Selecting the sample of farms from the FADN's field of observation

This chapter describes how farms are selected and the techniques that are used to achieve as high a degree of representativity as possible.

Member States conduct their own selection Top

Before the creation of FADN, several Member States were already conducting agricultural surveys based on farm accounts. Some of these surveys were based on a selective sample of farms - as opposed to the entire population of farms. To select a sample of farms, these Member States had established their own selection plans.

Most Liaison Agencies of the Member States continue to conduct national surveys and have thus retained their own selection plans. Current practice is for Liaison Agencies to design their own selection plans for the European Union survey. The plans are submitted to the FADN European Union Committee for approval. They vary in technical sophistication from one Member State to another.

Stratification Top

The use of stratification

Within FADN's field of observation, there is a great diversity of farming. Some farms are very large (in terms of their economic size) while others may be very small. Some farms concentrate on crop production, others specialise in livestock rearing while yet others practice mixed farming, that is, both crop and livestock production. On these two criteria alone i.e. - economic size and type of farming -, the field of observation of European Union farms is highly heterogeneous.

To ensure that the sample of farms adequately reflects this heterogeneity, Liaison Agencies stratify the field of observation before the sample of farms is selected. If this were not done, there would be a greater risk that particular categories of farm (say, large dairy farms in one region, or small fruit farms in another region) would not be represented adequately (or at all) by the sample.

Stratification is a statistical technique which is used to increase sampling efficiency (i.e. to minimise the number of farms required to represent the variety of farms in the field of observation). The Commission makes extensive use of this technique and uses three criteria for stratification: region, economic size and type of farming, as described in the following sections.


For FADN purposes the European Union is divided into FADN regions. All farms in FADN's field of observation are classified into economic size classes and type of farming.

A detailed typology has been created for use by various bodies at European Union level. It is sufficiently broad to encompass the many different types of farming that are found in the European Union. This typology is described in Commission Regulation (EC) No 1242/2008 of 8 December 2008.

Typology identifies the principal types of farming, which are then further broken down. How are farms allocated to a specific type? In other words, what are the definitions of different types of farming?

Types of farming are defined in terms of the relative importance of the different enterprises on the farm. Relative importance is itself measured quantitatively as a proportion of each enterprise's SO to the farms' total SO. (see example of classification of a farm).

For the purpose of computing Standard Results, the Commission uses groups of farming types. For more information on how these Standard Results are calculated and published, refer to Diffusion chapter.

Example of classification of a farm according to European Union typology

Assume: a farm with 50 dairy cows and 10 breeding sows and 5 dairy cows

two principal types of farming would appear to be suitable descriptions of this farm:

51specialist pigs
74mixed livestock, mainly granivores

To which type of farming does this farm belong?

EnterpriseSOSize of enterpriseEnterprise SOEnterprise SO as proportion of& farm's total SO
Breeding sows100050 breeding sows50.00083.3
Dairying20005 dairy cows10.00016.7%
  Farm's total SO60.000100%

The definition of the two principal types of farming are as follows:

51specialist pigspigs > 2/3 of farm's total SO
74mixed livestock, mainly granivoresgrazing livestock and forage ≤ 1/3 granivores in farm's total SO

Since breeding sows > 2/3 of farm's total SO, this farm is classified as "specialist pigs" for principal type of farming.

The definition of the 3 particular types of farming is as follows:

511specialist pig rearingbreeding sows contribute > 2/3 of farm's total SO
512specialist pig fatteningpiglets and othe pigs contribute > 2/3 of farm's total SO
513pig rearing and fattening combinedholdings in class 51 excluding those in classes 511 and 512

Since breeding sows contribute > 2/3 of farm's total SO, this farm is classified as "specialist pig rearing" for particular type of farming.

The universe and field of observation represented as a matrix of cells Top

The 3-way stratification of the universe allows it to be represented as a 3-dimensional matrix of cells. The number of farms in each cell is derived from the Farm Structure Survey (FSS) organised by Eurostat. This survey employs the same typology as that used for FADN.

Each cell corresponds to a specific category of farms. Some cells represent a large number of farms: for instance, in Ireland there are approximately 18 000 farms in the economic size class from 4 000 to less than 8 000 euro in the cell that practise farming type 46 - specialist cattle (rearing and fattening). Other cells represent very few farms: in Denmark for example, there are only about 40 farms of size from 15 000 to less than 25 000 which practise farming type 2 - specialist horticulture. Needless to say, some cells are empty - such as those representing vineyards, big or small, in Finland.

The Commission and the Liaison Agencies select the sample of farms not from the field of observation as a whole but from the cells which make up the field of observation. Sample farms are thus selected from each cell - in this way all the cells are, in principle, represented in the sample. Thus the FADN sample of farms reflects the heterogeneity in the field of observation.

Year of Farm Structure Survey (FSS)
Member State Farms FSS Coverage field of observation FADN
Total Field FADN Farms % SO % UAA % AWU % SO
Belgium 42850 31010 72.0 98.0 95.0 87.0 2007
Bulgaria 370490 115390 31.0 91.0 96.0 51.0 2007
Czech Republic 22860 14820 65.0 99.0 98.0 93.0 2007
Denmark 42100 29340 70.0 99.0 96.0 89.0 2007
Germany (*) 299130 196520 66.0 97.0 93.0 87.0 2007
Estonia 19610 8080 41.0 98.0 89.0 76.0 2007
Ireland 139890 105170 75.0 98.0 92.0 84.0 2007
Greece (*) 723010 341180 47.0 90.0 85.0 79.0 2007
Spain 989800 597970 60.0 98.0 92.0 84.0 2007
France 516100 317360 61.0 97.0 91.0 85.0 2007
Italy 1620880 838740 52.0 97.0 91.0 82.0 2007
Cyprus 38860 10530 27.0 92.0 76.0 70.0 2007
Latvia 83390 21940 26.0 91.0 73.0 52.0 2007
Lithuania 199910 53440 27.0 86.0 78.0 54.0 2007
Luxembourg 2200 1610 73.0 98.0 97.0 90.0 2007
Hungary 576810 107250 19.0 90.0 93.0 46.0 2007
Malta 12530 3080 25.0 93.0 56.0 54.0 2007
Netherlands (*) 72320 52220 72.0 99.0 93.0 90.0 2007
Austria 150170 95150 63.0 97.0 86.0 85.0 2007
Poland 1506620 730880 49.0 93.0 85.0 68.0 2007
Portugal 305270 114170 37.0 93.0 89.0 53.0 2007
Romania 3859040 1042570 27.0 83.0 78.0 59.0 2007
Slovenia 74650 41300 55.0 92.0 85.0 74.0 2007
Slovakia 24460 4260 17.0 96.0 95.0 76.0 2007
Finland 63870 42630 67.0 97.0 89.0 90.0 2007
Sweden 71090 29050 41.0 94.0 84.0 72.0 2007
United Kingdom 186660 94640 51.0 96.0 82.0 75.0 2007

Determining the optimal size of the sample Top

Sampling fractions vary from cell to cell. In some Member States, the Liaison Agencies have sufficient data on the variability of farms within the field of observation to compute optimal sampling fractions. In other cases, this is not possible and sampling fractions are set according to the number of farms in the cell. After the selection plan is drawn up, farms can shift from one cell to another if there is a change in their economic size or type of farming. This and other similar factors influence the sampling fraction as described below.

The extent to which the sample is random Top

Ideally, farms are selected at random from the field of observation. However, various factors prevent full randomisation:

  1. Availability of farm accounts. To complete the European Union FADN Farm Return, a suitable set of farm accounts (or similar financial information such as receipts, invoices, etc.) must be readily available. Some farmers do not have the necessary information at hand, and in these instances it is impractical to attempt to complete the Farm Return. In some countries, the Liaison Agencies assist farmers to keep accounts if these would not otherwise be kept.

    Overall, the number of farmers keeping accounts is gradually increasing.

  2. Voluntary participation. The participation of farmers is on a voluntary basis. Some of those farms initially selected for the sample may not want to participate. In this case, the farm will be replaced by drawing another farm from the same cell in the field of observation.

As a result; the sample is; effectively, drawn at random from the subset of farms within the field of observation which fulfil the above two conditions.

Selection plans Top

Before the beginning of each accounting period, Liaison Agencies are obliged to draw up a selection plan in accordance with Commission Regulation (EU) No 1291/2009 of 18 December 2009 and subsequent amendments. A variety of selection procedures are used in Member States. During implementation of the selection plan several problems can occur, for example there are not enough farmers who are willing to participate from particular cells and that the actual sample may fall short of the intended size and distribution.

The size of the FADN sample Top

The reasons why in practice the intended sample size may not be attained

There are several reasons why the intended sample size may not be attained or, indeed, may be surpassed. For example, it may be difficult to find sufficient farmers in a particular cell who are both willing to participate and who have the necessary information. Another explanation may be that a participating farmer may give up farming before the completion of the accounting year. A further reason may be that the European Union FADN Farm Return is incorrectly completed and unable to be corrected, thus failing at the control stage. (See Data Quality Chapter).

Actual sample size in recent years

The FADN sample size and average weights of a sample farm differ between Member States, as shown below.

Accounting year :      FSS : 2010      SO : 2007
Country Actual sample size Number of farms represented
in the field of observation
Average weight
of a sample farm
Belgium 1201 30620 25
Bulgaria 2298 115277 50
Czech Republic 1429 14820 10
Denmark 2055 28917 14
Germany (*) 8988 205877 23
Estonia 661 8012 12
Ireland 1048 103821 99
Greece (*) 3456 332902 96
Spain 8229 514873 63
France 7444 291433 39
Italy 10731 781221 73
Cyprus 432 10220 24
Latvia 1000 21968 22
Lithuania 1061 53397 50
Luxembourg 449 1548 3
Hungary 1919 105337 55
Malta 508 2959 6
Netherlands (*) 1468 51140 35
Austria 2088 93251 45
Poland 11194 727750 65
Portugal 2258 110588 49
Romania 5634 1042281 185
Slovenia 956 40961 43
Slovakia 521 4270 8
Finland 926 39173 42
Sweden 1050 27365 26
United Kingdom 2738 92361 34

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