EU FARM ECONOMICS OVERVIEW FADN 2007ec.europa.eu/agriculture/rica/pdf/EU_FEO_FADN_2012.pdf · 2015-06-02 · EU FARM ECONOMICS OVERVIEW FADN 2012 EXECUTIVE SUMMARY This report provides

European Commission

Directorate-General for Agriculture and Rural Development

http://ec.europa.eu/agriculture

Agricultureand RuralDevelopment


EU Farm Economics Overviewbased on 2012 FADN data

This report provides an overview of key economic developments in the European agricultural sector based on the latest data available in the Farm Accountancy Data Network (FADN) which are from 2012

European Commission


Disclaimer:This publication does not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein.

Contact:European CommissionDG Agriculture & Rural Development,Microeconomic analysis of EU agricultural holdingsE-mail: [email protected]: http://ec.europa.eu/agriculture/rica/index.cfm

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EUROPEAN COMMISSION DIRECTORATE-GENERAL FOR AGRICULTURE AND RURAL DEVELOPMENT Directorate E. Economic analysis, perspectives and evaluation; communication E.3. Economic analysis of EU agriculture

Brussels, May 2015

EU FARM ECONOMICS OVERVIEW

FADN 2012

EXECUTIVE SUMMARY

This report provides an overview of key economic developments in European agricultural

holdings based on 2012 data, the latest available in the Farm Accountancy Data Network

(FADN). The FADN survey represents farms that account for the majority of EU agricultural

production.

After the sharp decline in farm income in 2009, recovery started in 2010 and continued in

2012. Overall, income slightly increased due to higher agricultural producer prices and an

increase in the value of agricultural output. The latter is mostly linked to the performance of

animal output (+3.1 %) and to a lesser extent to that of crop production (+1.4 %). However,

significant income differences were observed across European regions as well as across

different types of farming. Despite the high input prices such as the cost of animal feed and

energy in 2012, farms specialised in granivores (pigs and poultry) and field crop farms

generated the highest income per person. From 2011 to 2012, income per person increased

for farms specialised in field crops, granivores, horticulture and other permanent crops, and

for mixed farms (mainly due to higher producer prices and volumes in animal and crop

production in 2012). It decreased for farms specialised in wine, grazing livestock and for

dairy farms. The latter two are due to the decrease of producer prices for milk and the

decrease in sheep meat production.

The income gap between the EU-N101 and EU-15 narrowed in 2011, but began to widen

again in 2012. The average remuneration of family labour in the EU-15 was four times

higher than in the EU-N10.

Finally, in comparison to the previous year, the proportion of direct payments to total

receipts in the EU-27 decreased from 11.9 % to 11.2 % in 2012. One of the reasons for this

was the increase in agricultural output.

1 EU-N10 refers to the ten Member States that joined the EU in 2004.

2

Income developments

The EU-27 average farm net value added (FNVA)2 increased by 2.7 % from 2011 to

2012, mostly due to increases in agricultural output (especially in the value of animal

output) and prices. Compared to 2009, FNVA was 32 % higher in 2012. Average FNVA

per annual work unit (FNVA/AWU) increased by around 4 %, from EUR 18 200 in 2011 to

EUR 19 000 in 2012.

This growth was driven by the increase in FNVA, with labour input remaining stable. It was

primarily influenced by an increase in agricultural real prices, reflecting the continued

recovery of commodity markets in 2012 after the low point in 2009. Remuneration per family

work unit3 stood at around EUR 12 900 in 2012, up from EUR 12 700 in 2011.

This income increase masked substantial differences across Member States, regions and

types of farming. Holdings in Denmark, the UK (England), north-western Germany and

northern France generated the highest FNVA/AWU in 2012. Denmark and the Picardie region

of France had the highest average FNVA/AWU in the EU. The regions with low

FNVA/AWU (i.e. below EUR 10 000) were mostly situated in the EU-N10. Only one region

in the EU-15, namely Norte e Centro (Portugal) had an average FNVA/AWU below

EUR 10 000.

On average, farms specialised in granivores, field crops, wine, horticulture and milk had the

highest FNVA/AWU, while the FNVA/AWU of farms specialised in other permanent crops,

grazing livestock (other than milk) and mixed activities remained below the EU-27 average.

In 2012, FNVA/AWU increased for farms specialised in granivores, horticulture, other

permanent crops and for mixed farms (crops and livestock), and decreased for farms

specialised in field crops, wine, milk and other grazing livestock. This increase was mainly

due to the higher producer prices and to a lesser extent to the volume of output in 2012.

Looking at the distribution of FNVA/AWU in the EU-N10 and EU-2,4 the average

income per worker in these countries remained significantly below the EU-15 level. In

more than 96 % of farms in the EU-2 and around 92 % of farms in the EU-N10, FNVA/AWU

was below the EU-15 average. In the EU-N10, average FNVA/AWU stood at around

EUR 9 500, but was under EUR 4 200 in more than 50 % of farms (median income).

FNVA/AWU was less than EUR 2 500 in 50 % of farms in the EU-2.

Role of direct payments

In 2012, on average, direct payments accounted for nearly 31 % of FNVA in the EU-27, down

from 32 % in 2011. This slight decrease was caused by a slight increase in FNVA and a slight

decrease in direct payments in 2012. The proportion of direct payments to FNVA was highest

in Finland (72 %). It was second-highest in Slovakia (71 %).

2 Farm net value added (FNVA) is used to remunerate the fixed factors of production (labour, land and

capital) whether they are external or family factors. In order to obtain a better measurement of the

productivity of the agricultural workforce and to take into account the diversity of farms, FNVA is also

calculated by annual working unit (AWU, work of one person occupied full time on a farm). This is one of

the FADN’s main income indicators.

3 Remuneration of family labour is equal to: FNVA + balance of subsidies and taxes – wages paid – paid rent

– estimated costs of own land and own capital. The value is given per family work unit (FWU).

4 EU-2 means Bulgaria and Romania.

3

However, direct payments accounted for only 12 % of FNVA in the Netherlands, showing that

Dutch agriculture is more focused on the more profitable sectors that are less dependent on

direct payments, such as horticulture and pig and poultry production.

The proportion of direct payments to agricultural income also fluctuated markedly with the

type of farming. In particular, direct payments represent a substantial part of FNVA (56-42 %)

in grazing livestock, mixed and field crop farms as a result of the historical orientation of the

CAP. On the other hand, subsidies account for only a very limited part of total revenue in

wine and horticulture holdings (6-4 %).

Direct payments helped to even out the variability in EU farm income. The average amount of

direct payments received in 2012 was EUR 9 140 per farm surveyed by FADN.5

Characteristics of farms represented by FADN

The structure of European farms covered by FADN varies markedly in several ways:

Asset value. The average farm size in terms of asset value was highest in Denmark and in

the Netherlands (EUR 2 500 000 and EUR 2 200 000, respectively), reflecting very high

land prices and the importance of sectors which typically need considerable investment

(such as milk, granivores and horticulture). In contrast, farms in Romania had the lowest

total asset value (below EUR 40 000) due to low land prices, small farm sizes and less

capital-intensive types of farming. Bulgaria almost tripled the asset value of its farms

from 2007 to 2012. The land price level in the EU-2 remains well below the EU-27

average.

Labour input. In the FADN survey, the average number of workers employed per farm

in the EU-27 stood at 1.6 AWU in 2012. However, it varied significantly across Member

States, ranging from 14.7 AWU in Slovakia to 1.1 AWU in Ireland. The average number

of workers per farm in horticulture (the sector with the highest labour input) was

approximately 2.5 times higher than in permanent crops other than wine holdings (the

sector with the lowest labour input).The share of unpaid labour (expressed as family

labour hours) accounted for 77 % of the total labour force in the EU-27 and represented

the most prevalent form of labour in all Member States except for Slovakia, the Czech

Republic, Hungary, Estonia and Bulgaria. In these Member States, the proportion of

family labour in the total labour force (in terms of hours worked) was below 50 %. The

average hourly wage of farm workers stood at EUR 7.2 in the EU-27 during 2012, up

4.9 % from the previous year. This nominal wage increase more than compensated for the

general increase in prices (EU-27 HICP6 inflation stood at 2.5 % in 2012).

5 Please note that FADN covers the farms that account for over 90 % of agricultural production in the EU.

It does not cover the smallest farms with low production. See Annex 1 for more details.

6 The Harmonised Index of Consumer Prices (HICP) is an economic indicator constructed to measure the

changes over time in the prices of consumer goods and services acquired by households. It is the official

measure of consumer price inflation in the euro zone for the purposes of monetary policy in the euro area

and for assessing inflation convergence as required under the Maastricht criteria.

4

Land use. The average size of farms covered by the FADN survey was 33 ha7 in 2012.

However, it varied considerably across Member States, ranging from 521 ha per farm in

Slovakia to 3 ha per farm in Malta. Rented land accounted for 54 % of total agricultural

area in the EU-27 in 2012. The land rents in the EU-27 have increased by 15 % since

2009, from EUR 143 per ha to EUR 164 per ha in 2012. Land rents were particularly high

in the Canaries (EUR 1150 per ha) and in the Netherlands (EUR 724 per ha), but

remained under EUR 30 per ha in the Baltic countries. They also differed markedly across

types of farming: the level of rent per hectare in horticulture and the wine sector was

8 to 9 times higher than the rental price paid by grazing livestock farms.

The Farm Accountancy Data Network (FADN) is a European system of sample surveys

that are run each year to collect structural and accountancy data of farms. Its aim is to monitor

the income and business activities of agricultural holdings and to evaluate the impacts of the

Common Agricultural Policy (CAP).

The scope of the FADN survey covers only farms whose size exceeds a minimum threshold

so as to represent the largest possible proportion of agricultural output, agricultural area and

farm labour, of holdings run with a market orientation. For 2012, the sample consisted of

approximately 83 000 holdings in the EU-27, which represent nearly 5.0 million farms (40 %)

out of a total of 12.2 million farms included in the FSS.8

The rules applied seek to provide representative data for three criteria: region, economic size

and type of farming. The FADN is the only harmonised source of micro-economic data,

which means that the accounting principles are the same in all EU Member States.

The most recent FADN data available for this report are for the 2012 accounting year, due to

time needed for data collection, control and processing.

For further information please see Annex 1 on ‘Farm Accountancy Data Network in the

context of the Farm Structure Survey − Methodology’ (page 56).

7 Please note, that the FADN survey does not contain all agricultural holdings in the EU-27, only those of a

certain minimum size (as specified in Council Regulation (EC) No 1217/2009). Based on this criterion many

small farms have been excluded from the field of survey. Accordingly, it should be emphasised that the

average farm size mentioned in the report does not correspond to the average farm size in the total

agricultural population. See more information in the methodological chapter.

8 FSS is the abbreviation of the Farm Structure Survey. It is carried out every 3 or 4 years as a sample survey

and once in ten years as a census by all Member States. The purpose of the survey is to obtain reliable data

on the structure of agricultural holdings in the European Union, in particular on land use, livestock and

labour force.

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CONTENTS

1. ECONOMIC SITUATION OF FARMS..................................................................... 6

1.1. Farm income ...................................................................................................... 6

1.2. Distribution of income .................................................................................... 14

1.3. Income components ......................................................................................... 21

1.4. Return on assets ............................................................................................... 23

2. IMPORTANCE OF DIRECT PAYMENTS FOR FARM INCOME ....................... 26

2.1. Proportion of direct payments in total revenue ............................................... 26

2.2. Proportion of direct payments in FNVA ......................................................... 27

3. CHARACTERISTICS OF FARMS REPRESENTED BY FADN .......................... 30

3.1. Financial structure ........................................................................................... 30

3.1.1. Total asset value ................................................................................ 30

3.1.2. Total liabilities ................................................................................... 32

3.1.3. Development of farm net worth ........................................................ 34

3.1.4. Solvency ............................................................................................ 35

3.1.5. Current and fixed assets .................................................................... 36

3.2. Labour ............................................................................................................. 39

3.2.1. Labour force ...................................................................................... 40

3.2.2. Remuneration of farm workers.......................................................... 42

3.3. Land ................................................................................................................. 44

3.3.1. Farm size ........................................................................................... 44

3.3.2. Importance of rented land.................................................................. 45

3.3.3. Level of land rents ............................................................................. 46

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1. ECONOMIC SITUATION OF FARMS

This chapter reviews the economic situation of farms across EU Member States, focusing

predominantly on the level, development and distribution of farm income. It also discusses

the various farm income components and the return farmers receive on their investment.

1.1. Farm income

For the purpose of this report, the income of agricultural holdings is measured using farm net

value added, family net income and the remuneration of family labour.

Farm net value added (FNVA) is equal to gross farm income minus costs of depreciation. It

is used to remunerate the fixed factors of production (labour, land and capital), whether they

are external or family factors. As a result, agricultural holdings can be compared regardless

of the family/non-family nature of the factors of production used.

FNVA = output + Pillar I and Pillar II payments + any national subsidies + VAT balance —

intermediate consumption — farm taxes (income taxes are not included) — depreciation.

The value is calculated per annual work unit (AWU) in order to take into account the

differences in the scale of farms and to obtain a better measure of the productivity of the

agricultural workforce.

Farm net income (FNI): After deduction of the external factors of production from the farm

net value added and by adding the balance of subsidies and taxes on investments, we get the

remuneration of family labour, own land and own capital which can be considered as farm

net income.

FNI = FNVA — total external factors + balance of subsidies and taxes on investments

Remuneration of family labour: In the agricultural sector, the bulk of the workforce consists

of family members who do not receive a salary but have to be remunerated from farm income.

As the FNVA is required to finance not only family labour but all fixed production factors,

another way of estimating income (the remuneration of family labour) is calculated as

follows:

Remuneration of family labour = FNVA + balance of subsidies and taxes — total external

production factors — opportunity costs of own land — opportunity costs of own capital. Or

starting from the previous indicator: farm net income — opportunity cost of own land —

opportunity cost of own capital

The value is calculated per family work unit (FWU). Only farms that use unpaid labour

(which in most cases means family members) are included in the calculation.

Results by Member State

FNVA varied significantly across EU Member States in 2012. Denmark ranked highest, with

EUR 167 600 per farm. This is 28 times higher than in Slovenia, the country with the lowest

value. The Netherlands, Slovakia and the Czech Republic also had high values. The EU-27

average was at around EUR 30 000 (see Figure 1.1). The main advantage of the average

FNVA/farm lies in its relative simplicity but it fails to reveal the differences in farm size, type

of farming or structural decreases in the labour force employed in agriculture. To overcome

this, FNVA is usually expressed per annual work unit (AWU), which can be seen as a

measure of partial labour productivity.

7

Viewed from this angle, the general picture of sizeable income variability within the EU

remains unaffected, though the ranking of Member States changes somewhat (Figure 1.2):

Denmark, the Netherlands and Belgium registered the highest FNVA per AWU, at

EUR 97 900, EUR 54 600 and EUR 43 100 respectively. This is almost three or, in the case of

Denmark, even five times the value of the average FNVA per AWU for the EU-27

(EUR 19 000), showing the predominance of granivore production, specialist horticulture and

milk sectors in the three countries’ agricultural sectors. At the other end of the spectrum,

Poland, Romania and Slovenia had the lowest FNVA per AWU (EUR 7 300, 5 400 and 4 000

respectively), because their agriculture has remained largely oriented towards less productive

types of farming, namely mixed farming and other permanent crops. It should also be noted

that in 2012 there was a decrease in the volume of almost all crop categories and the

agricultural output decreased most significantly in Romania and Slovenia.

It is also worth noting that, within the EU-15, only Portugal and Greece — Member States

characterised by a large number of small farms — had an FNVA per AWU below the EU-27

average. Except for Hungary, the Czech Republic and Estonia, EU-N10 Member States had

average income (FNVA/AWU) below the EU-27 average (EUR 19 000).

Figure 1.1: Farm net value added by Member State in 2012

(average per farm in EUR)

Source: Directorate General for Agriculture and Rural Development (DG AGRI) EU-FADN.

Farm net value added is an indicator that measures the remuneration of all fixed production

factors, whether they are external or family factors. In order to distinguish between them with

respect to income, we have to separate out the external factors of production from the

calculation. By doing this we arrive at farm net income (FNI). If we use this indicator, the

profitability in Member States changes. The most striking is the fact that Slovakia’s FNI was

the lowest out of all countries, although its FNVA was third highest in 2012. This can be

traced back to the characteristics of Slovakian agriculture, which is based mainly on large-

scale holdings cultivated by paid labour. The proportion of small family farms in total

agricultural land is very low today (less than 8 %).9

9 Number of holdings and utilised agricultural area in Slovakia, 2010 Agricultural Census.

http://ec.europa.eu/eurostat/statistics-explained/index.php/File:Figure_Number_of_holdings_and_Utilised_Agriculture_Area_(UAA)_by_UAA_size_classes_SK_2010.PNG

8

The Netherlands maintained its leading role in terms of farm net income, indicating that

income is still high enough to finance the estimated family factors of production, even after

deducting all external factors. The UK performed better when measuring FNI than it did for

FNVA, which shows that a significant part of its labour is family labour. The average FNI in

the EU-27 was EUR 19 800.

Figure 1.2: Farm net income by Member State in 2012


Source: DG AGRI EU-FADN

An alternative measure of agricultural income is the remuneration of family labour, as a high

proportion of work in the agricultural sector is carried out by family members. This is

expressed per family work unit (FWU) and is calculated by deducting from FNVA the costs

of wages, rent and interest paid, and the opportunity costs of own land and capital. At EU-27

level, the average remuneration of family labour per FWU stood at EUR 12 900 in 2012.

Denmark kept the first place from the previous year with the highest remuneration of family

labour per FWU, but the subsequent order has changed in 2012 compared to 2011. Denmark

was followed by the Netherlands (EUR 50 600) and France (EUR 33 800), who had the

second- and third highest remuneration of family labour in 2012. Denmark and the

Netherlands achieved these levels despite having had the highest opportunity cost of own land

among the Member States. The gap between the FNVA/AWU and remuneration of family

labour/FWU is the widest in Slovenia, Ireland and Sweden. The reasons behind this are the

high amount of interest paid by Swedish farmers and the high opportunity cost of own capital

in Slovenia (72 % of the family farm income). Slovenian farmers had the lowest remuneration

of family labour (EUR 590).

9

Figure 1.3: FNVA per AWU and remuneration of family labour per FWU, by Member

State in 2012

(average in EUR)


Results by EU group

Following the very high annual agricultural income (EUR 27 300) in 2011 in the EU-15,

FNVA per farm continued increasing to EUR 28 100 in 2012 (+3 %). In 2012 the increase in

the EU-27 value of agricultural output (+2 % in real terms) is linked to the performance of the

volume of animal output (+3.1 %) and to a lesser extent of crop production (+1.4 %).10

While

total labour input remained stable in the EU-N10, FNVA per farm marginally decreased from

EUR 17 600 to EUR 17 400, which also resulted in a decrease in the FNVA/AWU (by -0.2 %).

The remuneration of family labour per FWU in the EU-N10 decreased slightly more visibly,

from EUR 6 700 to EUR 6 600 (by -1.5 %).

In absolute terms, FNVA per AWU increased by EUR 6 300 or 29 % in the EU-15 in 2004-12,

and by EUR 4 500 or 92 % in the EU-N10 — a stronger increase in relative terms, but a

widening gap due to the fact that income in the EU-15 grew more in absolute terms. Looking

at the 2004-12 period, no convergence in nominal farm income can be observed between the

two groups of EU Member States.

Contrary to the slight decrease seen in the EU-25, FNVA per AWU in the EU-2 increased by

roughly 6.6 % between 2011 and 2012, from EUR 5 500 to EUR 5 800. At the same time the

remuneration of family labour stood at EUR 3 400 in 2011, and decreased to EUR 3 300

(by -2.9 %) in 2012.

10 Source: EU agriculture — Statistical and Economic Information — 2012.

http://ec.europa.eu/agriculture/statistics/agricultural/2012/pdf/overview_en.pdf.

http://ec.europa.eu/agriculture/statistics/agricultural/2012/pdf/overview_en.pdf

10

Figure 1.4: Long-term developments in FNVA per AWU and remuneration of family

labour per FWU



Regional differences

Map 1.1 shows the regional differences in FNVA per AWU in the EU-27 in 2012. Based on

this indicator, the agricultural holdings with the highest income per working unit were mainly

located in Denmark, the UK (England), north-western Germany, the Netherlands, northern

Italy, northern France and Belgium. In these regions, there is a high percentage of highly

intensive granivore production, horticulture and milk farms. On the other hand, regions with

very low farm income (below EUR 10 000 per year) were mostly situated in the EU-N10.

Only one region in the EU-15, Norte e Centro (Portugal), registered average farm income

below EUR 10 000.

11

Map 1.1: FNVA per AWU by FADN region in 2012

Source: DG AGRI EU-FADN.

When measured by the remuneration of family labour per FWU, the differences in income

between the EU-15 and the EU-N10 appear to be less pronounced compared to FNVA/AWU

(see Map 1.2). However, there are some regions in the EU-15 with extremely high income per

unit of family labour, such as the western part of eastern Germany (Sachsen-Anhalt EUR

104 700), and also in the north Mecklenburg-Vorpommern (EUR 88 800); and the Ile de

France (EUR 83 000) and Picardie regions (EUR 70 900) in France. The highest income per

FWU in the EU-15 is four times higher than in the Észak-Magyarország region in Hungary,

which registered the highest income per FWU (EUR 25 000) in the EU-N10. Income levels

are lowest in Bulgaria and Romania. The southern regions of Bulgaria (with EUR 1 600 and

EUR 2605, respectively) and Romania (EUR 2250) have especially low levels of

remuneration of family labour per FWU. The differences between the extreme values in the

EU-N10 have increased more in 2012 compared to 2011.

12

Map 1.2: Remuneration of family labour per FWU, by FADN region in 2012


Results by type of farming

Figure 1.4 shows significant differences in average FNVA across different types of farming.

In particular, average farm income was approximately four times higher in the granivore

sector than in the mixed crops and livestock sectors. One explanation for the relatively low

income of mixed farms is that many of them are very small. On the other hand, holdings

specialised in granivores could have had higher incomes in 2012 due to the growth in the

value of animal output which can be traced back to the increase in real producer prices. The

high income levels of farms specialised in granivores can also be explained by the fact that

most of these farms are big in terms of economic size.

When measured by FNVA per AWU, the general picture of income distribution by type of

farming changes (see Figure 1.5). Farms specialised in horticulture lost their position of

having the second highest FNVA in absolute terms, mainly due to the paid labour intensity

associated with this type of farming. Farms specialising in granivores had the highest FNVA

per AWU in 2012, and were followed by field crop farms. Field crop farms reached higher

income levels compared to 2011 due to higher producer prices for crops. The increase in real

prices (+7 %) offset the lower production values (-5.2 %).11

11 Source: EU agriculture – Statistical and Economic Information – 2012



13

The income of farms specialising in granivores, field crops, wine, horticulture and milk

production was above the EU-27 average. For permanent crop farms (other than wine), farms

specialising in grazing livestock (other than dairy) and mixed farms the income per worker

remained below average. The latter two types of farm had the lowest FNVA per AWU. From

2011 to 2012, FNVA per AWU decreased only for milk (by -12.8 %) and grazing livestock

farms (by -2.9 %), while income increased for all other types of farming. The income decrease

of dairy farms is due to the decrease of EU farm gate milk prices in 2012 compared to the

previous year.12

The remuneration of family labour per FWU does not significantly alter the

picture of relative productivity differences across various types of farming. While holdings

specialised in granivores and field crops remain at the top of the spectrum and mixed farms at

the bottom, dairy farms do slightly better than farms specialising in horticulture in terms of

remunerating family labour.

Figure 1.4: Average FNVA in the EU-27 by type of farming in 2012



12 Source: EU agriculture – Statistical and Economic Information – 2012



14

Figure 1.5: FNVA per AWU by type of farming in 2012

(in EUR)


Results by organisational form and EU group

From an organisational point of view, holdings in the FADN are divided into three groups:

(1) family farms, where the profits cover unpaid labour and own capital of the holder and the

holder’s family;

(2) partnerships, where the profits cover the production factors brought into the holding by a

number of partners (at least half of whom participate in the work of the farm as unpaid

labour); and

(3) other holdings with no unpaid labour or which are not included in the other two groups

(e.g. legal persons).

The results show that, on average, non-family farms generated higher FNVA than family

farms, with income disparities particularly visible in the EU-N10 and, to a lesser degree, in

the EU-15 and EU-2. The observed disparities across and within the three groups of Member

States mainly reflect differences in farm size. In the EU-N10, holdings classified as ‘other’

had the highest levels of FNVA. Income in these large commercial farms in the EU-N10

significantly exceeded the FNVA created by the corresponding group of holdings in the

EU-15 and EU-2 (EUR 302 800 as compared to EUR 88 400 and EUR 77 700, respectively).

On the other hand, on average, partnership farms in the EU-2 had significantly higher income

(EUR 199 200) than their counterparts in the EU-15 and EU-N10. On average, family farms

had the lowest FNVA levels out of all the organisational forms in each EU group.

15

Figure 1.6: FNVA by EU group and organisational form in 2012



When FNVA is weighted by AWU, non-family farms still tend to have higher income than

family farms across different EU groups (see Figure 1.7). However, in this case partnership

farms show higher values than the ‘other’ types (i.e. legal entities). In general, FNVA per

worker is greater in the EU-15 than in the EU-N10 or EU-2, irrespective of the organisational

type of farm. This can be partially explained by the larger labour force employed by holdings

in the new Member States.

Figure 1.7: FNVA per AWU and remuneration of family labour per FWU by EU group

and organisational form of the holding

(in EUR)


16

1.2. Distribution of income

As depicted by the ‘box-plots’13

in Figure 1.8, agricultural income varies considerably across

farms. The general pattern shows that a high proportion of farms have a relatively low income

level per worker, while a small proportion of holdings record a very high income level per

worker. For instance, the average FNVA per AWU in the EU-15 stood at around EUR 28 100

in 2012. However, 10 % of farms had an income per worker of more than EUR 55 500, and

50 % recorded an FNVA per AWU below EUR 15 100.

Average income per worker in the EU-N10 and EU-2 remained significantly below the EU-15

level. The mean of EU-N10 and EU-2 figures is in the upper 25 % of data, which means that

these box-plots are also skewed to the top (towards higher values). The EU-N10 average

income per worker stood at around EUR 9500, though 50 % of holdings had an income per

worker of less than EUR 4200. In the EU-2, half of the farms reported an FNVA per AWU of

less than EUR 2500.

Figure 1.8: Distribution of FNVA per AWU by EU group in 2012

(in EUR/AWU)


Figure 1.9 shows developments in income distribution for the EU as a whole in 2004-12.

Until 2007, income levels in the EU-27 were gradually increasing, as was average farm

income per AWU. From 2007 to 2009, the average level of income decreased. The box-plots

show that income in most farms decreased in the same period. The results shown by the Gini

coefficients (Figure 1.14.) help understand that some farms were able to maintain high

incomes because the inequality of income distribution deepened in 2009.

13 In the box plots, the inter-quartile range (between 25 % and 75 % of farms) is indicated by the yellow box;

the limits of 10 % of farms and 90 % of farms correspond to the end of lines (whiskers); the median (50 % of

farms) is the line crossing the yellow boxes, and the mean is shown by the ‘+’ sign.

17

This cannot be seen from the box-plots alone, as they show only 80 % of farms and exclude

the upper and lower 10 % of farms. The impact of the sizeable drop in agricultural output

prices is visible in the 2009 data, and explains the significant narrowing of the distribution of

income per AWU. After 2009, an upward tendency can be seen, leading once again to a wider

distribution of average income per worker in 2010 and 2011. In 2012, there was a slight

increase in average income per worker (by 4 %), and the upper whisker of the box-plot shows

that the upper 10 % of farms recorded higher average income than in 2011.

Figure 1.9: Distribution of FNVA per AWU by year

(in EUR/AWU)


Figure 1.10: Distribution of FNVA per AWU by type of farming in the EU-27 in 2012

(average in EUR/AWU)

Legend:

1 = Field crops

2 = Horticulture

3 = Wine

4 = Other permanent crops

5 = Milk

6 = Other grazing livestock

7 = Granivores


Figure 1.10 shows the distribution of FNVA/AWU by type of farm in the EU-27 in 2012.

18

In general terms, income distribution remains asymmetrical within each of the eight sectors

represented in the FADN (i.e. a small proportion of farms with very high income and a large

proportion of farms with low income14

).

The degree of these differences varies greatly across different types of farming. The most

pronounced differences between the mean and median values of FNVA/AWU are observed

for farms specialised in granivores. The distribution of FNVA/AWU is also highly uneven for

field crop and dairy farms (i.e. sectors with a larger inter-quartile range for FNVA/AWU). For

mixed farms, the best performing 25 % of farms have a larger impact on the average than the

remaining 75 % (their mean values are outside the boxes).

The trend in the distribution of FNVA/AWU over time varies from sector to sector. As shown

in Figure 1.11, the distribution of FNVA/AWU for specialised dairy farms became

increasingly asymmetric over the 2005-07 period. In 2007, income discrepancies were

particularly pronounced, and were accompanied by a significant increase in mean and median

levels. In 2008 and 2009, the degree of asymmetry decreased, as did mean and median

income. These developments were predominantly driven by increasing input prices in 2008

and the 2009 decrease in milk prices. From 2010 to 2011, FNVA/AWU increased, with the

mean income per worker approaching almost its 2007 level after a significant recovery in

prices and output during this period. In 2012, the income distribution became smoother as the

upper 10 % of farms registered a lower average income compared to 2011, and the mean and

median levels decreased.

Figure 1.11: Distribution of FNVA/AWU of dairy farms in the EU-15 by year

(in EUR)


14 Within a given sample, a single outlier will actually affect the average but will have no impact on the

median.

19

Figure 1.12: Distribution of FNVA/AWU of field crop farms in the EU-15 by year

(in EUR)


Figure 1.12 presents the average FNVA/AWU of specialised field crop farms. This ratio

fluctuated in 2004-12, with the first high point in 2007. The income peak was due to the fact

that the 2007 agricultural year was marked by a very sharp and remarkable increase in the

prices of many agricultural commodities, both in the EU and on world markets.

In the following two years (and especially in 2009), FNVA/AWU fell to the 2006 level, and

income distribution narrowed. In 2010-11, it returned to its 2007 level, and income

distribution became wider again. This recovery was the result of higher cereals prices and

volumes in 2010-11. As before, in 2012 the increase in real prices compensated the lower

production value for almost all crop categories. Consequently, farms specialised in field crops

had higher average income compared to 2011. While the best performing 10 % of farms had a

higher income level, the lowest 10 % of farms had lower income than in 2011 and the median

fell too. Therefore, the distribution has slightly shifted again in the direction of inequality.

For farms specialised in granivore production (Figure 1.13), average FNVA/AWU fell to a

low level in 2007 and 2008, as the dampening effect of extremely high feed prices more than

outweighed the favourable impact of higher output prices. After reaching their lowest points

in 2008, the median and mean values gradually started to increase slightly, in parallel with

decreasing income inequalities. In 2012, the best performing 10 % of farms reached a

significantly higher level of income, pushing up the mean value and causing income

distribution to widen again. This increase can be explained by the growth in volume and the

increase in producer prices (particularly for pork).

20

Figure 1.13: Distribution of FNVA/AWU of granivore farms in the EU-15 by year

(in EUR)


Figure 1.14 shows the distribution of income (FNVA) among the labour force (AWU) in the

EU-27 in 2012 using a Lorenz curve.15

In 2012, approximately one-third of the farm labour

force had a negative cumulated proportion of income.

The Lorenz curve shows that income is unevenly distributed among the labour force:16

80 %

of the labour force generated approximately 32 % of the farms’ income observed in FADN.

The remaining 20 % therefore generated 68 % of FNVA. Note that FNVA/AWU was negative

for around 6 % of total AWU employed in EU agriculture.

15 In order to draw the Lorenz curve, the income estimates are sorted in ascending order. Each observation is

weighted according to the weighting factor of the farm and the number of workers employed.

16 If income were equally distributed among the labour force, the Lorenz curve would become a straight line

linking the origin to the top right corner of the figure.

21

Figure 1.14: Lorenz curve of the distribution of FNVA/AWU in the EU-27 in 2012

So

urce: DG AGRI EU-FADN.

An alternative measure of the statistical distribution of income is the Gini index,17

which can

be between 0 and 1. The coefficient of 0 expresses perfect equality of income among the

labour force, while the coefficient of 1 reflects maximum concentration or inequality (with

one work unit capturing all the income in a sector).

Table 1.1 shows that income concentration in the EU-15 is typically lower than in the EU-

N10 or EU-2. In 2004-12, the highest income concentration was seen in the EU-2. Although

comparisons between groups should be made with caution, the observed differences partly

reflect differences in the structure of the farm sector.

For instance, due to the generally higher thresholds in the EU-15, the field of observation in

FADN does not include the lower economic size classes as it is in the most EU-N10

countries.

Looking at the development of the coefficient over time within each EU group, income

concentration has increased in the EU-15 from 2004 to 2011. In 2012, the income levels

converged again and reached the 2010 level. In the EU-N10, there have been minor

fluctuations in income distribution during the whole reference period. The economic crisis in

2009 seems to have increased income concentration in all EU groups, but the EU-N10 was

particularly affected by unequal income distribution. With the economic recovery, income

inequality narrowed in 2010, however there was still a slight concentration in 2011. Since

2011, income distribution has shifted again in the direction of inequality in the EU-N10, and

continued to do so in 2012.

In the EU-2, farm income inequalities were most apparent in the accession year (2007) and in

2009 due to the economic crisis. Income concentration gradually reduced over time due to the

increase of direct payments during the phasing-in process.

17 The Gini coefficient is usually based on the Lorenz curve. It can be thought of as the ratio of the area that

lies between the line of equality and the Lorenz curve over the total area below the line of equality.

22

Table 1.1: Development of the Gini coefficient of FNVA per AWU by EU group

2004 2005 2006 2007 2008 2009 2010 2011 2012

EU15 0.54 0.55 0.54 0.55 0.59 0.62 0.60 0.63 0.60

EU-N10 0.68 0.69 0.63 0.65 0.67 0.72 0.64 0.66 0.68

EU2 0.71 0.66 0.70 0.68 0.67 0.65 Source: DG AGRI EU-FADN

23

1.3. Income components

Results by EU group

Figure 1.15 shows the composition of farm receipts and expenses by EU group in 2012. On

average, expenses (including the remuneration of own factors of production) were higher than

receipts for farms in the EU-15, while receipts slightly exceeded expenses for the average

farm in the EU-N10 and EU-2.

On the revenue side, average receipts per farm in the EU-27 stood at EUR 82 000, out of

which total output represented EUR 71 200 (87 %) and subsidies18

EUR 10 800 (13 %). These

aggregated figures hide large differences between the EU groups, both in absolute and relative

terms: the average farm receipt in the EU-2 was roughly three times lower than in the

EU-N10 and 6.7 times lower than in the EU-15. In relative terms, subsidies accounted for

more than 17 % of average farm receipts in the EU-N10, compared to roughly 13 % both in

the EU-15 and in the EU-2.

Figure 1.15: Income components per farm by EU group in 2012



On the cost side, average farm expenses totalled EUR 82 700 in the EU-27. While this

aggregated figure again reflects highly contrasting price levels in the EU groups, the cost

structure as such has been found to be broadly similar across all countries. Intermediate

consumption19

represented approximately 50 % of total expenses.

18 Subsidies include the sum of net current and investment subsidies. They include EU coupled and decoupled

payments, less favoured area (LFA) payments, rural development payments and national aid. Net means the

balance of current subsidies and taxes plus the balance of subsidies and taxes on investment.

19 Intermediate consumption includes specific costs (including inputs produced on the holding) and overheads

arising from production in the accounting year. Specific costs can stem from seeds, seedlings, fertilisers,

crop protection products, feed for grazing stock and granivores etc.

24

Depreciation and expenses relating to external factors20

accounted for approximately 10-12 %.

The remainder was accounted for by the opportunity costs of own factors (family labour, own

land and own capital). While the EU-N10 and EU-15 show a similar distribution of cost

factors as the EU-27, for farms in the EU-2 intermediate consumption accounts for a smaller

part of total farm expenses (45 %) but opportunity costs account for a larger part of total own

factors (34 %).


In 2012, on average, farms specialised in granivores, field crops and horticulture showed a

positive balance of receipts and expenses as shown in Figure 1.16. Farms specialised in

granivores had the highest output of all farm types in the EU-27 (EUR 281 500). On the other

end of the spectrum, farms specialised in permanent crops other than wine generated the

lowest output, namely EUR 30 332. Grazing livestock farms recorded the highest average loss

per farm (EUR -8 100).

As concerns average direct payments per holding, farms specialised in field crops benefitted

most from subsidies (EUR 15 300 per farm), followed by dairy and grazing livestock farms

(EUR 15 200 and EUR 14 600 per farm, respectively). On the other hand, the horticulture

sector received, on average, the lowest amount of subsidies (EUR 2 700 per farm). The most

subsidised field crop farm received more than five times more subsidies than the least

subsidised horticultural farm.21

These discrepancies in subsidies across sectors still reflect the

past features of the CAP, which provided support in particular for the production of cattle and

field crops. However, note that horticultural farms have significantly higher receipts than field

crop or grazing livestock farms and might therefore be less reliant on public support.

Figure 1.16: Income components per farm by type of farming in 2012


Source: DG AGRI EU- FADN.

Note: Receipts (Rec), Expenses (Exp)

20 Expenses for external factors include wages, rent and interest paid.

21 This observation is based on the absolute value of subsidies for the average field crop and horticultural farm

disregarding the differences in the farm size of these two types of farming.

25

The cost structure varies markedly between sectors, reflecting differences in farm size,

technological processes and input prices. Granivore farms (typically large in economic size,

with technological processes involving a high turnover of animals) had the highest costs for

intermediate consumption due to feed costs (driven by higher prices for feeding stuffs),22

both

in absolute and in relative terms (EUR 202 500 per farm annually or nearly 73 % of total

expenses).

On the other hand, intermediate consumption on average totalled EUR 11 200 (or less than

29 % of total costs) for other permanent crop farms. Depreciation costs were, in relative terms,

broadly constant across sectors, amounting to around 11 % of total expenses. Granivore farms

spent least on depreciation (8 % of total expenses) while wine holdings spent most (13 %).

The proportion of external factors (wages, rent and interest paid) in total costs was

particularly high in the horticulture (21 %) and wine sectors (19 %), mainly due to the high

cost of external labour. On the other hand, other grazing livestock and granivore farms had

the lowest proportion of expenditure on external factors (around 8 %). In absolute terms,

horticulture holdings had the highest external factor costs (EUR 33 400), while farms

specialised in other grazing livestock, mixed and other permanent crops had the lowest (less

than EUR 6 000). Finally, the estimated costs of own production factors (family labour, own

land and own capital) as a proportion of total costs were highest for permanent crop farms

(44 %) and lowest for granivore farms (12 %).

1.4. Return on assets

Return on assets (ROA) measures the

effectiveness of a company’s assets in

generating revenue. It is defined as the

ratio of net income over total assets,

where the net income is defined as the

sum of FNVA and investment subsidies

minus wage costs, rent paid and the

opportunity costs of own labour.


The ROA of an average farm in the EU-27 remained similar to the previous year, at 2.0 % in

2012 and up from 1.8 % in 2010 (and only 0.4 % in 2009). Holdings in Hungary, Lithuania

and Estonia had the highest ROAs, mainly due to relatively low levels of opportunity costs

and fixed asset values (such as land and quotas). In 2012, six Member States registered a

negative ROA, with the lowest value recorded in Sweden (-2.6 %). In 2012, Sweden,

Slovenia, Malta, Slovakia, Finland and Ireland had the lowest ROAs in the EU (see Annex 8

for more details).

22 http://ec.europa.eu/agriculture/statistics/agricultural/2012/pdf/overview_en.pdf.

ROA=

FNVA

+ Balance of investment subsidies and taxes

- Wages paid

- Paid rent

- Capital costs

- Opportunity costs of family labour

Total assets

26

Figure 1.17: Return on assets by Member State in 2011-12




Granivore, horticulture and field crop farms had ROAs above 2.0 %, but this figure dropped

below 1 % for mixed crop-livestock holdings. Farms specialised in grazing livestock had a

negative ROA, which shows that they invested a high amount of capital into their production

while simultaneously receiving little income (see Figure 1.18). This result could be linked to

the slight decrease in production volume and in producer prices for some animal products.

Prices particularly dropped for milk (-4.8 %) in 2012.23

Figure 1.18: ROA in the EU-27 by type of farming in 2012



23 Source: EU agriculture – Statistical and Economic Information – 2012.



27

Trends by EU group

As shown in Figure 1.19, ROA fluctuated not only across EU groups but also over time for

each group. It decreased drastically for all countries in 2007-09 (except Bulgaria and

Romania) and from 2010 started to recover for all EU groups, albeit with varying intensity.

In the EU-15, all growth took place between 2009 and 2010, and ROA remained at its 2010

level even in 2012. In the EU-N10, the recovery process continued in 2011, reaching its

highest value in that year (3 %). The percentage of net income relative to farms’ total

resources in the EU-N10 decreased again in 2012 due to the decrease in net income (by -4 %)

and the increase in asset value. The increase in asset value can be explained by the high ROA

in 2011, which led farmers to invest in sowing crops and in equipment. After an increase in

2010, the average ROA marginally decreased in 2011 in the EU-2, and reached its highest

value (3.5 %) in 2012. In relative terms, this ROA was the highest among all EU groups in

2012, which actually masks that in absolute terms both net income and asset value were low

in the EU-2, only their ratio was high compared to other EU groups.

Figure 1.19: Changes in the ROA by EU group



28

2. IMPORTANCE OF DIRECT PAYMENTS FOR FARM INCOME

This chapter analyses the impact of direct payments on the income situation of European

farmers. Two economic indicators are used to express this: farm revenue and farm net value

added (FNVA). In our calculations, direct payments include total subsidies for operations

linked to production, including national aid.

2.1. Proportion of direct payments in total receipts


The average amount of direct payments received per holding in 2012 was EUR 9 140. The

proportion of direct payments in total revenue (output plus net current and investment

subsidies) in the EU-27 stood at 11.2 % in 2012, down from 11.9 % in 2011, as total farm

receipts increased by 5 % while the level of average direct payments per farm decreased by

1.4 %. This proportion varies among Member States. The total receipts of Irish, Greek and

Finnish farms are proportionately most dependent on subsidies (which represent nearly 20 %

of their total receipts). The importance of crops such as grain maize, wheat, spelt and

industrial crops, which used to be strongly supported before decoupling, explains the high

proportion of direct payments in Greece’s total revenue. In Finland, the high proportion of

public support in total receipts mainly reflects substantial national payments, which are

granted in addition to EU direct payments (national aid for southern Finland, northern aid and

national aid for crop production24

). Finally, direct payments account for the lowest proportion

of total receipts in the Netherlands (close to 3.5 %), where sectors with a lower proportion of

direct payments in total receipts, such as horticulture, pig and poultry production, are a

significant part of total agricultural output.

Figure 2.1: Proportion of direct payments in total receipts by Member State in 2012



24 Farming and Food in Finland. Ministry of Agriculture and Forestry, 2011.

29


As already stated, the proportion of direct payments in revenue varies markedly across types

of farming, reflecting mainly differences in average farm size. In addition, in the EU-15 the

historical model of the CAP was characterised by asymmetrical direct support across sectors

— a feature which has gradually been reduced following the 2004 reform. Figure 2.2 shows

that direct payments account for the highest proportion of total revenue in grazing livestock

(18.3 %) and field crop farms (15.7 %). On the other hand, they represent only a very limited

part of total revenue in the wine and horticulture sectors (3.3 % and 1.4 %, respectively).

Figure 2.2: Proportion of direct payments in total receipts by type of farming in 2012



2.2. Proportion of direct payments to FNVA

The role that direct payments play in sustaining farm income becomes even more apparent

when we look at their comparison with FNVA (see Annex 3). Consequently, if all other

factors remain equal, changes in direct payments will have a much greater impact on FNVA

than on total farm revenue.


In 2012, on average, direct payments accounted for nearly 31 % of FNVA in the EU-27, down

from 32 % in 2011 (Figure 2.3). This slight decrease was caused by a slight increase in FNVA

and a slight decrease in direct payments in 2012. The proportion of direct payments to FNVA

was highest in Finland (72 %), followed by Slovakia with the second-highest value in the EU-

27 (71 %). On the other hand, direct payments accounted for only 12 % of FNVA in the

Netherlands, which showed that the country was more focused on its highly profitable and

less subsidised sectors, such as horticulture and pig and poultry production.

Map 2.1 shows the regional differences in the proportion of direct payments to FNVA. The

lowest figure was seen in Hamburg (1 %), followed by Liguria and Trentino (2 % and 6 %,

respectively).

30

Figure 2.3: Proportion of direct payments to FNVA by Member State in 2012



Map 2.1: Proportion of direct payments to FNVA by FADN region in 2012


31


For total receipts, the proportion of direct payments to FNVA also fluctuates markedly

depending on the type of farming (Figure 2.4). In particular, direct payments represent a

substantial part of FNVA for grazing livestock, mixed and field crop farms, due to their

average farm size and the historical orientations of the CAP. Grazing and mixed farms

recorded below-average FNVA, while field crop farms had the highest average amounts of

direct payments in 2012, which led to the highest proportion of direct payments to FNVA in

these types of farming. On the other hand, direct payments play only a limited role in

sustaining income within the wine and horticulture sectors, which had one of the highest

FNVA in 2012.

Figure 2.4: Proportion of direct payments to FNVA by farm type in the EU-27 in 2012



32

3. CHARACTERISTICS OF ANALYSED FARMS

3.1. Financial structure

This chapter analyses the financial structure of agricultural holdings within the FADN field of

survey with respect to two main dimensions (country and type of farming) and using a

number of financial indicators derived from farm balance sheets.

3.1.1. Total asset value

Total assets are the property of the agricultural holding and are calculated as the sum of

current and fixed assets. Current assets in the FADN include non-breeding livestock, stock of

agricultural products and other circulating capital, holdings of agricultural shares, and

amounts receivable in the short term or cash balances in hand or in the bank. Fixed assets are

agricultural land, permanent crops, farm- and other buildings, forest capital, machinery and

equipment, and breeding livestock.

Long-term developments by EU group

Figure 3.1 shows that the value of total assets has been increasing in both the EU-15 and the

EU-N10. In the EU-15, the average value of total assets rose by more than 40 % in 2004-12,

while in the EU-N10 it nearly doubled during this period.

Figure 3.1: Long-term developments in the value of total assets (TA) and total

liabilities25

(TL)



25 The concept of total liabilities will be discussed in section 3.1.2.

33


As shown in Figure 3.2, the value of total assets of an average farm in the EU-27 stood at

approximately EUR 316 500 in 2012. However, this average masks sizeable variations across

Member States, reflecting differences in the structure of national agricultural sectors.

On average, Danish and Dutch farms held the highest amounts of assets (around

EUR 2 500 000 and EUR 2 200 000, respectively), reflecting very high land prices and the

importance of the types of farming that typically need considerable investment, such as milk,

granivores and horticulture production. In contrast, farms in Romania and Bulgaria had the

lowest values of total assets (under EUR 100 000) as they are characterised by less capital-

intensive types of farming and their farms have a smaller average economic size. These low

values of total assets were partly due to the lower land price levels in the EU-2.

Figure 3.2: Average total asset value per farm by Member State in 2012




Granivores and dairy farms have typically held the highest amounts of total assets — more

than three times the asset value of farms specialised in mixed (crop and livestock) farming,

which had the lowest values. These disparities are partly due to differences in capital intensity

across sectors.

34

Figure 3.3: Average total asset value by type of farming in the EU-27 in 2012



3.1.2. Total liabilities


In line with the general trend for total asset values (see Figure 3.1), total liabilities have also

increased. In the EU-15, the average value of total liabilities increased by 50 % in 2004-12,

while in the EU-N10 it rose by 48 % during this period.

In the EU-27, average liabilities per agricultural holding rose to EUR 47 900 in 2012, up from

EUR 47 400 in the previous year. As illustrated in Figure 3.4, both the total amount and the

composition of liabilities show wide variations across Member States. In absolute terms, the

Danish and Dutch farms had, on average, the highest total liabilities within the EU. In

contrast, total liabilities per farm remained very low in many Mediterranean Member States,

which may reflect difficulties farmers have in accessing credit markets in these countries.

However, these very low observed levels could also have resulted from different accounting

practices, where liabilities are typically included in farmers’ private rather than farm accounts.

In relative terms, agricultural holdings relied mostly on medium- and long-term loans, which

represented more than 90 % of total liabilities in Belgium, Italy, Cyprus, Denmark, Finland

and Slovenia. Short-term loans to finance agricultural activities were prominent in Hungary

(70 %), Slovakia (60 %), Lithuania (56 %) and Portugal (52 %).

35

Figure 3.4: Composition of liabilities per farm by Member State in 2012




As shown in Figure 3.5, farms specialised in granivores, specialised dairy and horticulture

had, on average, the highest total liabilities (EUR 206 500, EUR 96 700 and EUR 91 300,

respectively), which in fact mirrored the high total asset values observed in these farm types.

Permanent crop holdings recorded the lowest liabilities in 2012 (EUR 7 500), but they had the

second-lowest asset values as well.

Medium- and long-term loans were the dominant kind of liability for all farm types. Short-

term loans only played a significant role in wine holdings, where they accounted for around

45 % of total liabilities.

Figure 3.5: Composition of liabilities per farm in the EU-27 by type of farming in 2012



36

3.1.3. Development of farm net worth


Farm net worth is defined as the difference between total assets and total liabilities at the end

of the accounting year. In 2012, the average farm net worth stood at approximately

EUR 268 600 in the EU-27 (+1 % compared to 2011). The average net worth per agricultural

holding was highest in the UK (EUR 1 554 200), in the Netherlands (EUR 1 435 100), and

Denmark (EUR 997 500) (Figure 3.6). This shows the importance of the granivore and milk

sectors, which are characterised by above-average net worth values per farm (Figure 3.7).

Romanian (EUR 38 200) and Bulgarian (EUR 79 600) farms had the lowest values.

Figure 3.6: Farm net worth by EU group and Member State in 2011 and 2012



Figure 3.7: Farm net worth in the EU-27 by type of farming in 2012



Farm net worth for mixed farms (crops and livestock) was lowest, and remained significantly

below the EU-27 average, reflecting these farms’ lowest asset value in comparison with other

sectors.

37

3.1.4. Solvency

In this analysis, solvency is measured using the liabilities-to-assets ratio, which shows the

percentage of an agricultural holding’s assets that are financed through debt. This gives an

indication of a farm’s ability to meet its obligations in the long term (or its capacity to repay

liabilities if all assets were sold). The results should be interpreted with caution as a high

liabilities-to-assets ratio is not necessarily a sign of a financially vulnerable position. In fact, a

high ratio could also be an indication of a farm’s economic viability (i.e. its ability to access

outside financing), though there is certainly a threshold beyond which indebtedness will

compromise a farm’s financial health.

A high liabilities-to-assets ratio typically reflects heavy recourse to outside financing

(i.e. taking out loans). While the higher leverage (the amount of debt used to finance assets)

helps a farm to invest and typically increases its profitability, it comes at a greater risk as

leveraging magnifies both gains (when investment generates the expected return) and losses

(when investment moves against the investor26

).

As is the case for other financial indicators used, the liabilities-to-assets ratio varies

significantly across Member States and in some cases even within Member States, as shown

on Map 3.1. Farms in Denmark, France and the Netherlands had the highest liabilities-to-

assets ratio (at 60 %, 39 % and 36 %, respectively). The lowest average solvency levels were

observed in many Mediterranean Member States, as well as in Ireland, Romania and Slovenia

(below 3 %).

As has already been stated, these very low levels of indebtedness, and by extension of

solvency, could stem from the fact that in these Member States liabilities are typically not

included in the farm accounts but in farmers’ private accounts. However, in the case of

Ireland, low solvency levels mainly reflect relatively high asset values. As shown in Figure

3.8, the level of solvency also varies markedly across farm types, with farms specialised in

granivores, horticulture, and dairy production having the highest liabilities-to-assets ratios.

26 For example, due to unfavourable weather conditions or outbreaks of animal diseases.

38

Map 3.1: Average liabilities-to-assets ratio per farm by FADN region in 2012


Figure 3.8: Farm solvency in the EU-27 by type of farming in 2012



39

3.1.5. Current and fixed assets


Fixed assets27

account for the largest proportion of total assets in all Member States (see

Figure 3.9). In particular, total farm assets in Greece, Ireland, Malta and Slovenia consist

almost exclusively of fixed assets (more than 90 %). Farms there are mainly family-run and

may prefer the low investment risk accompanied with both reasonable and stable profitability

of fixed assets. The proportion of fixed assets was lowest in Slovakia (49 %), where the farms

are run mainly by companies whose operation relies more on current assets.

Figure 3.9: Composition of assets by Member State in 2012



Figure 3.10: Composition of fixed assets by Member State in 2012



27 Fixed assets include agricultural land, farm and other buildings, forest capital, machinery and equipment,

and breeding livestock.

40

The composition of fixed assets across Member States depends on the structure of the

agricultural sector. As shown in Figure 3.10, ‘land, permanent crops and quotas’ was the

largest component in most Member States in 2012. In particular, this category made up more

than 80 % of fixed assets in Ireland and the United Kingdom. On the other hand, ‘buildings’

were of major importance in Austria, Slovakia, Czech Republic and Romania (ranging from

45 % to 50 %). ‘Machinery’ accounted for the largest proportion of fixed assets in Lithuania

(50 %). Finally, ‘breeding livestock’ was the smallest component of fixed assets in all

Member States (ranging from 15 % in France to 1.6 % in Italy).

However, it should be stressed at this point that accounting practices vary markedly across

Member States. For instance, quotas are not marketable in some countries (e.g. France), so

they are not recorded as a farm’s separate asset, although their value is partly included in the

land value. Consequently, the value of the ‘land, permanent crops and quotas’ component is

underestimated compared to countries with marketable quotas (e.g. the Netherlands). There

are also differences in how land-related data is recorded. For example, in France, farmers in

some cases set up holdings that rent land to their members, and in this case the value of the

land is not included in these holdings’ total assets. This accounting practice thus increases the

relative proportion of other assets.


As shown in Figure 3.11, fixed assets accounted for 80 % of total assets in 2012. This

proportion varied slightly among types of farming, ranging from 84 % in specialised dairy

farms to 66 % in wine holdings.

Figure 3.11: Composition of assets by type of farming in 2012



For the composition of fixed assets, Figure 3.12 shows that ‘land, permanent crops and

quotas’ was the largest component in all farm types, though the proportion varied from more

than 80 % in farms growing other permanent crops to about 50 % in granivore farms. On the

other hand, granivore farms had the largest proportion of ‘buildings’ (32 %) and farms

growing other permanent crops had the lowest (10 %).

41

Farms specialised in horticulture recorded the largest proportion of ‘machinery’ in fixed

assets (about 16 %), while the proportion of ‘machinery’ in fixed assets for farms growing

other permanent crops was around 10 %, at the other end of the spectrum. Finally, ‘breeding

livestock’ accounted for the highest proportion of total assets in grazing livestock and dairy

farms (broadly 9 %).

Figure 3.12: Composition of fixed assets by type of farming in 2012



3.2. Labour

This section analyses the structure of the labour force employed by EU farms, focusing on the

average size of the labour force employed per farm, its composition, and wages paid. The

results show that the proportion of non-family labour in the total workforce is gradually

increasing in the EU-15, reflecting structural changes and increasing farm sizes. A similar

development can be observed in the EU-N10. In addition, there is significantly higher

variability across EU-N10 Member States, due to the predominance of very large farms often

organised as legal entities in many eastern European countries. There are Member States

where the proportion of family labour is higher than the EU-27 average in both the EU-15 and

the EU-N10. In terms of the proportion of unpaid working hours, Slovenia, Ireland and

Austria take the lead (about 95 %), while in Denmark and in the Netherlands this proportion is

around 50 %, showing balanced labour distribution between family and non-family labour

hours. In the EU-N10 the highest proportion of unpaid working hours (89 %) can be observed

in Romania. Slovakia (8 %) and the Czech Republic (22 %) are at the other end of the scale,

due to the predominance of very large farms, which are often organised as legal entities.

42

3.2.1. Labour force


The average total labour input of holdings stood at 1.6 AWU in 2012 in the EU-27, virtually

unchanged since the last two years, although it has decreased (by -11 %) compared to 2007.

As shown in Figure 3.13, it varied considerably across countries, ranging from 13.7 AWU in

Slovakia to 1.2 AWU in Greece. Slovak and Czech (6.5 AWU) farms had significantly higher

labour input compared to the remaining Member States, reflecting the predominance of very

large non-family agricultural holdings in their agriculture sector.

Figure 3.13: Labour input per farm (in AWU) by Member State in 2012



Figure 3.14 shows that labour input by type of farming was fairly close to the average

1.6 AWU per farm in all sectors apart from horticulture (with twice as much labour input) and

for granivore farms (where the AWU per farm was 25 % higher than the average).

Figure 3.14: Labour input per farm (in AWU) by type of farming in the EU-27 in 2012


43


Traditionally, a significant part of the labour force employed in agriculture is family labour.

Family labour as a proportion of total labour force28

represents the prevalent form of labour in

most Member States, with the exception of Slovakia, the Czech Republic, Hungary, Estonia

and Bulgaria. As Figure 3.15 shows, the proportion of paid labour in the total labour force in

these five countries was higher than 50 % — sometimes significantly so.

Figure 3.15: Proportion of working hours of paid and unpaid labour by Member State

in 2012



As shown in Figure 3.16, the proportion of paid labour is highest in horticulture holdings,

reflecting the typical recourse to seasonal workers. The proportion of paid labour is typically

lowest in grazing livestock, mixed (crops and livestock), and dairy farms.

28 The proportion is expressed as follows: time worked in hours by unpaid labour input (generally family) in the

holding divided by the time worked in hours by total labour input in the holding.

44

Figure 3.16: Proportion of working hours of paid and unpaid labour in the EU-27 by

type of farming in 2012


3.2.2. Remuneration of farm workers

Results by EU group

As shown in Figure 3.17, the nominal hourly wage increased in the EU-15 and in the EU-

N10. In the EU-15, the average nominal hourly wage rose by 23 % between 2004 and 2012,

from EUR 8 to EUR 10. In the EU-N10, it stood at EUR 4 in 2012, up from EUR 2 in 2004

(an increase of some 91 %). The average EU-2 nominal hourly wage came to around EUR 2,

up from EUR 1, which meant a 41 % increase over the 2007-11 period. Only the EU-2

showed a decrease in nominal hourly wage from 2011 to 2012 (by -3.7 %). Finally, the

average EU-27 nominal hourly wage stood at EUR 7.2 in 2012, compared to EUR 6.9 in

2011; this was an increase of about 5 % over this period. The average nominal hourly wage in

the EU-15 was approximately 2.5 times higher than in the EU-N10 and four times higher than

in the EU-2. Note that changes in the nominal wage more than compensated for price

increases over this period, so that the real hourly wage rose by around 2.4 % between 2011

and 2012 (EU-27 HICP29

inflation stood at around 2.5.% during this time).

29 The Harmonised Index of Consumer Prices (HICP) is an economic indicator constructed to measure the

changes over time in the prices of consumer goods and services acquired by households. It is the official

measure of consumer price inflation in the euro zone for the purposes of monetary policy in the euro area

and for assessing inflation convergence as required under the Maastricht criteria.

45

Figure 3.17: Long-term developments in average nominal wages




As Figure 3.18 shows, the average hourly nominal wage differs widely across the EU-27. In

2012, it was highest in Denmark (EUR 23) and lowest in Romania (EUR 2). Note that wages

in the EU-N10 and the EU-2, as well as in Greece and Portugal, were below the EU-27

average (EUR 7). Map 3.2 shows that the level of wages was highest in north-western

Europe: Denmark (EUR 23), Sweden (EUR 22), the French Champagne-Ardenne region

(EUR 18) and the Netherlands (EUR 15). At the other end of the scale were Romania,

Bulgaria and the central regions of Poland (around EUR 2).

Figure 3.18: Average nominal wages of paid labour in 2012

(EUR/hour)


46

Map 3.2: Average nominal wage by FADN region in 2012


47

3.3. Land

For most farm types, access to agricultural land is a precondition for economic activity. This

subsection analyses the amount of agricultural land available per farm, trends in the

ownership of land, and the cost of renting land.

3.3.1. Farm size

While it has already become clear throughout this report that the structure of farms varies

significantly across Member States, one of the most telling indicators of these differences is

the physical size of farms, measured by the average amount of agricultural land per farm. As

shown in Figure 3.19, the farms represented in the FADN are on average largest in Slovakia

(521 ha), followed by the Czech Republic (228 ha) and the UK (161 ha). Farms are smallest

in Greece, Cyprus (9 ha) and Malta (3 ha). The EU average was 32.7 ha in 2012, little

changed from the previous year. It should be noted that this average farm size is based on the

FADN survey, which does not cover all agricultural holdings in the EU but only those which

due to their size could be considered commercial. Thus the interpretation and the use of the

above-mentioned average farm size should be treated with caution (see the methodology

chapter for more information). The average farm size was mostly below the EU-27 average in

the Mediterranean countries, and in some of the Eastern European countries such as Poland,

Romania and Slovenia.

Figure 3.19: Total farm UAA30

by Member State in 2012

(average per farm in ha)

Source: DG AGRI EU- FADN

The average utilised agricultural land area was largest in field crop farms, followed by grazing

livestock farms. At the other end of the spectrum, horticultural farms were the smallest. The

average field crop farm (53 ha) was nearly nine times as large as the average horticultural

farm (6 ha) in 2011. However, it is important to stress that horticultural farms operate at a

much higher intensity, meaning that the land is a less important determinant of their level of

production.

30 UAA is the abbreviation of utilised agricultural area, which describes the area used for farming.

48

Figure 3.20: Total UAA of farms by type of farming in 2012

(average per farm in ha)


3.3.2. Importance of rented land

Structural change is ongoing in the agricultural sector, as reflected by the steadily decreasing

number of farms. Consequently, the remaining active farms tend to get larger as they buy or

rent the land previously used by farms which have ceased farming.

Figure 3.21: Long-term developments in the proportion of rented land in 2012

(average per farm in %)


As shown in Figure 3.21, the proportion of rented land in the EU-15 increased from about

51 % in 2004 to 54 % in 2012. This indicates that more than half of the land available on the

EU-15 market is rented rather than purchased. The proportion of rented land in the EU-N10

first dropped slightly from 51.5 % after the accession year, and then started to increase again

from 2006 until 2009. From 2009, there was another gradual decrease, so that the proportion

of rented land was below 50 % by 2012.

49

Note that these averages for different EU groups mask considerable national and regional

disparities, as shown on Map 3.3. Rented land as a proportion of total UAA is very high in

some regions of France (Picardie: 97 %; Lorraine and Bourgogne: 94 %), Slovakia (95 %31

),

Bulgaria (Severoiztochen: 92 %), Spain (Cantabria: 85 %), the Czech Republic, and in the

eastern and central regions of Germany. Conversely, it is below 30 % in many southern

European regions as well as in Ireland (19 %), Wales (26 %), Austria (28 %), Denmark (29 %),

and north-eastern Poland (30 %).

Map 3.3: Proportion of rented land in total UAA by FADN region in 2012


3.3.3. Level of land rents

As land prices are often influenced by factors originating outside the agricultural sector, the

annual rent farmers have to pay for one hectare of land is typically considered as the best

proxy for the cost of land. Map 3.4 shows that the level of land rents differs markedly across

EU regions. In 2012, the highest average land rent per ha was observed in the Canarias and in

the Hamburg region (approximately EUR 1 150 and EUR 780, respectively). Land rents were

also very high in the Netherlands (EUR 720) and in Denmark (EUR 640). On the other hand,

rents were particularly low in Latvia and Estonia (below EUR 30 per ha) and in many regions

with unfavourable conditions for intensive agricultural production, such as dry and

mountainous areas.

31 This very high proportion of rented land in total UAA reflects the business structure of Slovak agricultural

holdings (i.e. cooperatives renting land from their members).

50

In so far as the rental value of land reflects land scarcity, its level can be used as an indicator

of the risk of land abandonment. For instance, if land rents are high, it can be assumed that

farming is profitable and that there are enough farmers willing to use the land. On the other

hand, if rents are low, this indicates that there is little potential for making economically

profitable use of the land. Hence, adverse changes in the economic environment are highly

likely to result in land abandonment.

Map 3.4: Average land rent levels in the FADN regions in 2012


Results by farm type

The level of land rent depends on several factors, such as the scarcity of land, the degree of

competition between farmers in the local land market and the strength of demand for land in

different sectors. In areas where horticulture or wine production are important, suitable land is

scarce and land rents are much higher than, for example, in areas with extensive grassland.

Similarly, in areas with intensive livestock production, land prices tend to be higher because

additional land is often a precondition for expanding this production. Of course, other factors

such as the profitability of production, production structures and the institutional setting of

land markets must also taken into account as they influence the levels of land rents too. This

is mirrored in the average level of land rents per farm type shown in Figure 3.22.

51

Figure 3.22: Average land rent by farm type in 2012

(in EUR per ha)

Source: DG AGRI EU- FADN

Developments in land rent levels by EU group

As shown in Figure 3.23, the level of land rents in the EU-15 increased very gradually over

2004-12, from EUR 174 per ha to EUR 193 per ha. However, this trend was more pronounced

in the EU-N10, despite a small decrease in 2009: average land rent per hectare increased by

more than 117 % during this period, from around EUR 32 to EUR 70. In the EU-2, land rents

fell to EUR 63 in 2009 before increasing to EUR 120 in 2012 (+ 90 %). It is interesting to

observe that the average rent paid per ha has been, on average, higher in the EU-2 than in the

EU-N10 (over the period for which data are available). All in all, average land rents have

gradually increased in the EU since 2007 and stood at around EUR 164 per hectare in 2012

(+15 %). Finally, note that the land rent figures discussed in this subsection are averages and

do not therefore necessarily reflect prices in new rental contracts (which may be well above

the average level observed in the FADN).

Figure 3.23: Long-term developments in land rent levels

(in EUR per ha)


52

FIGURE INDEX

Figure1.1: Farm net value added by Member State in 2012 ................................................ 7

Figure 1.2: Farm net income by Member State in 2012 ……….…………………………8

Figure 1.3: FNVA per AWU and remuneration of family labour per FWU by Member

State in 2012 ....................................................................................................... 9

Figure 1.4: Long-term developments in FNVA per AWU and remuneration of family

labour per FWU ................................................................................................ 10

Figure 1.5: FNVA per farm in the EU-27 by type of farming in 2012 ............................... 13

Figure 1.6: FNVA per AWU by type of farming in 2012 ................................................... 14

Figure 1.7: FNVA by EU group and organisational form in 2012 ..................................... 15

Figure 1.8: FNVA per AWU and remuneration of family labour per FWU by EU group

and organisational form .................................................................................... 15

Figure 1.9: Distribution of FNVA per AWU by EU group in 2012 ................................... 16

Figure 1.10: Distribution of FNVA per AWU by year ......................................................... 17

Figure 1.11: Distribution of FNVA per AWU by type of farming in the EU-15 in 2012 .... 17

Figure 1.12: Distribution of FNVA per AWU of dairy farms in the EU-15 by year ............ 18

Figure 1.13: Distribution of FNVA per AWU of field crop farms in the EU-15 by year .... 19

Figure 1.14: Distribution of FNVA per AWU of granivore farms in the EU-15 by year ..... 20

Figure 1.15: Lorenz curve of the distribution of FNVA in the EU-27 in 2012 .................... 21

Figure 1.16: Income components per farm by EU group in 2012 ........................................ 23

Figure 1.17: Income components per farm by type of farming in 2012 ............................... 24

Figure 1.18: Rate of return on assets by Member State in 2011 and 2012 ........................... 26

Figure 1.19: ROA in the EU-27 by type of farming in 2012 ............................................... 26

Figure 1.20: Development of the ROA by EU group ........................................................... 27

Figure 2.1: Proportion of direct payments in total receipts by Member State in 2012 ....... 28

Figure 2.2: Proportion of direct payments in total receipts by type of farming in 2012 ..... 29

Figure 2.3: Proportion of direct payments to FNVA by Member State in 2012 ................. 30

Figure 2.4: Proportion of direct payments in FNVA by farm type in the EU-27, 2012 ..... 31

53

Figure 3.1: Long-term developments in the value of total assets (TA) and total liabilities

(TL) .................................................................................................................. 32

Figure 3.2: Average total asset value per farm by Member State in 2012 .......................... 33

Figure 3.3: Average total asset value by type of farming in the EU-27 in 2012................. 34

Figure 3.4: Composition of liabilities per farm by Member State in 2012 ......................... 35

Figure 3.5: Composition of liabilities per farm in the EU-27 by type of farming in 2012 . 35

Figure 3.6: Farm net worth per farm by EU group and Member State in 2011 and 2012 .. 36

Figure 3.7: Farm net worth per farm in the EU-27 by type of farming in 2012 ................. 36

Figure 3.8: Farm solvency in the EU-27 by type of farming in 2012 ................................. 38

Figure 3.9: Composition of assets by Member State in 2012 ............................................. 39

Figure 3.10: Composition of fixed assets by Member State in 2012 .................................... 39

Figure 3.11: Composition of assets by type of farming in 2012 ........................................... 40

Figure 3.12: Composition of fixed assets by type of farming in 2012 .................................. 41

Figure 3.13: Labour input per farm (in AWU) by Member State in 2012 ............................ 42

Figure 3.14: Labour input per farm (in AWU) by type of farming in the EU-27 in 2012 .... 42

Figure 3.15: Proportion of working hours of paid and unpaid labour by Member State in

2012 .................................................................................................................. 43

Figure 3.16: Proportion of working hours of paid and unpaid labour in the EU-27 by type of

farming in 2012 ................................................................................................ 44

Figure 3.17: Long-term developments in average nominal wages ....................................... 45

Figure 3.18: Average nominal wages of paid labour in 2012 ............................................... 45

Figure 3.19: Total farm UAA by Member State in 2012 ...................................................... 47

Figure 3.20: Total UAA of farms by TF in 2012 .................................................................. 48

Figure 3.21: Long-term developments in the proportion of rented land in 2012 .................. 48

Figure 3.22: Average land rent by farm type in 2012 ........................................................... 51

Figure 3.23: Long-term developments in land rent levels .................................................... 51

Figure 3.24: Physical farm size and Standard Output coverage of FADN compared to FSS

……………………………………………………………………….............. 56

Figure 3.25: FADN thresholds of the Member States in 2012 ..………………………….. 57

54

TABLE INDEX

Table 1.1: Development of the Gini coefficient of FNVA per AWU by EU group ............ 20

Table 1.2: Characteristics of the FSS and FADN ………………………………………... 56

MAP INDEX

Map 1.1: FNVA per AWU by FADN region in 2012 .......................................................... 11

Map 1.2: Remuneration of family labour per FWU by FADN region in 2012 .................... 12

Map 2.1: Proportion of direct payments in FNVA by FADN region in 2012 ...................... 30

Map 3.1: Average liabilities-to-assets ratio per farm by FADN region in 2012 .................. 38

Map 3.2: Average nominal wage by FADN region in 2012 ................................................. 46

Map 3.3: Proportion of rented land in the total UAA by FADN region in 2012 .................. 49

Map 3.4: Average land rent in the FADN regions in 2012 ................................................... 50

ANNEX INDEX

Annex 1: Farm Accountancy Data Network in the context of the Farm Structure Survey -

Methodology ......................................................................................................... 55

Annex 2: Definitions and their interpretations ...................................................................... 58

Annex 3: Income calculation ................................................................................................ 61

Annex 4: Threshold by Member State in 2012 (SO: Standard Output) ................................ 62

Annex 5: FNVA and remuneration of family labour per AWU by Member State and

organisational form in 2012 .................................................................................. 63

Annex 6: Number of holdings by type of farming in 2012 ................................................... 64

Annex 7: Breakdown of revenue and costs of EU farms in 2012 ......................................... 65

Annex 8: Balance sheet components in FADN ..................................................................... 66

Annex 9: Indicators by Member State in 2012 ..................................................................... 67

55

Annex 1: Farm Accountancy Data Network in the context of the Farm Structure

Survey — Methodology

The Farm Accountancy Data Network (FADN) is a European system of sample surveys

that are run each year to collect structural and accountancy data of farms. Its aim is to monitor

the income and business activities of agricultural holdings and to evaluate the impacts of the

Common Agricultural Policy (CAP). The FADN is the only harmonised source of micro-

economic data, which means that the accounting principles are the same in all EU Member

States.

FADN is linked strongly to the Farm Structure Survey (FSS) managed by Eurostat, since the

field of survey in the FADN is based on the FSS farms population. The FSS is organised in all

Member States in a harmonised base, whereas the characteristics are based on community

legislation, therefore comparable data are available for all countries in case of each survey.

The FSS population consists of all agricultural holdings in the EU of at least 1 ha.32

Although

the threshold for inclusion in the survey varies among countries, the FSS covers at least 98 %

of the total utilised agricultural area excluding common land and 98 % of the total number of

farm livestock units.

To ensure that the FADN sample provides representative data concerning the agricultural

population and reflects the heterogeneity of farming in Europe, the sample of farms is set up

on the basis of the typology classification that works on the same principle as in the FSS.

Farms are selected in the FADN sample on the basis of the official selection plan prepared by

each Member State. The selection plan is drawn up on the basis of the most recent statistical

data, from the Agricultural Census carried out every 10 years or the FSS carried out between

censuses. Consequently, the field of survey in FADN is actually a subset of the FSS.33

The selection plan defines the number of farms to be selected by region, type of farming,

economic size classes and specifies the detailed rules applied for selecting the holdings. The

3-way stratification of the universe based on the common typology classification allows it to

be represented as a 3-dimensional matrix of cells. The number of farms in each cell is derived

from the FSS. Each cell corresponds to a specific category of farms. An individual weighting

is applied to each farm in the sample and corresponds to the number of farms in the 3-way

stratification cell of the field of observations (or the FSS farms in a given cell) divided by the

number of farms in the corresponding cell in the sample (or the FADN farms in a given cell).

This weighting system is then used in calculating the FADN aggregated results used in this

report.

32 Member States can use thresholds different than 1 hectare, as long as they follow the coverage requirements

specified in Regulation (EC) No 1166/2008 of 19 November 2008 on farm structure surveys and the survey

on production methods.

33 Note that there are also methodological differences in data collection for the FSS and FADN. For example,

information on animals is requested in June for the FSS and an average of the number of animals over the

year is used in the FADN. Information on other gainful activities is requested for the FSS in the form of a

template, while in the FADN it is calculated based on accounts.

56

Table 1.2 Characteristics of FSS and FADN

FSS

FADN

Type of data Full population Sample of market-oriented farms

Extrapolation to the population based on

weighting factors

Thresholds Alternative thresholds (minimum

coverage should be guaranteed)

Based on Standard Output (formerly

SGM); separate thresholds for each

Member State

Sampling frequency 3-4 year interval Annual

Time series 1999; 2003; 2007; 2010 1989-2012

Spatial resolution Local Administrative Unit Farm identification at NUTS3 level

Information Structural Financial and structural

The FADN intends to cover Europe’s agricultural holdings in the best possible way in order

to represent the largest possible proportion of total agricultural output, area and farm labour

represented in the FSS (Figure 3.24).

Figure 3.24 Physical farm size and Standard Output coverage of FADN compared to

FSS

Note that the FADN’s field of survey does not cover all agricultural holdings in the EU but

only those which due to their size could be considered as market oriented.

57

Market-oriented farms must exceed a minimum economic size threshold measured in

Standard Output34

.

Because of the different farm structures in the European Union, each Member State specifies

their own thresholds. The threshold should ideally ensure high overall FADN coverage of the

FSS population in terms of Standard Output, but also of Utilised Agricultural Area and

Livestock Units at country level. The economic size thresholds range from as low as

EUR 2000 in Bulgaria and Romania to as high as EUR 25 000 in Belgium, Germany, France,

Luxemburg, Netherlands and the UK (Figure 3.25).

Figure 3.25 FADN thresholds in Member States in 2012 (in EUR)

The FADN is primarily designed for the evaluation of income and financial indicators. It is

not suitable for providing data on the farm structure of all farms, because it does not include

the whole agricultural population and applies thresholds. Furthermore, the FADN does not

focus on the totals of production but on average values per farm.

The most recent FADN data available for this report are for accounting year 2012. The

sample consisted of approximately 83 000 holdings in the EU-27, which represent nearly

5.0 million farms (40%) out of the total of 12.2 million farms observed in the FSS.

34 Standard Output (SO) is the average monetary value of the agricultural output at the farm-gate price of

each agricultural product (crop or livestock) in a given region. The SO is calculated by Member States per

hectare or per head of livestock, by using basic data for a reference period of five successive years. The SO

of the holding is calculated as the sum of the SO of each agricultural product present in the holding

multiplied by the holding’s number of hectares or heads of livestock. The SO coefficients are expressed in

euros and the economic size of the holding is measured as the total standard output of the holding expressed

in euros. Previously, using rules set by Decision 85/377/EEC, the economic size was measured as the total

Standard Gross Margin (SGM) of the holding expressed in European Size Unit (ESU) instead.

58

Annex 2: Definitions and their interpretations

Revenue items recorded in the FADN accounts

Output: includes crops and livestock production as well as other output if it is directly linked

to the farm’s activity, e.g. farm tourism, forestry, renewable energy, etc. It does not include

the household’s non-farm income.

Pillar I and Pillar II-type payments: in the context of this analysis, Pillar I and Pillar II-type

payments refer not only to the part financed by the EU but also to subsidies financed by

Member States, including national aid. The FADN does not allow for a clear distinction

between EU and national payments over such a long time period.

Investment subsidies: investment subsidies could be regarded as part of the Pillar II

payments. However, they are shown separately because they are treated differently in the

calculation of income estimates. As in the case of the Pillar I and Pillar II-type payments, they

include national payments.

Costs items recorded in the FADN accounts

Intermediate consumption: total specific costs and overheads arising from production in the

accounting year. Intermediate consumption for example includes the costs of feed, fertilisers,

crop protection and energy.

Depreciation: depreciation of capital assets estimated at replacement value.

(Net) Farm taxes: farm taxes, except VAT, and other taxes on land and buildings. Subsidies

on taxes are deducted. Personal income taxes are not taken into account.

(Net) Taxes on investment: taxes not arising from current productive activity in the

accounting year, net of subsidies.

Wages: wages and social security charges. Amounts received by workers considered as

unpaid workers (wages lower than a normal wage) are excluded.

Rents: rent paid for farm land and buildings and rental charges.

Estimation of the imputed unpaid family factor costs

Family labour cost: this cost is estimated on the basis of wages which the owner of the farm

would have to pay if s/he were to hire employees to do the work carried out by family

members.

It is estimated as the average regional wage per hour based on the FADN data35

multiplied by

the number of hours worked by family workers on the farm.

35 If there are not enough farms (fewer than 20) with paid labour at regional level, the national average is used.

59

It is commonly acknowledged that the number of hours worked by family workers is typically

overestimated. Thus, a ceiling of 3 000 hours per Annual Work Unit is applied (this is the

equivalent of 8.2 hours a day, 365 days a year, and corresponds more or less to the time that

can be spent on a farm by farmers milking cows).36

The use of hours makes it possible to give a manager more remuneration than an employee, if

s/he works more hours.

Reliable family labour cost estimates are difficult to obtain as records of hours worked on the

farm might be overestimated and it is not easy to determine what an appropriate remuneration

for family labour is. Farmers may agree to be remunerated at a below-average wage if they

consider farming as a way of life or have other sources of income for their household

(e.g. other gainful activities directly related to the holding, spouse working outside the farm,

etc.).

Own-capital cost

– Own-land cost: this cost is estimated on the basis of the rent that the owner of the farm

would have to pay if he were to rent the land s/he is using. It is estimated as the owned area

multiplied by the rent paid per hectare on the same farm or, if there is no rented land on the

farm, by the average rent paid per hectare in the same region and for the same type of

farming.37

– Cost of own capital (except land): the cost of own capital (permanent crops, buildings,

machinery and equipment, forest land, livestock and crop stocks) is estimated at its

opportunity cost. That is how much money the farmer could earn if he were to invest the

equivalent of its capital value in ‘safe’ financial assets.

The interest paid on the capital is not known, as this information is optional in the FADN

farm return. Nevertheless, in order to take into account the actual interest rate paid on the

farm, a ‘weighted’ interest rate is calculated as the weighted average of this interest rate for

liabilities and the long-term interest rate obtained from Eurostat. It should be noted that if the

‘weighted’ interest rate is lower than the long-term interest rate (which means that the

calculated rate of interest paid is lower than the long-term interest rate), the long-term interest

rate is used instead of the ‘weighted’ interest rate.

36 A constraint of this estimation method is that if a farmer were to receive a salary he would probably work

less.

37 If there are not enough farms (fewer than 20) in a given region for a given type of farming, the national rent

per hectare for this type of farming is used (based on the TF8 classification).

60

Own-capital value (excluding land and land improvement) is estimated as the average value

of the assets (closing plus opening valuation divided by two) multiplied by the real interest

rate.38

The correction is made by subtracting the inflation rate39

from the nominal interest rate.

The value of total circulating capital is not taken into account in the estimation process as data

are not sufficiently reliable in some Member States. The crop stocks value is included,

however.

To calculate unpaid capital costs, the interest paid is deducted from the sum of the own-land

cost and the cost of own capital except land to avoid double counting. The total capital cost

must be at least equal to the interest paid:

Imputed unpaid capital costs = Max (interest paid; own-land cost + estimated cost for own

capital except land – interest paid)

38 Any increase in the value of assets is excluded from income calculations. For example, land appreciates in

value over time, which is one of the reasons why investors invest in land. This gain is not included in the

income; therefore it would not be consistent to include it in the cost of capital. In addition, in the FADN

assets are valued at replacement value. Depreciation is based on this replacement value and therefore

already takes the increase in prices (inflation) into account. Consequently, it would be double counting to

include the inflation part of interest in the cost of capital.

39 The inflation rate is based on the Eurostat annual average rate of change in the Harmonised Indices of

Consumer Prices (HICPs), available from 1997. Inflation rates based on a GDP deflator and on a deflator of

gross fixed capital consumption have been tested, but were found to lead to very high negative costs for

capital, mainly in the EU-N10. An inflation rate calculated on the basis of price indices for gross fixed

capital consumption has been tested, as it seemed to be more closely related to assets. However, this rate has

been fluctuating widely over the years for certain Member States. In addition, land is one of the most

important assets which does not depreciate. It follows that the inflation rate of gross fixed capital

consumption may not have a closer relationship with the change in the price of agricultural assets than with

the consumer price indices.

61

Annex 3: Income calculation


62

Annex 4: Threshold by Member State in 2012 (SO40

: Standard Output)

Member State

Threshold

(in 1000

EUR)

Belgium 25

Bulgaria 2

Cyprus 4

Czech Republic 8

Denmark 15

Germany 25

Greece 4

Spain 4

Estonia 4

France 25

— France (Guadeloupe) 15

— France (Martinique) 15

— France (La Réunion) 15

Hungary 4

Ireland 8

Italy 4

Lithuania 4

Luxembourg 25

Latvia 4

Malta 4

Netherlands 25

Austria 8

Poland 4

Portugal 4

Finland 8

Sweden 15

Slovakia 15

Slovenia 4

Romania 2

United Kingdom 15

— United Kingdom (Northern Ireland) 15

40 The Standard Output (SO) is the average monetary value of the agricultural output at the farm-gate price of

each agricultural product (crop or livestock) in a given region. The SO is calculated by Member State per

hectare or per head of livestock, by using basic data for a reference period of five successive years. The SO

of the holding is calculated as the sum of the SO of each agricultural product present in the holding

multiplied by the holding’s relevant number of hectares or heads of livestock. The SO coefficients are

expressed in euros and the economic size of the holding is measured as the total standard output of the

holding expressed in euros.

63

Annex 5: FNVA and remuneration of family labour per AWU by Member State and organisational form in 2012


Source: DG AGRI EU-FADN Note. Where no information is displayed in a column, this is for confidentiality reasons (i.e. there were fewer than 15 holdings in the given category of the 2012 sample).

64

Annex 6: Number of holdings by type of farming in 2012

Farms represented Sample farms

Types of farming Sum Sum

Field crops 1 120 030 23 820

Horticulture 185 840 5 146

Wine 278 840 4 456

Other permanent crops 688 340 6 649

Milk 605 080 14 121

Grazing livestock 807 400 11 368

Granivores 170 050 5 785

Mixed (crops and livestock) 1 063 780 11 951

Total groups 4 919 360 83 296 Source: DG AGRI EU-FADN

65

Annex 7: Breakdown of revenue and costs of EU farms in 2012



Note: Receipts (Rec), Expenses (Exp).

66

Annex 8: Balance sheet components in the FADN


67

Annex 9: Indicators by Member State in 2012

Member

State

FNVA FNVA per

AWU

Income

remaining

per FWU

(*)

Return

on

assets

Proportion

DIRECT

PAYMENTS

in revenue

Proportion

DIRECT

PAYMENTS

in FNVA

Average

asset

value

Average

liabilities Net worth

Paid

labour

input

Unpaid

labour

input

Wages /

hour

Average

UAA

Proportion

of rented

land

Level of

rents

EUR EUR/AWU EUR/FWU % % % EUR EUR EUR % % EUR/hour ha % EUR/ha

BE 91 918 43 112 19 601 4.9 % 7.1 % 22.2 % 662 243 190 431 471 812 17.4 % 82.6 % 10.5 49.1 72.7 % 277.2

BG 18 969 7 692 3 247 6.1 % 12.4 % 30.9 % 99 054 15 780 83 275 52.8 % 47.2 % 1.8 35.7 89.3 % 163.2

CY 13 361 9 241 7 378 1.0 % 7.3 % 24.2 % 188 675 9 926 178 748 28.4 % 71.6 % 3.7 9.0 67.3 % 166.9

CZ 130 048 19 791 18 441 4.2 % 14.6 % 47.3 % 912 565 224 630 687 936 78.5 % 21.5 % 6.4 227.9 82.6 % 70.7

DK 167 619 97 888 79 925 3.1 % 7.1 % 21.2 % 2 467 701 1 470 169 997 532 49.7 % 50.3 % 23.3 95.3 29.0 % 641.6

DE 91 540 41 232 31 252 3.4 % 10.2 % 32.9 % 842 602 166 921 675 681 40.7 % 59.4 % 10.5 85.6 67.3 % 246.2

EL 14 077 12 202 -1 194 3.6 % 20.3 % 42.5 % 109 773 406 109 367 17.3 % 82.7 % 3.3 9.3 51.6 % 213.7

ES 28 030 20 033 14 856 1.9 % 14.1 % 30.2 % 263 385 7 685 255 700 23.8 % 76.2 % 7.6 38.6 36.8 % 115.9

EE 39 264 19 519 17 051 7.4 % 11.8 % 40.5 % 242 252 70 435 171 817 54.5 % 45.5 % 5.6 125.9 62.2 % 23.4

FR 77 253 38 041 33 831 5.2 % 12.0 % 35.9 % 436 510 169 077 267 433 30.3 % 69.7 % 13.4 85.4 87.7 % 168.0

HU 31 438 19 903 17 354 8.7 % 14.5 % 39.1 % 170 181 28 677 141 504 58.6 % 41.4 % 4.0 46.3 62.4 % 123.2

IE 28 905 23 683 6 341 -0.2 % 18.6 % 54.8 % 898 974 23 520 875 454 6.8 % 93.2 % 10.4 50.3 19.3 % 258.7

IT 28 653 22 699 18 896 0.4 % 8.9 % 18.8 % 388 298 3 347 384 951 20.1 % 79.9 % 8.9 15.3 43.1 % 193.1

LT 18 195 10 267 10 228 8.3 % 13.5 % 37.8 % 117 096 16 565 100 530 17.7 % 82.3 % 2.6 48.5 53.8 % 38.7

LU 60 088 33 711 26 827 0.6 % 11.8 % 47.5 % 1 129 609 250 321 879 287 18.6 % 81.4 % 11.3 79.1 52.6 % 217.7

LV 19 488 9 670 7 301 4.2 % 13.0 % 46.0 % 135 879 43 364 92 516 32.6 % 67.4 % 3.4 68.9 47.7 % 20.1

MT 10 289 7 390 6 383 -2.3 % 5.0 % 19.9 % 188 493 8 034 180 460 11.5 % 88.5 % 5.0 2.6 81.9 % 71.3

NL 150 707 54 634 50 607 2.1 % 3.5 % 11.7 % 2 238 490 803 345 1 435 145 44.6 % 55.4 % 15.3 35.7 41.3 % 724.7

AT 31 776 22 508 18 471 1.0 % 9.4 % 27.2 % 441 709 47 248 394 461 6.1 % 93.9 % 8.3 31.5 28.1 % 224.0

PL 12 736 7 375 5 606 1.3 % 12.9 % 36.8 % 156 236 9 525 146 710 12.4 % 87.6 % 2.9 18.8 26.7 % 68.2

PT 15 077 9 506 5 574 2.2 % 14.0 % 33.5 % 99 319 3 520 95 799 19.4 % 80.6 % 4.3 24.2 26.5 % 94.6

RO 7 093 5 440 3 270 2.8 % 12.0 % 24.6 % 39 774 741 39 033 11.0 % 89.1 % 1.7 10.1 56.5 % 93.6

FI 35 285 27 178 18 626 -0.8 % 16.5 % 72.2 % 428 061 112 898 315 163 19.2 % 80.8 % 13.8 54.7 33.9 % 215.8

SE 53 537 37 206 11 501 -2.6 % 10.6 % 47.9 % 934 995 291 931 643 064 19.9 % 80.1 % 21.4 101.3 54.1 % 218.4

SK 141 208 10 285 13 172 -1.3 % 15.4 % 71.7 % 941 465 129 657 811 809 92.4 % 7.6 % 5.8 521.5 95.0 % 41.3

SI 5 790 3 975 590 -2.5 % 11.9 % 69.0 % 193 767 4 732 189 035 4.4 % 95.6 % 4.0 11.6 35.0 % 97.7

UK 87 960 39 420 31 895 1.2 % 11.1 % 38.1 % 1 724 720 170 560 1 554 160 39.0 % 61.0 % 11.6 161.1 43.6 % 142.3

EU-27 29 587 18 957 12 886 2.0 % 11.2 % 30.9 % 316 437 47 863 268 575 22.7 % 77.3 % 7.2 32.7 54.2 % 164.4

EU15 42 844 28 125 19 891 1.9 % 10.8 % 29.9 % 480 992 78 048 402 943 25.3 % 74.7 % 10.2 41.9 54.1 % 193.0

EU-N10 17 399 9 506 6 568 2.4 % 13.4 % 40.3 % 172 483 16 723 155 760 23.1 % 76.9 % 4.1 30.1 48.7 % 70.0

EU2 8 279 5 831 3 268 3.5 % 12.1 % 26.0 % 45 694 2 243 43 451 16.6 % 83.4 % 1.8 12.6 65.8 % 120.3

Source: DG AGRI EU-FADN. (*) After deducting all economic costs except the opportunity costs for family labour.

European Commission


Disclaimer:This publication does not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein.

Contact:European CommissionDG Agriculture & Rural Development,Microeconomic analysis of EU agricultural holdingsE-mail: [email protected]: http://ec.europa.eu/agriculture/rica/index.cfm

European Commission

Directorate-General for Agriculture and Rural Development

http://ec.europa.eu/agriculture




This report provides an overview of key economic developments in the European agricultural sector based on the latest data available in the Farm Accountancy Data Network (FADN) which are from 2012

Documents

EU FARM ECONOMICS OVERVIEW FADN 2007ec.europa.eu/agriculture/rica/pdf/EU_FEO_FADN_2012.pdf · 2015-06-02 · EU FARM ECONOMICS OVERVIEW FADN 2012 EXECUTIVE SUMMARY This report provides