

€35.000

FNVA/AWU FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 10: Evolution of FFI/FWU by farm type, 2004-2012

Source: DG AGRI EU-FADN.

3.2.3.4. Size and type

Figure 11 shows the evolution of FFI/FWU between 2004 and 2012 by farm size and

type. Although not marked on the Figure to improve readability, the reader should recall

the structural break between the EU-25 and EU-27 which took place in 2007 and which will

have a disproportionate impact for smaller size groups.

As would be expected, in each farming type the smallest farms have the lowest incomes

(though it should be borne in mind that not all countries are represented in these classes)

and that absolute incomes increase across the size spectrum. Within each type the pattern

was similar across the size classes with the exception of the largest farms which generally

show greater volatility (partly because of their higher dependence on hired labour).

FFI/FWU in the largest size class also evolved differently in some farm types such as ‘Wine’

and ‘Other grazing livestock’; in others its movements were in the same direction as the

other size groups, but were more extreme. The dip in incomes between 2007 and 2009 is

present in all farm types and size classes, but the magnitude of the decreases varied by

farm type and size.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

€30.000

€35.000

€40.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Fieldcrops Horticulture Wine

Other permanent crops Milk Other grazing livestock

Granivores Mixed

EU-25

EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 11: FFI/FWU by type of farm and size class, 2004-2012

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Fieldcrops

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Horticulture

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Wine

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Other permanent crops

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Source: DG AGRI EU-FADN.

3.2.3.5. Age of farmer

Age in the FADN farm return can be reported for up to six combinations of

holders/managers and whether they are paid or unpaid per farm. To classify farms by the

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Milk

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Granivores

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Other grazing livestock

€0

€25.000

€50.000

€75.000

€100.000

€125.000

€150.000

€175.000

€200.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Mixed

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

age of the farmer, rather than just considering the principle farmer (which can be

misleading where other family members contribute to management), the age of each

holder/manager has been weighted by their respective contribution to their collective sum

of AWU. Indicators of farm income are assessed by this age of farmer indicator in Figure

12. The pattern of income is the same for both indicators and shows income increasing with

age up to the age of 54, after which income declines.

Figure 12: Indicators of farm income by age, EU-27 2010-2012

Source: DG AGRI EU-FADN.

3.2.3.6. Institutional structure

Figure 13 presents the indicators of farm income by ownership structure for the EU-27

and EU sub-groups. The first point to note is that, while FNVA/AWU is appropriate for farms

of all ownership structures, FFI/FWU is not meaningful for farms organised as legal entities

(company farms) where all the labour is treated as paid; FADN results do not calculate it

for farms that have zero unpaid labour. With that in mind, income (as measured by

FNVA/AWU) is lowest for all sub-groups for individual (family) farms and highest for farms

organised as partnerships; economic size provides part of the explanation for this with

partnerships tending to be more prevalent in larger size groups (European Commission,

2013). FNVA/AWU on company farms (other) falls between these extremes. For all sub-

groups with the exception of the EU-N10, FFI/FWU is considerably higher for farms

organised as partnerships than for individual (family) farms. The gap between FFI/FWU for

these organisational forms is greatest in the EU-N2 (a factor of 7.1) and least in the EU-15

(a factor of 1.8); for the EU-N10 FFI/FWU farms organised as partnerships exceeds that of

individual (family) farms by a factor of 3.2. It is expected that farm size is the key

explanatory factor of these differences rather than anything linked to the way in which

farms function under the three ownership structures shown.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

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

Age of farmer

FNVA/AWU FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 13: Indicators of farm income by ownership structure and EU sub-group,

2010-2012 average

Source: DG AGRI EU-FADN.

3.2.3.7. Less Favoured Area status

Figure 14 shows the indicators of income for farms in Less Favoured Areas (mountain and

non-mountain areas) and those in non-Less Favoured Areas (including those with no

significant area). As one would expect from the designation, income is higher in the

non-LFA, despite the LFA payments made.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

€30.000

€35.000

€40.000

€45.000

FNVA/AWU FFI/FWU FNVA/AWU FFI/FWU FNVA/AWU FFI/FWU FNVA/AWU FFI/FWU

EU-27 EU-15 EU-N10 EU-N2

(1) Individual (family) farms (2) Partnerships (3) Other

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 14: Indicators of farm income by Less Favoured Area status, EU-27 2010-

2012

Source: DG AGRI EU-FADN.

3.2.3.8. Volatility

Volatility can be considered at the group level (Member State, or type and size class) and

at the level of the individual farm. Group figures can be of interest, but they hide much of

what happens at the farm level because the short-run experiences of single businesses,

while significant to their operators, to an extent cancel each other out.

Group level volatility

The first approach is to examine the year-on-year changes seen in average result for

groups of Member States. While the direction of change is broadly similar in EU-15 and

EU-N10, the latter group shows a more pronounced variation, though in the last three

years of the series that is a closer commonality (Figure 15). The negative changes in the

middle of the period were generally recouped in following years.

€0

€5.000

€10.000

€15.000

€20.000

€25.000

LFA non-LFA

FNVA/AWU FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 15: Annual year-on-year change in farm income indicators

Source: DG AGRI EU-FADN.

Another, more formal, way of measuring volatility is using a coefficient of variation

; the

higher the coefficient, the greater the relative variation from year to year. The coefficients

have been calculated for 2004 to 2012.

The analysis here is carried out for size classes (Figure 16) and type of farming (Figure

17). It is clear that the variability of incomes, as measured by the coefficient of variation, in

FADN results is much greater in the smallest size class of farms, though it should be

recalled that this omits data from many Member States. Beyond that, variation rises with

larger farm size, though there is little difference between the medium size groups in terms

of FNVA/AWU. However, this must also reflect the domination of the largest size class by

‘Granivores’. Among farming types ‘Granivores’ is characterised by volatility of income,

closely followed (in terms of FFI/FWU) by ‘Fieldcrops’. At the other end of the volatility

spectrum, with the most stable incomes, are ‘Horticulture’ and ‘Other permanent crops’.

Standard Deviation/mean.

-40%

-30%

-20%

-10%

10%

20%

30%

40%

2005 2006 2007 2008 2009 2010 2011 2012

FNVA/AWU

-30%

-20%

-10%

10%

20%

30%

40%

2005 2006 2007 2008 2009 2010 2011 2012

FFI/FWU

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 16: Coefficient of variation of income indicators by farm size, 2004-2012

Source: DG AGRI EU-FADN.

Figure 17: Coefficient of variation by farm type, 2004-2012

Source: DG AGRI EU-FADN.

Farm level volatility

Almost all results reported in this document have been freshly calculated using the latest

FADN results. However, the data to construct a new assessment of farm-level volatility (an

0,00

0,05

0,10

0,15

0,20

0,25

(1) 2 000 - < 8

000 EUR

(2) 8 000 - < 25

000 EUR

(3) 25 000 - <

50 000 EUR

(4) 50 000 - <

100 000 EUR

(5) 100 000 - <

500 000 EUR

(6) >= 500 000

EUR

Var FNVA/AWU Var FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

0,00

0,05

0,10

0,15

0,20

0,25

0,30

(1)

Fieldcrops

(2)

Horticulture

(3) Wine (4) Other

permanent

crops

(5) Milk (6) Other

grazing

livestock

(7)

Granivores

(8) Mixed

Var FNVA/AWU Var FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

up to date version of (Figure 18) are not available, though it is unlikely that the overall

pattern would be much altered since the Commission published results for 1998-2007.

According to that analysis, a higher proportion of small farms appeared to see large

negative changes (more than 30%) in FNVA compared to the average of the three previous

years relative to large farms which in turn were more likely to see positive changes (up to

100%). Despite this general pattern, a high proportion of small farms recorded an increase

of more than 100% than did large farms. However, a key point to note from the Figure is

that 55% of large farms and 38% of small farms experienced income volatility of

±30% from the previous three year average. Such information is important to policy

that attempts to bring greater stability to the incomes of farm operators from their

agricultural activities.

Figure 18: Farm level volatility, 1998-2007

Source: Elaborated from European Commission (2010) based on EU-FADN data.

3.2.3.9. Distribution of incomes

Figure 19 presents the distribution of income (FNVA and FFI) among the labour force

(AWU) for the EU-27 using a Lorenz curve

. An average income at the farm level for the

period 2010-12 has been used. An equal distribution of income would be show a straight

line from the origin to the top right hand corner. The evidence seen here demonstrates that

the distribution of income is not equal. Furthermore, income for large parts of the farm

labour force was negative, much more so in the case of FFI. In FNVA terms, 20% of the

agricultural labour force generates 66% of FNVA with 10% accounting for 55% of FNVA.

A Lorenz curve is a graphical representation of the cumulative distribution of wealth or income. A straight line

from the origin to the top right hand corner at 45

would indicate perfect equality. The extent of deviation

from this straight line shows the extent of inequality.

More than

100%

-100 to -

70%

-70 to -30% -30 to 0% 0 to 30% 30 to 70% 70 to 100% More than

100%

Percentage of farms

Percentage change in FNVA compared to average of previous 3 years

Small farms (2-4 ESU) Large farms (above 100 ESU)

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

The lack of equality is even more noticeable in FFI terms where 20% of the labour force

generates 78% of the FFI but 10% generates 58% of FFI.

Given that these incomes cover three years, the numerical importance of labour units with

negative incomes from farming raises the question of how the holdings to which they

belong manage to stay in business. Income sources from outside the farm business are

expected to play a major part in explaining the persistence of such farms, though this

might also involve increases in borrowing against assets that may or may not be increasing

in value in real terms. Though non-agricultural income can be documented in countries

where farm accounts surveys collect such information (and, for example, is well

documented in the ARMS survey in the US), the lack of coverage of variables on other

household incomes by FADN means that no direct evidence can be drawn from the EU’s

main data source on farm economics. This is regrettable and points to the need for change

in the coverage of FADN to bring it in line with what many Member States already do in

their national surveys of farm accounts.

Figure 19: Lorenz curve of the distribution of FNVA and FFI, EU-27, 2010-2012

average

Source: DG AGRI EU-FADN.

The Gini coefficient can also be used to measure the distribution of income. This

coefficient is the ratio of the area between the line of equality

and the Lorenz distribution.

A value of 0 shows perfect equality of income and 1 perfect inequality.

Figure 20 presents the Gini coefficient for the various EU groupings. Some caution is

required in interpreting this data because the FADN field of observation differs by Member

State with smaller farms generally not included in the EU-15. That said, two patterns stand

out. First, the distribution of FNVA per AWU is less concentrated in the EU-15 than the EU-

N10 or EU-N2. Second, income concentration is generally decreasing in the EU-N10 and

EU-N2 showing a degree of convergence with the distribution in the EU-15. That said, it will

be at least five years before a definitive judgement on the extent of convergence can be

reached given annual fluctuations

. A final observation is that income concentration

increased in the EU-15 in 2008 and in the EU-N10 and EU-N2 in 2009 as a result of the

financial crisis before declining to pre-2008 levels in the case of the EU-15 and to trend in

the other groupings. The lack of change in income distribution between the beginning and

Straight line from the origin to the top right hand corner at 45

A reminder of the dangers of looking at short-term trends and focusing on annual data is provided by European

Commission (2014a) which, based on a data series finishing in 2011 concluded that income concentration was

increasing in the EU-15. With the addition of 2012 data this now looks incorrect with the 2008 to 2011 period

appearing to be a temporary phenomenon. However, this conclusion requires data from further years to be

confirmed.

-20

100

0 10 20 30 40 50 60 70 80 90 100

Cumulative share of FNVA

(%)

Share of AWU (%)

-20

100

0 10 20 30 40 50 60 70 80 90 100

Cumulative share of total

FFI (%)

Share of AWU (%)

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

end of the observation period in the EU-15 might suggest that a Gini coefficient of

around 60% is typical for the agricultural sector.

European Commission (2014b) notes that income inequality in the EU-N2 decreased as a

result of the increase in direct payments during the phasing-in process. An examination of

the balance of current subsidies and taxes reveals that subsidies did indeed increase by

higher proportions for smaller farms in both Bulgaria and Romania.

Figure 20: Development of the Gini coefficient of FNVA per AWU

Source: DG AGRI EU-FADN.

3.2.3.10. Wages of hired farm labour

Although the incomes of self-employed farmers are the main focus of our attention in this

report, there is interest in the earnings of hired workers, not least because they are

numerically significant in some Member States and opinion in some countries suggests that

there they are seen as part of the agricultural community for policy purposes. However, it

must be emphasised that the factors determining their incomes are fundamentally different

from those that drive the incomes of farmers; for example, wage levels are not directly

connected to the market conditions for agricultural commodities. FADN contains some data

that are relevant to the earnings of hired workers, and for completeness these are

reported. Figure 21 presents the evolution of agricultural wages from 2004 to 2012.

0,0

0,2

0,4

0,6

0,8

1,0

1,2

2004 2005 2006 2007 2008 2009 2010 2011 2012

Gini coeffieicnt

EU-15 EU-N10 EU-N2 EU-25 EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 21: Paid labour (€/hour), 2004-2012

Source: DG AGRI EU-FADN.

The key points are that, firstly, agricultural wages increased steadily (in nominal terms)

over the 2004-2012 period with only the EU-N2 group experiencing a decline in 2008 and

the EU-N10 one in 2009. Secondly, agricultural wages in the EU-N10 converged with those

in the EU-15, but those in the EU-N2 did not.

Agricultural wages averaged over the years 2010-2012 by farm type are shown in Figure

22. There are some apparent differences. Wages per hour are highest in the wine sector,

followed by the horticulture and milk sectors (the three sectors where wages exceed the

EU-27 average) and are lowest in ‘Other grazing livestock’ and ‘Fieldcrops’ farm types.

However, the way in which FADN takes account of casual labour is not clear and, in

practice, low-waged casual labour in the wine and horticultural sector might reduce the real

average wages in these sectors.

€0

€1

€2

€3

€4

€5

€6

€7

€8

€9

€10

2004 2005 2006 2007 2008 2009 2010 2011 2012

EU-15 EU-N10 EU-N2 EU-25 EU-27

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 22: Paid labour (€/hour) by farm type, 2010-2012 average

Source: DG AGRI EU-FADN.

Annual volatility in paid agricultural wages is shown in Figure 23. The main volatility is in

the EU-10 where wages have been rising more quickly (see above). There was a major

impact in 2009 in EU-10, which is possibly linked to the adverse economic conditions

experienced in these Member States at the time.

€0,00

€1,00

€2,00

€3,00

€4,00

€5,00

€6,00

€7,00

€8,00

€9,00

€10,00

(1)

Fieldcrops

(2)

Horticulture

(3) Wine (4) Other

permanent

crops

(5) Milk (6) Other

grazing

livestock

(7)

Granivores

(8) Mixed

Hourly wage EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 23: Annual year-on-year change in paid agricultural wages per hour

Source: DG AGRI EU-FADN.

-30%

-20%

-10%

10%

20%

30%

2005 2006 2007 2008 2009 2010 2011 2012

EU-15 EU-N10 EU-N2 EU-25 EU-27

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

4. THE DYNAMICS OF FARM INCOMES AND THE KEY

DRIVERS

KEY FINDINGS

 A substantial minority of holdings (at least a third) derive income from other

gainful activities, earnings from property, pensions and transfers. The drivers of

this income are largely those that shape the general economy. Some 12% of EU-27

farms also draw income from diversified activities and diversified activities increase

with scale. This income is also driven by general economic factors, although some

will be related to the agricultural economy.

 The most important component of agricultural revenue is returns from the market

which account for 86% of FADN Total Output for the EU-27.

 Market returns are driven by quantity of output and price. Yields have been

relatively stable, but prices, especially for crops, have fluctuated considerably over

the 2005 to 2012 period.

 Subsidies make up the balance of Total Output; there is no suggestion that

changes in subsidies have played a major role in the evolution of income.

 The most important cost element is total intermediate consumption which

accounts for two-thirds of total expenses for the EU-27. Depreciation accounts for

15% of total costs, wages paid 9%, rent 5% and interest payments 3%.

 Total intermediate consumption is made up of total specific costs (crop and

livestock) and overheads (machinery and building costs, energy, contract work and

direct inputs).

 These elements of intermediate consumption have all increased between

2004 and 2012, but specific crop costs have increased the least. Within specific crop

costs, fertiliser cost is the most volatile element. Within overheads, energy costs

have been the most volatile and showed the sharpest absolute increase.

 Although the use of paid labour has declined, wages paid per farm increased

steadily between 2007 and 2012

 The importance of these income components differs by farm type. Subsidies

account for a quarter of the value of total output in ‘Other grazing livestock’ farms,

but less than 5% in the horticulture, granivore and wine sectors. There is less

difference in the relative importance of costs by farm type, although paid wages are

more important in the horticulture and wine sectors.

 Analysis by farm size shows that the relative importance of subsidies decreases

as farm size increases.

The way in which farming incomes have been changing over time has been described in

previous sections. Here we are concerned with the explanations for these changes and the

factors that drive them. While the emphasis has to fall on the incomes that farmers derive

from their agricultural activities, it is necessary to first outline the broader picture that

embraces the incomes of the households of farmers, as this bears a close relationship with

the CAP’s core aim of ensuring a fair standard of living for the agricultural community.

When examining drivers, it is helpful to break these down according to scale (from global to

local, following the model of Hazell and Wood (2008)) and by time period.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

4.1. Farm household income

By definition, farm households will receive part of their incomes from farming, and in many

cases where farming is carried on as a commercial activity this will be a major source

though not necessarily the largest in terms of earnings. As noted in Chapter 1, a

substantial minority of holdings in the Farm Structure Survey (at least a third and

probably a much higher proportion if spouses and partners are included) have some other

gainful activity (OGAs) outside the farm businesses, to which should be added earnings

from property (interest and rent) and various forms of pensions and transfers.

The important point to recognise in connection with OGAs and earning from property is that

the drivers are largely those that shape the general economy rather than those specific to

agriculture. The opportunity for farm households to take employment off the farm or build

a business will be affected by issues such as the general level and growth in consumer

spending growth, interest rates, government interventions to stimulate economic activity

and so on.

Then there is the issue of diversification on the farm into activities that are not strictly part

of the farm business, e.g. tourism, handicraft, processing of farm products, wood

processing, aquaculture, contract work using farm equipment, etc. Some 12% of EU-27

farms are diversified in this sense, and the proportion increases with farm size (see

Barthomeuf, 2008).

While pressure to consider on-farm diversification will mirror inversely what is happening to

profitability of agriculture, the opportunities to diversify and the earnings from them are

again likely to be driven primarily by what is happening in the general economy, though for

the process of farm products and for contract work using farm equipment (which may be

for other farms and forestry holdings) a case could be made that there may be a partial

connection with developments in the agricultural economy.

At the farm level the growth of OGAs and of diversification are commonly associated with

inter-generational change, so factors that impinge on decisions on succession and on

career choices by younger family members will act as drivers to the non-farming incomes

of farm households (Hill, 2012).

It should not be forgotten that, in the long-term, changes in the real value of assets

constitute an element in personal income. Farm families tend, as a group, to hold more

assets than society in general in most countries principally because of the value of the

agricultural land that they own. They are thus in a position to make substantial real capital

gains when land prices rise, even when these movements are brought about by non-

agricultural factors; these gains help explain why some farmers persist in remaining in

agriculture. Of course, were land prices to fall they would make capital losses. It follows

that factors that determine land prices are drivers of long-term income change

. One of

these is the preferential treatment given in taxation systems in many Member States to

wealth in the form of agricultural assets, particularly to capital gains on agricultural land

and on its transfer between generations (OECD, 2005). It follows that national government

policy in this area of tax legislation can materially affect long-term income. As things stand

Drivers of land prices are considered by European Parliament (2013b); Swinnen, et al. (2008); and the

Framework 7 project Factor Markets. Grant agreement N°: 245123-FP7-KBBE-2009-3.

http://www.factormarkets.eu/content/rural-land-market

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

and despite the commonality of preferential treatment, there are differences between

countries in capital taxation that are significant both to the comparisons between farmers

4.2. Income from agricultural activity

Any analysis of the drivers of change in the income from agricultural activity, the patterns

of which were described in Chapter 1 above, has to reflect the elements that compose the

indicators used to measure income and its changes. In this report they are, at

microeconomic level, FNVA/AWU and FFI/FWU and their equivalents at macroeconomic

level of NVA/AWU and Entrepreneurial Income per AWU of Family Labour Input (Indicators

A and B respectively when expressed in real terms and in index form). The definitions of

these indicators were given in Chapter 2 above. In short, the main elements are the value

of outputs, the costs of producing that output (which differ between the indicators),

subsidies received that are related to that production (though not necessarily coupled to it),

and the volume of the labour among which the rewards are divided. These are the main

groups of drivers that we need to examine.

4.2.1. Results by EU group

In order to focus on the most important drivers of change and to understand other

comparisons it is necessary first to know about the main components of both the revenue

received and the costs.

Figure 24 presents the composition of income and expenses/income by EU grouping using

an average for the 2010-2012 period. The difference between income and expenses is

Family Farm Income (FFI), shown in the right hand bar for each grouping

. Most family

farmers draw their income from what they would understand as profit (FFI), the difference

between income and expenditure.

The first point to note is the large difference between the absolute amounts of

revenue and expenditure per farm between EU groups. Average income in the EU-15 is

2.3 times that in the EU-N10 and 6.5 times higher than that in the EU-N2. However, the

focus of attention here has to fall on their compositions.

The most important revenue component seen in FADN results is returns from the

market. This accounts for 86% of FADN Total Output for the EU-27 and EU-15, 82% for

the EU-N10 and 88% for the EU-N2; subsidies (the sum of net current and investment

subsidies) make up the balance. These include EU coupled and decoupled payments, less

favoured area (LFA) payments, rural development payments and national aid, in all cases

net of any relevant taxes (but not, of course, taxes on incomes).

The most important cost element for all groupings is total intermediate consumption

which accounts for just over two-thirds (68%) of total expenses for the EU-27 grouping

This is a broadly consistent proportion across the sub-groups. The next most important cost

component is depreciation which accounts for 15% of costs in the EU-27; again this is

European Commission (2014b) presents similar information, but instead of showing FFI, shows the estimated

opportunity costs of ‘own factors’, which comprises imputed values for the farmers’ time, own land and own

capital. This sometimes leads to expenses being higher than income which leads to statements about

profitability which are somewhat misleading.

Note that European Commission (2014b) states that intermediate consumption accounts for only half of total

expenses; this is because these total expenses include own factors, the rewards to the farmer’s input, which is

potentially misleading.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

consistent across the sub-groups. Wages paid account for 9% of total costs for the EU-27,

rent for 5% and interest payments 3%. While the importance of wages is comparable

across the groupings, rent is highest in the EU-N2 at 7% and lowest in the EU-N10 at 3%

(the EU-15 is the same as the EU-27). Interest payments are lower in both the EU-N10

(2%) and the EU-N2 (1%) while again, the EU-15 is the same as the EU-27. In summary,

there are in fact few differences in the components of income.

The biggest difference between the groups is in fact in Family Farm Income which is

equivalent to a quarter of total output (24%) in the EU-27, EU-15 and EU-N10, but is a

third (33%) of total output in the EU-N2, although in absolute terms it is smallest there.

Figure 24: Income components per farm by EU group, 2010-12 average

Source: DG AGRI EU-FADN.

In addition to the components of farm income it is also necessary to consider the impact

of structural change over time. As farms increase in scale returns per labour unit will

increase. Average farm size tends to increase over time (European Commission, 2013) and

this will exert some upward influence on farm incomes when measured at the level of the

farm or, as we do throughout this analysis, per unit of labour.

€0

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€40.000

€60.000

€80.000

€100.000

€120.000

Receipts Expenses

and income

Receipts Expenses

and income

Receipts Expenses

and income

Receipts Expenses

and income

EU-15 EU-N10 EU-N2 EU-27

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Receipts Expenses

and income

Receipts Expenses

and income

Receipts Expenses

and income

Receipts Expenses

and income

EU-15 EU-N10 EU-N2 EU-27

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Another factor which is not a component of income, but which influences income as

measured per labour unit, is the quantity of labour used. This tends to decrease over

time as labour efficiency increases (European Commission, 2013). This will also manifest as

an upward influence on income when measured as a return to labour over time.

4.2.2. Results by type of farming

In absolute terms per farm both the values of revenues and the costs were highest

among granivores, horticulture and milk farms, and these also had the largest sales to the

market (Figure 25). The lowest, both for total revenue and for sales to the market,

occurred among the ‘other permanent crops’ farms. While it is clear that the market is the

main source of revenue for all farming types, accounting for some 85% of the total, and

hence changes there will be the main revenue drivers, the importance of subsidies is not

uniform. They accounted for about a quarter of the value of total output in the ‘Other

grazing livestock’ group, but a far lower share (less than 5%) in horticulture, granivores

and wine farms; even quite large changes in subsidies are thus unlikely to make major

impacts on the total value of output among these farming types.

On the costs side, the balance between the ways in which the various categories of costs

absorb revenues, and what is left to form FFI, is broadly similar across the farming types.

Paid wages are relatively more important in horticulture and wine, so what happens to

labour costs could be expected to be a more significant driver there than among other farm

types. However, in all farm types the largest costs are those that make up ‘intermediate

consumption’ rather than those of the ‘fixed factors’ (payments for rent, interest and hired

labour) and hence this is likely to be where the biggest cost-based drivers of income are

located.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 25: Income components per farm by EU farm type, 2010-12 average

Source: DG AGRI EU-FADN.

4.2.3. Results by size of farm

Some interesting patterns emerge from examination of income components by farm size

(Figure 26), though the relationship between farm size and the dominant farm

types, and of coverage of Member States should be borne in mind (particularly the

importance of mixed farms and Bulgaria, Romania and Portugal to the smallest size class

and of granivores and horticulture to the largest size classes). Nevertheless, a general

relationship is seen in which the relative importance of subsidies declines with

increasing size of farm, more than halving between the smaller size classes and the

largest (from about one fifth to less than one tenth of the total value of output). Another

feature is the rise in relative importance among the costs of intermediate consumption with

increasing farm size. Wages paid take a larger share among the biggest farms, but this is

probably a reflection of the dominance of granivores and horticulture in this size class.

Perhaps surprising is the finding that the proportion of total output that remains to the

operators as FFI declines as larger farm classes are encountered, though of course the

absolute amounts will be larger.

€0

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€200.000

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€300.000

R E & I R E & I R E & I R E & I R E & I R E & I R E & I R E & I

Fieldcrops Horticulture Wine Other

permanent

crops

Milk Other

grazing

livestock

Granivores Mixed

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

R E & I R E & I R E & I R E & I R E & I R E & I R E & I R E & I

Fieldcrops Horticulture Wine Other

permanent

crops

Milk Other

grazing

livestock

Granivores Mixed

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 26: Income components per farm by economic size, 2010-12 average

Source: AGRI EU-FADN.

4.2.4. Changes in income components between 2004-2006 and 2010-2012

A further method of identifying the key drivers of income is to look at the changes in

absolute amounts of each element between two representative periods, in our case

between the averages of two three-year periods (2004-2006 and 2010-2012). From this it

is possible to identify which items were responsible for overall changes in income. For

example, was there a rise in the value of output and no change in costs, or static output

and a fall in costs, or some other combination? On the costs side, some elements may

have changed dramatically in percentage terms but, because they are small in

absolute terms, have very little impact on overall costs and incomes.

By way of summary, the absolute change in the components of income between the

average for the 2004-2006 and 2010-2012 periods is set out in Figure 27 for the EU-25 and

the two EU sub-groups that it is possible to examine over this period. The figure makes

clear that the key components which drive the development of income are, on the revenue

side, total output, and on the cost side, total intermediate consumption. There is some

difference in the scale of changes by EU grouping, most notably the greater increase in

subsidies in the EU-N10. This aside, changes to the components of income were lower in

€0

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€400.000

€600.000

€800.000

€1.000.000

€1.200.000

€1.400.000

R E & I R E & I R E & I R E & I R E & I R E & I

(1) 2 000 - < 8

000 EUR

(2) 8 000 - <

25 000 EUR

(3) 25 000 - <

50 000 EUR

(4) 50 000 - <

100 000 EUR

(5) 100 000 -

< 500 000 EUR

(6) >= 500

000 EUR

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

R E & I R E & I R E & I R E & I R E & I R E & I

(1) 2 000 - < 8

000 EUR

(2) 8 000 - < 25

000 EUR

(3) 25 000 - <

50 000 EUR

(4) 50 000 - <

100 000 EUR

(5) 100 000 - <

500 000 EUR

(6) >= 500 000

EUR

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

the EU-N10 than in the EU-15, although this is largely because these changes are from a

lower base.

Figure 27: Change in value of income components 2004-06 average compared to

2010-12 average by EU sub-group

Source: DG AGRI EU-FADN.

Figure 28 presents similar analysis for farm type. The same general pattern prevails in

that total output and total intermediate consumption are the key components of income in

terms of change over the period. Key points to note are that the granivore sector saw the

greatest changes in these components, although as has been explained above, this is partly

the result of the correlation between this farm types and increased scale. The larger

increase in wages paid in the horticultural sector should also be noted, as should the

greater increase in depreciation in the granivore and milk sectors.

€0

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€10.000

€15.000

€20.000

€25.000

€30.000

Total Output Total

subsidies

Total

intermediate

consumption

Depreciation Wages paid Rent Interest

EU-25 EU-15 EU-N10

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 28: Change in value of income components 2004-06 average compared to

2010-12 average by farm type

Source: DG AGRI EU-FADN.

4.2.5. Changes in the key drivers

Agricultural income varies substantial from one year to the next as a natural consequence

of weather and other short-term factors and is anticipated by farmers (though they may

occasionally represent disasters for individuals). This is why in this report we focus on

income averaged over a three year period. In this section we focus on medium and long-

term variation and trends.

From the above, and from the literature, it is clear that the main drivers of income are on

the revenue side of the income calculation, the value of total output, which is the

combination of market output (price and quantity) as well as subsidies. Prices are affected

by trends, medium-term slumps and high-price periods. Quantity is affected by changes in

productivity or more/less factors of production, such as capital. Subsidies can be changed

by policy decision.

On the cost side of the income calculation, the main items are the costs of intermediate

production (price and quantity, trends and medium-term movements) and labour costs,

which are a combination of wage levels (trends) and quantities of labour employed (to give

labour costs). Other relatively minor drivers are interest costs (again a combination of

levels of charges, although in the period considered these were largely static, and the

amount of borrowing) and rents. Depreciation is a cost that has changed in absolute

amounts more than labour, though we have not treated it as a main driver because, by its

nature, the rate at which capital items are assumed to be consumed is set administratively

-€20.000

€0

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€100.000

€120.000

€140.000

Total output Total

subsidies

Total

intermediate

consumption

Depreciation Wages paid Rent Interest

Fieldcrops Horticulture Wine Other permanent crops

Milk Other grazing livestock Granivores Mixed

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

and is independent of market conditions, and the stock to which it applies can only change

gradually.

When looking at indicators expressed per work unit (either total labour or only family

labour), it is necessary to look at how the amount of labour used in agriculture has

changed. These issues are considered in turn in the sub-sections below.

4.2.6. Total output

Figure 29 shows the two principal components of ‘Total output’: crops and crop products

and livestock and livestock products on FADN farms. When using this data source to trace

developments in drivers over time care has to be taken to account for the enlargement that

took place in 2007, so that the series should be properly interpreted as falling into two

sections, 2004-2006 and 2007-2012 (this is not the case for Eurostat data which is EU-27

throughout the period of interest). It is also necessary to recall that FADN results are given

in nominal values, and that inflation will have caused small but gradual changes in values

over the runs of years studied (annual inflation of the Euro averaged a little less than 2%

over the period).

In the pre-enlargement period shown in Figure 30 there is no noticeable trend in either the

value of crop or livestock output. Following the drop in levels associated with the inclusion

of Bulgaria and Romania into the EU, the first three years were characterised by stagnation

or decline to 2009, after which there was a noticeable rise.

Figure 29: Evolution of the components of Total Output per farm, EU-25 2004-

2006, EU-27 2007-2012

Source: DG AGRI EU-FADN.

€0

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2004 2005 2006 2007 2008 2009 2010 2011 2012

Total Output: crops and crop products Total Output: livestock and livestock products

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Total output is the product of quantity of output and price. Of the two, when looking

at group average results the more volatile element is the market prices obtained by

farmers, and this is particularly clear with farm crops.

Figures from Eurostat (that cover the EU-27 throughout the period) show that prices of

crop products rose substantially from 2005 to 2008, typically by about 50%, but then fell

dramatically in a single year, with prices in 2009 almost back to the 2005 level. However,

from 2009 to 2012 there was a sustained recovery to levels that exceeded the previous

peak. Prices for livestock and livestock products were relatively more stable, with only

milk showing a similar pronounced fall in 2009. Other categories were quite stable, while

poultry showed a rising trend.

Figure 30: Evolution of crop and livestock prices, EU-27, 2005 = 100

Source: Eurostat.

Of course, at the farm level there can be changes in physical crop output and animal

performance that can affect the business revenue, and occasionally there will be disease or

climatic conditions that are more widely experienced. However, at group average level

there is a remarkable consistency of yields over time. Figure 31 shows wheat and maize

yields and milk output per dairy cow, taken from FADN. Bearing in mind the break in the

series associated with enlargement in 2007, across the EU wheat yields and maize yields

have been stable though perhaps with a slight downward trend. In contrast, milk yields per

cow have shown a small but steady rise.

100

150

200

2005 2006 2007 2008 2009 2010 2011 2012

Crop price index (2005=100)

Cereals (including seeds)

Oil seeds and oleaginous fruits (including seeds)

Protein crops (including seeds)

100

150

200

2005 2006 2007 2008 2009 2010 2011 2012

Livestock price index

(2005=100)

Cattle excluding calves Pigs Sheep and goats Poultry Cows' milk

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 31: Evolution of yield per unit of output, EU-25 2004-06, EU-27 2007-12

Source: DG AGRI EU-FADN.

Turning to the other main element in the revenue of farms, subsidies, we see that at EU

level the accession of Bulgaria and Romania lowered the average received per farm (Figure

32). However, from 2007 there was a modest rise to 2010, since when the level has been

approximately sustained. Certainly, at EU-27 level there is no suggestion that changes in

subsidies have had a major part to play in the evolution of incomes. However, the

importance of payments for public goods via subsidies, for example agri-environment

payments under the second pillar of the CAP should be noted, although these are

replacing more production related subsidies rather than increasing the total amount of

subsidy available.

2004 2005 2006 2007 2008 2009 2010 2011 2012

Yield per hectare/yield per cow

Wheat yield (tonnes/ha) Maize yield (tonnes/ha) Milk yield (tonnes/cow/year)

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 32: Evolution of subsidies, EU-25 2004-06, EU-27 2007-12

Source: DG AGRI EU-FADN.

4.2.7. Costs of intermediate production

From the analysis of income components above, the key cost element to focus on is “total

intermediate consumption”. This is defined within FADN as “total specific costs (including

inputs produced on the holding) and overheads arising from production in the accounting

year”. “Total specific costs” includes specific crop costs (bought and home-grown seeds and

plants, fertilisers, crop protection and other crop specific costs) and specific livestock costs

(bought and home-grown feed for grazing livestock, bought and home-grown feed for pigs

and poultry and other livestock specific costs). “Overheads” includes machinery and

building current costs, energy, contract work and other direct inputs.

Figure 33 shows the evolution of specific crop costs, specific livestock costs and total

farming overheads

for the EU-27. Specific crop costs per hectare increased gradually

after enlargement, but without large variations between years. Livestock costs per

livestock unit appeared to be quite stable either side of enlargement, but fell in 2009 and

then increased steadily but quite rapidly, rising by some

€103 per farm between 2007 and

2012). In contrast, farming overheads per farm were on a rising trend before

enlargement (a 10% rise between 2004 and 2006), and this has continued consistently

since 2007 with a steady upward trend from 2007 to 2012 that resulted in a 33% increase

over this period, or just over €4,000 per farm.

It is not possible to calculate overheads with reference to any other unit than the farm. The requirement for

FADN to be representative in terms of farm sizes mitigates against the risk that the trend is influenced by

structural change.

€0

€2.000

€4.000

€6.000

€8.000

€10.000

€12.000

€14.000

€16.000

€18.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

EU-27 EU-15 EU-N10 EU-N2

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 33: Evolution of specific crop and livestock costs and total farming

overheads, EU-25 2004-16, EU27 2007-12

Source: DG AGRI EU-FADN.

Among the specific crop costs, fertilisers are clearly the category that has been the most

volatile and has increased the most per farm at EU level (Figure 34). Costs were rising

before EU enlargement, but among EU-27 there was a rapid upward shift from 2007 for two

years, a sharp drop in 2010, subsequently followed by a further short rise to leave

spending per farm almost double the 2007 level and representing an increased cost of

some

€2,500 per farm. In contrast, the other elements of crop costs were more stable and

showed gentler upward trends.

Among the costs of producing livestock, expenditures per farm showed no clear trend up to

2009, but since then have risen quite sharply, by in the region of

€2,000 per farm for both

grazing livestock and for pig and poultry farms.

€0

€2.000

€4.000

€6.000

€8.000

€10.000

€12.000

€14.000

€16.000

€18.000

€0

€100

€200

€300

€400

€500

€600

€700

€800

€900

2004 2005 2006 2007 2008 2009 2010 2011 2012

Total farming overheads

Specific crop and livestock costs

Specific crop costs per hectare Specific livestock costs per Livestock Unit

Total farming overheads per farm

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 34: Evolution of specific crop and livestock costs per farm, EU-25 2004-06,

EU-27 2007-12

Source: DG AGRI EU-FADN.

Turning again to overheads, energy costs stand out as being the least stable and showing

the sharpest absolute rise (Figure 35). Not only was there a sharp increase in EU-25 for the

period 2004-2006, but since enlargement to EU-27 these has been an addition to costs of

some

€1,500 per farm between 2007 and 2012. The

rises of the other components have

been persistent, but steadier.

€0

€1.000

€2.000

€3.000

€4.000

€5.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Seeds and plants (including home-grown) Fertilisers

Crop protection and pesticides Other specific crop costs

€0

€2.000

€4.000

€6.000

€8.000

€10.000

€12.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Feed for grazing livestock (including home-grown)

Feed for pigs & poultry (including home-grown)

Other livestock specific costs

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 35: Evolution of the elements of total farm overheads, EU-25 2004-06, EU-

27 2007-12

Source: DG AGRI EU-FADN.

4.2.8. Interest costs

As might be expected, costs of the so-called ‘fixed factors’ (hired labour, borrowed capital

and rented land) tend not to be major short-term drivers of income. Rents change so

slowly that they can be ignored as drivers of income change at group level, though or

course for individual farmers a rent increase can be a significant event.

A ‘fixed factor’ that carries the potential for cost changes that are volatile and unpredictable

is borrowed capital, in that, while the size of loans taken for land purchase and other

investments is unlikely to vary much in the short-term, this does not necessarily apply to

short-term loans taken to finance working capital and to assist farmers dealing with

fluctuation in their profitability. Also, interest rates are generally determined by factors

outside the control of farmers, and even outside the influence of agricultural policy; interest

rates may, in some circumstances shift in unpredictable and potentially damaging ways.

However, the evidence from FADN farms is that, over the period under study interest costs

have not been placing increasing pressure on the incomes from farming. This has happened

despite rises in level of borrowing. On average, the average size of long and medium-

term loans has been trending upwards, both before and after enlargement (Figure 36). So

too have short-term loans, though at a much lower level per farm. However, after a sharp

rise between 2007 and 2008, the overall amount of interest paid per farm has been in

decline.

€0

€1.000

€2.000

€3.000

€4.000

€5.000

€6.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Machinery & building current costs Energy Contract work Other direct inputs

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 36: Evolution of value of outstanding loans and annual interest per farm,

EU-25 2004-2006, EU-27 2007-2012

Source: DG AGRI EU-FADN.

4.2.9. Labour costs

Costs of hired labour are not a particularly major driver of the incomes of farms for EU

agriculture as a whole, though they can be important for some types of farming, such

as horticulture and granivores. Some countries will be more sensitive to changes in labour

costs than others because of their greater dependence on hired labour.

Labour as a factor of production can be important as a driver of farm income change for

two main reasons. First, there is the cost that farm businesses have to pay for hired labour.

Second there is the number of hired workers. Analysis of FADN results shows that the

volume of paid labour used on the average FADN farm (measured in hours of input) is

much smaller (less than a third) than the amount of unpaid (‘family’) labour (Figure 37).

Both categories have been declining, but the wages paid to the hired labour had been

rising, the result of increases in wages more than offsetting falling numbers of employees.

The average cost per farm has risen by almost

€1,000 between 2007 and 2012.

However, at EU-27 level the change is gradual.

€0

€200

€400

€600

€800

€1.000

€1.200

€1.400

€1.600

€1.800

€2.000

€0

€5.000

€10.000

€15.000

€20.000

€25.000

€30.000

€35.000

€40.000

2004 2005 2006 2007 2008 2009 2010 2011 2012

Interest paid

Value of outstanding loans

Long & medium-term loans Short-term loans Interest paid

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 37: Evolution of labour use and wages paid per farm, EU-25 2004-2006,

EU-27 2007-2012

Source: DG AGRI EU-FADN.

Another critical influence of the volume of labour is in the construction of income indicators.

As has been shown earlier, at both aggregate and farm levels, the most cited income

indicators are expressed per work unit (total or unpaid ‘family’ labour), depending on the

indicator. It is quite possible that income per farm or for the agricultural sector is declining

over time, but income per work unit will increase if the volume of labour declines

sufficiently quickly, as has commonly been found. This makes the accurate measurement of

labour inputs critical, though the ability to quantify it, especially the unpaid labour of self-

employed farmers and their families, is notoriously difficult, especially in the short-term.

€0

€1.000

€2.000

€3.000

€4.000

€5.000

€6.000

€7.000

500

1.000

1.500

2.000

2.500

3.000

3.500

2004 2005 2006 2007 2008 2009 2010 2011 2012

Wages paid

Paid and unpaid labour (hours)

Unpaid labour (hours) Paid labour (hours) Wages paid

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

5. DIFFERENCES BETWEEN MEMBER STATES

KEY FINDINGS

 A Common Agricultural Policy does not result in a common absolute level of

income for the average farm in different Member States. Belgium, Denmark,

Germany, France, Luxembourg, the Netherlands and the UK stand out as having

high farm income. Amongst the EU-N10 Member States, only in the Czech Republic,

Estonia and Hungary do farm income indicators exceed or come close to the EU-27

average.

 The main reason for this is the size of farms; the mix of farm types also plays a

role. However, when farms of the same size and type are compared, performance is

often equivalent throughout the EU-28 and sometimes higher in the EU-N10 and EU-

N2 than it is in the EU-15.

 The influence of farm structure is also important at the regional level with farm

incomes varying widely within Member States. This regional variation is especially

noticeable in France and Germany.

 In terms of the growth in farm incomes between figures averaged for the 2004-2006

and 2010-2012 periods, EU-N10 Member States have outperformed EU-15 Member

States as a result of higher market prices, access to the single market and

increased public support. The increase in farm income per unit of labour in these

Member States also reflects decreases in total labour use. Despite these increases,

farm income in the EU-N10 and especially the EU-N2 lags behind that in the

EU-15.

 Within this overall trend, farm incomes are highly variable from year to year, but

farm incomes in different Member States move in different directions and by

different magnitudes, partly the result of structural difference in farm type.

 Some Member States have higher levels of income variation than others. Again this

is partly structural with income in the granivore and fieldcrop sectors relatively

instable while income in horticulture and permanent crops is relatively stable.

The relatively low variability in farm income seen in Greece, Spain and Italy reflects

the substantial proportion of other permanent crop farm types in these Member

States.

 There is a tendency for EU-N12 Member States to have higher coefficients of

variation than EU-15 Member States, but this is partly the result of the general

upward trend in farm incomes that these Member States have experienced.

 Farm income levels differ between Member States within farm type, although this

is partly the result of the structure of farms within FADN. A key factor in differences

between Member States by farm type is actually farm size within the FADN sample.

 As economic size increases, it becomes more common for farms from the EU-N10

to show higher FFI/FWU than farms in the EU-15. For the largest size group, only

farms in Italy and the UK from the EU-15 have farm income higher than the EU-27

average.

 Agricultural wages differ markedly between Member States. In Denmark, the

Netherlands and Sweden wage levels average more than €15 per hour while in

Bulgaria, Greece, Latvia, Lithuania, Poland and Romania the average is

€3 or less.

 Agricultural wages vary little within Member States, although there are some

exceptions with wages higher in Champagne than in the rest of France and higher in

the east of Germany where the wages of company farm managers and

administrators are included in the figures.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Comparisons between Member States with regard to the incomes of farmers from

agriculture can be based on differences in a number of parameters. The most useful are

specific levels, directions of change and variability. While the focus of attention must be on

the rewards of self-employment in farming, the earnings of hired workers should not be

ignored as they are also seen as members of the agricultural community in some Member

States.

As in earlier chapters, there are two main source of information: Eurostat’s income

indicators based on the aggregate Economic Accounts for Agriculture, and the European

Commission’s Farm Accountancy Data Network EU FADN). Both are used here.

5.1. Differences in income levels

The main conclusion when comparing absolute incomes across Member States is that a

Common Agriculture Policy does not result in a common absolute level of income

in an average farm in different Member States, largely because size structure differs

by Member State. Using FADN results

, absolute levels of FNVA/AWU and FFI/FWU in

Member States, averaged of for the years 2010-2012 to allow for short-run changes at

group level, are shown in Figure 38. Seven Member States stand out as having relatively

high levels of both indicators during this period - Belgium, Denmark, Germany, France,

Luxembourg, the Netherlands and the UK. FNVA/AWU was considerably higher in Denmark

than in any other Member State

. The Czech Republic, Estonia and Hungary were the only

EU-N10 Member States where farm income indicators exceeded or were close to the EU-27

average.

The reader should recall that the field of observation of FADN differs by Member State meaning that in some

Member States small farms are not included in the results (see Annex 1). This has implications for EU level

results.

The difference between FNVA/AWU and FFI/FWU in Denmark (FNVA/AWU is more than twice FFI/FWU) reflects

the unusual dominance there of an approach to inter-generational transfer that involves children borrowing

from financial institutions to buy the farm from parents. This provides an asset which can provide a pension for

the parents but results in substantial interest payments which are included within FNVA, but are removed in

the FFI calculation. Heavy interest costs are often a stimulant to seeking off-farm jobs.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 38: FNVA/AWU and FFI/FWU by Member State (2010-2012 average)

Source: DG AGRI EU-FADN.

The explanation for these differences will include factors such as the predominant types of

farming and the market situation these faced in the period 2010-2012; it will also be a

function of management skill and other determinants of productivity. However, the main

factor will be the distribution of farms by size (and hence the average farm size). The

clear relationship between farm size and income levels (both FNVA/AWU and

FFI/FWU), which applies both generally and within types of farming, has already been

commented upon (Chapter 1). Those Member States that have predominantly large farm

business in FADN tend to have the highest incomes in Figure 39, and those with

predominantly small farms (Bulgaria, Romania, Greece and Portugal) are among the

countries that have the lowest incomes (see Map 1 for distribution by farm size within the

FADN sample). Supplementary analysis has shown that for farms of the same size and

type, farm performance is often equivalent throughout the EU-28 and sometimes higher in

the EU-N10 and EU-N2 than it is in the EU-15

For example, FFI/FWU averaged for the three years 2010-12 in the Romanian milk sector was €58,561 and

€55,388 in the Latvian milk sector compared to values between €26,473 in France and €50,709 in Ireland and

encompassing Belgium, Germany, Spain and the UK, amongst others.

€0

€10.000

€20.000

€30.000

€40.000

€50.000

€60.000

€70.000

€80.000

€90.000

€100.000

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

FNVA/AWU FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Figure 39: FADN coverage of economic farm size (ES) by Member State, 2010-

2012

Source: DG AGRI EU-FADN.

In countries that have a regional FADN structure there are often differences between

regions in absolute income levels, reflecting the geographical distribution of types of

farming and, to some extent, farm sizes (for example, Germany). Thus care has to be

taken, when comparing Member States in terms of absolute incomes, to recognise that a

single country average can hide substantial regional variations.

In terms of FNVA/AWU in the years 2010-2012 incomes were relatively high (>€40,000 per

AWU) in Belgium, the Netherlands and Denmark but also in most of England (not the South

West or West Midlands) much of northern France (Nord Pas de Calais, Picardy, Normandy,

Ile de France, Champagne, Lorraine, Centre, Burgundy and Poitou-Charentes) and northern

Germany (Schleswig-Holstein, Mecklenburg-Vorpommern, Niedersachsen and Sachsen-

Anhalt), and in the Lombardy region of Italy. France and Germany demonstrated a

particularly wide range of regional comparisons. In term of the lowest levels of FNVA/AWU,

these typified Latvia and Lithuania and many, though not all, of the regions of Poland,

Bulgaria and Romania, together with the Norte region of Portugal.

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

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

Proportion of farms represented in the FADN sample by

consolidated ES class

(1+2+3) 2 000 - <50 000 EUR (4+5+6) >=50 000 EUR

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Map 1: FNVA in Euro per AWU by FADN region, 2010-2012 average

Source: DG AGRI EU-FADN.

When turning to our preferred income indicator (FFI/FWU) for 2010-2012 a pattern

emerges that, while echoing that shown by FNVA/AWU, has substantial differences (Map 2).

The highest levels of income are no longer in Belgium and the Netherlands though they are

still found in regions of England, France and Denmark. In Germany the higher incomes are

concentrated in fewer regions (Mecklenburg-Vorpommern and Sachsen-Anhalt), and in

France there is a greater degree of regional differences than shown by FNVA/AWU with the

highest FFI/FWU in Picardy, Ile de France, Champagne, Centre and Poitou-Charentes. The

locations of regions with the lowest levels of income are broadly similar using either

indicator.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Map 2: FFI in Euro per FWU by FADN region, 2010-2012 average

Source: DG AGRI EU-FADN.

5.2. Differences in direction of change

The second income issue to examine is the way that income levels have changed over time.

In doing this it is important to bear in mind the potentially misleading impression that can

be gained by focusing on specific years. By using FADN’s FFI/FWU indicator averaged for

the 2004-2006 and 2010-2012 periods we have reduced the risk of presenting a misleading

impression somewhat (Figure 40). The data within FADN are nominal, so in real terms

increases would be rather less than suggested.

The average increase in FADN’s FFI/FWU between the two periods of 2004-2006 and 2010-

2012 was 59%. Only a small number of Member States saw a decrease in nominal terms

(Spain, Luxembourg and Malta). Belgium and Greece saw very small nominal increases

which in practice probably reflect a static real position. Most of the largest increases came

in the EU-N10, as might be expected given their lower starting point. Hungary, Lithuania,

Slovakia and Estonia all saw FFI/FWU more than double. Eurostat (2014) points to the

positive effects on these new entrants of an increase in public support granted to the farm

sector, higher market prices and access to the single market. The growth of incomes in

these countries reflects not only what is happening in the NVA (or FFI) per farm, but also in

the shedding of labour that was typical over this period. Eurostat (2014) also points out

that despite this positive performance, income in the EU-N10 still lags that in the EU-15;

income in the EU-N2 is further behind (see also Figure 6 in Chapter 3.2.3.1).

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

The large increase in FADN’s FFI/FWU in Sweden is the result of an unusually low starting

base while that in Denmark is a mixture of a very low value in 2004 and a very high one in

2012 which, despite the use of averages, has a substantial impact.

Other Member States saw growth in FADN’s FFI/FWU that was far smaller than typical;

most of the six with least growth were EU-15 countries (Luxembourg, Ireland, Belgium and

Finland), though two were EU-N10 (Malta and Hungary). However, Eurostat also points out

that, despite the successive income boosts experienced by the EU-N12, agricultural income

per AWU in 2014 for this group of countries came to an average around

€5,800 compared

to about

€24,500 for the EU

-15.

Figure 40: Change in FFI/FWU, average 2010-2012 vs average 2004-2006

Source: DG AGRI EU-FADN.

Note: Bulgaria and Romania compare 2010-12 with 2007-09.

5.2.1. Changes: short-term

Income levels and trends in income over a period do not insulate farmers from short-term

income movement. Though these may be anticipated and to some extent counteracted at

the farm level by steps such as choice of and mix between enterprises, informal and formal

insurance and other risk-reducing strategies, to which CAP and Member State policy

interventions may add further stability, nevertheless large short-term shifts in income will

place strain on the ability of farms to cope. Some indication of year-on-year change in

FFI/FWU is given in Figure 41. This shows that in any one year, while some Member States

saw a fall in FFI/FWU, others saw an increase. Member States which saw an increase

(decrease) in one year frequently saw a decrease (increase) in the next (17 Member

-50%

50%

100%

150%

200%

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

Change in FFI/FWU 2004-06 average vs 2010-12 average

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

States). Of course, some types of farming and some sizes of farm will have experienced

shifts that are both greater and lesser than the national averages, and individual farms

(rather than the group averages shown here) will have shown a further degree of

instability.

Figure 41: Annual change in FFI/FWU, 2010-11 and 2011-12

Source: DG AGRI EU-FADN.

However, as has been noted repeatedly, looking at changes between individual years is not

a reliable guide to the typical level of income variability within a country, even at national

level. For this, it is necessary to consider the variation over a run of years and the

conventional way of expressing this is as a coefficient of variation (described in Chapter

3.2.3.8). The key point is that this takes into account the different absolute levels of

income. The coefficients for the period 2004-2012 are shown in Figure 42.

The most noticeable feature is that some countries have far higher levels of income

variation than others, though this does not necessarily apply equally to both of the

income indicators chosen. In particular, Denmark shows an extraordinary degree of

instability in FFI/FWU (also seen in Figure 41); this reflects primarily the small margin left

from NVA after its typically high interest charges are deducted

(as well as rent and

wages) and hence small changes in NVA (which are not exceptional by the standards of

many other Member States) are transformed into very large shifts in FFI. There is a

tendency for EU-N12 Member States to have somewhat higher coefficients of variation than

the EU-27 average, but in part this will reflect the general trend of increasing incomes seen

in them.

See, for example, van der Veen, et al. (2002) who explain that this is partly a function of family farm transfer

between the generations using credit.

-50%

50%

100%

150%

200%

250%

300%

350%

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

2010-11 change 2011-12 change

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Attention has already been drawn to what appears to be inherent instability over time in

some types of farming (granivores and fieldcrops) and stability in others (horticulture

and other permanent crops), and variability at Member State level will reflect their

relative composition by type. The relatively low variability seen in Greece, Spain and Italy

reflects the substantial proportion of other permanent crop farm types in these Member

States (28% to 44% c.f, EU-27 average of 14%). Cyprus also has a high proportion of

permanent crops (42%), but incomes appear to be less stable because they have risen

steadily over the period.

Figure 42: Coefficient of variation of farm income indicators by Member State,

2004-12

Source: DG AGRI EU-FADN.

5.3. Comparisons between Member State incomes for each main

farm type (FADN data)

Figure 43 presents a comparison between FFI/FWU in all Member States for the main

eight farm types. This is presented in index form (EU-27 = 100) to facilitate comparisons

between farm types. Zero values (for example Fieldcrops: Luxembourg) indicate no data.

To a large extent the data reflect different national farm income levels such that for all farm

types incomes tend to be highest in EU-15 Member States.

For fieldcrops, the highest incomes are seen in Denmark, the UK and the Netherlands. The

Member States with above EU-27 average incomes are all from the EU-15. For

horticulture the largest incomes are found in the UK and Netherlands; FFI/FWU in

Hungary exceeds the EU-27 average. In the wine sector FFI/FWU is highest in Luxembourg

followed by France. Incomes in the Romanian wine sector are relatively low in FFI/FWU

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

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

Var FNVA/AWU Var FFI/FWU EU-27 FNVA/AWU EU-27 FFI/FWU

DK = 6.11

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

terms. For other permanent crops FFI/FWU is again relatively high in EU-15 Member

States, in this case Belgium and Denmark. Incomes in Greece and Portugal are below the

EU-27 average and comparable with the level in many EU-N12 Member States. In the milk

sector FFI/FWU is highest in Italy, with high levels also seen in the UK, Netherlands Ireland

and Belgium. The Czech Republic, Hungary and Malta all have approximately average

FFI/FWU in this sector. FFI/FWU in the other grazing livestock sector appear less

heterogeneous than in many other sectors and a number of EU-N12 Member States have

incomes at or above the EU-27 average (Cyrus, Czech Republic, Hungary, Latvia and

Slovakia). Denmark stands out as having had negative average FFI/FWU for the 2010-12

period

. FFI/FWU in the Italian granivore sector is more than three times the EU-27

average; this indicator is more than twice the EU-27 average in the UK. FFI/FWU in

Bulgaria, Malta and Romania is very much lower than is typical. FFI/FWU is more than five

times higher than the EU-27 average in the Belgian and UK mixed farm sectors and more

than four times the average in France and Netherlands. However, this result is partly the

result of the structure of farms within FADN. Some 29% of mixed farms in the sample are

in Poland and 44% in Romania and, because incomes are low in these Member States,

largely as a result of the number of small farms, this reduces the EU-27 average

considerably. FFI/FWU in Sweden was on average negative over the 2010-2012 period in

Sweden.

Figure 43: FFI/FWU by farm type and Member State, 2010-2012 average, EU-27 =

100

This is largely explained by the high borrowing and interest charges associated with inter-generational land

transfer which is a characteristic of this country.

-200

-100

100

200

300

400

500

600

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

Fieldcrops

-200

-100

100

200

300

400

500

600

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

Horticulture

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

-200

-100

100

200

300

400

500

600

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

Wine

-200

-100

100

200

300

400

500

600

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

Other permanent crops

-200

-100

100

200

300

400

500

600

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

Milk

-200

-100

100

200

300

400

500

600

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

Other grazing livestock

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Source: DG AGRI EU-FADN.

5.4. Comparisons between Member States of farms by economic

size group

Figure 44 presents a comparison between FFI/FWU in all Member States for the six farm

size groups as defined by Economic Size. This is presented in index form (EU-27 = 100)

to facilitate comparisons between size groups. Zero values indicate no data as a result of

the minimum size thresholds in use. A key difference from the investigation by farm type is

that there is much less difference between Member States suggesting that a key

factor in differences between Member States by farm type actually reflect the different

size structure which itself is influenced by the size thresholds used in FADN. In other

words, a comparison between Member States of a specific farm type is confounded by the

difference in size structure.

That said, FFI/FWU in Bulgaria and Romania is below the EU-27 average for the smallest

two size groups, although farm incomes in Slovenia were lowest in both cases. From the

25,000-50,000 EUR size group upwards, farm incomes in Romania start to be higher than

the EU-27 average and for farms in the two groups in excess of 100,000 EUR this is also

true for Bulgaria. In fact, as economic size increases, it becomes more common for farms

from the EU-N10 to show higher FFI/FWU than farms in the EU-15. For the largest size

group, only farms in Italy and the UK from the EU-15 have farm income higher than the

EU-27 average (farm incomes in Portugal equal the EU-27 average in this size class).

-200

-100

100

200

300

400

500

600

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

Granivores

-200

-100

100

200

300

400

500

600

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

Mixed

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 44: FFI/FWU by Economic Size and Member State, 2010-2012 average, EU-

27 = 100

100

200

300

400

500

600

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

(1) 2 000 - 8 000 EUR

100

200

300

400

500

600

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

(2) 8 000 - < 25 000 EUR

100

200

300

400

500

600

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

(3) 25 000 - < 50 000 EUR

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Source: DG AGRI EU-FADN.

5.5. Agricultural wages in Member States

For reasons that have been given above, agricultural wages are not treated alongside the

entrepreneurial incomes of farmers in this analysis. However, in view of the opinion among

some that they constitute part of the agricultural community for agricultural policy

purposes, they are included here. That said, it should be recalled that the determinants of

wage levels for hired workers are radically different from those that determine the residual

incomes of independent farmers. In particular, the level of wages paid in the rest of the

local economy will be a major determining factor.

100

200

300

400

500

600

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

(4) 50 000 - < 100 000 EUR

100

200

300

400

500

600

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

(5) 100 000 - < 500 000 EUR

100

200

300

400

500

600

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

(6) >= 500 000 EUR

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Comparisons between countries (and regions) have been made in terms of the average

calculated wage rate within FADN (the average amount spent on hired labour in the

national FADN sample divided by the average number of hours of labour supplied); this

may differ from other metrics (such as average wages or that found by national surveys of

hired employees working in agriculture).

The average of annual figures for the years 2010-2012 are shown in Figure 45. The degree

of difference between the highest wage countries and the lowest wage ones is very large –

the ratio between wages per hour in Denmark and in Bulgaria is in the order of 10:1. Three

countries (Denmark, the Netherlands and Sweden) have wage levels averaging more than

€15 per hour, whereas in six (Bulgaria, Greece, Latvia, Lithuania, Poland and Romania) it is

€3 or less.

Figure 45: Paid wages per hour (2010-12 average)

Source: DG AGRI EU-FADN.

5.5.1. Regional differences in wages paid

The regional variation of wages paid within countries is noticeably less than was observed

with the income of farmers (Map 3). For example, in France only one region (Champagne)

appears to have wages that are outside the range

€10

-15 per hour, whereas FFI/FEU was

spread over four different levels. Wages in Germany are similarly more homogeneous,

although are higher in the East where farm managers and administrators on large farms

are included which increases the average. This is in line with the hypothesis that the wages

paid are generally determined more by wages levels in the general national economy than

by the profitability of farming in particular regions (the Champagne region of France may

well be an exception).

€0

€5

€10

€15

€20

€25

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

Average wages paid EU-27

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

Map 3: Average nominal wages paid by FADN region, 2010-12 average

Source: DG AGRI EU-FADN.

An analysis of the variation of wages paid per hour was carried out along similar lines to

that applied to the income of farmers (Figure 46). This is difficult to interpret because the

level of wages has been rising relatively quickly in the EU-N12 Member States which is

included within the variation (whereas in the EU-15 they have been far steadier suggesting

less volatility). The countries with the seven highest coefficients of variation are all new

Member States. That said, Spain, Luxembourg, Austria and Finland are countries among

the EU-15 that have displayed relatively high coefficients of variation in the wages levels.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

Figure 46: Coefficient of variation in paid wages by Member State, 2004-2012

Source: DG AGRI EU-FADN.

0,05

0,1

0,15

0,2

0,25

0,3

0,35

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

Var hourly wage EU-27

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

100

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

101

6. RECOMMENDATIONS FOR FUTURE INCOME

SUPPORT UNDER THE CAP

KEY FINDINGS

Based on our analysis the recommendations to the European Parliament are that:

 Further consideration is given to the re-establishment of IAHS statistics, since

they are needed to assess the extent to which the CAP is achieving this core

objective of a fair standard of living.

 Data sources that relate to the entire economic activities of the households

(and other institutional units) that operate farms should be encouraged.

 A study be undertaken to assess the relative attributes of a safety net for the

incomes of farm households for the EU, including its costs, and the necessary

technical conditions that would be required for it to operate successfully.

 When considering the need for support of incomes, the wealth of agricultural

holdings should be taken into account.

 Suitable caveats should be used when FADN data are reported to make clear the

impact of the field of observation on the results.

 Consideration should be given to the need to represent people (farm holdings)

rather than production. A suitable balance needs to be struck between the current

production/land use focus of FADN and the social impact of the CAP.

 Attention should be diverted away from interventions that attempt to combat

instability directly at the farm level and towards risk management schemes that

prepare farm operators to better anticipate and cope with instability. This

could involve further studies.

 Consideration should be given as to how the occupiers of small farms can enhance

their economic prospects by building their skills and other forms of human capital.

 We recommend that policies that increase market participation and ease the

adjustment of farm businesses and households should be further supported and that

current impediments to access be examined.

In the terms of reference for this study on ‘Comparison of farmers’ incomes in the EU

Member States’ the European Parliament pointed out that the central aim of the CAP is to

support the incomes of farmers. It drew attention to Article 39(1)(b) of the TFEU which,

carried over the words of the earlier Treaties concerning the aims of the CAP specifically the

objective of ensuring a ‘fair standard of living for the agricultural community, in particular

the individual earnings of persons engaged in agriculture’. As noted in previous chapters,

neither the ‘fair standard of living’ nor the ‘agricultural community’ have been officially

defined in the policy context. However, it is clear that, where farm families have income

sources additional to what they receive from farming, these can be important in

determining their overall standard of living.

6.1. The need for reliable statistics on agricultural household

incomes

Our ability to describe and comment on the central components of the ‘farm problem’ in the

EU – poor comparability of incomes between farmers and other groups in society, poverty

Policy Department B: Structural and Cohesion Policies

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102

among farm households, and income instability (or volatility) is severely hampered by poor

data availability. As has been established earlier in this analysis, in many Member States

data do not currently exist by which the disposable income of agricultural households

(proxies for their standards of living) might be assessed.

Although Eurostat has in the past attempted to set up statistics on this subject (Income of

the Agricultural Households Sector – IAHS – statistics), currently no operational official EU

monitoring system exists by which the total household incomes of farmers can be assessed

and compared with other groups in society or their evolution monitored. This represents a

major gap in information relevant to the performance of the CAP. While a feasibility study

has been made to rebase the Eurostat statistics on a uniform basis in Member States,

following comments by the European Court of Auditors (2004) and endorsed by the

Council, and potential data sources by which this could be done have been identified, no

action has been taken since it reported in 2007. A recommendation to the European

Parliament is that further consideration is given to the re-establishment of IAHS

statistics, since they are needed to assess the extent to which the CAP is

achieving this core objective of a fair standard of living.

The EU system of monitoring incomes at the farm level (FADN) does not currently collect

data on incomes received by farm operators from non-farm sources, though in some

Member States the national survey that contributes to FADN does cover this other income.

At national level there is often little or no information on the numbers of farm households

that are considered to be in poverty

. Also, variability of household income is likely to be

less extreme than that seen in the profits from farming because of the more stable other

sources of income that many farm families receive. This lack of farm household data is for

a range of reasons but primarily because farmers in many countries are not taxed

according to their accounted income but on other bases; in many instances these special

treatments provide benefits (‘tax expenditures’ or concessions) that are not usually counted

when measuring the public support of agriculture, but can form part of the explanation why

some operators remain in agriculture (Defra, 2012; OECD, 2005). In such countries

taxation records are not a source of relevant information on incomes. A second

recommendation, closely allied to the first, is that data sources are encouraged

that relate to the entire economic activities of the households (and other

institutional units) that operate farms. In addition to assisting with income

measurement, such data are highly likely to be relevant to understanding issues such as

the viability, sustainability and resilience of farm firms

, their intensity of land use,

investment levels and succession patterns. In other words, the sort of issues which are

addressed through the second pillar of the CAP (although take up of specific measures,

such as risk management tools, is a decision for Member States

Although the picture is currently imperfect and incomplete, from the fragmented statistics it

appears that, as a group, farmer households in most Member States are not a particularly

A rare exception is Ireland where there are special payments for landholders whose incomes fall below

specified thresholds (the so-called ‘farmers dole’). Some 20-25% of holders seemed to qualify in the 1980s. A

sharp rise was noted between 2008 and 2010 in numbers who actually received the means-tested benefit (the

Farm Assist Scheme), a period over which incomes from farming dropped sharply; in the latter year about ten

thousand farmers had their income poverty means tested and were paid, about 10% of the total number of

self-employed farmers. It was evident that this benefit was regarded as a last resort by farm households and,

according to the farming press, many more who might have qualified did not apply (quoted in Hill (2012) Farm

Incomes, Wealth and Agricultural Policy, CABI p. 49.)

For example, see Defra (2012).

Under Commission Delegated Regulation (EU) No 807/2014 and Implementing Regulation (EU) 808/2014, the

detail of the risk management tools to be used is largely left to the Member State which means that they will

not be uniform across the EU.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

103

low income sector in society. This finding potentially eases the path of CAP reform. If

approximate parity can be assumed, attention could then be focused on other aspects of

the income problems that agriculture faces, such as instability, including the provision of

(stable) policy payments for the provision of environmental services and risk management

tools. Of course, change to the current support system might threaten the relative income

position of the farming community in the short-term, but action to counter this could not be

justified without the sort of evidence that a robust monitoring system, currently lacking but

which has been proposed, could provide. Sector-average figures would not be enough, and

information necessary to enable targeting on low-income cases would be needed. Whether

the problem of low disposable incomes among certain types of farmers is addressed

through the CAP or through general policies on poverty is a matter that would need debate.

When considering policy alternatives it would be wise to look beyond the current poor

statistical situation. Data availability can change. Thus it would be wrong to ignore a radical

‘social’ approach to supporting the income of poor farmers that identified farm households

that had incomes below some level deemed to be the minimum ‘fair’ level and provided

payments to bring them up to that level (supplying a household safety net). Though no

assessment of the impact and costs of such a system for the EU or any individual Member

State seems to have been published, analysis for the US (Gundersen et al., 2000) suggests

that such payments directly targeted at low-income farm households could not only

achieve the living standard objective more effectively than the current system but that the

total public cost would be lower than under the present support arrangements (Box 9). In

the US there would be an unmistakeable redistribution so that, while low income

households would receive more than at present, many of the recipients of large payments

would experience falls; this is probably a factor that caused the attention in the US to shift

over the first few years following the publication of this ERS analysis from the notion of a

safety net applying to farm households to one applying to the revenues or profits from the

farm business.

Box 9: Safety net for farm households (based on Gundersen et al., 2000)

Government assistance to the US farm sector provides relatively little to small farms.

Instead, most government assistance through traditional farm program instruments is

to larger farms. This report looked at the issue from a different perspective, one which

might have reduced government spending and ensure that all full-time farmers received

an income to meet basic needs. It applied the concept of a farm household safety net

based on a set of standards commonly used in the economics literature and in Federal

assistance programs for low- to moderate-income households.

The report considered four safety net scenarios that would assure farm households a

certain level of income or consumption:

 Income equal to that of the median non-farm household in the region.

 Income equal to 185% of the poverty line.

 Income equal to the average nonfarm household's annual expenditures.

 Income equal to the median hourly earnings of the non-farm self-employed ($10 per

hour).

The analysis estimated the distribution effects and costs of the four scenarios for two

time periods: 1993-97 and 1999-2003. Under any of the four safety net scenarios all

very small farm households would receive payments and payments per recipient to

other small farms would be more than twice as high as under existing programs.

Larger farms would lose in the new system. In terms of the total cost the new system

Policy Department B: Structural and Cohesion Policies

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104

would result in lower public expenditure as long as the safety net threshold was less

than about $30,000. Of course, this mechanism could be combined with the

continuation of some programs (such as environmental ones), in which situation the

overall cost would reflect that mix.

Given that evidence for the EU points to a similar distribution of benefit under the CAP, with

the bulk of payments going to the larger farms and small farms getting relatively little, the

general findings are likely to apply too (although it should be noted that there is a greater

element of redistribution under the 2014-2020 CAP, see European Parliament (2015b)).

However, the absence of adequate data on household income of farmers in many Member

States currently prevents detailed assessment. Nevertheless, a further recommendation

is that a study be undertaken to assess the relative attributes of a safety net for

the incomes of farm households for the EU, including its costs, and the necessary

technical conditions that would be required for it to operate successfully.

should be noted that our use of the term “safety net”, which relates to the household,

differs from that in Agrosynergie (2013) where the term relates only to the transformation

of market intervention under Council Regulation (EC) 73/2009.

Moving from incomes to wealth, from the perspective of social equity it does not seem

reasonable that the assets held by farm families, and real gains made on them, should be

ignored when considering support for their standards of living. Current income

measurement, whether of household incomes or of the income from farming alone, ignores

wealth and capital gains (or losses), yet such factors are important to strategic decisions,

such as that to stay in or exit from farming. One of the drivers of land prices is the

preferential treatment given in taxation systems in many Member States to wealth in the

form of agricultural assets, particularly to capital gains on agricultural land and on its

transfer between generations (OECD 2005). A recommendation is that, when

considering the need for support of incomes, the wealth of agricultural holdings

should be taken into account. A step in this direction would be a comprehensive

inventory of the way in which Member States treat agricultural assets in capital taxation.

6.2. Statistics based on people rather than production

One of our main sources of data from which we have calculated results is FADN. It is worth

noting that this dataset is oriented towards covering production rather than individual

farmers. A consequence of this is that Member States apply thresholds based on Economic

Size that vary between countries. As an outcome, the smallest sizes of farms only contain

data from a limited number of Member States. Only when an economic farm size of

€25,000 is reached are all Member States present in the data.

This can lead to some misconceptions when discussing the situation among small farms and

also means that average income in those Member States where data from small farms are

included is biased downwards. However, it is still the case that average farm incomes in

Member States with a large proportion of small farms will be lower than in Member States

with fewer small farms, even though these are excluded from FADN.

It is worth noting that such a ‘social approach’ to support was outlined, and roughly costed, by the Commission

in its 1985 Green Paper Perspectives for the Common Agricultural Policy (Commission 1985c). Thought to

concern some 1 – 1.5 million farmers at the time and imply a cost of 1,000 million Ecu per year at the

beginning, it could be limited to the existing generation of farm holders and thus become self-eliminating.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

105

We therefore recommend that suitable caveats be used when FADN data are

reported to make clear the impact of the field of observation on the results. A

related recommendation is that consideration be given to the need to represent

people (farm holdings) rather than production. A suitable balance needs to be

struck between the current production/land use focus of FADN and the social

impact of the CAP.

6.3. Income stabilisation

The issue of income stabilisation can be considered at the level of the farm household or of

the farm business. The two are, of course, related, since the main cause of household

variation between years is likely to be the profits from farming

. Instability (volatility) at

the farm business level may lead to inefficiencies in resource use and (in extreme cases not

seen for some time in the EU) threaten security of supply. Chapter 1 presented evidence on

the extent of income variation at the group and individual farm levels, the latter being the

larger, and the case for averaging over three years as a norm when assessing farm

incomes. It is clear that income instability is greater in some types of farming than in

others, and that the main driver of short-term variation is price volatility in the markets for

farm products. It is also clear that, in retrospect, concerns over income levels in single

years and shifts between years can give an exaggerated impression of longer-term

movements; for example, 2009 proved to be a passing experience of depressed income

levels rather than a precursor of persistent low incomes. It is also apparent than the

incomes from farming are relatively less stable among small farms than among large ones.

Knowing about income instability is one thing. Taking action to combat it, with the intent of

producing a net benefit to society, is quite another. Some EU countries (UK, Ireland and

the Netherlands) already achieve a degree of smoothing of year-on-year income

fluctuations by means of averaging in the tax system. France enables farmers who are

taxed on their accounted income to deduct as an expense payments deposited in a

‘professional savings account’ that can be drawn down in circumstances such as a sharp

decrease in income. Sweden has a similar arrangement.

At the EU level, since Agenda 2000, an explicit aim of the CAP has been to contribute to the

stability of farm incomes. Reforms, notably the introduction of the Single Payment Scheme

and now the Basic Payment Scheme, have changed the economic environment of farming

with support now more targeted

. Opinion is not uniform on the impact of direct income

support on farm income stability. However, it is clear that farmers are now expected to

take prime responsibility for coping with market-related risk and uncertainty. This has led

to a much increased level of policy interest in risk management initiatives by the European

Commission, which published or sponsored several important studies on the management

of risk and uncertainty between 2001 and 2009 (European Commission, 2001, 2005a,

2005b; JRC 2006, 2009; LEI, 2007)

. It concluded that successive reforms to the CAP,

while encouraging European farmers to be more market oriented, left agriculture open to

crises caused by natural disasters, livestock diseases or plant pests, or economic crises

such as caused by the unexpected closure of important export markets. These may

endanger a farm's viability or even affect the economic stability of an entire rural area.

Incomes from OGAs and on-farm diversification may also be variable, but data are not yet available through

FADN, although information on diversification will be collected in the future. If income from these activities is

unrelated to agricultural income then it will stabilise household income, although if it varies in the same way as

agricultural income it could make household income more volatile.

For a review of the latest CAP reform, see European Parliament (2015b).

Other, more recent, work on this subject includes European Parliament (2015a) and Meuwissen, et al. (2008).

Policy Department B: Structural and Cohesion Policies

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106

Among the options considered by the European Commission (2001) as potential ‘fields of

action’ for intervention using public funds were:

 Providing the conditions in which private markets in risk reduction instruments can

work (such as the legislative framework, or training on risk management tools for

farmers)

 Lowering the costs of risk-management tools, such as by providing subsidies for

insurance or re-insurance (see more recently European Parliament, 2015a).

Subsidies could also be justified on a temporary basis to encourage the development

of market solutions. This might include assistance to setting up mutual support

schemes, or tax concessions for establishing reserve funds.

 Providing public risk coverage, e.g. by providing disaster aid payments, public

insurance and re-insurance, or a specific safety net in which payments are made

direct to farmers, the last being a new form of instrument within the CAP.

The OECD has also issued a number of studies on risk in agriculture (OECD 2000, 2008a,

2008b, 2009). Points made that are significant in the present context are (a) the

widespread lack of information on whole-farm income instability; and, (b) the ability to tier

risks into layers, though their margins are rather blurred. The layers comprise, first, normal

commercial risk that farm operators could be expected to shoulder and cope with by

traditional means such as diversifying their business (a move that runs counter to the trend

towards greater specialisation seen among EU farms) or entering into contracts with buyers

or more sophisticated financial instruments such as hedging. Second, there are risks for

which market insurance is available (such as fire). Third, there is market failure risk,

where, for reasons including lack of information, private insurance solutions do not present

themselves. Examples of the last include catastrophic drops in income caused by prolonged

droughts, outbreaks of animal disease that disrupt normal patterns of trade, and historical

incidents and events. Typically these depress incomes in a widespread way, perhaps of all

the farms in a particular region.

The distinction between periods of low incomes flowing from natural disasters and those

resulting from other causes is important, as different sets of rules apply under international

trade agreements as to what can trigger government intervention and the degree of

support that can be offered. Safety-nets, applied to the farm business (as opposed to the

household, discussed earlier), whereby direct payments (‘counter-cyclical payments’) are

made to individual farms suffering low incomes, are superficially attractive in that they give

support only when needed and not when incomes are satisfactory, thereby improving the

efficiency of public spending. Rules under the Agreement on Agriculture that forms part of

Uruguay GATT Agreement of 1993 (formally signed in 1994 and carried forward into the

World Trade Organisation rules) have the effect of constraining the amount of safety net

support. These say a farm can only be eligible for safety-net payments if its income (the

definition of which is not specified) from agriculture becomes less than 70% of its average

income of the preceding three years (or an average of three out of the previous five,

leaving out the highest and lowest, the so-called ‘Olympic average’). Moreover, the

payments must not be greater than 70% of the shortfall between the income of the

particular year and the three-year average.

See European Parliament (2014a) on the limits of EU regulation on agricultural derivatives and the issue of

competence for this topic within Commission Services.

Comparison of farmers’ incomes in the EU Member States

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107

A few non-EU countries have used safety-net scheme following these trade rules (the main

examples being USA and Canada)

. Though the EU has not operated schemes along the

lines used in the US or Canada, simulation exercises have been conducted by the European

Commission using FADN data. In 2001 the Commission published estimates of the cost of

topping up income (Family Farm Income) of the individual farm to 70% of the average

income in its previous three years. In 1997, 20% of FADN farms (EU-12) would have

qualified for safety net payments and cost a total of

€3

.5 billion. In the UK in 1996 some

12.5% of farms would have received payments, but this rose to 24.5% in 1997.

A similar exercise using FADN (EU-15) was carried out as part of the Impact Assessment of

the 2008 CAP Health Check. The period covered was 1989 to 2003. Eligibility for

stabilisation payments was again restricted to farms that had suffered an income fall of

greater than 30% compared with its historical average, but Farm Net Value Added (FNVA)

was this time the preferred income indicator. The largest shares of expenditure for the

period as a whole, if such a programme were introduced, were found to be Italy (20%),

Spain (18%), France (15%) and Germany (14%). Total cost varied from

€8

billion to

€12

billion per year, averaging

€9.3

billion (which might be compared with Pillar I spending in

2007 of

€43

billion).

The Commission has revisited this issue in the context of the 2013 CAP reform. European

Commission (2011a) examined extending the current framework for insurances and mutual

funds; an Income Stabilisation Tool (IST); and, a crisis fund. The annual cost of the IST

was estimated at

€7 billion on the assumption that about 20% of farmers were

compensated for a 30% income loss. This compares to an appropriation of between

€36

billion and

€40 billion on direct payments in the 2014 to 2020 programming period

(European Parliament, 2015c). The Commission concluded that insurances and mutual

funds could contribute to both increasing the stability of income and mitigating the effects

of production risks, although care would be needed to avoid distorting production decisions.

The Commission also concluded that a "one size fits all" solution would not be appropriate

given the heterogeneity of risks faced.

Though the budgetary cost of making countercyclical direct payments to farms

specifically to help them cope with income instability, up to the limits permissible, is low

compared with that of Single Payments/Basic Payments

which gives support irrespective

of income need, such safety nets have some substantial drawbacks as far as the

Commission is concerned. These include the wide variability from year to year in the

number of farms qualifying for payments and in the aggregate cost

, an unwelcome

feature when generally the move has been towards making the costs of the CAP more

rather than less predictable; some additional tool to limit the expenditure might be needed.

Differences between the relative amounts of benefit going to particular Member States

compared with what they receive under the present arrangements could be a political

stumbling block. From the perspective of the farmer, support may be available only when

the most pressing need for support has passed and possibly too late, though a system of

interim payments may circumvent this disadvantage.

In the US ‘Agricultural Gross Revenue’ and ‘Agricultural Gross Revenue-Lite’ were introduced in a pilot capacity

in 2001 and 2003 respectively. In Canada the Income Stabilisation (CAIS) programme, introduced in 2003.

The later scheme – AgriStability – retained the essential characteristics of its predecessor. These are reviewed

in Hill (2012).

Mary, et al. (2013) investigated the impact of an Income Stabilisation Tool and concluded that the impact

would vary from farm to farm.

See European Parliament (2013a) for details at the Member State level.

Variability in annual cost would also be an issue given that annual (rather than multi-annual) payments form a

principle of the EU Budget.

Policy Department B: Structural and Cohesion Policies

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108

Most recently, Article 39 of Regulation (EU) No 1305/2013 on support for rural

development provides Member States with the option of supporting an income stabilisation

tool in the form of financial contributions to mutual funds and providing compensation to

farmers for a severe drop in their income. Under this measure, up to 70% of lost income

can be reimbursed by a mutual fund if income drops by at least 30% below a three-year

average figure

. For every

€1 paid in by the farmer, an additional €0.65 is to be added

from the CAP’s second pillar. Direct payments and all other public support are considered

as ‘income’ under the rules. At the time of writing it is not clear how farmers will

demonstrate their income levels, especially where they are not required to keep an

account. European Commission (2015) reports that, as of 21 May, 2015, 13 Member States

had taken up the risk management option in 15 RDPs. Some

€2.7 billion of

public funds will

be spent and 675,000 holdings will participate. Almost all the funds (€2.2 billion) will be

allocated to insurance premiums, €417 million to mutual funds and €130 million to income

stabilisation.

A key factor that apparently rules out the use of a comprehensive income safety net within

the CAP is the lack of a data system to enable it to operate

. Information of high quality

from each individual farm in the EU would be needed. Both the US and Canada base their

safety nets on data supplied by farmers from their accounting systems to their national

taxation authorities. There are severe penalties for false accounting. The data therefore

has a good degree of quality assurance, within the conventions used for the purposes of

taxation. As has been pointed out, in many EU Member States some or all farmers do not

have to submit income accounts for taxation, being assessed on a flat-rate (area-linked)

basis. Though income data will be available for holdings that happen to be in the FADN

sample, these form only a small minority. The lack of reliable income data for a large

number of EU farms rules out the possibility of introducing a safety net along the lines

allowed under international trade rules. To set up a special system to enable a CAP safety

net to work would take time and involve a large administrative burden, both on national

governments and on individual farms, factors which make it highly unattractive. Also

because personal taxation is something over which Member States retain sole competence,

there is no practical possibility of all EU countries adopting tax systems that compel their

farmers to keep tax accounts that might supply the income data necessary to implement an

income safety net.

We therefore recommend that attention is diverted away from interventions that

attempt to combat instability directly at the farm level and towards schemes that

prepare management on farms to better anticipate and cope with instability.

6.4. Support for small farms

One feature of the CAP reforms agreed in late 2013 and to be applied from 2014 or 2015

was the special support system for small farms (the Small Farmers Scheme - SFS).

Optional for Member States, any farmer claiming support may decide to participate in the

Small Farmers Scheme and thereby receive an annual payment fixed by the Member State

of normally between

€500 and €1,250, regardless of the farm size. Member States may

choose from different methods to calculate the annual payment, including an option

whereby farmers would simply receive the amount they would otherwise receive. The

Commission claimed that this will be an enormous simplification for the farmers concerned

Either the farmer’s average income in the past three years or a three year average from the preceding five

years excluding the highest and lowest values.

See also European Parliament (2015a) for other complicating factors.

Comparison of farmers’ incomes in the EU Member States

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109

and for national administrations. Participants will not be subject to cross-compliance

controls and sanctions, and will be exempt from greening. The related impact assessment

(quoted in European Commission, 2011b), showed that approximately one third of farms

applying for CAP funding have an area of 3 hectares or less, but this accounts for just 3%

of the overall agricultural area in the EU-27.

Evidence presented in this report suggests a clear link exists between the economic

size of farm business and the income per Work Unit received. Also, farms of

economic size greater than

€25,000 of Standard Output in Member States that joined the

EU in 2004 and 2007 seem to perform at levels similar to those seen in EU-15, and in the

largest size groups farms in N-2 appear to outperform those in other countries. If there is a

problem of a low income level from farming activity, the strategic solution is to facilitate the

growth of farm sizes, and specifically the exit of operators who currently depend on the

farm for their incomes, but whose scale of operations are too small

. This will enable

remaining farms to absorb the released land, though history suggests that this may not go

primarily to enable small farms to expand, but may be absorbed by larger units that are in

a strong position to bid for it by purchase or rent.

The appropriate policy response is to put in place forms of support that assist

households with small farms to develop other sources of income, either on the farm

or elsewhere in the economy (this is distinct from the Small Farmers’ Scheme under the

2014-2020 CAP). Rural Development Programmes, funded in part by the CAP’s Pillar 2,

often already have schemes to provide vocational training, but the strategic need is for a

broader range of enabling skills. While diversification frequently requires business training,

factors such as the general level of education may also be important, together with the

ability to work in sectors that are often little connected with agriculture, but which can be

carried on in combination with farming. In Member States where there are fewer non-

agricultural employment opportunities, these require creation, something that Rural

Development Programmes can assist with. History and empirical evidence suggests that

there is almost no professional or commercial activity that cannot be found in combination

with farming, lending important attributes to the farm operator’s existence that often goes

beyond additional incomes, such as financial stability, resilience in times of adversity, more

social contacts and other benefits.

A recommendation for policy is that consideration is given as to how the

households that occupy small farms can enhance their economic prospects by

building their skills and other forms of human capital.

6.5. Balance between support and market orientation

Our analysis has established that subsidies (which include the increasingly important

payments to farmers for the provision of public goods such as environmental services) are

not the main source of revenue of EU farms, and sectors that generate the highest incomes

(FFI/FWU) for their operators tend to be those where subsidies have the least relative

significance. This greater market orientation, and the flexibility to respond by

adjusting size and other characteristics, seems to be an important characteristic of

successful farms.

There is a small incentive under the second pillar of the CAP for farmers who are eligible for SFS to transfer

their holding permanently to another farmer. The value of this incentive is 120% of the eligible payment.

However, this is only a weak incentive and may lead to the creation of notional transfers that will not impact

on operational structure.

Policy Department B: Structural and Cohesion Policies

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110

Discussions on support have been conducted primarily with direct payments under the

CAP’s Pillar 1 in mind (these have accounted for the main expenditure). However, this is

often a too narrow approach. Provision of assistance to structural adjustment has

already been mentioned above, but there are several other measures within Pillar 2 that

are important in supporting indirectly the incomes of farm occupiers and in facilitating their

development, thereby assisting in achieving the CAP’s central objective of a fair standard of

living for the agricultural community.

Rural Development Programmes frequently aim to increase farm productivity and

competitiveness by measures that facilitate knowledge transfer, develop management

capacity, encourage better marketing and the establishment and maintenance of

cooperation. The assistance they offer to the development of on-farm diversification and to

off-farm occupations, mentioned above in the context of small farms, is, of course, more

generally relevant and applicable across the size spectrum. We recommend that policies

that increase market participation and ease the adjustment of farm businesses

and households should be further supported and that current impediments to

access be examined.

Comparison of farmers’ incomes in the EU Member States

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111

REFERENCES

 Agra CEAS Consulting (2007) Feasibility Study on the Implementation of Income of

Agricultural Households Sector (IAHS) Statistics. Final Report for European Commission

(Eurostat).

 Agra CEAS Consulting (forthcoming) Costs and Good Practice in FADN Data Collection.

Final report for DG AGRI, European Commission. AGRI-2014-EVAL-01.

 Agrosynergie (2013) Evaluation of the Structural Effects of Direct Support. Final Report

to European Commission. July, 2013.

 Barthomeuf, L.-T. (2008) Other Gainful Activities, Pluriactivity and Farm Diversification

in EU-27. LTB D(2008), 17488, European Commission, Directorate General for

Agriculture and Rural Development, G.2. Economic analysis of EU agriculture, Brussels.

 Canberra Group (2001) Expert Group on Household Income Statistics – The Canberra

Group: Final Report and Recommendations. Ottawa.

 Commission of the European Communities - see also European Commission below.

 Commission of the European Communities (1982) Indicators of Farm Income. Working

document of the Services of the Commission, VI/308/82 EN (0082d). The Commission,

Brussels.

 Commission of the European Communities (1985a) Agricultural incomes in the

Community. Green Europe Newsflash 29. The Commission, Brussels.

 Commission of the European Communities (1985b) Income Disparities in Agriculture in

the Community. Green Europe 208. The Commission, Brussels.

 Commission of the European Communities (1985c) Perspectives for the Common

Agricultural Policy – The Green Paper of the Commission. European Community

Newsflash: Green Europe. 33. The Commission, Brussels. Also COM(85) 333 final.

 Commission of the European Communities (1989) The European Farm Accountancy

Data Network: an A,–Z of Methodology. Directorate General for Agriculture, Unit A-3,

Analysis of the situation of Farm Holdings, The Commission, Brussels.

 Commission of the European Communities (2001) Risk management tools for EU

agriculture, with a special focus on insurance. Working Document, Agriculture

Directorate-General. The Commission, Brussels.

 Commission of the European Communities (2005a) Communication from the

Commission to the Council on risk and crisis management in agriculture. COM, 74. The

Commission, Brussel

 Commission of the European Communities (2005b) Commission Staff Working

Document on risk and crisis management in agriculture. SEC (2005) 320 [COM(2005)

74]. The Commission, Brussels.

 Cordts, W., Deerberg, K. H. and Hanf, C. H. (1984) Analysis of the intrasectoral income

differences in West German agriculture. European Review of Agricultural Economics, 11,

pp323–342.

 de Frahan, B. H., Nkunzimana, T., De Blander, R., Gaspart, F. and Sumner, D. A.

(2008) Farm Household Incomes and Reforming the CAP. Paper prepared for the 109th

EAAD Seminar; The CAP after the Fischler Reform: National Implementations, Impact

Assessment and the Agenda for Future Reforms', Viterbo, Italy.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

112

 Defra (2012) Farm Household Income and Household Composition: Results from the

Farm Business Survey: England 2010/11. Published 30 August, 2012.

 ECA (2004) Measurement of Farm Incomes by the Commission. Special Report No

14/2003, Court of Auditors of the European Communities, Luxembourg [also appeared

as Court of Auditors (2003)].

 European Commission (1997) AGENDA 2000: for a stronger and wider Union.

Document drawn up on the basis of COM(97) 2000 final. Bulletin of the European Union

supplement 5/97. ISBN 92-828-1034-8.

 European Commission (2008) COMMISSION STAFF WORKING DOCUMENT

accompanying the Proposals for COUNCIL REGULATION establishing common rules for

direct support schemes under the common agricultural policy for farmers and

establishing certain support schemes for farmers COUNCIL REGULATION on

modifications to the common agricultural policy by amending Regulations (EC) No

320/2006, (EC) No 1234/2007, (EC) No 3/2008 and (EC) No […]/2008 COUNCIL

REGULATION amending Regulation (EC) No 1698/2005 on support for rural

development by the European Agricultural Fund for Rural Development (EAFRD)

COUNCIL DECISION amending Decision 2006/144/EC on the Community strategic

guidelines for rural development (programming period 2007 to 2013) Impact

Assessment. {COM(2008) 306 final} {SEC(2008) 1886}. Brussels, 20.5.2008.

SEC(2008) 1885.

 European Commission (2009) Why Do We Need A Common Agricultural Policy?

Discussion Paper by DG Agriculture And Rural Development December 2009.

 European Commission (2010a) Consultation Document for Impact Assessment of the

Reform of the CAP towards 2020.

 European Commission (2010b) The CAP towards 2020: Meeting the food, natural

resources and territorial challenges of the future. Communication from the Commission

to the European Parliament, the Council, the European Economic and Social Committee

and the Committee of the Regions. Brussels, 18 November 2010, COM(2010) 672 final.

 European Commission (2010c) Developments in the income situation of the EU

agricultural sector. Brussels, December 2010.

 European Commission (2011a) Commission Staff Working Paper, Impact Assessment on

Risk Management, Common Agricultural Policy towards 2020, Annex 6. SEC (2011)

1153, October 2011.

 European Commission (2011b) CAP Reform – an explanation of the main elements.

MEMO/11/685. Brussels, 12 October 2011.

 European Commission (2013) Structure and dynamics of EU farms: changes, trends and

policy relevance. EU Agricultural Economics Briefs. No 9, October, 2013.

 European Commission (2014a) CAP context indicators 2014-2020, December 2014

(http://ec.europa.eu/agriculture/cap-indicators/context/2014/full-text_en.pdf)

 European Commission (2014b) EU farm economics overview based on FADN data 2011.

September 2014. DG Agriculture and Rural Development.

 European Commission (2014c) Definition of variables in FADN standard results. RI/CC

882 Rev. 9.2. Community Committee for the Farm Accountancy Data Network.

December 2014.

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

113

 European Commission (2015) The CAP towards 2020: Implementation of Rural

Development Policy. State of Play of RDPs. Based on information available on

21.05.2015.

 European Parliament (2013a) European Council Conclusions on the Multiannual

Financial Framework 2014–2020 and the CAP. Note for Directorate-General for Internal

Policies Policy Department B: Structural and Cohesion Policies Agriculture and Rural

Development. Authors: Little, J., Massot, A., Ragonnaud, G. and Tropea, F.

 European Parliament (2013b) Possible effects on EU land markets of new CAP direct

payments. Study for Directorate-General for Internal Policies Policy Department B:

Structural and Cohesion Policies Agriculture and Rural Development. Authors:

Swinnen, J., Ciaian, K., Kancs, d’A., Herck, K. van and Vranken, L.

 European Parliament (2014) Financial Instruments and Legal Frameworks of Derivatives

Markets in EU Agriculture: Current State of Play and Future Perspectives. Study for

Directorate-General for Internal Policies Policy Department B: Structural and Cohesion

Policies Agriculture and Rural Development. Author: Vander Stichele, M.

 European Parliament (2015a) Comparative Analysis of Risk Management Tools

Supported by the 2014 Farm Bill and the CAP 2014-2020. Study for Directorate-General

for Internal Policies Policy Department B: Structural and Cohesion Policies Agriculture

and Rural Development. Author: Cordier, J.

 European Parliament (2015b) First Pillar of the CAP: II – Direct Payments to Farmers.

Fact Sheets on the European Union – 2015.

 European Parliament (2015c) The Common Agricultural Policy in Figures. Fact Sheets on

the European Union – 2015.

 Eurostat (1995) Manual of the Total Income of Agricultural Households (Rev.1), Theme

5 Series E. Eurostat, Luxembourg.

 Eurostat (1997) Manual on the Economic Accounts for Agriculture and Forestry (Rev.1).

Eurostat, Luxembourg.

 Eurostat (2000) Manual on the economic accounts for Agriculture and Forestry

(Rev.1.1). Theme 5. Eurostat, Luxembourg.

 Eurostat (2002) Income of the Agricultural Households Sector – 2001 Report. Theme 5,

Eurostat, Luxembourg.

 Eurostat (2010) Draft Version of European System of Accounts: ESA 2010. Eurostat,

Luxembourg.

 FAO (2011) Statistics on rural development and agricultural household income. Wye

Group Handbook: Second edition. Ed. Berkeley Hill and Graham Eele. 2011.

http://www.fao.org/wairdocs/am087e/am087e.pdf

 Gardner, B. L. (1992) Changing economic perspectives on the farm problem. Journal of

Economic Literature. 30, pp62-101.

 Gundersen, C., Morehart, M., Whitener, L., Ghelfi, L., Johnson, J., Kassel, K., Kuhn, B.,

Mishra, A., Offutt, S. and Tiehen, L. (2000) A Safety Net for Farm Households. AER-

788, Economic Research Service, USDA, Washington.

 Hazell, P. and Wood, S. (2008) Drivers of change in global agriculture. Philosophical

Transactions of the Royal Society B (2008), 363, 495-515.

 Hegrenes, A., Hill, B. and Lien, G. (2001) Income stability among agricultural

households - evidence from Norway. Journal of Farm Management, 11(1), pp1-12.

Policy Department B: Structural and Cohesion Policies

____________________________________________________________________________________________

114

 Hill, B. (1990) In search of the Common Agricultural Policy's "agricultural community".

Journal of Agricultural Economics, 41(3), pp316–26.

 Hill, B. (1991) Calculation of Economic Indicators: Making Use of RICA (FADN)

Accountancy Data. Document series, Commission of the EC, Brussels.

 Hill, B. (2000) Linking the established subsystems of economic statistics to provide a

rounded view of agriculture. In Pauli, P, (ed.), Agricultural Economic Statistics,

Proceedings of the Seventh IWG-AGRI Seminar, Luxembourg 5–7 July, 2000, pp46–74,

Eurostat, Luxembourg.

 Hill, B. (2003) A conceptual framework for estimating agricultural household income in

EU countries. Paper to the OECD Seminar on Agriculture and Rural Incomes, Labour

Mobility and Rural Development Policies in Estonia, Latvia and Lithuania 10-12 June

2003, Tallinn, Estonia. p18 (OECD website).

 Hill, B. (2012) Farm Incomes, Wealth and Agricultural Policy – Filling the CAP’s Core

Information Gap. 4th Edition. CAB International. ISBN 978-1-84593-847-5.

 Hill, B. and Brookes, B. (1993) Farm Incomes in the European Community in the 1980s.

Document Series, European Commission, Brussels.

 Hill, B. and Platt, S. (2003) Measurement of farm household income and wealth versus

agricultural activity income: Methodological work to be undertaken. Who is doing it?

Joint ECE/Eurostat/FAO/OECD meeting on Agricultural and Food Statistics in Europe.

Geneva 2-4 July, United Nations Economic Commission for Europe.

 Hyvönen, K. (2004) A short history of the FADN and other activities than agriculture.

In: Poppe, K. J. (ed.), PACIOLI 12: Income Issues in Farm Households and the Role of

the FADN, Report 8.04.03. Agricultural Economics Research Institute (LEI), The Hague.

 JRC (2006) Agricultural insurance schemes. Joint Research Centre (European

Commission), Ispra, Italy.

 JRC (2009) Risk Management and Agricultural Insurance Schemes in Europe. Joint

Research Centre (European Commission), Ispra, Italy.

 LEI (2007) Data analysis on price, production and income volatility and crisis. LEI

working papers WP2, Income Stabilisation in European Agriculture, Madrid.

 Mary, S., Santini, F. and Boulanger, P. (2013) An Ex-Ante Assessment of CAP Income

Stabilisation Payments using a Farm Household Model. Agricultural Economics

Society>87th Annual Conference, April 8-10, 2013, Warwick University, Coventry, UK

 Meuwissen, M. P. M, van Asseldonk, M. A. P. M. and Huirne, R. B. M. (eds.) (2008)

Income Stabilisation in European Agriculture; Design and Economic Impact of Risk

Management Tools. Wageningen Academic Press, the Netherlands.

 Meuwissen, M. P. M. and Huirne, R. B. M. (1998) Feasibility of Income Insurance in

European Agriculture. Paper to the American Agricultural Economics Association Annual

Meeting, 1998.

 Meuwissen, M. P. M., Huirne, R. B. M., and Hardaker, J. B. (1999) Income Insurance in

European Agriculture. European Economy No 2, The Commission, Brussels.

 Meuwissen, M. P. M., Huirne, R. B. M. and Skees, J. R. (2003) Income Insurance in

European Agriculture. EuroChoices, Spring 2003, pp12–17.

 Meuwissen M., van Asseldonk M. and Huirne R. (2008) Income stabilization in

agriculture; reflections on an EU-project. P. 17-31 in “Income Stabilisation in European

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

115

Agriculture – Design and economic impact of risk management tools”, Wageningen

Academic Publishers, 222 p.

 OECD (2000) Income Risk Management in Agriculture. Organisation for Economic Co-

operation and Development, Paris.

 OECD (2002) Farm Household Income Issues in OECD Countries: A Synthesis Report.

Organisation for Economic Co-operation and Development, Paris.

AGR/CA/APM(2002)11/FINAL. [Also published as OECD (2003)].

 OECD (2003) Farm Household Income – Issues and Policy Responses. Organisation for

Economic Co-operation and Development, Paris.

 OECD (2004) Policy Brief: Farm Household Incomes – towards better informed policies.

Organisation for Economic Co-operation and Development, Paris.

 OECD (2005) Taxation and Social Security in Agriculture. Organisation for Economic

Co-operation and Development, Paris. Main author Hill, B.

 OECD (2008a) An Assessment of Risk Exposure in Agriculture: A Literature Review.

Working Party on Agricultural Policies and Markets. TAD/CA/APM/WP(2008)23/FINAL.

[Authors, Coble, K. H. and Barnett, B. J., Department of Agricultural Economics,

Mississippi State University], Organisation for Economic Co-operation and Development,

Paris.

 OECD (2008b) An Overview of Risk-related Policy Measures. Working Party on

Agricultural Policies and Markets. TAD/CA/APM/WP(2008)23/FINAL. [Author, Moreddu,

C.], Organisation for Economic Co-operation and Development, Paris.

 OECD (2009) Risk Management in Agriculture - A Holistic Conceptual Framework.

Working Party on Agricultural Policies and Markets. [Author, Antón, J.].

TAD/CA/APM/WP(2008)22/FINAL. Organisation for Economic Co-operation and

Development, Paris.

 Swinnen, J., Ciaian, P., and Kancs, d’A. (2008) Study on the Functioning of Land

Markets in the EU Member States under the Influence of Measures Applied under the

Common Agricultural Policy. Centre for European Policy Studies (CEPS) final report of a

study carried out on behalf of the European Commission, Directorate General for

Agriculture and Rural Development under contract 30-CE-0165424/00-86.

 UN (2008) System of National Accounts 2008. Commission of the European

Communities - Eurostat, International Monetary Fund, Organisation for Economic

Cooperation and Development, United Nations, World Bank, Brussels/Luxembourg, New

York, Paris, Washington.

 UNECE (2007) Rural Households’ Livelihood and Well-Being: Statistics on Rural

Development and Agriculture Household Income. The Wye Group Handbook.

Eds Berkeley Hill and Jan Karlson UNECE/FAO/OECD/The World Bank/Eurostat 2007.

 van der Veen, H. B., van Rommel, K. H. M. and Venema, G. S. (2002) Family farm

transfer in Europe: A focus on the financial and fiscal facilities in six European countries.

Report 6.02.04. Agricultural Economics Research Institute (LEI), The Hague. May 2002.

LEGAL REFERENCES

 Consolidated version of the Treaty on the Functioning of the European Union. Official

Journal of the European Union. 26/10/2012. C326.

 Regulation No 79/65/EEC of the Council of 15 June 1965 setting up a network for the

collection of accountancy data on the incomes and business operation of agricultural

holdings in the European Economic Community. Official Journal of the European Union.

23/06/1965. 1859/65.

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 Council Regulation (EC) 73/2009 of 19 January 2009 establishing common rules for

direct support schemes for farmers under the common agricultural policy and

establishing certain support schemes for farmers, amending Regulations (EC) No

1290/2005, (EC) No 247/2006, (EC) No 378/2007 and repealing Regulation (EC) No

1782/2003.

 Regulation (EU) No 1305/2013 of the European Parliament and of the Council of 17

December 2013 on support for rural development by the European Agricultural Fund for

Rural Development (EAFRD) and repealing Council Regulation (EC) No 1698/2005.

Official Journal of the European Union. 20/12/2013. L347.

 Regulation (EU) No 1308/2013 of the European Parliament and of the Council of 17

December 2013 establishing a common organisation of the markets in agricultural

products and repealing Council Regulations (EEC) No 922/72, (EEC) No 234/79, (EC) No

1037/2001 and (EC) No 1234/2007. Official Journal of the European Union.

20/12/2013. C347.

 Commission Delegated Regulation (EU) No 807/2014 of 11 March 2014 supplementing

Regulation (EU) No 1305/2013 of the European Parliament and of the Council on

support for rural development by the European Agricultural Fund for Rural Development

(EAFRD) and introducing transitional provisions. Official Journal of the European Union.

31/07/2014. L227.

 Commission Implementing Regulation (EU) No 808/2014 of 17 July 2014 laying down

rules for the application of Regulation (EU) No 1305/2013 of the European Parliament

and of the Council on support for rural development by the European Agricultural Fund

for Rural Development (EAFRD). Official Journal of the European Union. 31/07/2014.

L227.

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ANNEX: DATA SOURCES ON THE REWARDS FROM

AGRICULTURAL PRODUCTION

The two main data sources are the Economic Accounts for Agriculture (Eurostat) and the

Farm Accountancy Data Network (FADN) operated by DG AGRI.

The Economic Accounts for Agriculture

Aggregate economic accounts for agriculture have been published within the EU since 1964,

and from 1969 onwards the six original Member States adopted the common definitions

and procedures of the EU’s Economic Accounts for Agriculture (EAA). For long operated by

a ‘gentleman’s agreement’ between the statistical authorities in Member States, the EAA

was given its own legal basis in 2004 (Regulation (EC) No 138/2004), which served to

underline at the time of EU enlargement the national responsibility to apply the agreed

methodology and to supply data based on it to Eurostat.

An important feature of aggregate accounting for agriculture is that information used in

building the account mostly comes from industry-level sources and not from grossing up

the results of surveys of the accounts of individual farms (though survey data will be used

to fill in gaps). This means that all agricultural production is covered (including non-

agricultural activities which are not separable in the data sources). For example, the value

of output is estimated principally from data on the area of crops and average yields (to give

a volume of crop production) and numbers of livestock, each multiplied by appropriate

prices found from market reports and from the relatively small number of first

users/purchasers (such as dairies). The values of inputs, such as feedstuffs, fertilisers and

seeds, are derived principally from sales from other industries to agriculture, something

possible because of the largely agricultural nature of many of these inputs (animal

feedstuffs and agro-chemicals, etc. being mainly taken by farmers). Similarly, labour costs

can be estimated from multiplying the numbers of workers taken from censuses by annual

average earnings found by surveys.

Data sources vary between Member States and, although the methodology is harmonised,

detailed inventories of how Member States generate information have shown differences

that undermine the appearance of comparability of results, though probably not seriously

when changes over time are the focus of attention.

The advantage of this approach is largely one of speed; the estimates of the aggregate

value of outputs and costs of inputs can be more quickly produced than if reliance were to

be placed on surveys of sets of farm accounts. Preliminary calculations of the income from

agricultural production based on aggregate accounts can be available in Eurostat before the

end of the calendar year to which they relate. For policy-makers, rapid availability of

estimates is important, though perhaps less so now than when the CAP operated principally

using commodity support prices which were adjusted annually.

A substantial revision of the EAA methodology was made in 1997 and applied from 1999

(Eurostat 1997). First, a change of presentation was made. In line with changes in the UN

System of National Accounts and the European System of Accounts (SNA93/ESA95) the

EAA97 was split into a series of three current transactions accounts:

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118

 The Production account, with its balancing item of Net Value Added.

 The Generation of Income account, with its balancing item of Operating Surplus

(termed Mixed Income where unincorporated businesses are concerned because it

includes the rewards both for self-employed labour and for capital (this term is used

in the SNA93)).

 The Entrepreneurial Income account, with its balancing item of Entrepreneurial

Income (which is equivalent in the previous Eurostat methodology to Net Income

from Agricultural Activity of Family Labour Input).

Within the conceptual framework of the EAA97 there is also a Capital account, not dealt

with here because it cannot yet be compiled on a complete basis and because it attracts

relatively little attention among policy decision-makers.

Second, and more important than the change in presentation, are the revisions that

concern substance. In addition to many adjustments to individual items (such as the timing

of transactions, the calculation of own-account capital formation and the inclusion of

computer software as capital assets) there were some fundamental changes to the EAA

with regards to the basic unit, the measurement of output, the method of valuation and to

the calculation of capital consumption. These are explained fully in Hill (2012, Chapter 4).

Perhaps the most significant was the broadening of coverage to allow the value of

production to include not only that of strictly agricultural commodities but also non-

agricultural activities that could not be separated in the basic data sources (for example,

small-scale food processing and retailing on farms). However, it must be emphasised that

diversified activities on the farm that kept separate accounts and off-farm businesses run

by farms were still excluded. Furthermore, some long-established problems were

continued, including the issue of how to allocate the interest costs incurred by institutional

units (household-firms and companies) between agriculture and other activities that might

be carried on by the business (and in the case of households, their borrowings for

consumption purposes).

Table 1: Economic Accounts for Agriculture: current transactions accounts from

1999

PRODUCTION ACCOUNT

GENERATION OF INCOME

ACCOUNT

ENTREPRENEURIAL

INCOME ACCOUNT

Output

Net Value Added

Net Operating Surplus (Mixed

Income)

Minus Intermediate

consumption

minus compensation of

employees

minus interest paid

Minus consumption of fixed

capital

minus other taxes on

production

minus rent paid

plus other subsidies on

production

= Net Value Added

= Net Operating Surplus

(Mixed Income)

= Net Entrepreneurial

Income

Source: Eurostat (1997).

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119

The EU also revised its previous indicators of income from agricultural production as part of

the EAA97 methodology. Bearing in mind that the coverage of output and basis of valuation

are both changed from the previous system, and that other detailed alterations took place,

the indicators applied since 1999 are as follows:

 Indicator A: Index of the real income of factors in agriculture per annual

work unit. This is calculated by taking the Net Value Added at basic prices that

appears in the Production account and adjusting it by adding ‘other subsidies on

production’ and deducting ‘other taxes on production’, dividing by the labour input,

and expressing in deflated and index form. Without these adjustments, NVA (at

basic prices) would be sensitive to the classification of subsidies as being ‘on

products’ or ‘other subsidies on production’

. NVA in this form is referred to as

being at Factor Cost.

 Indicator B: Index of real net agricultural Entrepreneurial Income per

unpaid annual work unit. Entrepreneurial Income contains the same broad

elements as the former ‘net income from agricultural activity of family labour input’,

though the label is now more appropriate. It is retained for countries where

agriculture is organised almost totally as unincorporated holdings.

 Indicator C: Net Entrepreneurial Income of agriculture. This aggregate is

given in absolute terms, but may also be expressed in index form. The important

point is that it is not calculated per unit of non-hired labour and so is suitable for

uses involving countries where the output from corporate farms is an important part

of the total.

Despite the revisions, it is clear that the approach embodied in each of the present

Indicators remains essentially one of trying to gauge the rewards to a hybrid bundle of

factors used in the production of agricultural commodities. NVA at Factor Cost is a long way

from the personal incomes of the agricultural community (unless there is no borrowing, no

renting of land, no hired labour and no other sources of income to the household). While

Entrepreneurial Income coincides broadly with what might be seen as profit, it only relates

to that originating from agricultural activity and excludes that which might come from other

activities carried on within the farm business, unless these are very minor and inseparable

in the basic data sources.

The Farm Accounts Data Network (FADN)

At EU level, the farm accounts surveys of all the Member States are brought together under

the co-ordination of the Commission’s Directorate-General for Agriculture and Rural

Development (DG AGRI) as the Farm Accountancy Data Network (FADN), also known by its

French acronym RICA. This was established in 1965 ‘with the specific objective of obtaining

data enabling income changes in the various classes of agricultural holding to be properly

monitored’ (Commission, 1982). The justification for FADN was rooted in policy, in that

‘...the development of the Common Agricultural Policy requires that there should be

available objective and relevant information on incomes in the various categories of

agricultural holdings and on the business operation of holdings coming within categories

which call for special attention at Community level’ (EEC Regulation 79/65). FADN is

Decoupled payments under the Single Payment Scheme (now the Basic Payments) are an ‘other subsidy on

production’. While such payments could be easily handled within an accounting system based on the

institutional unit, they caused a difficulty in activity accounts. Treating them strictly would have resulted in

them not being included in the value of agricultural production or in Value Added at basic prices. This would

have shown a major fall in statistics on the Value Added from agricultural production at the point of revision of

the methodology, which was deemed to be unacceptable. Their inclusion in the calculation of Indicator A

preserves a degree of continuity with the preceding set of ‘income indicators’.

Policy Department B: Structural and Cohesion Policies

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120

therefore not a single survey but is an amalgamation of national surveys carried out by

Member States. In some countries these predated RICA, as in the UK, but in others they

were started from scratch. The nature of FADN is in part a reflection of the approaches

inherited from these pre-existing surveys. Ways of collecting the data vary from country to

country, but there is a fundamental harmonised methodology which applies to the concepts

of income employed and, increasingly, to the selection of the sample (Commission, 1989).

FADN focuses on agricultural holdings deemed to be commercial, in the sense that they are

large enough to provide a main activity for the farmer and a level of income sufficient to

support his or her family (Commission, 1985a). The interpretation of what is commercial

has changed. The original Council Regulation 79/65 stipulated that the field of survey

should cover those agricultural holdings, which (a) are run as market-oriented holdings,

and (b) provide the main occupation of the operator.

During the first three years, data were taken only from agricultural holdings having an area

exceeding five hectares, with the exception of holdings producing wine, fruit, vegetables

and olives. In 1972 this was amended. In addition to being market-oriented, and providing

the main occupation of the operator, it was to be of a size capable of employing at least

one worker (1 work unit) over a year, though this threshold could be reduced to 0.75 work

units. (Hyvönen, 2004). These criteria implied a discrimination against part-time farmers in

the sample, but this was justified by the belief that ‘main-living’ farms constituted the most

important target for agricultural policy measures, an interpretation which should not go

unnoticed. However there was a revision of this thinking in 1981, and from 1982/3

selection thresholds have been made only in terms of size in Economic Size Units (which

are based on Standard Gross Margin). No notice is to be taken when selecting the sample

of any other gainful activities in which the operator may engage.

There is a minimum size threshold that varies between Member States, reflecting their

different farm size structures as shown in the periodic EU Farm Structure Survey. In

particular, Belgium, Germany, the Netherlands and the UK (excluding Northern Ireland)

have imposed size thresholds that exclude many holdings that would be eligible for

inclusion in FADN in the other Member States. Thresholds are periodically revised. Users of

published results at EU level should be aware that not all countries are presented in the

smallest size groups.

Consequently, while the overwhelming majority of farming activity falls within the FADN

field of observation, only 42% of the EU’s agricultural holdings found in its farm structure

survey are represented (2015). Figures vary widely between countries. For example, in

Slovakia only 17% of farms are covered by FADN, but these represent 96% of the

economic activity, whereas in Ireland 75% of the farms are covered, with 98% of the

activity. Though numerically important, holdings below the FADN size thresholds contribute

very little in terms of agricultural activity. In many Member States, especially more recent

additions to the Union, it is likely that the coverage of holdings within FADN is even lower

because some farms are small that they fall below the size for qualification for inclusion in

the Structure Survey. Altogether the FADN sample consists of just under 87,000 holdings

(2014), corresponding to about 1.7% of all holdings within the FADN’s field of observation.

Comparison of farmers’ incomes in the EU Member States

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121

Table 2: FADN field of observation

Member State

Farms in

the Farm

Structure

Survey

Farms in

the FADN

field of

observation

FADN field of

observation

Farms %

SO %

UAA %

AWU %

Belgium

42,850

31,010

Bulgaria

370,490

115,390

Czech

Republic

22,860

14,820

Denmark

42,100

29,340

Germany

299,130

196,520

Estonia

19,610

8,080

Ireland

139,890

105,170

Greece

723,010

341,180

Spain

989,800

597,970

France

516,100

317,360

Italy

1,620,880

838,740

Cyprus

38,860

10,530

Latvia

83,390

21,940

Lithuania

199,910

53,440

Luxembourg

2,200

1,610

Hungary

576,810

107,250

Malta

12,530

3,080

Netherlands

72,320

52,220

Austria

150,170

95,150

Poland

1,506,620

730,880

Portugal

305,270

114,170

Romania

3,859,040

1,042,570

Slovenia

74,650

41,300

Slovakia

24,460

4,260

Finland

63,870

42,630

Sweden

71,090

29,050

United

Kingdom

186,660

94,640

Source: DG AGRI EU-FADN.

Policy Department B: Structural and Cohesion Policies

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122

Altogether the FADN sample consists of about 81,000 holdings (EU-27, 2007),

corresponding to about 1.5% of all holdings within the FADN’s field of observation. The

sample is stratified by economic size (in European Size Units), by farming type and by

region and all published results are weighted appropriately. In the strict sense, the sample

is not random, since it is drawn from holdings that keep accounts and participation by

farmers is voluntary. However, the representative nature of the sample is under constant

scrutiny.

Another feature of the sample is that its composition changes a little from year to year as

holdings enter or leave the survey. There are good statistical reasons why a turnover is

required; the experience in some national surveys is that the greater information that

becomes available to co-operating farms enables their performance to improve so that they

are no longer typical of the generality of farms. Part of any difference in results from year

to year can be laid at the door of this changing sample, though the impact is unlikely to be

substantial in countries where FADN is well established and the sample is of stable size.

Nevertheless, the gradual drift up in average size must be borne in mind when interpreting

income movement over time.

A comprehensive set of data relating to many aspects of the farm business is collected.

The items are specified on a standard Farm Return, which is established in Community

legislation (the latest of which is Commission Regulation (EC) 868/2008, operating from the

financial year 2009). This contains detailed instructions on how the Farm Return is to be

completed and provides definitions of the terms used. Though having the advantage that

Member States are obliged to provide this data, the legal basis of the Farm Return makes

any major changes to it a cumbersome process. Currently data are collected covering the

physical and value details of animal and crop output, the costs of crop variable inputs (such

as seeds and fertilisers), of animal feedingstuffs, labour, interest and land charges, details

of spending and receipts from livestock, deadstock and machinery, the debt situation,

grants, subsidies and Value Added Tax (VAT). The data relate to the whole farm, so that,

for example, it is not at present possible to allocate the input of fertiliser between the

various crops on the holding and to calculate measures of enterprise profitability. This has

severely limited the ability of FADN to monitor the impact of the CAP’s main policy

instruments at farm level.

The data collected relate only to farming activity on the holding (though for national

purposes some Member States collect additional information). For the FADN the borderline

between agricultural and non-agricultural is based on the standard industrial classification

used within the EU. Agricultural activity is deemed to include agricultural contracting

(primary stage activity, such as ploughing and harvesting for other farmers). Thus, if the

resources of the holding are used in food manufacturing or any other non-farming activity

which contributes to the income of the farmer and his household, in principle these are not

covered in the FADN. This exclusion also applies to any building activities which the farmer

may undertake himself rather than by employing a builder. However, it is clear that FADN

does not collect information on any off-farm activities which the farmer or his family may

engage in (as hired workers or as self-employed), or on pensions, property extraneous to

the agricultural holding, personal taxation or private insurance.

FADN’s main income measures are Farm Net Value Added, expressed per farm or per

Annual Work Unit (FNVA/AWU) (that is, per full-time person equivalents working on the

farm) and Family Farm Income (FFI), per farm or per Family Work Unit (FFI/FFI). For

farms with no family labour the residual is termed Farm Net Income and this is expressed

per unit of total labour input. Figure 47 shows how these are calculated. There are also

Cash Flow indicators.

Comparison of farmers’ incomes in the EU Member States

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123

NVA is the difference between the value of farm output and the variable inputs purchased

from other sectors of the economy, after adjustment for subsidies and taxes on production

and for the consumption of capital (in the form of a depreciation allowance). Produce

consumed by the farm household is valued as part of output. Changes in stocks of output

and inputs are taken into account. As a concept it is close to Net Value Added as used in

the aggregate Economic Accounts for Agriculture (described previously in this chapter),

though there are differences in detail. FNVA is the sum that is available for rewarding all

the fixed factors of production, that is, all the labour, land and capital used on the farm

irrespective of who owns them. As with the industry-level indicator, the reason why NVA

per AWU is used without distinguishing between farmer labour and hired workers seems to

do with interpretation of the intentions of Article 39 of the Treaty of Rome as relating to all

people working in agriculture (employed, self-employed and family help). However, such a

figure can mask marked differences between the rewards of hired workers and of farmers

and their families.

FNVA is capable of being distributed in a variety of ways. In the earlier phase of the FADN

attempts were made to calculate a Labour Income by deducting costs for all other inputs,

including imputed rents for owned land and a notional interest charge for the working

capital of the business. Such calculations were eventually abandoned because of the

difficulties of settling on the levels of imputed costs (Hill, 1991). However, a measure called

the remuneration of family labour has been reported recently (European Commission,

2014a) that once again involves imputation; it is calculated by deducting from FNVA the

costs of wages, rent and interest paid (as FNI below) and the opportunity costs of own land

and capital. This is expressed per family work unit (FWU). It is debateable whether the old

difficulties have been overcome or just forgotten.

As a measure of income, FNVA falls short of what most farmers would perceive as their

profit because no deductions are made for interest payments on loans, for rents on

tenanted land and for the cost of hired labour. In the early stages of FADN some Member

States experienced difficulty in obtaining reliable information on some of these fixed

factors, particularly interest payments, so FNVA was the most convenient common measure

which could be adopted.

For a time, FNVA tended to be replaced as a measure of income by Family Farm Income

(FFI). The same concept is now called Farm Net Income, a reflection that enlargement has

increased the proportion of farms that do not have the family-run structure that dominates

the EU-15, though the term FFI is still used in situations where family (unpaid) labour is

greater than zero and in the FADN definition of variables (European Commission, 2014c).

FFI is a concept first used in the 1984 report on incomes covering the years 1978/9 to

1981/2. This is the residual remaining to the farmer and the other unpaid labour of the

household after the deduction of interest payments, rent payments and the costs of hired

labour. It represents the reward to the farmer and his family from using their owned land,

capital and labour input in agricultural activity on the holding. In practice it accords broadly

with the notion of profit from farming which is available for consumption spending, for

saving and investment or for other calls on personal income (such as taxation). Of course,

there may be other income sources which contribute to this spending and saving, but they

are not derived from farming the holding and are therefore outside the coverage of FADN.

Capital gains (and losses) on land and other assets do not form part of FFI, though they too

might be considered as elements in the long-term rewards from farming and might form

the basis of borrowing for consumption and investment purposes. More recently the

Commission appear to have once again focused on FNVA.

Policy Department B: Structural and Cohesion Policies

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124

Figure 47: The calculation of Economic Indicators in the FADN

Source: European Commission (2014b)

Again, FNI/FFI is often expressed per annual work unit of unpaid (family) labour (Family

Work Unit, or FWU), including the farmer, in order to reflect the varying amounts of such

Opening Stocks of

Livestock Products

Closing Stocks of Livestock Products

Sales of Livestock Products

Farmhouse Consumption of

Livestock Products

Farm Use of Livestock Products

Sales of Livestock

Purchase of

Livestock

Farmhouse Consumption of Livestock

Livestock growth and appreciation

OTHER OUTPUT

(SE256)

TOTAL OUTPUT LIVESTOCK &

PRODUCTS (SE206)

Closing

Stocks

Opening

Stock

Sales

Farmhouse

Consumption

Farm Use

TOTAL OUTPUT CROPS

& PRODUCTS (SE135)

Total specific costs

(SE281)

Total farming

overheads (SE336)

TOTAL

OUTPUT

(SE131)

Taxes

(SE390)

Total subsidies excl.

investment (SE605)

VAT on

Sales

VAT

reimbursed

by the

State

VAT on

Purchases

VAT Balance excl.

Investment

(SE395)

Balance current

subsides & taxes

(SE600)

Total

Intermediate

consumption

(SE275)

GROSSFARM INCOME (SE410)

FARM NET

VALUE

ADDED

(SE415)

FARM NET INCOME

(SE420)

FAMILY FARM INCOME

(SE430N)

Annual

Work

Units

(SE010)

Balance subs & taxes on

investment (SE405)

Annual Work

Units (SE010)

Family Work

Units (SE015)

FARM NET

VALUE

ADDED per

Annual Work

Unit (SE425)

Subsidies on

investment

(SE406)

Depreciation (SE360)

Wages Paid (SE370)

Rent Paid (SE375)

Interest Paid

(SE380)

Total external

factors (SE365)

Payments to

daily outgoins

(SE407)

VAT on

investments

(SE408)

FARM NET INCOME

per Annual Work

Unit

FAMILY FARM

INCOME per Family

Work Unit (SE430)

If family Work Unit (SE015)>0

Comparison of farmers’ incomes in the EU Member States

____________________________________________________________________________________________

125

labour used. As long as its definition is borne in mind, FNI/FFI is a very useful measure on

two counts: first, it represents what would generally be accepted as being entrepreneurial

income (or profit) derived from farming; and, second, by excluding the hired labour force,

it covers only those people whose welfare the CAP is in practice primarily aimed – farmers

and their families.

FFI is conceptually close to Eurostat’s aggregate Net Income from Agricultural Activity of

Family Labour Input and, when expressed per unit of family labour input, to Indicator B. A

number of additional income indicators have been proposed and investigated by FADN (Hill,

1991).