EU farm economics 2012

Transcription

1 EU farm economics 2012 based on FADN data

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3 EUROPEAN COMMISSION DIRECTORATE-GENERAL FOR AGRICULTURE AND RURAL DEVELOPMENT Directorate L. Economic analysis, perspectives and evaluations L.3. Microeconomic analysis of EU agricultural holdings Brussels, May 2013 EU FARM ECONOMICS OVERVIEW FADN 2009 EXECUTIVE SUMMARY 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 The main finding is that declines in average farm income over the past two years (2008 and 2009) wiped out virtually all of the gains achieved between 2004 and 2007 in both EU-15 and EU-10. Moreover, higher macroeconomic volatility has reversed the incipient convergence process between old and new Member States to the point that no tangible convergence in nominal farm income was observed over the period Finally, without the slightly higher amount of public support, as measured by the sum of EU and national subsidies, the above-mentioned contraction in farm income would have been even more pronounced. Income developments EU-27 average farm income declined sharply in 2009, due mainly to a sizeable drop in agricultural output prices. Based on the FADN data, average farm net value added per annual work unit (FNVA/AWU) contracted by around 17 %, from in 2008 to in This decline was entirely driven by the fall in FNVA, as AWU increased only marginally, and was primarily driven by a substantial drop in agricultural output prices (in particular in the crop, milk and meat sectors), reflecting both supply and demand developments in a difficult global economic environment. Looking at an alternative measure of farm income, remuneration per family work unit (i.e. income available after remuneration of all the external production factors labour, land and capital and adjusted for the opportunity cost of capital), stood at around in 2009, down from in the previous year. This decline masks substantial differences across Member States/regions and types of farming. Based on FNVA/AWU, farms in Denmark, the Netherlands, the UK and Belgium enjoyed, on average, the highest income in 2009, while those in Slovakia, Romania and Bulgaria were at the opposite side of the spectrum. Lombardy (Italy) was the region with the highest average income per farm within the EU. Regarding the income differences by type of farming, granivore, wine and horticulture holdings registered, on average, the highest FNVA/AWU. On the other hand, other permanent crops and mixed farm incomes remained well below the average. Income declined across all types of farming in 2009, with the notable exception of granivore farms, whose FNVA/AWU increased by around 20 % compared to 2008 as feed prices dropped in roughly equal proportions. Finally, at individual farm level, the income situation remains highly varied, even when differences in farm structure are taken into account. 1

4 Looking at the distribution of FNVA/AWU at farm level, the EU-10 and EU-2 average income per worker remained significantly below the EU-15 level. More than 95 % of farms in both EU-10 and EU-2 had an income which was below the average FNVA per AWU observed in EU-15. The EU-10 average income per worker stood at around 5 700, yet more than 50 % of holdings had an income per worker of less than (median income). In EU-2, half of the farms had an FNVA per AWU of less than Role of direct payments Direct payments helped to smooth the variability in EU farms income. In EU-27, the average share of direct payments in total farm revenue rose from 12.1 % in 2008 to 13.5 % in 2009 as total farm receipts dropped considerably, while the level of public support increased slightly. This share varies considerably across both Member States, with the Irish farms being proportionately most dependent on subsidies (which represent nearly 25 % of total farm revenues). The share of direct payments in revenue also differs substantially across types of farming, with the highest shares observed in grazing livestock and field crops farms (above 20 %). On the other hand, subsidies account for only a very limited part of total revenue in wine and horticulture holdings (less than 2.5 %). Farm structure Structure of European farms varies markedly in several ways: Financial configuration. The average farm size in terms of asset value, based on the 2009 data, was highest in Denmark and the Netherlands ( and respectively), reflecting very high land prices and the importance of sectors which typically necessitate considerable investments (such as milk, granivore and horticulture). By contrast, farms in Bulgaria and Romania displayed the lowest values of total assets (below 50000) as they tend to be smaller and oriented towards less capital-intensive types of farming. In addition, the general price level in EU-2 remains well below the EU- 27 average. Labour input. The average number of workers employed per farm stood at 1.6 AWU at EU-27 level in However, it varied significantly across Member States, ranging from 15.5 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 larger than in permanent crops other than wine holdings (the sector with the lowest labour input). Family labour accounted for 77 % of the total labour force in EU-27 and thus represented the most prevalent form of labour in all but five Member States (Slovakia, the Czech Republic, Hungary, Bulgaria and Estonia). The average hourly wage of farm workers stood at 6.34 in EU-27 during 2009, up 6.3 % from a year earlier. This nominal wage increase more than compensated for the general increase in price level (EU-27 HICP inflation stood at 1.0 % in 2009). Land use. The average EU farm size was 32 ha in 2009, little changed from a year earlier. However, it displayed considerable variability across Member States, ranging from 575 ha per farm in Slovakia to 4 ha per farm in Malta. Rented land accounted for 53 % of the total agricultural area at EU-27 level in Land rents were particularly high (above 700 per ha) in the Netherlands and Canarias (Spain), while they remained below 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 price paid by grazing livestock farms. At EU-27 level, however, land rents have changed little since 2007 at 143 per ha. 2

5 The Farm Accountancy Data Network (FADN) is a European system of sample surveys that are run each year and collect structural and accountancy data relating to the farms; their 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 cover the most relevant part of the agricultural activity of each EU Member State (MS), i.e. at least 90 % of the total Standard Gross Margin 1 (SGM) and 90 % of Utilised Agricultural Area covered in the Farm Structure Survey (FSS, EUROSTAT). For 2009, the sample consists of approximately holdings in EU-27, which represent nearly 5.0 million farms (36 %) out of a total of 13.7 million farms included in the FSS. 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 2009 accounting year due to time lags stemming from complex data collection, control and processing. For further information see: 1 The Standard Gross Margin (SGM) is the difference between the standardised monetary value of gross production and the standardised monetary value of certain special costs. This difference is calculated for the various crop and animal characteristics (per hectare or per animal) at the level of the survey district for each Member State and given in euro. By multiplying the areas or the number of animals by the corresponding SGM and then adding these totals together, the total SGM of the holding is obtained. By adding the total SGM of all holdings of a Member State, the total Member State SGM is obtained. The concept of SGM is used to calculate the economic size and the type of farming in the FADN and in the Farm Structure Survey (FSS) organised by EUROSTAT. 3

6 CONTENTS 1. ECONOMIC SITUATION OF FARMS Farm income Distribution of income Income components Return on assets IMPORTANCE OF DIRECT PAYMENTS FOR FARM INCOME Share of direct payments in total revenue Share of direct payments in FNVA FARM STRUCTURE Financial structure Total asset value Total liabilities Development of farm net worth Solvency Current and fixed assets Labour Labour force Remuneration of farm workers Land Farm size Importance of rented land Level of land rents

7 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 Farm income For the purpose of this report, the income of agricultural holdings is measured by means of the farm net value added 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 (work, 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 employed. FNVA = output + Pillar I and Pillar II payments + VAT balance -intermediate consumption - farm taxes (income taxes are not included) - depreciation. The value is given 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. Remuneration of family labour: In the agricultural sector the bulk of the work force does not receive a salary but has to be remunerated from the farms income. As the FNVA is required to finance not only family labour but all production factors, another income estimator the remuneration of family labour is estimated as follows: Remuneration of family labour = FNVA + balance of subsidies and taxes - wages paid - paid rent - estimate of the costs for own land - estimate of the costs for own capital. The value is given by family labour unit (FWU). Only farms with unpaid labour (which in most cases means family members) are included in the calculation. Results by Member State The FNVA continued to show significant variability across EU Member States in 2009: it ranged between in the Netherlands and in Romania, with the EU-27 average standing at around (see Figure 1.1). While the main advantage of FNVA as an indicator for measuring income developments lies in its relative simplicity, it fails to account for differences in farm size, type of farming or structural decline in the labour force in agriculture. To do so, FNVA is typically expressed per AWU, which is nothing less than a measure of partial labour productivity. Viewed from this angle, the general picture of sizeable income variability within the EU remains unaffected, though the ranking of MS changes somewhat (Figure 1.2). Denmark, the Netherlands and the UK registered the highest FNVA per AWU of , and respectively. This is more than two or, in the case of Denmark, even three times the value of the average FNVA per AWU for the EU-27 ( 13900), reflecting the predominance of highly productive granivore production, specialist horticulture and milk sectors within the agricultural sector in these three economies. At the other end of the spectrum, Bulgaria, Romania and Slovakia displayed the lowest FNVA per AWU ( 3 800, 3650 and respectively) as their agriculture has remained largely oriented towards less productive types of farming, namely mixed farming and other permanent crops. Note also that within EU-15, FNVA per AWU was below the EU-27 average only in Greece and Portugal two MS that are characterised by a large number of small farms. 5

8 DK NL UK BE DE IT LU FI FR SE AT ES IE CZ EL HU MT EE PT CY LT LV PL SI BG RO SK NL CZ UK BE DK DE FR LU IT FI AT SE ES SK EE MT HU IE EL PT LV LT CY BG PL SI RO Figure1.1: Farm net value added by Member State in ,000 90,000 75,000 60,000 45,000 30,000 15,000 FNVA EU27 FNVA 0 An alternative measure of agricultural holdings income, namely the remuneration of family labour expressed per family work unit, sheds a significantly different light on farm income distribution within the EU in Denmark, the MS with the highest FNVA per AWU, actually displayed the lowest remuneration of family labour per FWU within EU-27 ( ), caused by the large amount of interest paid by Danish farmers and the high level of wages. The MS with the highest remuneration for family labour per FWU were the UK ( ), Belgium and Italy ( each). At EU-27 level, the average farm income stood at in Figure 1.2: FNVA per AWU and remuneration of family labour per FWU by Member State in ,000 40,000 30,000 20,000 10,000 FNVA/AWU EU27 FNVA/AWU Remuneration of family labour/fwu EU27 Remuneration of family income/fwu 0-10,000-20,000-30,000-40,000-50,000 6

9 Results by EU groups EU-15 agricultural holdings income, whether measured by FNVA per AWU or the remuneration of family labour per FWU, declined in 2009 for the second consecutive year to and respectively on the back of a sizeable drop in agricultural output prices. These two consecutive years of declines actually wiped out most of the revenue gains achieved over the period and were primarily driven by decreases in FNVA / the remuneration of family labour, as AWUs / FWUs had remained fairly stable. Farm income developments in EU-10 closely mirrored the general pattern observed in EU-15, with the 2009 FNVA per AWU and the remuneration of family labour per FWU decreasing to and respectively. It is worth pointing out that without the increase in (net) subsidies in both EU-15 and EU-10, the negative income developments observed in would had been even more pronounced. Regarding the convergence of revenues between EU-10 and EU- 15 (based on FNVA per AWU), farm income in EU-10 was growing at a faster pace than in EU-15 over the period , though the level of income was actually diverging in absolute terms between the two groups of MS. The opposite happened during 2008 and 2009: agricultural holdings income registered larger falls in relative terms in EU-10 than in EU-15, yet the gap in the levels of income actually narrowed slightly. To sum up, based on the available FADN data over the period , no tangible convergence in nominal farm income was observed between EU-10 and EU-15. Finally, contrary to the general trend observed in EU-25, EU-2 farm income rose by roughly 50 % between 2007 and 2009 to stand at (FNVA per AWU) and (the remuneration of family labour per FWU). Figure 1.3: Long-term developments in FNVA per AWU and remuneration of family labour per FWU 30,000 EU27 FNVA/AWU EU15 FNVA/AWU EU10 FNVA/AWU EU27 Remuneration of family labour/fwu EU15 Remuneration of family labour/fwu EU10 Remuneration of family labour/fwu 25,000 20,000 15,000 10,000 5, Regional differences Map 1.1 shows the regional differences in FNVA per AWU within EU-27 in Based on this indicator, the agricultural holdings with the highest incomes were mainly located in Denmark, Belgium, the Netherlands, northern Germany, northern France, northern Italy, the UK (England and Wales) and northern Spain (Castilla-León). On the other hand, regions with very low farm incomes (i.e. below per year) were mostly, but not exclusively, 7

10 situated in EU-10 MS. However, Portugal (Norte e Centro), Greece (Ipiros-Peloponissos- NissiIoniou) and Italy (Abruzzo) also registered very low average farm incomes. Map 1.1: FNVA per AWU by FADN region in2009 When measured by the remuneration of family labour per FWU, the differences in 2009 income between EU-15 and EU-12 appear to be less pronounced (see Map 1.2). Northern Italy, alongside north-eastern Germany, England, two Spanish regions (Castilla-León and Comunidad Valenciana) and southern Belgium (Wallonia), registered the highest income per unit of family labour. While income levels tend to be lower in eastern and southern Europe, many western European countries/regions (e.g. Denmark, southern Sweden, the Netherlands, Ireland, France, Austria and southern Germany) also displayed very low remuneration of family labour per FWU, reflecting higher wages and land rents. 8

11 Map 1.2: Remuneration of family labour per FWU by FADN region in 2009 Results by type of farming Figure 1.4 depicts large discrepancies in FNVA per farm across different types of farming. In particular, average farm income was approximately four times larger in the horticulture sector than in the mixed crops and livestock sector. One possible explanation for the relatively low income of mixed farms is that many of them are typically very small and mainly located in EU-10, where income levels tend to be generally lower. On the other hand, horticulture holdings appear to be more frequent in EU-15. When measured by FNVA per AWU, the general picture of income distribution by type of farming remains little changed (see Figure 1.5). The granivore, wine and horticulture sectors continued to display above--average incomes, while permanent crops other than wine and mixed farms income remained below the average. Note that FNVA per AWU declined for all types of farming in 2009 compared to 2008 levels, except for granivore farms, which registered an almost 20 % increase in income as feed prices dropped in roughly equal proportions. The remuneration for family labour per FWU, which by definition remains below FNVA per AWU, does not significantly alter the picture of relative productivity differences across various types of farming of different types of holdings (with granivores, horticulture and wine holdings remaining at the top of the spectrum, and mixed farms at the bottom). 9

12 Figure 1.4: FNVA per farm in EU-27 by type of farming in ,000 FNVA EU27 FNVA 60,000 50,000 40,000 30,000 20,000 10,000 0 Horticulture Granivores Wine Milk Grazing livestock Fieldcrops permanent crops Mixed (crops and livestock) Figure 1.5: FNVA per AWU by type of farming in ,000 25,000 FNVA/AWU EU27 Remuneration of family income/fwu Remuneration of family labour/fwu EU27 Remuneration of family income/fwu 20,000 15,000 10,000 5,000 0 Granivores Wine Horticulture Milk Grazing livestock Fieldcrops permanent crops Mixed (crops and livestock) Results by organisational farm and EU group From the organisational point of view, holdings in the FADN are divided into three groups: (1) family farms, where the profits cover the 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 non-family farms generated, on average, higher FNVA than family farms, with income disparities particularly visible in EU-10 and, to a lesser degree, in EU-15 and EU-2. The observed disparities both across and within the three groups of MS mainly 10

13 Partnerships Total Partnerships Total Partnerships Total Partnerships Total reflect differences in farm size. While holdings classified as other displayed the largest FNVA within each group of MS, income of these large commercial farms in EU-10 significantly exceeded the FNVA created by the corresponding group of holdings in EU-15 and EU-2 ( as compared to and respectively). On the other hand, EU-15 partnerships and especially family farms had, on average, significantly higher incomes that their counterparts in new Member States. Figure 1.6: FNVA per farm by EU group and organisational form in , , , , ,000 80,000 60,000 40,000 20,000 0 EU15 EU10 EU2 EU27 11

14 Partnerships Total Partnerships Total Partnerships Total Partnerships Total When FNVA is weighted by AWU, the conclusion that non-family farms tend to display higher incomes than family farms remains valid across different EU groups (see Figure 1.7). The FNVA per worker (a measure of partial labour productivity) is greater in EU-15 than in EU-10 or EU-2, irrespective of the organisational type of farm a phenomenon that can be explained partially 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 35,000 30,000 FNVA/AWU Remuneration of family labour/fwu 25,000 20,000 15,000 10,000 5,000 0 EU15 EU10 EU2 EU27 12

15 1.2. Distribution of income As depicted by box-plots 2 in Figure 1.8, agricultural incomes vary considerably across farms. The general pattern is that a large proportion of farms display 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 EU-15 FNVA per AWU stood at around in However, 10 % of the farms had an income per worker of more than , while half of the farms recorded FNVA per AWU below In line with past regularities, the EU-10 and EU-2 average income per worker remained significantly below the EU-15 level. Alternatively, more than 95 % of farms in both EU-10 and EU-2 had an income which was below the average FNVA per AWU observed in EU-15. While FNVA per AWU is also unevenly distributed in the new MS, the degree of income disparity was less pronounced compared to EU-15. The EU-10 average income per worker stood at around 5 700, though more than 50 % of holdings had an income per worker of less than In EU-2, half of the farms returned FNVA per AWU of less than Figure 1.8: Distribution of FNVA per AWU by EU groups in 2009 Figure 1.9 (see next page) shows developments in income distribution for the EU as a whole over the period Until 2003, income discrepancies in EU-15 were gradually rising along with the average farm income. However, the average level of income dropped markedly and income discrepancies narrowed somewhat following the 2004 enlargement. The structural impact of the 2007 accession of Romania and Bulgaria is less visible in the data owing to their lower relative weight with respect to the size of the EU at that time and a favourable general income situation during that year. Finally, the impact of a sizeable drop in agricultural output prices is clearly visible in the 2009 data, as evidenced by a strong decline in the 2 In the box plots the inter quartile range (range between 25 % of farms and 75 % of farms) is indicated by the yellow box; the limits of 10 % of farms and 90 % of farms corresponds to the end of lines (whiskers); the median (50 % of farms) is the line crossing the yellow boxes, and the mean corresponds to the + sign. 13

16 average income level and a less uneven, though still highly asymmetrical, income distribution. Figure 1.9: Distribution of FNVA per AWU by year Figure 1.10: Distribution of FNVA per AWU by type of farming in EU-15 in 2009 Legend: 1 = Field crops 2 = Horticulture 3 = Wine 4= permanent crops 5= Milk 6= grazing livestock 7= Granivores 8= Mixed Figure1.10 illustrates the distribution of income by type of farming in In general terms, income distribution remains highly asymmetrical within each of the eight sectors typically distinguished in the FADN (i.e. a small proportion of farms with a very high income and a large proportion of farms with low incomes 3 ). The degree of these income discrepancies 3 While the high-income farms substantially raise the average income level, they have only limited impact on the median level of income (within a given sample, a single outlier will actually distort the average but will have no impact on the median). 14

17 greatly varies across different types of farming. As in the previous years, the most pronounced differences between the mean and median values of income are observed for granivores farms. Though, the distribution of income is also highly uneven within the milk, field-crop and mixed sectors (i.e. sectors with a large interquartile range for FNVA per AWU). The trend in the distribution of income over time varies from sector to sector. As shown in Figure 1.11, the distribution of income for specialised dairy farms widened progressively until Since then, the degree of income asymmetries has diminished along with the reductions in mean and median income levels. These developments were predominantly driven by increasing input prices in 2008 and declines in milk prices in Figure 1.11: Distribution of FNVA per AWU of dairy farms in EU-15 by year Figure 1.12: Distribution of FNVA per AWU of field crop farms in EU-15 by year 15

18 As shown by Figure 1.12, the average income of specialised field-crop farms followed overall a very gradual upward trend between 1999 and This long-run tendency masks in particular large changes in income distribution in 2007, which were triggered by spikes in cereals prices. In the case of farms specialised in granivore production, the degree of income asymmetries as well as the mean and median levels of income fluctuated substantially over time, mainly reflecting large swings in output prices (Figure1.13). Income fell to a particularly low level in 2007 as the dampening effect of extremely high feed prices more than outweighed the favourable impact of higher output prices. Overall, the income distribution tends to widen in years characterised by high income. This suggests that some farms can benefit more from the favourable situation than others, probably due to economies of scale. Figure 1.13: Distribution of FNVA per AWU of granivore farms in EU-15 by year Figure1.14 (see next page) illustrates the distribution of income (FNVA) among the labour force (AWU) in EU-27 in 2009 by means of a Lorenz curve. 4 As the 2009 income of a large share of the farm labour force was negative, so too is the cumulated share of income up to a certain point. The Lorenz curve shows that income is unevenly distributed among the labour force: 5 80 % of the labour force generated approximately 35 % of income of the whole agricultural sector. The remaining 20 % thus realised 65 % of FNVA. Finally, note that FNVA per AWU was negative for about 32 % of total AWU employed in EU agriculture. 4 5 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. If income were equally distributed within the labour force, the Lorenz curve would become a straight line linking the origin to the top right corner in the Figure. 16

19 Cumulated share of total FNVA[%] Figure 1.14: Lorenz curve of the distribution of FNVA in EU-27 in Share of AWU[%] An alternative measure of the statistical dispersion of income is the Gini index, 6 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 inequality (with one work unit capturing the entire income of the sector). Table 1.1 shows that the income concentration in EU-15 is typically lower than in EU-10 or EU-2, with the latter group displaying the highest income concentration (unequal distribution). Though comparisons between groups should be made with caution, the observed differences partly reflect disparities in the structure of the farm sector. For instance, the sample includes very small farms in EU-10 and EU-2, which are mostly excluded in EU-15. Looking at the development of the coefficient over time within each EU group, income concentration has changed little in EU-15 since In EU-10, the income disparities had been narrowing following EU accession (due, in part, to increasing CAP support) though the initial declines were almost completely reversed over the last two years under review. Finally, farm income inequalities in EU-2 have continued to narrow since EU accession in Table 1.1: Development of the Gini coefficient of FNVA per AWU by EU groups EU EU EU 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. 17

20 1.3. Income components Results by EU groups Figure 1.15 illustrates the composition of farm receipts and expenses by EU groups in It shows that an average farm operated at a loss (after the remuneration of own factors) irrespective of the EU group considered. On the revenue side, the average receipts per farm in EU-27 stood at , out of which total output and public support 7 represented (84 %) and (16 %) respectively. These aggregated figures mask large differences, both in absolute and relative terms, among the EU groups: the average farm revenue in EU-2 was roughly 2.5 / 6 times lower than in EU- 10 and EU-15 respectively. In relative terms, subsidies accounted for more than 21 % of average farm revenue in EU-10 as compared to roughly 15 % in both EU-15 and EU-2. Figure 1.15: Income components per farm by EU groups in , ,000 80,000 60,000 40,000 20,000 0 Receipts Expenses Receipts Expenses Receipts Expenses Receipts Expenses EU27 EU15 EU10 EU2 Total output Public support Total intermed. Consumption Depreciation Total external factors Own factors On the cost side, average farm expenses totalled in EU-27. While this aggregated figure again reflects highly contrasting price levels among the EU groups, the cost structure as such has been found to be broadly similar within the EU. Intermediate consumption represented approximately 50 % of the total expenses. Depreciation and expenses for external factors 8 accounted for approximately 10 % each. The remainder is accounted for by the (estimated) opportunity costs of own factors (family labour, own land and own capital). It is worth noting that, in relative terms, the opportunity costs for own family labour were highest in EU-2, for own land in EU-15 and for own capital in EU-10. This reflects, among other things, differences in farm size, type of farming and the relative prices of input factors across the EU groups. 7 8 Public support is the sum of net current and investment subsidies. It includes EU coupled and decoupled payments, less favoured area (LFA) payments, rural development payments and national aid. Expenses for external factors include wages, rent and interest paid. 18

21 Results by type of farming In 2009, granivore farms not only generated the largest output of all farm types in EU-27 ( ) but were also the only type operating at a profit after the remuneration of own factors of production, as shown by Figure On the other end of the spectrum, permanent crops other than wine holdings returned the lowest output, namely The highest average loss per farm was recorded by specialised dairy farms ( ) though, in relative terms, mixed crops and livestock farms were the most affected, with the average loss representing almost 16 % of the total revenues. As to the average direct payments per holding, grazing-livestock farms benefitted from most subsidies ( ), followed by specialised dairy and field crops farms ( and respectively). On the other hand, the horticulture sector received, on average, the least public support ( 2 000).These discrepancies in subsidies across sectors still reflects the past features of the CAP, which provided support in particular for the production of cattle and field crops: in many MS, decoupled direct payments per hectare have remained linked to the historical level of support received by farms. Figure 1.16: Income components per farm by type of farming in , , , , , ,000 75,000 50,000 25,000 0 Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Fieldcrops Horticulture Wine permanent crops Milk Grazing livestock Granivores Mixed (crops and livestock) Total Groups Total output Public support Total intermed. consumpt. Depreciation Total external factors Own factors Source: DG AGRI EU- FADN. Note. Receipts (Rec), Expenses (Exp). The cost structure varies markedly among sectors, reflecting differences in farm size, technological processes and input prices. Granivore farms (typically large in size with technological processes involving a high turnover of animals) had the highest costs for intermediate consumption (due to feed costs), both in absolute and in relative terms ( or nearly 70 % of the total expenses). On the other side of the coin, intermediate consumption totalled, on average, (or represented less than 30 % of the total cost) for other permanent crop farms. Interestingly, depreciation costs were, in relative terms, broadly constant across sectors, accounting for around 11 % of total expenses. The share of external factors (wages, rent and interest paid) in total costs was particularly high in the horticulture and wine sectors (somewhat above 20 %) due mainly to for the high cost of external labour. On the other hand, other grazing livestock and granivore farms were the type of farms with the lowest share of expenditure on external factors (around 8 %). In absolute terms, horticulture holdings returned the largest external factors costs ( ), while other grazing livestock and other permanent crops farms spent the least (both less than 6 000). Finally, the 19

22 LT BG HU RO EL BE IT EE ES UK AT DE PT LV CZ CY LU PL NL IE DK MT FR SI FI SE SK estimated costs of own production factors (family labour, own land and own capital), as a share of total costs, were highest in permanent crop other than wine farms (above 40 %) and lowest in granivore farms and horticulture holdings (around 15 %) 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, with net income being defined as the sum of FNVA and net subsidies less wage costs, rent paid and the opportunity costs for own labour. Results by Member State As shown by Figure 1.17, the ROA of an average EU-27 farm declined sharply to 0.4 % in 2009, down from 1.8 % a year earlier. Holdings in the Baltic countries, Hungary, Romania and Bulgaria typically tend to display the largest ROAs, mainly due to relatively low levels of opportunity costs and asset values. On the other hand, 13 Member States registered a negative ROA in 2009 (as compared to six in the previous year), with Slovakia and Sweden having the lowest ROA in the EU (see Annex 8 for more details). Figure 1.17: Rate of return on assets by MS in 2008 and 2009 ROA= FNVA + Balance of subsidies and taxes - Wages paid - Paid rent - Opportunity costs for family labour Total assets 12% 9% Average EU27 6% 3% 0% -3% -6% -9% -12% -15% Results by type of farming The ROA varied considerably across different farm types (see Figure 1.18). Granivore, horticulture and wine farms have continued to display above-the-average levels of ROA. In particular, the ROA of granivore holdings (4.9 %) was nearly 12 times greater than the average for the whole agricultural sector in EU-27 (0.4 %). permanent crops, and mixed crops and livestock holdings were the only two types of farms that registered negative a ROA in 2009 (-0.1 % and -0.9 % respectively). 20

23 Figure 1.18: ROA in EU-27 by type of farming in % 4.5% 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% -0.5% -1.0% Granivores Horticulture Wine Milk Grazing livestock ROA 2009 Average EU-27 Fieldcrops permanent crops Mixed (crops and livestock) Trend by EU group As shown by Figure 1.19, ROA also displayed marked fluctuations not only among the EU groups but also over time for a given group, especially during the latest years included in the sample, reflecting higher volatility of macroeconomic fundamentals as well as weather-related factors (e.g. a drought in Bulgaria and Romania during 2007). A tentative upward trend could be distinguished in the case of ROA developments in EU-15 before turbulent economic conditions considerably compressed the return in Note also that ROA in all EU groups has remained at relatively low levels compared to other sectors of the economy. Figure 1.19: Development of the ROA by EU groups 6% 5% EU27 EU15 EU10 EU2 Linear (EU15) 4% 3% 2% 1% 0% -1% -2% -3%

24 IE EL SK FI LV LT BG CZ HU FR SE ES PT PL EE UK DE LU RO SI AT DK BE CY IT MT NL 2. IMPORTANCE OF DIRECT PAYMENTS FOR FARM INCOME This chapter analyses the impact of direct payments (DP) on the income situation of European farmers. Two concepts of income are considered in turn, namely farm revenue and FNVA Share of direct payments in total revenue Results by Member State The share of DP in total revenue (output plus net current and investment subsidies) in EU-27 rose from 12.1 % in 2008 to 13.5 % in 2009 as total farm receipts dropped substantially, while the level of public support increased slightly. This share varies widely among Member States, with Irish farms total receipts being proportionately most dependent on subsidies (which represent nearly 25 % of total revenue). The importance of crops such as tobacco, grain maize and cotton, which used to be strongly supported before decoupling, is the main explanatory factor behind the high share of DP in total revenue observed in Greece. In Finland, the large share of public support in total receipts mainly reflects substantial national payments, which are granted in addition to EU direct payments. Finally, DP account for the lowest share of total revenue in the Netherlands (close to 4 %), where sectors with a lower share of DP in total revenue, such as horticulture, pig and poultry production, represent a significant proportion of total agricultural output. Figure 2.1: Share of public support in total receipts by MS in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Source: DG AGRI EU-FADN %Public support on receipts %Output on receipts EU27% of public support Results by type of farming As already indicated, the share of DP in revenue varies markedly across types of farming, reflecting mainly differences in average farm size. In addition, in EU-15, the historical model of the CAP was characterised by asymmetrical direct support across sectors an element which has been gradually smoothed following the 2004 reform. Figure 2.2 (see next page) shows that public support accounts for the highest share of total revenue in grazing livestock (26 %) and field crops farms (22 %). On the other hand, subsidies represent only a very limited part of total revenue in the wine and horticulture sectors (2 % and 1 % respectively). 22

25 Figure 2.2: Share of direct payments in total receipts by type of farming in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Grazing livestock Fieldcrops Mixed (crops and livestock) Milk permanent crops Granivores Wine Horticulture %Public support on receipts %Output on receipts Total Groups % of public support 2.2. Share of direct payments in FNVA The role direct payments play in sustaining farm revenue becomes even more apparent when we look at their share in FNVA a concept which measures net farm income, i.e. after deduction of costs (see Annex 2). Consequently, changes in direct payments will, all other things being equal, have a much larger impact on FNVA than total farm revenue. Results by Member State In 2009, DP accounted on average for nearly 40 % of FNVA in EU-27, up from 33 % in 2008 (Figure 2.3). This steep increase is due largely to a sizeable drop in FNVA in difficult economic conditions. In particular, the share of DP in FNVA rose sharply to 444 % in Slovakia in 2009 (up from 69 % a year earlier), following a 25 % increase in the amount of net subsidies in combination with a more than 80 % drop in FNVA (caused mainly by a sharp contraction in both crops and livestock production). On the other hand, direct payments represented only 15 % of FNVA in the Netherlands, reflecting the orientation of the Dutch sector towards (highly profitable and) less subsidised sectors, such as horticulture and pig and poultry production. Finally, Map 2.1 illustrates the regional differences in the share of DP in FNVA. The latter was lowest in Hamburg (1 %), followed by Liguria and Trentino (2 % and 4 % respectively). 23

26 SK FI SE IE LV CZ EE FR HU LU LT DE UK SI DK BG PL EL AT PT ES RO BE CY MT IT NL Figure 2.3: Share of direct payments in FNVA by MS in % % % Public support in FNVA EU % % % % % % % 50.00% 0.00% Map 2.1: Share of direct payments in FNVA by FADN region in

27 Results by type of farming The share of direct payments in agricultural income also fluctuates markedly with the type of farming (Figure 2.4). In particular, public subsidies represent a substantial part of FNVA in field crops, mixed farming, grazing livestock and specialised dairy farms as a result of historical orientations of the CAP. On the other hand, direct payments play only a limited role in sustaining income within the wine and horticulture sectors. Figure 2.4: Share of direct payments in FNVA by farm type in EU-27, % 60% %Public support infnva EU 27 50% 40% 30% 20% 10% 0% Fieldcrops Mixed (crops and livestock) Grazing livestock Milk permanent crops Granivores Wine Horticulture 25

28 3. FARM STRUCTURE 3.1. Financial structure This chapter analyses the financial structure of agricultural holdings within the EU by reference to two main dimensions (country and type of farming) and by means of a number of financial indicators derived from farms balance sheets 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 (TA) has been following an upward trend in both EU-15 and EU-10. In the former, the average value of total assets rose by more than 50 % over the period , while in the latter it increased by nearly 80 % between 2004 and Figure 3.1: Long-term developments in the value of total assets (TA) and liabilities (TL) 450, , , , , , , ,000 50,000 0 EU15 TA EU15 TL EU10 TA EU10 TL Results by Member State As shown by Figure3.2, the total value of assets of an average EU-27 farm stood at approximately in However, this average masks sizeable variations across Member States on the back of differences in the structure of national agricultural sectors. Danish and Dutch farms held, on average, the most assets (around and respectively), reflecting very high land prices as well as the importance of types of farming which typically necessitate considerable investments, such as milk, granivore or horticulture 26

29 DK NL UK LU IE SK CZ DE SE BE AT FI FR IT MT ES EE SI CY HU PL LT LV PT EL BG RO production. By contrast, farms in Bulgaria and Romania had the lowest total assets (under ) as they are, on average, relatively smaller and predominantly oriented towards less capital-intensive types of farming. Moreover, these low total assets have also partly reflected the lower general price level in EU-2. Figure 3.2: Average total asset value per farm by MS in ,500,000 2,250,000 2,000,000 1,750,000 1,500,000 1,250,000 1,000, , , ,000 Total assets EU27 Total assets 0 Results by type of farming Dairy and granivore farms have typically held the highest total assets roughly three times the assets of other permanent crops farms, which posted the lowest value. These disparities are due, among other things, to differences in the typical degree of production process capital intensity across sectors. Figure 3.3: Average total asset value by type of farming in EU-27in , ,000 Total assets EU27 Total assets 400, , , ,000 0 Milk Granivores Horticulture Grazing livestock Wine Fieldcrops Mixed (crops and livestock) permanent crops 27

30 DK NL SE CZ LU BE SK DE FR UK FI EE AT HU LV IE MT LT BG PL ES IT CY SI PT RO EL EU Total liabilities In EU-27, total liabilities have, on average, accounted for a small proportion of farms funding sources. In this respect, it is worth pointing out that while the 2004 and 2007 enlargements have affected the average level of total liabilities per farm, the impact has been substantially smaller than on total assets per farm. Results by Member State In line with the general trend for total asset values (see Figure 3.1), total liabilities have also edged up, albeit at a slower pace, in both EU-15and EU-10. In EU-27, average liabilities per agricultural holding rose to in 2009, up from in the previous year. As illustrated by Figure 3.4, both the total amount and composition of liabilities show wide variations across Member States. In absolute terms, the Danish and Dutch farms had, on average, the greatest total liabilities within the EU. By contrast, total liabilities per farm remained very low in many Mediterranean Member States, which could, prima facie, reflect difficulties farmers have in accessing credit markets in these countries. However, these very low observed levels could also result from different accounting practices, where liabilities are typically included in farmers private rather than farm accounts. Agricultural holdings relied most on short-term loans to finance their activities in Hungary, Portugal, Slovakia, the UK and Lithuania (with short-term loans accounting, on average, for around half of total liabilities). By contrast, medium- and long-term loans represented more than 90 % of total liabilities in Belgium, Italy, Slovenia, Cyprus, Denmark and Finland. Figure 3.4: Composition of liabilities per farm by MS in ,300,000 1,200,000 1,100,000 1,000, , , , , , , , , ,000 0 Long & medium-term loans Short-term loans Results by type of farming As shown by Figure 3.5, granivore, horticulture and specialised dairy farms had, on average, the highest total liabilities ( , and respectively), which in fact mirrored the high total asset values observed in these farm types. Permanent crops other than wine holdings recorded the lowest liabilities in 2009 ( 6 700). Regarding the composition of 28

31 NL UK DK LU IE SK DE CZ SE BE AT IT ES MT FI FR SI CY EE PL HU LT PT EL LV BG RO liabilities, wine holdings relied most on short-term loans to finance their activities, while the specialised dairy farms did so least (these loans accounted for around 45 % and 15 % of total liabilities respectively). Figure 3.5: Composition of liabilities per farm in EU-27 by type of farming in , , ,000 80,000 60,000 40,000 20,000 Long & medium-term loans Short-term loans 0 Granivores Horticulture Milk Mixed (crops and livestock) Wine Fieldcrops Grazing livestock permanent crops Total Results by Member State 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 2009, the average farm net worth stood at approximately in EU-27 (+0.7 % compared to 2008). The average net worth per agricultural holding was highest in the Netherlands, the UK and Denmark (Figure 3.6), reflecting the importance of the granivore and milk sectors, which are characterised by above-average net worth per farm (Figure 3.7 on the next page). The lowest values were registered by Romanian and Bulgarian farms. Figure 3.6: Farm net worth per farm by EU group and MS in 2005 and ,250,000 1,125,000 1,000, EU , , , , , , ,

32 Figure 3.7: Farm net worth per farm in EU-27 by type of farming in , , , EU , , , , ,000 50,000 0 Milk Granivores Grazing livestock Wine Fieldcrops Horticulture Mixed (crops and livestock) permanent crops Solvency In the present analysis, solvency is measured by the liabilities-to-assets ratio. 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 of the 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 increase its profitability, it comes at greater risk as leveraging magnifies both gains (when investment generates the expected return) and losses (when investment moves against the investor 9 ). As for other farm financial indicators, the liabilities-to-assets ratio varies substantially across Member States and in some cases even within Member States, as shown by Map 3.1 (see next page). Farms in Denmark, France and the Netherlands had the highest liabilities-to-assets ratio (at 52 %, 39 % and 38 % respectively). The lowest average solvency levels were observed in many Mediterranean Member States (below 3 %). As has already been indicated, 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 the private accounts of farmers. 9 For example, due to unfavourable weather conditions or outbreaks of animal diseases. 30

33 As depicted by Figure 3.8, the level of solvency also varies markedly across farm types, with horticulture, granivore and specialised dairy farms recording the highest liabilities-to-assets ratios, though the latter remained overall at relatively restrained levels (below 50 %, which means that most farms assets were financed through equity). Map 3.1: Average liabilities-to-assets ratio per farm by FADN region in 2009 Figure 3.8: Farm solvency in EU-27 by type of farming in % 2009 EU % 30% 25% 20% 15% 10% 5% 0% Horticulture Granivores Milk Mixed (crops and livestock) Fieldcrops Wine Grazing livestock permanent crops 31

34 IE UK ES CY DK IT NL EL DE PT PL SI SE LU BE MT FI HU BG LV RO FR AT LT EE CZ SK EU27 EL IE SI MT PL UK IT NL DK BE PT CY DE FI LU RO EE AT SE CZ LT LV ES HU BG FR SK EU27 EU15 EU10 EU2 Results by Member State Current and fixed assets Fixed assets 10 account for the largest proportion of total assets in all Member States (see Figure 3.9). In particular, the total farm assets in Greece, Ireland and Slovenia consist almost exclusively of fixed assets (around 95 %). Figure 3.9: Composition of assets by MS in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Fixed assets Current assets Figure 3.10: Composition of fixed assets by MS in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Land, perma. Crops & quotas Buildings Machinery Breeding livestock The composition of fixed assets across MS depends, on the structure of the agricultural sector. As shown by Figure 3.10, land, permanent crops and quotas were the largest component in 10 Fixed assets include agricultural land, farm and other buildings, forest capital, machinery and equipment and breeding livestock. 32

35 most Member States in In particular, this category made up more than 80 % of fixed assets in Ireland, the United Kingdom and Spain. On the other hand, buildings were of major importance in Austria, the Czech Republic, Romania and Slovakia (in the range 45 % to 50 %). Machinery accounted for the largest share of fixed assets in Lithuania (more than 50 %). Finally, breeding livestock was the smallest component of fixed assets in all Member States (its share ranged from 15 % in France to 1.5 % in Denmark). It should be stressed at this juncture, though, that accounting practices vary markedly across Member States. For instance, quotas are not marketable in some countries (e.g. France), in which case they are not recorded as a separate asset of a farm, 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 the recording of data relative to land. For example, in France, farmers in some cases establish holdings that rent land to their members, in which case the value of the land is not included in the total assets of these holdings. This accounting practice thus increases the relative share of other assets. Results by type of farming As illustrated by Figure 3.11, fixed assets accounted overall for 82 % of total assets in This share showed some variability among the different types of farming, ranging from 87 % in specialised dairy farms to 70 % in wine holdings. Figure 3.11: Composition of assets by type of farming in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Milk Grazing livestock Fieldcrops Fixed assets Mixed (crops and livestock) Current assets permanent crops Horticulture Granivores Wine Total Groups 33

36 Regarding 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 share varied from more than 80 % in other permanent crops farms to about 50 % in granivore farms. On the other hand, the latter had the largest share of buildings (35 %) and the former the lowest (10 %). Horticulture holdings recorded the largest share of machinery in fixed assets (about 17 %), virtually twice as much as on other permanent crops farms, which was at the other end of the spectrum. Finally, breeding livestock accounted for the highest share of total assets in grazing livestock and dairy farms (somewhat below 10 %). Figure 3.12: Composition of fixed assets by type of farming in 2009 Land, perma. Crops & quotas Buildings Machinery Breeding livestock 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% permanent crops Fieldcrops Wine Grazing livestock Milk Mixed (crops and livestock) Horticulture Granivores Total Groups 3.2. Labour This section analyses the structure of the labour force employed by EU farms, focusing on the average labour employed per farm, the composition of the labour force and the wages paid. The results show that the share of non-family labour in the total workforce is gradually increasing in EU-15, reflecting structural changes and increasing farm sizes. While in EU-10 this share appears to be at comparable levels to EU-15, there is significantly higher variability across Member States due to the predominance of very large farms in many eastern European countries, which are often organised as legal entities. 34

37 SK CZ NL BG EE UK DE LV BE FR MT LT HU PL LU SI DK RO AT PT SE FI ES IT CY EL IE Results by Member State Labour force The labour input of holdings stood at 1.6 AWU in 2009, virtually unchanged from a year earlier. As shown by Figure 3.13, it varied considerably across countries, ranging from 15.5 AWU in Slovakia to 1.1 AWU in Ireland. Besides Slovakia, Czech farms also returned a significantly higher labour input compared to the remaining Member States (7.3 AWU), reflecting the predominance of very large non-family agricultural holdings. Figure 3.13: Labour input per farm (in AWU) by MS in Labour/farm EU 27 Average Results by type of farming 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). Figure 3.14: Labour input per farm (in AWU) by type of farming in EU-27 in Labour/farm Total Groups Horticulture Granivores Milk Wine Mixed (crops and livestock) Grazing livestock Fieldcrops permanent crops 35

38 SI IE AT EL PL LU PT RO MT FI BE SE LT ES IT CY FR LV DE UK NL DK EE BG HU CZ SK EU27 Results by Member State Traditionally a large part of the labour force employed in agriculture is family labour. Family labour as a share of total labour is decreasing over time, though it still represents the prevalent form of labour in most Member States with the exception of Slovakia, the Czech Republic, Hungary, Bulgaria and Estonia. As Figure 3.15 shows, the share of paid labour in the total labour force in these five countries was higher than 50 % sometimes significantly so. Figure 3.15: Share of working hours of paid and unpaid labour by MS in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Share of unpaid labour (family labour hours) Share of paid labour Results by type of farming As shown by Figure 3.16, the share of paid labour is highest in horticulture and wine holdings, reflecting the typical recourse to seasonal workers. The share of paid labour is typically lowest in grazing livestock and dairy farms. Figure 3.16: Share of working hours of paid and unpaid labour in EU-27by type of farming in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Grazing livestock Share of unpaid labour (family labour hours) Milk Mixed (crops and livestock) Fieldcrops permanent crops Share of paid labour Granivores Wine Horticulture Total Groups 36

39 Results by EU group Remuneration of farm workers As shown by Figure 3.17, the nominal hourly wage followed an upward trend in both EU-15 and EU-10. In EU-15, the average nominal hourly wage rose by 37 % between 1999 and 2009, from 6.89 to In EU-10, it stood at 3.38 in 2009, up from 2.17 in 2004 (an increase of some 56 %). Conversely, the average EU-2 hourly wage oscillated in nominal terms around 1.25 over the period The average nominal hourly wage declined in 2009 only in EU-10 (by around 6.3 %), while it registered moderate increases in both EU-15 and EU-2 (+1.6 % and +2.6 % respectively). Finally, the average EU-27 nominal hourly wage stood at 6.34 in 2009, compared to 5.97 in 2008 and 5.61 in 2007, i.e. an increase of about 13.1 % over this period. Note that changes in the nominal wage more than made up for price increases over the corresponding period, so that the real hourly wage rose by around 8 % between 2007 and 2009 (EU-27 HICP inflation stood at around 4.7 % over this period). Figure 3.17: Long-term developments in average nominal wages 10 EU27 EU15 EU10 EU2 Linear (EU15) Results by Member State As Figure 3.18 shows (see next page), the average hourly nominal wage differs widely within EU-27. In 2009, it was highest in Denmark ( 22.0) and lowest in Romania ( 1.23). Note that wages in all EU-12 MS as well as in Greece and Portugal were below the EU-27 average ( 6.34). Map 3.2 shows that the level of wages was highest in the north-west of Europe: Denmark, the Netherlands, Sweden and the French region Champagne-Ardenne all had an average hourly wage of above The contrasting extreme was below 2.5 in Romania, Bulgaria, the eastern regions of Poland, and Lithuania. 37

40 DK NL SE FI FR LU UK BE IE DE IT AT ES MT CZ SK SI EE PT CY EL HU LV LT PL BG RO Figure 3.18: Average nominal wages of paid labour in Wages/hour EU27 Avearge Map 3.2: Average nominal wage by FADN region in 2009 Source: DG AGRI EU-FADN 38

41 SK CZ UK EE SE DE DK LU FR LV FI HU LT BE IE ES AT NL BG PT PL IT RO SI EL CY MT 3.3. Land For most farm types, access to agricultural land is a precondition for economic growth. This subsection analyses the amount of agricultural land available per farm, trends in the ownership of land and the cost of renting land Farm size While it has already become clear throughout this chapter 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 amount of agricultural land per farm. Here again, the overall picture is confirmed: based on the 2009 data, an average farm in Slovakia was more than 160 times larger than its counterpart in Malta (575 ha vs 4 ha see Figure 3.19). The EU average farm size was 32 ha in 2009, little changed from a year earlier. Figure 3.19: Total farm UAA by Member State in 2009 (average per farm in ha) UAA EU27 UAA DG AGRI EU- FADN When measured by farm types, the average utilised agricultural land area was largest in grazing-livestock farms, followed by field-crop farms. At the other end of the spectrum, horticultural farms were the smallest. However, it is important to stress that they operate at a much higher intensity (i.e. the land is a less important determinant of their level of production). 39

42 Figure 3.20: Total UAA of farms by TF in 2009 (average per farm in ha) UAA EU27 UAA Grazing livestock Fieldcrops Milk Mixed (crops and livestock) Granivores Wine permanent crops Horticulture DG AGRI EU- FADN 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 share of rented land (average per farm in %) 54.0% EU27 EU15 EU10 Linear (EU15) 53.0% 52.0% 51.0% 50.0% 49.0% 48.0% 47.0% Source: DG AGRI EU- FADN. As shown by Figure 3.21, the share of rented land in EU-15 has been fluctuating around an upward trend, rising from about 50 % in 1999 to 53.5 % in This indicates that a large part of the land becoming available on the EU-15 market is rented rather than sold. However, the situation is the reverse in EU-10, as evidenced by a falling trend in the share of rented land since Note that these averages for different EU groups mask considerable national and regional disparities, as depicted by Map 3.3. Rented land as a proportion of total UAA is 40

43 very high in Slovakia (96 % 11 ), France, eastern and central regions of Germany, the Czech Republic, western Hungary and Bulgaria. Conversely, it is below 30 % in many southern European regions, Ireland, Wales, Denmark, north-eastern Poland, Sud-Vest-Oltenia (Romania) and the Hamburg region (Germany). Map 3.3: Share of rented land in the total UAA by FADN region in 2009 Source: DG AGRI EU- FADN 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 the EU regions. In 2009, the highest average land rent per ha was observed in the Netherlands and Canarias (approximately 735 and 710 respectively). Land rents were also very high in the Hamburg region (Germany), Denmark, Alto-Adige (Italy) and Ribatejo e Oeste (Portugal), where they were well above 500 per ha. Rents were particularly low, on the other hand, in the Baltic countries (below 30 per ha) and in many regions with unfavourable conditions for intensive agricultural production, such as dry and mountainous areas. In so far as rent 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, 11 This very high share of rented land in total UAA reflects the business structure of Slovak agricultural holdings (i.e. cooperatives renting land from their members). 41

44 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 in the FADN regions in 2009 Source: DG AGRI EU- FADN. Results by farm type The level of land rents 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 from different sectors. In areas where horticulture or wine production is of importance, suitable land is scarce and land rents are much higher than, for example, in areas with extensive grassland, as the profitability of horticulture and wine production is much higher. Similarly, in areas with intensive livestock production, land prices tend to be higher because additional land is often a precondition for expanding this production. This is mirrored in the average level of land rents per farm type shown in Figure 3.22 on the next page. 42

45 Figure 3.22: Average land rent by farm type in 2009 (average per farm in per ha) 1, Horticulture Wine Granivores permanent crops Source: DG AGRI EU- FADN Development by EU group Rent/ha Total Groups Milk Fieldcrops Mixed (crops and livestock) Grazing livestock As shown in Figure 3.23, the level of land rents in EU-15 increased very gradually over the period , from around 161 per ha to 175 per ha. However, this trend was more pronounced in EU-10 during the period , despite a small decrease in the last observed year: average land rent per hectare rose by more than 45 % during the period under review, from around 33 to 49. In EU-2, land rents followed a hump-shaped pattern, with the average per hectare falling to nearly 62 in 2009, yet remaining nearly 7 % above its 2007 level. All in all, average land rent has changed little since 2007 in the EU as a whole, standing at around 143 per hectare. 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 can be well above the average level observed in the FADN). Figure 3.23: Long-term developments in land rents (average per farm in per ha) 200 EU27 EU15 EU10 EU2 Linear (EU15) Source: DG AGRI EU- FADN. 43

46 FIGURE INDEX Figure 1.1: Farm net value added by Member State in Figure 1.2: FNVA per AWU and remuneration of family labour per FWU by Member State in Figure 1.3: Long-term developments in FNVA per AWU and remuneration of family labour per FWU... 7 Figure 1.4: FNVA per farm in EU-27 by type of farming in Figure 1.5: FNVA per AWU by type of farming in Figure 1.6: FNVA per farm by EU group and organisational form in Figure 1.7: FNVA per AWU and remuneration of family labour per FWU by EU group and organisational form Figure 1.8: Distribution of FNVA per AWU by EU groups in Figure 1.9: Distribution of FNVA per AWU by year Figure 1.10: Distribution of FNVA per AWU by type of farming in EU-15 in Figure 1.11: Distribution of FNVA per AWU of dairy farms in EU-15 by year Figure 1.12: Distribution of FNVA per AWU of field crop farms in EU-15 by year Figure 1.13: Distribution of FNVA per AWU of granivore farms in EU-15 by year Figure 1.14: Lorenz curve of the distribution of FNVA in EU-27 in Figure 1.15: Income components per farm by EU groups in Figure 1.16: Income components per farm by type of farming in Figure 1.17: Rate of Return on Assets by MS in 2008 and Figure 1.18: ROA in EU-27 by type of farming in Figure 1.19: Development of the ROA by EU groups Figure 2.1: Share of public support in total receipts by MS in Figure 2.2: Share of direct payments in total receipts by type of farming in Figure 2.3: Share of direct payments in FNVA by MS in Figure 2.4: Share of direct payments in FNVA by farm type in EU-27, Figure 3.1: Long-term developments in the value of total assets (TA) and liabilities (TL).. 26 Figure 3.2: Average total asset value per farm by MS in

47 Figure 3.3: Average total asset value by type of farming in EU-27 in Figure 3.4: Composition of liabilities per farm by MS in Figure 3.5: Composition of liabilities per farm in EU-27 by type of farming in Figure 3.6: Farm net worth per farm by EU group and MS in 2005 and Figure 3.7: Farm net worth per farm in EU-27 by type of farming in Figure 3.8: Farm solvency in EU-27 by type of farming in Figure 3.9: Composition of assets by MS in Figure 3.10: Composition of fixed assets by MS in Figure 3.11: Composition of assets by type of farming in Figure 3.12: Composition of fixed assets by type of farming in Figure 3.13: Labour input per farm (in AWU) by MS in Figure 3.14: Labour input per farm (in AWU) by type of farming in EU-27 in Figure 3.15: Share of working hours of paid and unpaid labour by MS in Figure 3.16: Share of working hours of paid and unpaid labour in EU-27 by type of farming in Figure 3.17: Long-term developments in average nominal wages Figure 3.18: Average nominal wages of paid labour in Figure 3.19: Total farm UAA by Member State in Figure 3.20: Total UAA of farms by TF in Figure 3.21: Long-term developments in the share of rented land Figure 3.22: Average land rent by farm type in Figure 3.23: Long-term developments in land rents TABLE INDEX Table 1.1: Development of the Gini coefficient of FNVA per AWU by EU groups

48 MAP INDEX Map 1.1: FNVA per AWU by FADN region in Map 1.2: Remuneration of family labour per FWU by FADN region in Map 2.1: Share of direct payments in FNVA by FADN region in Map 3.1: Average liabilities-to-assets ratio per farm by FADN region in Map 3.2: Average nominal wage by FADN region in Map 3.3: Share of rented land in the total UAA by FADN region in Map 3.4: Average land rent in the FADN regions in ANNEX INDEX Annex 1: Methodology Annex 2: Income calculation Annex 3: Threshold by Member State in 2009 (ESU: European size units) Annex 4: FNVA and remuneration of family labour per AWU by Member State and organisational form in Annex 5: Number of holdings by type of farming in Annex 6: Breakdown of revenue and costs of EU farms in Annex 7: Balance sheet components in FADN Annex 8: Indicators by Member State in

49 Annex 1: Methodology 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 activity, e.g. farm tourism, forestry, renewable energy, etc. It does not include non-farm income of the household. 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 aids. 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 the income estimators. 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 includes for example costs for 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 factors costs Family labour cost: this cost is estimated on the basis of wages which the owner of the farm would have to pay if he were to hire employees to do the work carried out by the family members. It is estimated as the average regional wage per hour based on the FADN data 12 multiplied by the number of hours worked by family workers on the farm. It is commonly acknowledged that the number of hours of family workers is typically overestimated. Thus, a ceiling of hours per Annual Work Unit is applied (this is the 12 If there are not enough farms (fewer than 20) with paid labour at regional level, the national average is taken into account. 47

50 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). 13 The use of hours makes it possible to give a manager more remuneration than an employee if he is working more hours. Reliable family labour costs 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). 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 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. 14 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 (LT) interest rate obtained from Eurostat. It should be noted that if the weighted interest rate is lower than the LT interest rate (which means that the calculated rate of interest paid is lower than the LT interest rate), the LT interest rate is used instead of the weighted interest rate A constraining factor of the estimation method is that if a farmer were to receive a salary he would probably work less. 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). 48

51 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. 15 The correction is made by subtracting the inflation rate 16 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 however included. 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 has to 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 - interests paid) 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. The inflation rate is based on the Eurostat annual average rate of change in the Harmonised Indices of Consumer Prices (HICPs), available from 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 EU-10. 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 MS. 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. 49

52 Annex 2: Income calculation 50

53 Annex 3: Threshold by Member State in 2009 (ESU: European size units) Member State Threshold (ESU) Belgium 16 Bulgaria 1 Cyprus 2 Czech Republic 4 Denmark 8 Germany 16 Greece 2 Spain 4 Estonia 2 France 8 Hungary 2 Ireland 2 Italy 4 Lithuania 2 Luxembourg 8 Latvia 2 Malta 8 Netherlands 16 Austria 8 Poland 2 Portugal 2 Finland 8 Sweden 8 Slovakia 8 Slovenia 2 Romania 1 United Kingdom 16 ( * ) (*) 8 ESU for Northern Ireland. 51

54 Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Annex 4: FNVA and remuneration of family labour per AWU by Member State and organisational form in FNVA/AWU Remuneration of family labour/fwu BE BG CY CZ DK DE EL ES EE FR HU IE IT LT LU LV MT NL AT PL PT RO FI SE SK SI UK 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 2009 sample). 52