EU FARM ECONOMICS OVERVIEW

Transcription

1 EU FARM ECONOMICS OVERVIEW FADN

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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, September 2010 EU FARM ECONOMICS OVERVIEW FADN 2007 EXECUTIVE SUMMARY This note provides an overview of the development of key economic indicators in the European agricultural sector. The analysis is based on data from the Farm Accountancy Data Network (FADN). The latest data available are from Income situation Until 2007, agricultural incomes in the EU have shown a general improvement. In EU15 the average nominal income has increased between 1998 and 2007 by 5.8 %, annually, while since accession it has increased in EU10 annually by 16.2 %. As a result in 2007 the average farm income measured as farm net value added (FNVA) per annual work unit (AWU), was in the EU27. It has to be kept in mind, however, that from this amount all production factors (labour, land and capital) have to be remunerated. At the same time, the estimate of the economic profit/awu (an indicator measuring the profitability of farms which takes into account the costs for all production factors, including family labour) was However, this average figure hides the fact that only a minority of farms operated profitably. During the period only 35% of the farms in the EU25 were able to cover all of their economic costs. For small farms the percentage was even lower. Even among the large farms, only slightly over 60% were able to cover all costs. In practice, this means either that family labour is not appropriately remunerated or that family assets do not provide adequate returns. It also has to be stressed that the income situation is highly heterogeneous. There are huge differences between the three categories set out below: Regions and Member States (MS): Denmark, the Netherlands and Belgium were the MS with the largest FNVA/AWU, while Slovenia, Bulgaria and Romania showed the lowest values for this indicator. The economic profit per AWU was highest for farms in Belgium, Luxembourg and Germany and lowest in Denmark. The striking difference between FNVA and economic profit in Denmark is due to the very high costs of financing and labour. Farm types: In 2007, wine farms had the largest FNVA/AWU ( ), while dairy farms made the highest economic profit/awu ( 3 900). Mixed holdings, on the other hand, recorded the lowest FNVA/AWU ( ) and grazing livestock farms the lowest economic profit/awu ( ). Individual farms: Due to the specific situation of each farm, there remain large variations in farm incomes, even when structural parameters are taken into account. 2

4 In addition to the FNVA and the economic profit, the potential of farms to remunerate family labour and capital was also estimated. The first estimate was made by calculating the residual income available for family workers after deducting all other costs and the second by calculating the "return on assets" (ROA) indicator. In 2007 the average amount remaining for the remuneration of each family worker in the EU27 was The highest amounts (> ) were available in Belgium, the UK, Luxembourg, France and the Netherlands, while in many eastern European farms (in Cyprus, Poland, Bulgaria, Slovenia and Romania) the amount available per family worker is below However, the lowest value was observed in Denmark, where the estimated amount was negative, which meant that, on average, the work of family members was not remunerated at all. This was mainly due to high wages and capital costs. The average ROA in farms in the EU27 was 2.8% in Holdings in eastern European countries such as Lithuania (13.8%), Latvia (9.2%), Estonia (9.5%) and Bulgaria (8.4%) posted the largest ROA in The indicator was negative in Portugal (-0.3%), Sweden (-0.8%), Cyprus, (-1%), Slovenia (-2.5%) and Romania (-5.3%). The high values in some eastern European countries are due not only to high income levels but also to low opportunity costs for labour and relatively low asset values. Furthermore, it has to be borne in mind that eastern European farms frequently need a high ROA in order to pay the often high interest rates. Role of direct payments Farms depend heavily on direct payments. In the EU27 the average share of direct payments in FNVA (from which all production factors have to be remunerated) was 28 % in Although this average figure has not changed significantly in recent years, it nevertheless differs widely from one MS to another. Direct payments as a share of income also differ considerably between farm types, being highest in mixed and other grazing livestock farms, at 41 % and 50 % respectively. By contrast, in the horticulture and wine sectors, the share is below 10 %. Without Pillar I and Pillar II payments the share of profitable farms would drop from 35% to less than 20%. Field crops, grazing livestock and mixed farms would be affected in particular. In these sectors even the overwhelming majority of large farms would not be profitable, as only 20-25% of these farms would be able to cover all of their costs. Large farms in the pig and poultry, horticulture and permanent crop sectors are more profitable and less reliant on direct payments. Financial structure of farms European farms differ greatly in asset value. The size of farms in terms of asset value is highest in Denmark ( ), the Netherlands ( ), the United Kingdom ( ) and Slovakia ( ). By contrast, the asset value was the lowest in farms in Bulgaria and Romania, with and respectively. Thus the average asset value of a farm in the Netherlands is 65 times the asset value of a farm in Romania. As regards farm types, dairy farming was the type with the largest total assets ( ) in 2007, followed by pig and poultry farms ( ). permanent crops (i.e. holdings producing citrus and other fruit, olives and other permanent crops) posted the lowest total assets, with

5 The highest liabilities-to-assets ratio was found in farms in Denmark and the Netherlands, with 56% and 36% respectively. At regional level, farms in Brittany, Picardie, Haute-Normandie and Mecklenburg-Vorpommern have had a liabilities-to-assets ratio of more than 45% on average. Farming activities such as horticulture, pigs & poultry and dairy farming are important in most of these areas, as they tend to have relatively large asset values and high liabilities-to-assets ratios. The lowest shares are found in Greece, Spain, Italy and Romania. This might indicate that farms have problems in accessing the credit market. However, it might also be due to accounting practices (in some MS liabilities might be recorded not in the farm accounts but in the private accounts of the holder). Labour input Owing to differences in structure, the average number of workers employed per farm differs widely. It ranges on average from 1.16 AWU in Ireland to AWU in Slovakia. On average, the EU27 farms reported 1.71 AWU. The labour input per farm is highest in horticulture and lowest in other permanent crops. Family labour still accounts for 77% of the total labour force in the EU27. In only three MS - Slovakia, the Czech Republic and Hungary - did paid labour accounted for more than 50% of the total. Due to the employment of seasonal workers, the share of paid labour is the highest in the sectors horticulture and wine. Granivore farms also employ a relatively large proportion of paid workers. The share of paid labour is lowest in milk and grazing livestock farms. Costs for external production factors Due to structural change, external production factors take on greater importance in the agricultural sector. Costs differ significantly between the MS: The highest wages were found in Denmark ( 20.9/hour) and Sweden ( 17.0) and the lowest in Bulgaria ( 1.0/hour), closely followed by Romania ( 1.4) and Poland ( 2.1). All EU12 MS plus Greece were below the EU27 average. Land rents are particularly high in the Netherlands, Denmark, northern Germany and Greece, whereas they are very low in eastern Europe and in many regions where natural conditions are unfavourable for intensive agricultural production, such as dry and mountainous areas. The real interest rate (calculated by subtracting the inflation rate from the nominal interest for long term bonds) ranged in 2007 from -3.3% in Bulgaria to 4.9% in Latvia. The negative figure in Bulgaria is due to the fact that the rate of inflation in Bulgaria was higher than the interest rate. 4

6 The Farm Accountancy Data Network (FADN) is a European system of sample surveys that take place 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 those farms exceeding a minimum economic size (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) covered in the Farm Structure Survey (FSS, EUROSTAT). For 2007, the sample consists of approximately holdings in the EU27, which represent 5.4 million farms (39%) out of a total of some 14 million farms included in the FSS. The applicable rules are aimed at providing representative data along three dimensions: region, economic size and type of farming. FADN is the only harmonised source of microeconomic data, which means that the accounting principles are the same in all EU MS. The most recent FADN data available for this report are for the 2007 accounting year 2 ; this is because of the time needed to collect the data from all the EU MS. 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. By multiplying the areas or the number of animals by the corresponding SGM and then adding the products 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 for the determination of the economic size and the type of farming in FADN and in the Farm Structure Survey (FSS) organised by EUROSTAT. 2 Some information is still provisional for Spain and Greece Moreover it should be noted that Malta 2004 is missing and that Dutch 2000 data are estimates based on 1999 data. 5

7 CONTENTS 1. DEVELOPMENT OF FARM INCOME FNVA and the economic profit in Distribution of income Income components OTHER PERFORMANCE INDICATORS Available remuneration for family labour Return on assets ROLE OF DIRECT PAYMENTS Share of direct payments in total revenue Share of direct payments in FNVA Importance of direct payments for farm profitability FINANCIAL STRUCTURE Total asset value Total liabilities Development of farm net worth Solvency Current and fixed assets COMPOSITION OF LABOUR INPUT COSTS FOR EXTERNAL PRODUCTION FACTORS Remuneration of farm workers Level of land rents Costs of capital

8 1. DEVELOPMENT OF FARM INCOME For the purposes of this report, the income of the holding is measured by estimating the farm net value added (FNVA) and the economic profit. FNVA: FNVA is used to remunerate the fixed factors of production (work, land and capital), whether they be external or family factors. As a result, holdings can be compared regardless of the family/non-family nature of the factors of production employed. FNVA = output + Pillar I and Pillar II-type payments + VAT balance - intermediate consumption - farm taxes (income taxes are not included) depreciation. The value is given per 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. Economic profit: the economic profit corresponds to the amount remaining after remuneration of all production factors. Thus, as in the case of the FNVA, holdings can be compared irrespective of the family/non-family nature of the factors of production employed. However, a part of the costs is not taken from the FADN farm accounts but is estimated. The size of the estimates depends to a large extent on the methodological assumptions made when they are calculated. Economic profit = FNVA + subsidies on investment-taxes on investment-wages-rent-costs of own labour- costs of own capital- costs of own land. The value is given per AWU. A negative value for economic profit does not necessarily mean that a farm is forced to cease production. If the farmer accepts that his/her own production factors are not fully remunerated the farm can continue to produce even if the economic profit is negative over a long period. Of course, this is only possible if other costs such as intermediate consumption, depreciation and external factors can be paid and the farmer has sufficient income to live on FNVA and the economic profit in 2007 Results by Member State The average FNVA per farm for the EU27 was in Slovakia had the largest FNVA ( ) and Romania had the lowest ( 4 800) (see Graph 1.1). The average economic profit per farm was 2500, with the Czech Republic at the head of the EU ( ) and Denmark bringing up the rear ( ). Some MS show a large gap between FNVA and economic profit that can be explained in different ways. In Slovakia, the Czech Republic, the United Kingdom and Germany the remuneration of paid and family labour is the main factor explaining this gap. In the Netherlands and Denmark the heavy cost of external capital also lowers the estimate of economic profit. 7

9 Graph 1.1: Farm net value added (FNVA) and economic profit per farm by MS in FNVA Profit EU27 FNVA EU27 Profit SK NL CZ UK DK DE BE LU FR SE AT FI EE IT MT ES IE HU LT LV EL PL PT CY BG SI RO The picture changes slightly when FNVA and economic profit are expressed per AWU (Graph 1.2). As far as the EU27 is concerned, the large differences between MS are inherent in the structure of their agriculture. The average FNVA/AWU for EU27 was in 2007, while economic profit/awu was The MS with the highest average FNVA per AWU were Denmark, the Netherlands and Belgium. Specialist horticulture, granivore and arable crop production are the main types of farming that pull up the results of these countries. However, the MS with the highest FNVA/AWU (Denmark) showed a wide gap between the two income indicators. This is due to the large amount of interest paid by Danish farmers and the high wages. In the EU15, Ireland, Portugal and Greece - three MS which are characterised by a large number of small farms - had FNVA/AWU below the EU average, while in the EU10 the average income was below the EU27 average in all MS except Estonia. Within the EU10, Romania, Bulgaria and Slovenia posted the lowest FNVA/AWU. Denmark and Sweden had the lowest economic profit/awu ( and respectively). Graph 1.2: FNVA/AWU and economic profit/awu by MS in FNVA/AWU Profit/AWU EU27 FNVA/AWU EU27 Profit/AWU DK NL BE UK LU SE DE FR FI AT IT IE ES MT CZ EE HU EL LT SK LV CY PT PL SI BG RO Results by EU groups 8

10 Economic profit/awu and FNVA/AWU both showed an upward trend from 1998 to 2007 (see Graph 1.3) for the EU15 and from 2004 to 2007 for the EU10. FNVA per AWU in EU15 rose fairly steadily from in 1998 to over in 2007, which is an annual increase of 5.8 % on average. Taking 2007 out of the picture, since it was a special year due to the exceptional market situation, the average increase in income would still be 4.9 %. In EU10 and EU2, average FNVA was significantly lower. After 2004, FNVA per AWU rose more rapidly in EU10 (16% per year) than in EU15 (7% per year). This indicates that incomes in EU15 and EU10 were converging, although the level of income is still much lower in EU10. At the beginning of the reference period the estimate of the economic profit was negative. However, it rose steadily from in 1998 to in In EU15 the improvement was due, among other things, to low opportunity costs for capital and only moderate increases in land rents and wages. In EU10 the economic profit ranged from -300 in 2005 to in Although average economic profit was negative for a long period, the reality shows that the majority of farmers stayed in farming. This is because the economic profit takes into account imputed costs of own factors. Farmers who cover all costs except the cost for own factors might opt to continue farming if they accept that their own production factors are not fully remunerated. Graph 1.3: Trend in FNVA/AWU and economic profit/awu from 1998 to /AWU EU27 FNVA/AWU EU27 Profit/AWU EU15 FNVA/AWU EU15 Profit/AWU EU10 FNVA/AWU EU10 Profit/AWU Regional differences The more disaggregated the level of analysis, the more volatile income estimates become. This is why 3-year averages at regional level are used for the presentation of income results. Map 1.1 shows the regional differences in FNVA/AWU. The holdings with the highest agricultural income per worker (> per year) are mainly located in Benelux, northern Germany, northern Italy and the UK, while most regions with low incomes (< per year) are located in eastern Europe. However, the average income in Greece and Portugal was also low. 9

11 Map 1.1: FNVA/AWU by FADN region, Average As regards economic profit, the differences in income between the EU15 and the EU12 are less pronounced (Map 1.2). Regions in Spain, northern Germany, northern France and some regions in Italy and Hungary display the highest values for economic profit, while the economic profit is negative in the Scandinavian countries, southern France, the UK, Slovakia and in parts of Italy, Poland, Portugal and Romania. The regional pattern for the economic profit indicator does not always correspond to that of the FNVA indicator. For instance, the Baltic countries, the Czech Republic and northern Hungary, which have low FNVA/AWU, show a relatively high value for economic profit, while in Denmark, the Netherlands and to some extent Sweden and Finland, the economic profit/awu estimate is negative. This is mostly due to the labour costs, which are very high in the Scandinavian countries and the Netherlands, but are low in the EU12 3. Additionally, in many MS of the EU12, the real interest rate was low as a result of high inflation. This led to lower and sometimes negative values for the estimate of own capital costs. 3 As most of the farms have a "family character", labour costs are mainly due to the family labour that is estimated using the wage level of the agricultural employed workers (which is particularly high in Scandinavian countries). 10

12 Map 1.2: Economic profit/awu by FADN region, Average Results by type of farming FNVA per farm was highest in the horticulture, wine and milk sectors, at , and , respectively (see Graph 1.4). Mixed farms, on the other hand, had the lowest FNVA per farm on average ( ). One explanation for the relatively low income of mixed farms is that many small mixed farms are located in the EU10, where income levels are generally lower, while horticulture, wine and milk farms are more frequent in the EU15. Horticulture, milk and wine were also the most profitable farm types in 2007, whereas mixed and grazing livestock farms were not able to cover all of their costs. The big difference between FNVA and the economic profit in the horticulture sector is mainly due to the high labour input. 11

13 Graph 1.4: FNVA and economic profit per farm in the EU27 by type of farming in 2007 FNVA Profit Total Groups FNVA Total Groups Profit Horticulture Wine Milk Granivores Fieldcrops Grazing livestock permanent crops Mixed (crops and livestock) In 2007 the level of FNVA per AWU was highest in wine farms ( ), and lowest in mixed farms ( ). Incomes of dairy and field crop farms were stronger than in most other years due to high prices for milk and cereals in that year. The FNVA of granivore farms, on the other hand, was relatively low and they suffered a drop in income due to high input prices. The economic profit was highest for milk farms, followed by farms producing granivores. Grazing livestock and mixed farms were not profitable on average (Graph 1.5). Graph 1.5: FNVA/AWU and economic profit/awu by type of farming in FNVA/AWU Profit/AWU EU27 Profit/AWU EU27 Profit/AWU Wine Milk Granivores Horticulture Fieldcrops Grazing livestock permanent crops Mixed (crops and livestock) Total Groups From the organisational point of view, holdings in the FADN are divided into three groups: (1) family farms, where the economic results cover the unpaid labour and own capital of the holder and the holder s family; (2) partnerships, where the economic results 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). 12

14 Results by EU groups The results show that non-family farms have a higher FNVA on average than family farms. In the EU10, as well as in the EU15 and the EU2, holdings classified as other showed the largest FNVA. Due to their superior size, the income of the "other" farms was highest in the EU10 at around , compared with in the EU15. However, family farms and partnerships had a much better income in the EU15. In contrast to EU10 and EU2, the FNVA of partnerships in the EU15 was at almost the same level as the income of the "other" farms. With respect to profitability only non-family farms are able to cover all economic costs. Graph 1.6: FNVA and economic profit per farm by EU group and organisational form in FNVA Economic profit Partnerships Total Partnerships Total EU15 EU10 EU2 Total Even when the same indicators are expressed per AWU, non-family farms still record higher values than family farms (see Graph 1.7). However, the FNVA per worker is highest in nonfamily farms in the EU15. in the EU15 have a higher FNVA per worker than all organisational types in the EU10 and the EU2. This can be explained by the larger labour force employed by the holdings in the EU10 and the EU2. Graph 1.7: FNVA and economic profit/awu by EU group and organisational form /AWU FNVA/AWU Economic profit/awu Partnerships Total Partnerships Total EU15 EU10 EU2 Total Partnerships Partnerships Total Total Partnerships Partnerships Total Total 13

15 1.2. Distribution of income Agricultural incomes vary considerably between farms. The pattern is that a large proportion of farms have relatively low income levels per worker, while a small proportion of farms have a very high income per worker. For instance, in 2007 the average income per worker in the EU15 was around ; however, about 10% of the farms had an income per worker of more than , while more than half of the farms had an income per worker of less than In the EU10 and the EU2 the average income is much lower than in EU15, but the income is also not evenly distributed. Average income per worker in the EU10 was around 7 900, but more than half of the farms had an income per worker of less than In the EU2, half of the farms had a annual income of even less than per worker. The distribution of the agricultural income is illustrated in Graph 1.8 with the help of "boxplots" 4. Graph 1.8: Distribution of FNVA/AWU by EU groups Graph 1.9 provides information on the change in income distribution over time for the entire EU. Between 1997 and 1999 the distribution was fairly stable, while average income and the variance of income increased slightly between 2000 and The most significant change occurred after the enlargement in 2004, when the EU10 joined. This led to a lower general level of income and a reduction of the variance. The same effect was observed in 2007 with the accession of Romania and Bulgaria. However, this effect is less visible owing to the favourable income situation during this year. 4 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 in the yellow boxes. 14

16 Graph 1.9: Distribution of FNVA/AWU by year Graph 1.10 provides information on the distribution of income by type of farming in In each sector there is a small proportion of farms with very high income and a larger proportion of farms with low income (the high-income farms raise the mean income significantly, but have little impact on the median). The most pronounced differences between mean and median are observed for granivore and wine producing farms. We may also note that the distribution of income is very wide for the milk, field crop and granivore sectors (the interquartile range is higher). Graph 1.10: Distribution of FNVA/AWU by type of farming in the EU15 Legend: 1 = Field crops 2 = Horticulture 3 = Wine 4= permanent crops 5= Milk 6= grazing livestock 7= Granivores 8= Mixed The trend in the distribution of income over time varies from sector to sector. For specialised dairy farms, the distribution of income widened slightly over time (Graph 1.11). Median and mean levels showed an almost constant increase. In 2007, income increased as a result of exceptionally high milk prices. 15

17 Graph 1.11: Distribution of FNVA/AWU of dairy farms in the EU15 by year For specialised field crop farms, the distribution did not show any marked change over time, except in 2007 (Graph 1.12). However, median and mean levels do show a slow but relatively constant increase, and the spread appeared to have become wider after The biggest change can be seen in the year 2007, when income rose due to the high price levels. Graph 1.12: Distribution of FNVA/AWU of field crop farms in the EU15 by year In the case of farms specialised in granivore production, there were significant changes in both median and mean levels over time (Graph 1.13). This was mainly due to highly volatile output prices. Income was particularly low in the years 1998 and In 2007, income fell due to extremely high feed prices which could not be offset by higher output. Generally, the distribution seems to be wider in years with high income, which suggests that some of the farms can benefit more from the favourable situation than others. This could be due to economies of scale. 16

18 Graph 1.13: Distribution of FNVA/AWU of granivore farms in the EU15 by year In Graph 1.14 the distribution of income (FNVA) among the labour force (AWU) in the EU27 in 2007 is displayed in the form of a Lorenz curve 5. As the income of some farms was negative, the cumulated share of income is initially negative. The graph shows that income is not equally distributed among AWU. If this were the case, cumulated income would increase in a linear fashion from the bottom left corner to the top right corner. FNVA/AWU in the EU27 was negative for about 5 % of total AWU engaged in agriculture. Thereafter the cumulative income started to increase, indicating that the FNVA of these AWU was greater than zero. 80% of the AWU generate about 40% of income of the total farm sector. Thus, 60% of income was realised by the remaining 20%. Graph 1.14: Lorenz curve of the distribution of FNVA in the EU27 in Cumulative share of total FNVA [%] Share of AWU [%] 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. 17

19 The GINI index measures the importance of the unequal distribution of income 6. The coefficient can range from 0 to 1. In this context, 1 means that income is completely concentrated and 0 that income is evenly distributed among AWU. The figures show that the income concentration in the EU15 is lower than in the EU10 or the EU12 (table 1.1). However, in the EU15 it remained almost constant, whereas in the EU10 it decreased. The highest concentration (unequal distribution) was observed for the EU2. Comparisons between groups should be made with care, as the field of observation is different. In the EU10 and the EU2 the sample also includes very small farms, which in most cases are excluded in the EU15. However, the differences in the sample reflect the structure of the farm sector and are therefore justified. Nonetheless, it is the development of the coefficient over time that is the most meaningful indicator. Table 1.1: Development of the Gini coefficient of FNVA/AWU by EU-groups EU EU EU The Gini coefficient is usually defined, 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. 18

20 1.3. Income components Results by EU groups In 2007, the average output per farm in the EU27 was (see Graph 1.15) compared with in the EU15, in the EU10 and in the EU2. Average subsidies 7 (current subsidies minus taxes) stood at in the EU27, representing 14% of the total revenue. The average farm in the EU15 received in public funding (14%), while the average in the EU10 and the EU2 was (14%) and (12%) respectively. On the cost side, the sum of intermediate consumption and depreciation (IC + D ) of the average farm in the EU27 was In the EU15, IC + D expenses totalled on average , while those costs were and in the EU10 and the EU2, respectively. The average amount of costs for external factors (wages, rent and interest paid) was 9 000, , and in the EU27, the EU15, the EU10 and the EU2, respectively. The opportunity costs for own factors were estimated at , , and in the EU27, the EU15, the EU10 and the EU2, respectively. Graph 1.15: Income components per farm by EU-groups in Rec Exp Rec Exp Rec Exp Rec Exp EU27 EU15 EU10 EU2 Total output Public support Total intermed. Consumption Depreciation Total external factors Own factors Note. Rec. stands for receipts and Exp. stands for expenses. Results by type of farming In 2007 granivore farms generated the largest output of all farm types in the EU27 ( ), while other permanent crops had the lowest output (with see Graph 1.16 The highest average direct payments per holding were received by grazing livestock farms ( ), followed by holdings specialising in milk and field crops ( and , respectively). Milk, grazing livestock and field crops receive the largest amount of direct payments per farm because historically the CAP has provided support in particular to the production of cattle and field crops. These farm types continue to receive the highest support because the receipt of DP is related to the amount of land kept in good agricultural 7 Public support includes EU coupled and decoupled payments, less favoured area (LFA) payments, rural development payments and national aid. 19

21 and environmental condition, and in many MS the amount of direct payments receivable per ha is linked to the historical level of support received by the farmer. Horticulture farms received the lowest funding per farm ( 1 400). Because of their size, granivore farms have also the highest costs for intermediate consumption and depreciation ( ), while other permanent crop farms have the lowest ( ). Due to high labour input the share of external factors (wages, rent and interest paid) in total costs was the highest in horticulture and wine farms (23% of total costs), followed by farms growing other permanent crops (17%). Granivore farms were the type of farms on which total external factors made the smallest impact(10%). In absolute terms, horticulture holdings spent the most money on total external factors ( ), while growers of other permanent crops spent the least ( 5 100). The estimated costs for own production factors (family labour, own land and own capital), as a share of total costs, were the highest in other permanent crop farms (48%), followed by grazing livestock and wine farms (37% and 36%, respectively) and the lowest in granivore and horticulture farms (13% and 18%). Graph 1.16: Income components per farm by type of farming in 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 Own factors Total external factors Source: DG AGRI EU- FADN Note. Rec. stands for receipts and Exp. stands for expenses. 20

22 2. OTHER PERFORMANCE INDICATORS This section presents the results of two other performance indicators: first, an estimate of the income available for the remuneration of family labour and, second, the results concerning the indicator "Return on Assets (ROA)" Available remuneration for 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. This section presents estimates of the amounts available to remunerate family labour. These are estimate is made by deducting from the FNVA the costs for external production factors and the estimates of the opportunity costs for own land and own capital. Only farms with unpaid labour (which in most cases means family members) were included. Results are provided by family labour unit (FWU). 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 Results by Member State In 2007 the average amount remaining for the remuneration of each family worker in the EU27 was The highest amounts for the remuneration of family workers (> ) were available in Belgium, the UK, Luxembourg, France and the Netherlands. On many eastern European farms the amount available per family worker is on average less than (Cyrus Poland, Bulgaria, Slovenia and Romania). However, the lowest value observed was for Denmark, where the estimate was negative - meaning that on average there was nothing left to remunerate family workers. This was due to high wages to remunerate paid workers and capital costs. Graph 2.1: Available remuneration per FWU by MS in 2006 and 2007 /FWU Average EU27 in BE UK LU FR NL DE IT SE SK ES FI AT CZ HU EE MT IE LT EL LV PT CY PL BG SI RO DK Source: DG AGRI EU- FADN Results by type of farming 21

23 With respect to farm types, the income left to remunerate family labour is highest in wine and horticulture farms and it is lowest in grazing livestock and mixed farms (Graph 2.2). Therefore, the sequence is similar to the picture of average FNVA/AWU. Graph 2.2: Available remuneration FWU in the EU27 by type of farming in 2007 /FWU EU27 average Wine Horticulture Milk Granivores Fieldcrops permanent crops Grazing livestock Mixed (crops and livestock) Source: DG AGRI EU- FADN Trend by EU-group The income left to remunerate family labour has tended to increase over time (Graph 2.3). This is most visible for the EU15, where the average amount increased from about in 1998 to about in Apart from the improvement in productivity which took place mainly in the context of structural change, another reason for this development was the falling cost of capital (see also Annex 8). However, particularly in the EU2 and the EU10, but also in the EU15, the amounts are still comparatively small. Graph 2.3: Development of the available remuneration per FWU by EU-group /FWU EU27 EU15 EU10 EU2 Linear (EU15) Source: DG AGRI EU- FADN 22

24 2.2. Return on assets The return on assets (ROA) shows the effectiveness of a company s assets in generating revenue. It gives an idea of the returns received by the farm from the total capital invested. It is defined as the ratio of the FNVA, less the cost for wages, paid rent and the opportunity costs for own labour, divided by the total asset value. ROA= FNVA + Balance of subsidies and taxes - Wages paid - Paid rent - Estimate of the costs for family labour Total asset value Results by Member State In 2007 the average ROA for the EU27 was 2.8%. Holdings from eastern European countries such as Lithuania (13.8%), Latvia (9.2%), Estonia (9.5%) and Bulgaria (8.4%) showed the largest ROA in 2007 (Graph 2.4). The indicator was negative in Portugal (-0.3%), Sweden (- 0.8%), Cyprus (-1%), Slovenia (-2.5%) and Romania (-5.3%). The high values in some eastern European countries are due not only to high income levels but also to low opportunity costs for labour and relatively low asset values. Furthermore, it has to be kept in mind that eastern European farms typically need a high ROA to pay the often high interest rates (see also Table 6.1). Graph 2.4: Rate of Return On Assets by MS in 2006 and % Average EU27 in % 5% 0% LT EE HU FR PL DE AT IT UK SK FI PT CY RO -5% -10% Results by type of farming The level of the ROA differs according to the different farm types. It is highest in horticulture farms, with 5%, followed by granivore, field crop and wine farms (all around 4%). In mixed, other permanent crops and in particular grazing livestock farms, the ROA is much lower. 23

25 Graph 2.5: ROA in the EU27 by type of farming in % ROA 2007 Average EU27 in % 4% 3% 2% 1% 0% Horticulture Granivores Fieldcrops Wine Milk Mixed (crops and livestock) permanent crops Grazing livestock Trend by EU-group The RAO has tended to increase over time (Graph 2.6). This is most visible for the EU15, where a long time interval is available. In EU15 the indicator increased from 0.5% in 1998 to 2.8% in In the EU10 the ROA increased from 2005 on. By contrast the ROA in the EU2 was negative (2007). For all EU-groups the figures of the indicator are relatively low in comparison to other sectors of the economy. Graph 2.6: Development of the ROA by EU groups 5% EU27 EU15 EU10 EU2 Linear (EU15) 4% 3% 2% 1% 0% -1% % -3% -4% Year 24

26 3. ROLE OF DIRECT PAYMENTS This chapter analyses the importance of direct payments for the income situation of European farmers by providing information on the share of direct payments in farm revenue and FNVA, and by analysing the impact of direct payments on farm profitability on the basis of multiannual averages Share of direct payments in total revenue Results by Member State The share of direct payments (both national and EU) in total receipts provides some initial information about the importance of public support for farming. In 2007 the share of DP in total revenue was 13% on average in the EU27, down from 16% in However, the share differs from one Member State to another. It is highest in Finland (30%), Ireland (30%) and Greece (27%). In Finland this is mainly due to substantial national payments which are granted in addition to EU direct payments. In Greece, the amount is particularly high due to the importance of crops such as tobacco, grain maize and cotton which, before decoupling, used to be strongly supported. Direct payments as a share of revenue are the lowest in the Netherlands, where sectors such as horticulture and pig and poultry production are of major importance. Graph 3.1: Share of public support in total receipts by MS in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% FI IE EL LV FR PT LT SK RO CZ UK SI HU SE MT EE LU DE AT ES BG DK PL BE CY IT NL %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 differs from one farm type to another. The highest level of public support was found in grazing livestock, with 25%, and the lowest in horticulture with 1% (see Graph 3.2). 25

27 Graph 3.2: 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 3.2. Share of direct payments in FNVA The importance of direct payments for farmers becomes clearer when one examines their share of FNVA, because the deduction of costs means that the share of DP in income is larger than its share of the revenue. Results by Member State As far as revenue is concerned, the share of DP in FNVA differs between MS. However, due to the different farm structures in the MS, the order of MS differs slightly from the order of the share of DP in total revenue. The share of DP in FNVA is highest in Finland, Slovakia and Ireland with 65%, 59% and 53% respectively, and lowest in Italy and the Netherlands, with 14% and 13% respectively. Graph 3.3: Share of direct payments in FNVA by MS in % 60% 50% 40% 30% 20% 10% 0% FI SK IE SI CZ HU SE LV FR UK RO EL LU DK DE EE PT MT CY LT BG AT PL BE ES IT NL EU27 26

28 Results by type of farming The share of direct payments in agricultural income also differs between farm types. In particular, the share of direct payments in the incomes of mixed farms and other grazing livestock farms was 41% and 50 % respectively, and thus much higher than the average for the EU27 (Graph 3.4). Direct payments are of less importance for the income of wine and horticulture farms. Graph 3.4: Share of direct payments in FNVA by farm type in the EU27, % 50% 40% 30% 20% 10% 0% Grazing livestock Mixed (crops and livestock) Fieldcrops Milk Granivores permanent crops Wine Horticulture Total Groups Results by type of farming and size class The share of direct payments in agricultural income also differs between large farms and small farms (Table 3.1). In order to have a stable picture, the average of three years ( ) is used. In wine and other permanent crop farms the share decreases with farm size. In the other farm types the pattern is less clear. In the largest farms the share of direct payments in FNVA is lower than the average. However, if one disregards the smallest and largest farms, the share of direct payments in FNVA often increases with farm size. Table 3.1: Share of direct payments in FNVA by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 41.9% 36.4% 46.4% 51.0% 56.0% 48.4% 49.3% Horticulture 2.8% 1.7% 1.6% 2.4% 2.8% 2.0% 2.2% Wine 13.4% 8.5% 8.2% 5.5% 4.9% 3.2% 4.7% permanent crops 30.6% 20.7% 17.7% 15.4% 11.2% 11.3% 15.8% Milk 32.2% 28.0% 21.9% 29.9% 35.5% 30.3% 31.8% grazing livestock 61.8% 46.2% 49.0% 59.7% 59.2% 47.0% 55.0% Granivores 3.8% 6.7% 15.2% 13.8% 12.2% 9.8% 10.5% Mixed 44.6% 36.6% 34.8% 47.5% 51.3% 43.6% 44.9% Total 37.9% 27.8% 31.5% 36.1% 37.5% 28.7% 32.5% 3.3. Importance of direct payments for farm profitability So far, with farm income we have mainly referred to FNVA, which represents the amount of income available to remunerate the production factors land, labour and capital. The profitability problem of the agricultural sector and its dependency on direct payments 27

29 becomes even more visible when the costs for own and external production factors are taken into account. Table 3.2 provides information on production costs, including the imputed costs for own production factors. While the farms are on average able to cover variable costs, the average total costs are higher than market revenue even on the largest farms. Thus, on average, farms need direct payments in order to be profitable. Table 3.2: Farm structure, revenue and share of input costs in farm output in the EU25 by size class, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Economic size (per farm) UAA (per farm) Labour (per farm) Farms represented* Share in output of the sector 2% 6% 7% 16% 25% 45% 100% Output (per farm) share of output PI payments (per farm)** 16% 16% 17% 18% 17% 12% 15% PII payments (per farm)** 9% 5% 8% 7% 4% 1% 4% Intermediate consumption 58.7% 44.3% 50.5% 56.4% 59.6% 59.3% 57.4% Depreciation 21.7% 15.3% 16.7% 15.7% 14.9% 11.5% 13.8% Farm taxes 1.1% 1.2% 1.1% 1.2% 1.1% 1.0% 1.1% Taxes on investment 0.8% 0.7% 0.7% 0.7% 0.5% 0.2% 0.5% Wages 3.2% 5.3% 5.4% 5.5% 5.9% 12.2% 8.5% Rents 1.0% 1.4% 2.1% 3.6% 5.2% 5.3% 4.5% Costs own labour*** 69.8% 71.7% 52.6% 36.9% 22.4% 8.8% 24.4% Costs own land*** 5.3% 7.4% 7.5% 7.0% 5.2% 4.0% 5.2% Costs capital*** 9.4% 4.5% 5.4% 4.6% 3.7% 3.0% 3.8% Total costs 170.9% 151.8% 142.0% 131.7% 118.5% 105.2% 119.1% * No of farms represented during the three years period **includes national part of subsidies *** imputed costs Structure Revenue Costs/Output However, results differ between farm types and size classes. To illustrate this, Table 3.3 and Table 3.4 provide information on variable costs (intermediate consumption) and total costs as a share of market revenue. It is shown that variable costs are on average lower than market revenue for all size classes and farm types (the share is below 100%). Thus, farms are generally able to cover variable costs with market revenue. However, this is often not the case for total costs, as in most cases total costs exceed 100% of market revenue. This is true in particular in the cases of field crop, milk, grazing livestock and mixed farms. Although the gap between costs and revenue diminishes with increasing size, even large farms are generally not profitable on the basis of market revenue alone. Table 3.3: Share of variable costs (intermediate consumption) in market revenue by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 53% 47% 55% 61% 63% 62% 60% Horticulture 52% 43% 41% 42% 47% 51% 48% Wine 31% 31% 28% 33% 36% 34% 34% permanent crops 60% 58% 55% 60% 61% 60% 60% Milk 60% 58% 55% 60% 61% 60% 60% grazing livestock 79% 65% 65% 69% 69% 66% 68% Granivores 77% 74% 73% 67% 67% 66% 67% Mixed 64% 60% 59% 66% 69% 68% 67% Total 59% 44% 51% 56% 60% 59% 57% 28

30 Table 3.4: Share of total costs in output by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 168.5% 162.7% 158.6% 144.7% 131.4% 118.8% 132.9% Horticulture 106.6% 101.6% 103.7% 94.5% 95.0% 92.9% 94.2% Wine 199.3% 166.7% 137.6% 113.3% 99.3% 87.8% 103.1% permanent crops 187.5% 138.6% 124.1% 107.3% 95.5% 92.7% 112.4% Milk 153.8% 137.7% 133.7% 121.1% 107.8% 118.3% grazing livestock 287.8% 196.3% 171.0% 157.0% 136.1% 112.3% 147.2% Granivores 98.3% 96.8% 105.2% 102.5% 96.2% 91.0% 93.7% Mixed 181.1% 153.9% 133.5% 134.7% 122.1% 113.3% 123.3% Total 170.9% 151.8% 142.0% 131.7% 118.5% 105.2% 119.1% However, these are only averages. The situation at farm level is more complex. To illustrate this, Tables 3.5 and 3.6 provide information on the share of farms in the EU25 which are able, respectively, to cover variable and total costs based on market revenue alone. It is shown that variable costs are covered by more than 90% of farms, while only 20% of farms would be able to cover total costs without receiving Pillar I and Pillar II payments. The situation would be particularly difficult for field crops, grazing livestock and mixed farms. In these sectors even the vast majority of large farms would not be profitable, as only 20-25% of these farms would be able to cover total costs. Large farms in the pig & poultry, horticulture and permanent crop sectors are more profitable and less reliant on direct payments. Table 3.5: Share of farms where variable costs (intermediate consumption) are covered by market revenue by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 89% 90% 84% 84% 89% 94% 88% Horticulture 99% 99% 99% 99% 98% 99% 99% Wine 95% 89% 98% 97% 97% 99% 95% permanent crops 89% 98% 97% 98% 98% 98% 97% Milk 94% 96% 96% 96% 98% 99% 97% Grazing livestock 70% 82% 81% 80% 86% 91% 81% Pig & poultry 97% 96% 98% 98% 97% 96% 97% Mixed 93% 96% 94% 89% 94% 98% 94% Total 89% 93% 91% 89% 93% 97% 92% Table 3.6: Share of farms where total costs are covered by market revenue by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 9.2% 12.4% 14.7% 16.8% 17.8% 20.5% 14.4% Horticulture 21.5% 37.3% 40.5% 49.4% 47.2% 50.9% 44.4% Wine 10.2% 13.6% 18.7% 32.1% 42.9% 57.2% 27.1% permanent crops 10.6% 23.1% 29.1% 40.4% 50.4% 53.6% 27.4% Milk 6.2% 13.1% 21.6% 18.1% 16.0% 29.5% 18.4% Grazing livestock 3.1% 6.3% 14.7% 18.7% 18.0% 24.0% 13.6% Pig & poultry 29.5% 21.9% 22.6% 37.4% 49.7% 57.9% 39.5% Mixed 3.5% 7.4% 16.4% 24.7% 19.1% 24.4% 12.6% Total 7.6% 15.5% 20.1% 24.9% 24.8% 34.1% 19.7% This situation is addressed by the CAP because field crop, grazing livestock and mixed farms are the ones receiving the largest amount of direct payments (Table 3.7). Furthermore, it has to be noted that the amount of direct payments increases considerably with farm size. 29

31 Table 3.7: Amount of direct payments per AWU by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops Horticulture Wine permanent crops Milk Grazing livestock Pig & poultry Mixed The receipt of Pillar I and Pillar II payments significantly increases the profitability of farms (Table 3.8 and 3.9). The share of farms covering variable costs increases to almost 100% and the share of profitable farms (which cover total costs) increases from under 20% to 35%. The profitability of field crop, mixed and other grazing livestock farms improves the most. This is true for large farms in particular. For instance, the share of large profitable field crop, grazing livestock and mixed farms jumps from slightly more than 20% to over 60%. Overall this shows that, in particular, land based production systems such as field crop and grazing livestock farms, which ensure that the bulk of the agricultural area is kept in good agricultural and environmental condition, depend the most on direct payments. Table 3.8: Share of farms with positive gross farm income by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 98% 99% 97% 98% 99% 99% 99% Horticulture 100% 99% 99% 99% 98% 99% 99% Wine 98% 99% 98% 98% 98% 99% 98% permanent crops 96% 99% 99% 99% 99% 99% 99% Milk 99% 99% 100% 99% 100% 100% 99% Grazing livestock 96% 98% 98% 98% 99% 99% 98% Pig & poultry 97% 98% 99% 98% 98% 98% 98% Mixed 98% 99% 99% 98% 99% 100% 99% Total 98% 99% 98% 98% 99% 99% 99% Table 3.9: Share of profitable farms by farm type and size class in the EU25, Average EU-25, average Economic size (potential gross margin in 1000 ) < >120 Total Field crops 19.2% 22.0% 29.9% 38.0% 48.6% 61.3% 32.0% Horticulture 29.0% 39.1% 43.7% 51.3% 49.6% 53.4% 47.0% Wine 15.9% 16.0% 23.9% 37.0% 50.0% 63.3% 31.8% permanent crops 15.6% 33.0% 37.4% 51.1% 59.7% 64.4% 36.4% Milk 21.3% 29.3% 38.4% 37.6% 45.4% 62.5% 42.1% Grazing livestock 12.6% 21.5% 34.3% 41.9% 49.8% 65.1% 34.7% Pig & poultry 31.8% 25.7% 34.5% 51.1% 60.7% 68.1% 49.1% Mixed 8.6% 15.8% 35.1% 44.2% 47.7% 63.3% 27.4% Total 14.9% 25.0% 33.7% 42.2% 49.5% 62.4% 34.5% 30

32 4. FINANCIAL STRUCTURE The indicators described in this section provide ways to compare the financial structure of different agricultural holdings. Items from the balance sheet have been used to calculate them. Annex 4 sums up the average values of the different financial indicators by MS and the EU27 in Total asset value Total assets are the property of the agricultural holding and are calculated as the sum of the current and fixed assets of the holding. Current assets in the FADN include non-breeding livestock, stock of agricultural products and other circulating capital (such as advances for crops, holdings of agricultural shares and amounts receivable in short-term or cash balances in hand or in the bank). Fixed assets include agricultural land, farm and other buildings, forest capital, machinery and equipment, and breeding livestock. Trend by EU group The value of total assets (TA) showed an upward trend in the EU15 from 1998 to 2002, when the value of an average holding s assets stood at (Graph 4.1). However, the data show a slight decrease (to ) in This was followed by another rise in the average value between 2004 and The first FADN data from the EU10 (Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovenia and Slovakia) were delivered in The average total assets value for the EU10 in 2004 was In 2007, the EU10 average total assets per farm stood at In the EU2, average total assets and total liabilities were and respectively (not shown in the graph). Graph 4.1: Trend in the value of assets (TA) and liabilities (TL) by EU group, EU15 TA EU15 TL EU10 TA EU10 TL Note: the vertical line corresponds to 2004, the year in which the first data from the new Member States (the Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovenia and Slovakia) were registered. Values in current euros. TA: Total assets, TL: Total liabilities. 31

33 Results by Member State In Graph 4.2 the average asset value is given by MS and compared to the EU27 mean. The asset value is the highest for farms in Denmark ( ), the Netherlands ( ), the United Kingdom ( ) and Slovakia ( ). By contrast, the asset value was the lowest for farms in Bulgaria and Romania, at and respectively. Graph 4.2: Average asset value per farm by MS in 2007 Total assets EU27 Total assets DK NL UK SK IE LU DE CZ SE BE AT FI FR IT ES MT EE SI CY HU LT LV PT PL EL BG RO Results by type of farming Milk farming was the type with the highest total asset value ( ) in 2007 (see Graph 4.3), followed by granivore farms with permanent crops (holdings producing citrus and other fruit, olives and other permanent crops) posted the lowest total assets, with The average farm in the EU27 had total assets of Graph 4.3: Average asset value by type of farming in the EU27 in 2007 Equity EU27 Total assets Milk Granivores Grazing livestock Wine Horticulture Fieldcrops Mixed (crops and livestock) permanent crops 32

34 4.2. Total liabilities In the EU27 total liabilities made up only for a small proportion of farm financing on average. Although the enlargement also had an effect on average total liabilities per farm, the impact was much smaller than on total assets. Results by Member State In line with the trend in the asset value of the last ten years (see Graph 4.1), total liabilities in the EU15 showed a steady increase, starting with in 1998 and ending on in Average liabilities also increased in the EU10 from in 2004 to in In the EU2, average total liabilities were In the EU27 average liabilities per agricultural holding were in 2007 (see Graph 4.4). Denmark was the MS with the heaviest liabilities per farm ( ), followed by the Netherlands ( ), while Greek agricultural holdings had almost no liabilities 8. The United Kingdom, Slovakia and Hungary are the countries where farmers rely the most on short-term loans to finance their holdings, and these loans account for more than 50% of their total liabilities. In farms in Belgium and Cyprus, by contrast, long- and medium-term loans account for more than 95% of their liabilities. Graph 4.4: Composition of liabilities per farm by MS in 2007 Long & medium-term loans Short-term loans DK NL SE CZ LU UK BE DE FR SK FI EE HU AT LV IE LT MT PL ES BG IT SI PT CY RO EL Results by type of farming As Graph 4.5 shows, granivores, horticulture and milk are the types of farming with the largest liabilities ( , and respectively). On the other hand the value of total assets is also the highest in these farm types. permanent crop farms recorded the lowest liabilities in 2007 ( 6 600). As regards the composition of these liabilities, all types of farming have a percentage of short-term loans ranging from 18% (milk) to 44% (wine). 8 In some Member States, the share of liabilities is surprisingly low. To some extent this can be explained by the difficulty of farmers to access credit markets. However, another explanation could be that in these countries liabilities are not included in the farm accounts but in the private accounts of the farmers. 33

35 Graph 4.5: Composition of liabilities per farm in the EU27 by type of farming in 2007 Long & medium-term loans Short-term loans Granivores Horticulture Milk Wine Mixed (crops and livestock) Fieldcrops Grazing livestock permanent crops Total Groups 4.3. Development of farm net worth Results by Member State Farm net worth was calculated as total assets minus total liabilities at the end of the accounting year. In 2007 the average farm net worth was in the EU27. Net worth was highest in the UK, Slovakia and the Netherlands and lowest in Bulgaria and Romania. In comparison to 2004, the net worth increased the fastest in Ireland, Spain and the UK. Net worth decreased in particular in France, the Netherlands, Denmark and Slovakia. Graph 4.6: Farm net worth per farm by EU group and MS in 2004 and EU UK SK NL IE LU DK DE CZ SE BE AT IT ES MT FI FR SI CY EE HU PT LT EL PL LV BG RO Milk farms had the highest net worth ( ) and mixed farms the lowest ( ) (see Graph 4.7). 34

36 Graph 4.7: Farm net worth per farm in the EU27 by type of farming in EU Milk Grazing livestock Granivores Wine Fieldcrops Horticulture permanent crops Mixed (crops and livestock) 4.4. Solvency Solvency measures the ability of farms to meet their obligations in the long term. In the framework of this analysis, the liabilities-to-assets ratio is used to measure solvency. This solvency measure provides an indication of the enterprise's ability to repay all liabilities if all of the assets were sold. In terms of the interpretation of the results it has to be emphasised that a high liabilities-toassets ratio is not necessarily a bad sign. On the contrary, it can be an indication of economic viability as it shows that farms have access to outside financing. It indicates that creditors are confident that the farmers will be able to repay their loans. However, there is certainly a point at which the amount of liabilities becomes a problem. For instance, if the liabilities are higher than the value of assets, this is a clear sign of financial problems. A high liabilities-to-assets ratio is normally caused by use of outside financing i.e. taking out loans. Increasing leverage normally results in higher returns on equity i.e. profitability of the farm. It indicates that farmers find investment opportunities to increase their income in the long run. The liability to asset ratio differs between MS and between regions. Farms in Denmark and the Netherlands had the highest liability to asset ratio (with 56% and 36% respectively). At regional level, farms in Brittany, Picardie, Haute-Normandie and Mecklenburg-Vorpommern had with on average very high liability-to-asset ratios of more than 45% (Map 4.1). The lowest percentages are found in Greece, Spain, Italy and Romania 9. The level of liabilities varies not only between regions but also between farm types (Graph 4.8). The level is highest in horticulture, pigs & poultry farms and milk farms. This 9 In some Member States, the share of liabilities is surprisingly low. One explanation could be that in these countries liabilities are not included in the farm accounts but in the private accounts of the farmers. 35

37 confirms that a high level of liabilities does not necessarily indicate a problem, because the income of these farm types in most years is above average. Map 4.1: Average liabilities-to-asset ratio per farm by FADN region in

38 Graph 4.8: Farm solvency in the EU27 by type of farming in % 30% 2007 Total % 20% 15% 10% 5% 0% permanent crops Grazing livestock Wine Fieldcrops Mixed (crops and livestock) Milk Granivores Horticulture 4.5. Current and fixed assets Results by Member State Fixed assets 10 make up the biggest proportion of the total assets of each farm in the EU27 (Graph 4.9). In Ireland, Greece and Slovenia, the total assets of each farm consist almost exclusively of fixed assets (more than 95% of total assets). Graph 4.9: Composition of assets by MS in % 80% 60% 40% 20% 0% IE EL SI MT IT UK CY BE NL DE DK PT LU PL FI EE AT RO SE CZ SK LT LV HU BG ES FR Total EU15 EU10 EU2 Fixed assets Current assets The composition of the total fixed assets of each farm by MS depends on the structure of the agricultural sector. In 2007 land, permanent crops and quotas were the biggest components in countries such as Ireland, the United Kingdom, Ireland, Cyprus, Spain and Italy, and 10 Fixed assets include agricultural land, farm and other buildings, forest capital, machinery and equipment and breeding livestock. 37

39 buildings were of major importance in Slovakia and the Czech Republic (see Graph 4.10). In Lithuania and Latvia machinery accounted for a relatively large share of assets value, while Breeding livestock remained in a range from 2% (Italy) to 16% (France) of total fixed assets. At this point it should be added that there are differences between MS in the way that assets and factors are recorded. Quotas, for instance, are not handled in the same way in every MS. In some they are not marketable, so they are not recorded in the total assets of the farm, although they might be reflected since they are partly included in the land value. As a result, the item land, permanent crops and quotas is lower. These differences can be seen, for example, between the Netherlands, which has marketable quotas, and France, which does not. There are also differences in recording data about land, as is the case with France, where farmers form companies that rent land to their members. Consequently, land is not included in total assets of French farms, which increases the relative share of other assets. Graph 4.10: Composition of fixed assets by MS in % 90% Land, perma. Crops & quotas Buildings Machinery Breeding livestock 80% 70% 60% 50% 40% 30% 20% 10% 0% 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 EU27 Results by type of farming In 2007, fixed assets were 80% of total assets (see Graph 4.10): 67% were in the form of land, permanent crops and quotas, 16% buildings, 12% machinery and the remaining 4% breeding livestock. These percentages vary widely, depending on the type of farming considered (see Graph 4.11). In wine and other permanent crops, field crops, grazing livestock and milk farms land, permanent crops and quotas represent a large share of total asset value (all over 60%), whereas granivore farms are less dependent on land and rely more on buildings. Horticulture farms have the highest share of machinery (18% of fixed assets), followed by mixed farming (15%) and field crops (14%). Breeding livestock accounts for a higher share of total assets in grazing livestock and milk farms (both 9%). 38

40 Graph 4.11: Composition of assets by type of farming in % 80% 60% 40% 20% 0% Milk Grazing livestock Fieldcrops Mixed (crops and livestock) Horticulture Granivores permanent crops Fixed assets Current assets Wine Graph 4.12: Composition of fixed assets by type of farming in % Land, perma. Crops & quotas Buildings Machinery Breeding livestock 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 39

41 5. COMPOSITION OF LABOUR INPUT Results by Member State The labour input of holdings, expressed in AWU, revealed considerable differences between MS in 2007, from 1.16 AWU in Ireland to AWU in Slovakia. On average, EU27 farms reported 1.71 AWU (Graph 5.1). Graph 5.1: Labour input per farm (in AWU) by MS in Labour input in AWU SK CZ NL EE BG UK LV DE RO LT BE FR MT HU SI PL LU PT AT DK SE FI IT ES CY EL IE Results by type of farming The labour input by type of farming is highest in "horticulture" and lowest in the "other permanent crops" sector (Graph 5.2). Graph 5.2: Labour input per farm (in AWU) by type of farming in EU27 in Labour input in AWU Horticulture Granivores Milk Wine Mixed (crops and livestock) Grazing livestock Fieldcrops permanent crops Total Groups 40

42 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, but it still represents the majority form of labour in most MS. Only in Slovakia, the Czech Republic and Hungary is the majority of the labour force paid (see Graph 5.3). Graph 5.3: Share of working hours of paid and unpaid labour by MS in 2007 Share of unpaid labour (family labour hours) Share of paid labour EU27 average 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% SI IE AT EL PL FI LU MT PT BE RO ES SE LT IT FR CY LV DE UK DK NL BG EE HU CZ SK Results by type of farming Due to the employment of seasonal workers, the share of paid labour is highest in horticulture and wine farms. Granivore farms also employ a relatively large share of paid workers. The share of paid labour is lowest in milk and grazing livestock farms. Graph 5.4: Share of working hours of paid and unpaid labour in EU27by type of farming in 2007 Share of unpaid labour (family labour hours) Share of paid labour EU27 average 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Fieldcrops Horticulture Wine permanent crops Milk Grazing livestock Granivores Mixed (crops and livestock) 41

43 6. COSTS FOR EXTERNAL PRODUCTION FACTORS 6.1. Remuneration of farm workers Due to structural changes and increasing farm sizes, the share of non family labour in the total workforce is increasing in the EU15. In large farms in eastern Europe, which are often organised as legal persons, there is a predominance of non-family labour. Thus, the costs of non-family labour are growing in importance. Results by EU group On average, wages ( /hour) showed an upward trend between 1998 and 2007 (see Graph 6.10). In the EU15, wages increased by 30% on average, from 6.80/hour in 1998 to 8.90 in In the EU10, wages rose by 41% in 2007 compared with 2004, with the amount paid increasing from 2.20/hour to In 2007 the average wage in the EU27 was 5.80/hour. Graph 6.1: Trend in average wages per working hour from 1998 to 2007 /hour 10 EU25 EU15 EU10 EU2 Linear (EU15) Year Note: EU10 comprises the new MS from 2004 (the Czech Republic, Cyprus, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovenia and Slovakia). EU15 comprises the MS that formed the EU until Values in current euros. Results by Member State The level of wages differs widely in the EU27 (Graph 6.2). The highest wages were found in Denmark ( 20.9/hour) and the lowest in Bulgaria ( 1.0/hour). All EU12 MS, but also Greece, were below the EU27 average. Map 6.1 shows that wages were the highest in the north-west of Europe. In Denmark, the Netherlands and many Scandinavian and French regions, the average wage per working hour was higher than 12 Euro. By contrast, in the EU12, Portugal, Greece and some regions in southern Italy and southern Spain, the average wage per working hour was less than 6 Euro. In Poland, Romania, Bulgaria, Latvia and Lithuania, the hourly wage was even below three Euro. 42

44 Graph 6.2: Average wages per hour of paid labour by MS and EU group in 2007 /hour Wages/hour EU27 0 DK SE NL FR FI UK IE DE BE LU IT ES AT CZ MT SK PT CY SI EL HU EE LV LT PL RO BG EU27 EU15 EU10 EU2 Map 6.1: Average wage in the FADN regions,

45 6.2. Level of land rents As land prices are often influenced by factors outside the agricultural sector, the best measure for the costs of land is usually the annual rent farmers have to pay for one hectare of land. The regional level of land rents is shown in Map 6.1. It shows that the costs of leasing land differ within the EU. Rents are particularly high in the Netherlands, Denmark, northern Germany and Greece, whereas they are very low in eastern Europe and in many regions with unfavourable conditions for intensive agricultural production, such as dry and mountainous areas. The level of the land rent can be used as an indicator of the risk of land abandonment. It reflects the scarcity and the potential for economic use of this factor of production. If the land rent is 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 land rents are low, this indicates that there is little economical incentive to use the land and that adverse changes in the economic environment can result in land being abandoned. Map 6.2: Average land rent in the FADN regions in 2007 Source: DG AGRI EU- FADN 44

46 6.3. Costs of capital The costs of capital (other than land) also differ between MS. As an indication for the costs of capital, Table 6.1 shows the regional level of the real interest rate. This rate is calculated by subtracting the inflation rate from the nominal interest rate for long term bonds. Thus, it represents the annual real costs of borrowing money. In 2007 the real interest rate ranged from -3.3% in Bulgaria to 4.9% in Latvia. The minus sign in Bulgaria is due to the fact that inflation in Bulgaria was higher than the interest rate. All other things being equal, this suggests that in Bulgaria it was economically more profitable to invest in a farm asset instead of investing in long term bonds. Although the differences in the real interest rate are significant, it has to be emphasised that this mainly applies to the MS which had not introduced the Euro. Within the Euro zone the real interest rates were similar. Table 6.1: Average real interest rate in the FADN regions in 2007, in % year Interest rate Inflation rate Real interest rate Belgium Bulgaria Cyprus Czech Republic Denmark Germany Greece Spain Estonia France Hungary Ireland Italy Lithuania Luxembourg Latvia Malta Netherlands Austria Poland Portugal Romania Finland Sweden Slovakia Slovenia United Kingdom Source: EUROSTAT, Global Insight Elaboration DG AGRI 45

47 GRAPH INDEX Graph 1.1: Farm net value added (FNVA) and economic profit per farm by MS in Graph 1.2: FNVA/AWU and economic profit/awu by MS in Graph 1.3: Trend in FNVA/AWU and economic profit/awu from 1998 to Graph 1.4: FNVA and economic profit per farm in the EU27 by type of farming in Graph 1.5: FNVA/AWU and economic profit/awu by type of farming in Graph 1.6: FNVA and economic profit per farm by EU group and organisational form in Graph 1.8: Distribution of FNVA/AWU by EU groups Graph 1.9: Distribution of FNVA/AWU by year Graph 1.10: Distribution of FNVA/AWU by type of farming in the EU Graph 1.11: Distribution of FNVA/AWU of dairy farms in the EU15 by year Graph 1.13: Distribution of FNVA/AWU of granivore farms in the EU15 by year Graph 1.14: Lorenz curve of the distribution of FNVA in the EU27 in Graph 1.15: Income components per farm by EU-groups in Graph 1.16: Income components per farm by type of farming in Graph 2.1: Available remuneration per FWU by MS in 2006 and Graph 2.2: Available remuneration FWU in the EU27 by type of farming in Graph 2.3: Development of the available remuneration per FWU by EU-group Graph 2.4: Rate of Return On Assets by MS in 2006 and Graph 2.5: ROA in the EU27 by type of farming in Graph 2.6: Development of the ROA by EU groups Graph 3.1: Share of public support in total receipts by MS in Graph 3.2: Share of direct payments in total receipts by type of farming in Graph 3.3: Share of direct payments in FNVA by MS in Graph 3.4: Share of direct payments in FNVA by farm type in the EU27, Graph 4.1: Trend in the value of assets (TA) and liabilities (TL) by EU group,

48 Graph 4.2: Average asset value per farm by MS in Graph 4.3: Average asset value by type of farming in the EU27 in Graph 4.4: Composition of liabilities per farm by MS in Graph 4.5: Composition of liabilities per farm in the EU27 by type of farming in Graph 4.6: Farm net worth per farm by EU group and MS in 2004 and Graph 4.7: Farm net worth per farm in the EU27 by type of farming in Graph 4.8: Farm solvency in the EU27 by type of farming in Graph 4.9: Composition of assets by MS in Graph 4.10: Composition of fixed assets by MS in Graph 4.11: Composition of assets by type of farming in Graph 4.12: Composition of fixed assets by type of farming in Graph 5.1: Labour input per farm (in AWU) by MS in Graph 5.2: Labour input per farm (in AWU) by type of farming in EU27 in Graph 5.3: Share of working hours of paid and unpaid labour by MS in Graph 5.4: Share of working hours of paid and unpaid labour in EU27by type of farming in Graph 6.1: Trend in average wages per working hour from 1998 to Graph 6.2: Average wages per hour of paid labour by MS and EU group in TABLE INDEX Table 3.1: Share of direct payments in FNVA by farm type and size class in the EU25, Average Table 3.2: Farm structure, revenue and share of input costs in farm output in the EU25 by size class, Average Table 3.3: Share of variable costs (intermediate consumption) in market revenue by farm type and size class in the EU25, Average Table 3.4: Share of total costs in output by farm type and size class in the EU25, Average Table 3.5: Share of farms where variable costs (intermediate consumption) are covered by market revenue by farm type and size class in the EU25, Average

49 Table 3.6: Share of farms where total costs are covered by market revenue by farm type and size class in the EU25, Average Table 3.7: Amount of direct payments per AWU by farm type and size class in the EU25, Average Table 3.8: Share of farms with positive gross farm income by farm type and size class in the EU25, Average Table 3.9: Share of profitable farms by farm type and size class in the EU25, Average Table 6.1: Average real interest rate in the FADN regions in MAP INDEX Map 1.1: FNVA/AWU by FADN region, Average Map 1.2: Economic profit/awu by FADN region, Average Map 4.1: Average liabilities-to-asset ratio per farm by FADN region in Map 6.1: Average wage in the FADN regions, Map 6.2: Average land rent in the FADN regions in ANNEX INDEX Annex 1: Methodology Annex 2: Income calculation Annex 3: Threshold by MS in 2007 (ESU: European size units) Annex 4: FNVA and economic profit per AWU by MS and organisation in Annex 5: Number of holdings by type of farming in Annex 6: Breakdown of economic profit of farms in the EU27 in Annex 7: Balance sheet components in FADN Annex 8: Overview of structural parameters, revenues and costs (absolute values in and share in output) in farms in the EU15 and EU Annex 9: Indicators by MS in

50 Annex 1: Methodology Revenue items recorded in the FADN accounts Output: includes not only output of crops and livestock activities, but also 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 with Pillar I and Pillar IItype payments, reference is made not only to the part financed by the EU but also to subsidies financed by the MS, including national aids. The FADN does not allow a clear distinction to be made 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 e.g. costs for feed, fertilisers, crop protection and energy. Depreciation: depreciation of capital assets estimated at replacement value. Farm taxes: farm taxes and other dues (not including VAT and the personal taxes of the holder) and taxes and other charges on land and buildings. Subsidies on taxes are deducted. Taxes on income are not taken into account. Taxes on investment: subsidies and taxes not arising from current productive activity in the accounting year. 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 is estimated on the basis of the 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 obtained in the FADN database 11 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 sometimes overestimated. Thus the method uses a maximum of hours per Annual Work Unit (this 11 If there are not enough farms (fewer than 20) with paid labour at regional level, the national average is taken into account. 49

51 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) 12. The fact of using hours makes it possible to remunerate a manager more than an employee if he is working more hours. Calculating a reliable estimate is difficult because records of hours worked on the farm might be overestimated, and it is not easy to determine what is an appropriate remuneration for family labour. Farmers may indeed agree to be remunerated less than they would be according to the average agricultural wage. They may consider farming as a way of life or benefit from other sources of income for their household (other gainful activities directly related to the holding, spouse working outside the farm, etc). Own capital cost Own land cost: this is estimated on the basis of the rent that the owner of the farm would have to pay if he was obliged to rent the land he is using. It is estimated as the owned area multiplied by the rent paid per ha on the same farm or, if there is no rented land on the farm, by the average rent paid per ha in the same region and for the same type of farming 13. Cost for 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 gain if he were to invest the equivalent of its capital value in a bank. 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 taken from the Global Insight database for the net worth. 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. In the end, the own capital value (excluding land and land improvement) is estimated as the average value of the assets (closing plus opening valuation divided by 2) multiplied by the real interest rate 14. The correction is made by subtracting the inflation rate 15 from the nominal 12 A constraining factor of the estimation method is that if a farmer were to receive a salary he would probably work less. 13 If there are not enough farms (fewer than 20) in a given region for a type of farming, the national rent per ha for the given type of farming is used (the TF8 classification is used). 14 The 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 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. 50

52 interest rate. Where the inflation rate is higher than the interest rate, the real interest rate may be negative, leading to a negative cost of capital which will contribute positively to the profit (it is more profitable to invest in farm assets than to put the money in the bank). The total circulating capital is not valued because of the unreliability of this variable in some MS. Nevertheless, the crop stocks value is taken into account. To calculate the unpaid capital costs, in order to avoid double counting, we have to deduct the interest paid from the sum of the own land cost and the cost for own capital except land: Imputed unpaid capital costs = own land cost + estimated cost for own capital except land interests paid Total cost of imputed unpaid family factors is then the sum of family labour costs and unpaid capital costs: Imputed unpaid family factors = family labour cost + unpaid capital costs Or Imputed unpaid family factors = family labour cost + (own land cost + estimated cost for own capital except land interest paid) 15 The inflation rate is based on the Eurostat annual average rate of change in Harmonized Indices of Consumer Prices (HICPs) available from Inflation rates based on price indexes of GDP and gross fixed capital consumption have been tested, but they are very high and were leading to very high negative costs for capital, mainly in the EU10. An inflation rate calculated on the basis of price indexes 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. Therefore the inflation rate of gross fixed capital consumption must not have a closer relationship with the change in the price of agricultural assets than with the consumer price indices. 51

53 Annex 2: Income calculation 52

54 Annex 3: Threshold by MS in 2007 (ESU: European size units) Member State Threshold (ESU) Belgium 16 Bulgaria 1 Cyprus 2 Czech Republic 4 Denmark 8 Germany 16 Greece 2 Spain 2 Estonia 2 France 8 Hungary 2 Ireland 2 Italy 4 Lithuania 2 Luxembourg 8 Latvia 2 Malta 8 The Netherlands 16 Austria 8 Poland 2 Portugal 2 Finland 8 Sweden 8 Slovakia 6 Slovenia 2 Romania 1 The United Kingdom 16* * The threshold of 16 was used for the whole UK, but Northern Ireland has an ESU threshold of 8. 53

55 Annex 4: FNVA and economic profit per AWU by MS and organisation in 2007 /AWU FNVA/AWU Economic profit/awu Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships Partnerships CY CZ EE HU LT LV MT PL SK SI BE DK DE EL ES FR IE IT LU NL AT PT FI SE UK BG RO Note. In cases where no information is displayed in a column, this is for confidentiality reasons (because there are fewer than 15 holdings in the category concerned in the sample studied). 54

56 Annex 5: Number of holdings by type of farming in 2007 Farms represented Sample farms Types of farming Sum Sum Field crops Horticulture Wine permanent crops Milk Grazing livestock Granivores Mixed (crops and livestock) Total groups

57 Annex 6: Breakdown of economic profit of farms in the EU27 in Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp BE CY CZ DK DE EL ES EE FR HU IE IT LT LU LV MT NL AT PL PT FI SE SK SI UK Note. Rec. stands for Receipts and Exp. stands for expenses. Total output Public support Total intermed. Consumption Depreciation Total external factors Own factors Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp Rec Exp 56

58 Annex 7: Balance sheet components in FADN 57

59 Annex 8: Overview of structural parameters, revenues and costs (absolute values in and share in output) in farms in the EU15 and EU10 Costs Revenue Structure All farm types EU-15 ø ø change Economic size (per farm) % UAA (per farm) % Labour (per farm) % Output (per farm) % abs. share abs. share abs. share PI payments (per farm)* % % 35.3% % PII payments (per farm)* % % 187.0% % Intermediate consumption % % 35.8% % Seeds % % 39.9% % Fertilisers % % 22.5% % Crop protection % % 26.7% % Feed % % 28.0% % Machinery & buildings % % 26.8% % Energy % % 72.9% % Contract work % % 36.1% % % % 43.9% % Depreciation % % 25.6% % Farm taxes % % 30.4% % Taxes on investment % % -4.7% % Wages % % 50.2% % Rents % % 37.6% % Costs own labour** % % 12.5% % Costs own land** % % 4.2% % Costs capital** % % -39.8% % Total costs % % 23.8% % * Includes national part of subsidies ** imputed costs EU-10 ø

60 Annex 9: Indicators by MS in 2007 Member State FNVA Profit FNVA per AWU Profit per AWU Income remaining per FWU* Return on assets Share DP in revenue Share DP in FNVA Average asset value Average liabilities Net worth Solvency Paid labour input /AWU /AWU % % % % % % /hour BE % 9% 23% % 18% 82% 9.3 BG % 10% 25% % 48% 52% 1.0 CY % 9% 30% % 28% 72% 3.8 CZ % 14% 45% % 82% 18% 4.4 DK % 10% 34% % 43% 57% 20.9 DE % 12% 34% % 37% 63% 9.3 EL % 20% 35% % 11% 89% 3.5 ES % 11% 19% % 20% 80% 6.2 EE % 12% 34% % 48% 52% 3.5 FR % 14% 39% % 27% 73% 11.9 HU % 13% 44% % 64% 36% 3.5 IE % 22% 53% % 6% 94% 9.4 IT % 8% 14% % 23% 77% 7.3 LT % 14% 29% % 22% 78% 2.1 LU % 12% 35% % 15% 85% 9.3 LV % 14% 43% % 35% 65% 2.4 MT % 13% 31% % 16% 84% 4.4 NL % 4% 13% % 44% 56% 13.8 AT % 11% 25% % 7% 93% 6.1 PL % 9% 24% % 14% 86% 2.1 PT % 14% 34% % 16% 84% 3.8 RO % 14% 36% % 18% 82% 1.4 FI % 20% 65% % 14% 86% 11.9 SE % 13% 44% % 21% 79% 17.0 SK % 13% 59% % 93% 7% 3.9 SI % 12% 49% % 4% 96% 3.6 UK % 13% 37% % 42% 58% 11.7 EU % 12% 28% % 23% 77% 5.8 EU % 12% 28% % 23% 77% 8.9 EU % 11% 31% % 25% 75% 3.1 EU % 13% 34% % 22% 78% 1.3 * After deduction of all economic costs except the opportunity costs for family labour Unpaid labour input Wages / hour 59

61

62 This report provides an overview of the development of key economic indicators in the European agricultural sector. The analysis is based on data from the Farm Accountancy Data Network (FADN). The latest data available are from Directorate General for Agriculture and Rural Development The text of this publication is for information purposes only and is not legally binding European Union, 2010 photo - pizzodisevo