Farm structure (ef)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Department for Environment Food and Rural Affairs (Defra) Supplementary contacts: Scottish Government (SG) Welsh Government (WG) Department of Agriculture, Environment and Rural Affairs (DAERA-NI) 

Time Dimension: 2016-A0

Data Provider: UK6

Data Flow: FSS_ESQRS_A


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT

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1. Contact Top
1.1. Contact organisation

Department for Environment Food and Rural Affairs (Defra)

Supplementary contacts:

  • Scottish Government (SG)
  • Welsh Government (WG)
  • Department of Agriculture, Environment and Rural Affairs (DAERA-NI) 
1.2. Contact organisation unit
Farm Surveys Team, Farming Statistics unit
1.5. Contact mail address
Foss House, Kings Pool
1-2 Peasholme Green,
York. YO1 7PX.  UK


2. Statistical presentation Top
2.1. Data description
1. Brief history of the national survey 
The main source of agricultural statistics in the UK is the annual June survey of agriculture, which collects detailed information on crops area, grassland areas, livestock populations and labour. The survey has been running since 1866 and is a very stable and reliable source. More recently, separate surveys are conducted in England, Wales, Scotland and Northern Ireland by the administrations in these countries with the results compiled at the UK level. In the  UK, a farmer must register for a holding number if they intend to buy, sell or move livestock, sell crops for human consumption or claim any agricultural subsidies. Each of the administrations in England, Wales, Scotland and Northern Ireland maintains registers of agricultural holdings and receive regular updates from administrative sources (e.g. CAP payments), particularly offices that issue holding numbers, that capture new holdings and changes to contact details for an existing holding number. The annual surveys are conducted as sample surveys other than in those years when a full census is required.

 

2. Legal framework of the national survey 
- the national legal framework In the UK, agricultural data is compiled by the administrations in Scotland, Wales and Northern Ireland and in England, by the UK Government's Department for Environment, Food and Rural Affairs. The relevant legislation for the collection of agricultural information are:

In England, the Agricultural Statistics Act 1979 as amended by the Agriculture (Amendment) Act 1984, provides the power to obtain statistical information relating to agriculture from any owners or occupiers of land used for agriculture.  

In Scotland, the Agriculture Act 1947 provides the Scottish Government with the power to obtain statistical information relating to agriculture from any owners or occupiers of land used for agriculture.

In Wales, the Agricultural Statistics Act 1979 as amended by the Agriculture (Amendment) Act 1984, provides the power to obtain statistical information relating to agriculture from any owners or occupiers of land used for agriculture. The powers enshrined in this Act were devolved to the National Assembly for Wales following the Government of Wales Act 2006.

In Northern Ireland, the Agricultural Statistics (Northern Ireland) Order 2004 provides the Department of Agriculture and Rural Development (Northern Ireland) with the power to obtain agricultural information in relation to any land comprised in an agricultural unit.

- the obligations of the respondents with respect to the survey Respondents are legally required (if selected) to supply data on core areas such as land, crops, livestock and labour.
- the identification, protection and obligations of survey enumerators Not relevant.
2.2. Classification system

[Not requested]

2.3. Coverage - sector

[Not requested]

2.4. Statistical concepts and definitions
List of abbreviations
BPS = Basic Payment Scheme

GAEC = good agricultural and environmental conditions

2.5. Statistical unit
The national definition of the agricultural holding
The national definition of the holding is as according to the EU definition, it is a single unit, both technically and economically, which has a single management  and which undertakes agricultural activities listed in Annex I within the economic territory of the European Union, either as its primary or secondary activity  (along the lines of the Regulation 1166/2008, art 2.a). We considered the following agricultural activities: the growing of non-perennial crops, the growing of perennial crops, plant propagation, animal production, mixed farming. Holdings exclusively maintaining agricultural land in GAEC are included. Support activities to agriculture and post harvest crop activities are excluded if they are undertaken exclusively.
2.6. Statistical population
1. The number of holdings forming the entire universe of agricultural holdings in the country
We only monitor holdings with activity levels above thresholds so we do not know the total number including small holdings.

 

2. The national survey coverage: the thresholds applied in the national survey and the geographical coverage
Different survey thresholds are applied across the four UK devolved agriculture departments.

England use the FSS thresholds (Annex II of Regulation 1166/2008) plus additional records with > 1 ha of hardy nursery stock, any area of mushrooms and holdings with temporarily reduced levels of activity e.g. empty pig/poultry sheds or short term rented out land (land > 5 ha that has been let on a short term basis at the last survey).

Northern Ireland include all active farm businesses with >=1 ha of farmed land, or with any cattle, sheep, goats, pigs, significant poultry or horticultural activity.

Wales include all holdings with a Standard Gross Margin (SGM) >0.

Scotland include all holdings with >=0.5 ha farmed land or have crops (including temporary grass) or have >1 livestock unit or >=1 worker, have deer or >=20 poultry. 

For all the UK, the FSS thresholds are implicitly covered in the national survey definition.

 

3. The number of holdings in the national survey coverage 
218 494

 

4. The survey coverage of the records sent to Eurostat
The records included in the UK FSS population are those with activity levels above the thresholds stated in Annex II of Regulation 1166/2008 (and shown below) plus additional records with >1 ha of hardy nursery stock (B_4_5$ha) or any area of mushrooms (B_6_1$ha). We also include holdings with temporarily reduced levels of activity e.g. empty pig/poultry sheds or short term rented out land (land > 5ha that has been let on a short term basis at the last survey) as we consider these still to be genuine agricultural holdings.

The thresholds mentioned above are as follows:

 

Characteristic Threshold Eurofarm code
Utilised agricultural area Arable land, kitchen gardens, permanent grassland, permanent crops >5 ha A_3_1$ha
Permanent outdoor crops Fruit, berry, citrus and olive plantations, vineyards and nurseries >1 ha sum(B_4_1$ha, B_4_2$ha, B_4_3$ha, B_4_4$ha, B_4_5$ha)
Outdoor intensive production Tobacco >0.5 ha B_1_6_1$ha
Hops >0.5 ha B_1_6_2$ha
Cotton >0.5 ha B_1_6_3$ha
Fresh vegetables, melons and strawberries, which are outdoors or under low (not accessible) protective cover >0.5 ha B_1_7_1$ha
Crops under glass or other

(accessible) protective cover

Fresh vegetables, melons and strawberries >0.1 ha B_1_7_2$ha
Flowers and ornamental plants (excluding nurseries) >0.1 ha B_1_8_2$ha
Bovine animals All >10 Head C_2$heads
Pigs All >50 Head C_4$heads
Breeding sows >10 Head C_4_2$heads
Sheep All >20 Head C_3_1$heads
Goats All >20 Head C_3_2$heads
Poultry All >1 000 Head C_5$heads
Hardy nursery stock All >1 ha B_4_5$heads
Mushrooms All >0 B_6_1$ha
Temporary reduced numbers All temporarily empty pig and poultry at last survey >0  
Short term lets All land has been let on a short term basis at the last survey >5 ha  

Notes:

    • Tobacco, cotton, olive plantations, citrus plantations are NE characteristics.
    • Hops is NS characteristic.

 

For England, the scope of the records sent to Eurostat is the same as the scope of the national survey.

For the rest of the UK, the scope of the records sent to Eurostat is smaller than their national survey (see above in item 2. for national threshold definitions).

 

5. The number of holdings in the population covered by the records transferred to Eurostat
183 919

 

6. Holdings with standard output equal to zero included in the records sent to Eurostat
We have 720 holdings in our population for England which have zero standard output and appear to have no farming activity.

They have areas included in “fallow land” (B_1_12) and permanent grassland and meadow no longer for production purposes (B_3_3) which are all eligible for subsidies, therefore the land is kept in GAEC conditions.

If a holding only has fallow or permanent grassland which is no longer being kept in GAEC conditions, it is removed from our holding register.

 

7. Proofs that the requirements stipulated in art. 3.2 the Regulation 1166/2008 are met in the data transmitted to Eurostat
As we no longer survey holdings below threshold, we cannot quantify this for 2016. However, when we changed to using thresholds in 2010, our analysis showed that we only excluded 0.9% of UAA and 0.4% livestock units. We still monitor all newly registered holdings and where they record levels of activity above thresholds in the administrative sources i.e. Payment Scheme, Cattle Tracing System, Sheep and Goat Inventory, etc, we automatically include them in our structure survey population. Therefore we are confident we are still capturing the majority of farming activity in the UK.

 

8. Proofs that the requirements stipulated in art. 3.3 the Regulation 1166/2008 are met in the data transmitted to Eurostat
For all the UK, the FSS thresholds are implicitly covered in the national survey definition.
2.7. Reference area
Location of the holding. The criteria used to determine the NUTS3 region of the holding
To enable FSS data to be grouped into different geographic areas, such as region or county, every holding must be allocated a grid reference. These are typically held as an Easting and Northing (in metres) that relates to the British National Grid. We convert these into standard latitude/longitude for transmission to Eurostat in the FSS dataset. To maximise existing departmental data and improve consistency, we use the following data in this order of preference:

1. Firstly, where the holding has returned a Single Payment Scheme (SPS) subsidy claim, we use the grid reference provided on SPS. This relates to the grid reference of the land parcels covered by the claim.

2. If no grid reference can be found, we use grid references provided on the Cattle Tracing System (CTS). This relates to the location of the cattle.

3. For the very small number of holdings where no grid reference can be found, the postcode of the farm address is used to estimate a grid reference.

Whilst we have a location for every holding, caution needs to be exercised when using them. Ultimately they are our best point estimate for the centre of a spatial entity which can often cover a large land area. In the UK around 80% of holdings are smaller than 100 ha (1 km2) but there are almost 3 500 whose area is at least 500 ha (and this includes just over 1 000 farms whose area exceeds 1 000 ha or 10 km 2). These estimates provide a very useful aid to interpretation but ultimately should be considered as an indicative location and not a precise one.

We compare the point estimates described above to national mapped shapefiles (produced by the Office for National Statistics) which outline where the regional boundaries lie. Where the holding point estimate falls within a NUTS3 boundary, we assign the whole holding to that region.
2.8. Coverage - Time
Reference periods/dates of all main groups of characteristics (both included in the EU Regulation 1166/2008 and surveyed only for national purposes)
In the UK the majority of the data was collected on the survey form that arrived with the farmer on 1 June so most of the data collected from it was representative of the period July 2015 to June 2016 (or the 2015/2016 crop year). 

Exceptions are:

(a) livestock items which were obtained from the bovine register as at 1 June 2016, and 

(b) rural development payments, which were approved between 1 June 2013 and 1 June 2016 and sourced from administrative data. 

2.9. Base period

[Not requested]


3. Statistical processing Top
1.Survey process and timetable
The United Kingdom has a longstanding and well established annual June survey of agriculture that collects information on land use, crops, livestock and labour for national policy and evidence requirements. To meet the requirements of the 2016 FSS, additional questions were included in this survey. Administrative data are used where possible so to minimise the burden on survey respondents. In the UK, separate surveys are conducted in England, Wales, Scotland and Northern Ireland. The statistical teams responsible for these surveys coordinate their work so to meet the requirements of the FSS.

Each of the statistical teams have their own well established timetable and organisation for the survey. Typically, the process is

  • Develop the paper questionnaire and online data collection system (where application). Finalise the questionnaire. Test online data collection system. Online system goes live. (April 2015 - December 2015)
  • Determine sample strategy and finalise numbers in selection. Complete selection. (February 2016 - April 2016)
  • Complete validation specification and coding. (February 2016 - April 2016)
  • Survey forms and email invitations to complete survey are sent to respondents. (May 2016)
  • Reminders are sent (email and paper). (June 2016 - August 2016)
  • Data received is validated, queried and corrected. (June 2016 - October 2016)
  • Online collection and paper survey is closed. (September 2016 - October 2016)
  • Administrative data is obtained, principally cattle data from the bovine register. (August 2016 - December 2016)
  • Statistical analysis is carried out. (August 2016 - December 2016)
  • Early results for England, Wales, Scotland and Northern Ireland are compiled and published. This is not a FSS publication but a routine statistics release of the June survey of agriculture results. (August 2016 - October 2016)
  • Final results for England, Wales, Scotland and Northern Ireland are compiled and published. This is not a FSS publication but a routine statistics release of the June survey of agriculture results. (September 2016 - December 2016)
  • Further work is carried out to prepare the FSS dataset for transmission to Eurostat. (January 2017 - December 2017)

 

2. The bodies involved and the share of responsibilities among bodies
Within the UK, agriculture is a devolved matter, which means that the Scottish and Welsh Governments and the Northern Ireland Assembly have responsibility for agricultural policy and data provision in Scotland, Wales and Northern Ireland. Defra is responsible for compiling and supplying the UK dataset but the devoved administrations  are fully responsible for the data collection within their respective countries.

These domestic arrangements mean that agricultural policy, data collection methods and data availability can vary slightly between the four countries. As data supplier, Defra tries to harmonise the data collection methodologies where possible but ultimately, as long as they supply the data specified in Regulation (EC) No 1166/2008, Defra has limited powers to influence the methodologies chosen in these countries.

Each administration has its own statistical staff who are responsible for cleaning and analysing their data. A lead statistical analyst in each administration undertakes the bulk of the statistical work with support from additional analysts and a survey support team. When the data is returned to the statistical teams, they run a series of validation checks on the data and the survey support teams follow up these with phone calls where appropriate to ensure data quality.

 

3. Serious deviations from the established timetable (if any)
No serious deviations.
3.1. Source data
1. Source of data
The survey collected data from sampled farms on (non-organic) land use and livestock (except cattle and in Northern Ireland poultry and pigs), farm labour, diversification and other gainful activities. Only in England, for some characteristics such as crops and livestock, we produce a full holding level imputed dataset using response data to estimate for the non-sampled (and non-responding) holdings.
The survey collected data from administrative sources on organic farming, cattle, rural development payments and common land.   In Northern Ireland, data on poultry and pigs were also derived from administrative sources and in Scotland, most data on crops and land was collected via an administrative database.

The following characteristics have been collected only from the sample: labour force, other gainful activities, irrigation, soil management, rural development, legal type, A_3_3_1 (more than 50% of production self-consumed by the holder) and A_3_3_2 (more than 50% of sales are direct sales).

 

2. (Sampling) frame
The source of the frame are farm registers compiled from administrative sources.

A list frame approach is used in each country, i.e. a list of agricultural holdings.

In the UK any farmer will need to register a holding number for the holding in question if they intend to buy, sell or move livestock, sell crops for human consumption or claim any agricultural subsidies thus there is generally a very strong incentive to register. All of the statistical teams in the UK receive regular updates to their register that capture new holdings (and changes to contact details for an existing holding number). These registers are maintained continuously as they are used for a number of farm surveys.  

 

3. Sampling design
3.1 The sampling design
The sampling design is one-stage stratified random sample of holdings.

We select one sample but for England only, we apply different extrapolation factors depending on the characteristics:

- For some characteristics such as crops and livestock, we produce a full holding level imputed dataset using response data to estimate for the non-sampled and non-responding holdings. Thus we obtain land and livestock characteristics for all holdings in England. These characteristics have an extrapolation factor of 1 (and we use extrapolation factor A09).

- For characteristics where we are unable to impute, we use response data only and use the extrapolation factor A10 to enable grossing up to national totals.

3.2 The stratification variables
Separate samples are carried out for each country. Holdings are stratified by farm size and farm type. NUTS1 region is not used in the sample design as good regional coverage is achieved using farm size and farm type.
3.3 The full coverage strata
There are full coverage strata. Where A09A$ID=999 these are all UK common land records sourced from administrative data (see item 8.1-4.1 for more details on common land). There are other strata where holdings were selected for surveying as per the methods described above and, by chance, these holdings were all surveyed and all responded.
3.4 The method for the determination of the overall sample size
The sample size was determined by working backwards from the confidence intervals provided by Eurostat in Annex IV (precision requirements) of Regulation 1166/2008 and inflating this based on our estimated response rate.
3.5 The method for the allocation of the overall sample size
Holdings are divided into groups (strata) with higher sampling rates being used in the strata with large farms size.  

Separate strata with higher sampling rates for horticultural holdings are used to ensure adequate precision.

Neyman Allocation was used to determine sample size allocation between strata. The allocation was calculated for all land and livestock variables separately using June 2005 data, then the mean allocation for each strata was used in each stratum. 

3.6 Sampling across time
A new sample is drawn each time.
3.7 The software tool used in the sample selection
The sample is selected with a computer package (a bespoke Farm Survey System) that randomly selects the required number of holdings for each stratum.
3.8 Other relevant information, if any
Not available.

 

4. Use of administrative data sources
4.1 Name, time reference and updating
Organic data: For holdings within Great Britain, the organic data items within FSS come from data provided by the various organic certification bodies responsible for the monitoring of all organic operators. This data is provided to Defra on an annual basis and comprises land-use areas and livestock numbers. The data is provided to Defra to allow us to make the required annual organics return to Eurostat.  Data is provided in arrears at the end of the following January.  The data is gathered via annual inspections carried out by the certification bodies.  As these inspections are carried out throughout the year this does mean that the data does not relate to a specific point in time but this method of data collection is historic and has been fit for purpose for the provision of the annual Eurostat organic return. In Northern Ireland, a register of all organic producers is held by a specialist unit at Greenmount Campus (College of Agriculture, Food and Rural Enterprise).

Rural development payments: There are a large number of clauses within the rural development payments regulation and it is up to member states to choose how to divide up their pot and which parts of the regulation they will fund.  Within the UK each devolved administration has opted to fund slightly different parts of the regulation, but overall the only area where there are significant numbers of beneficiaries is for agri-environment scheme payments. The exact source of the administrative data varies from country to country but basically it comes from the unit who makes the payments.  In some cases this is a single central source (as occurs in Wales and NI) or a number of sources (England and Scotland).

Cattle: In Great Britain, the headcounts of the numbers of cattle were obtained from the Cattle Tracing System (CTS). In Northern Ireland, the Animal and Public Health Administration (APHIS) system, which is also an EU audited cattle tracing system, is used. These provide a continuous record of the births, deaths and all movements of individual cattle in Great Britain thus it is possible to obtain a snapshot of all cattle on any given date. This date can be chosen to coincide with the reference date of the FSS.

Crop areas: In Scotland the Single Application Form (SAF) that farmers complete annually to claim farm subsidies contains detailed crop information. Any holdings that were in-scope for FSS2016 who submitted a Single Farm Payment (SFP) claim had their land data from the SAF dataset automatically integrated into the 2016 FSS dataset. 

Poultry and pigs: In Northern Ireland, data on poultry and pigs were derived from administrative sources, the Northern Ireland Annual Inventory of Pigs and the Northern Ireland Bird Register Update.

4.2 Organisational setting on the use of administrative sources
No rights of access to administrative data are defined in legislation. Administrative data may be shared by agreement subject to the provisions of the Data Protection Act 1998. We are unable to influence the design or revisions of the administrative sources.
4.3 The purpose of the use of administrative sources - link to the file
Please access the information in the file at the link: (link available as soon as possible)

 

4.4 Quality assessment of the administrative sources
  Method  Shortcoming detected Measure taken
- coherence of the reporting unit (holding) The same definition of holdings are used for these datasets.    
- coherence of definitions of characteristics Cattle: The Cattle Tracing System provides information on cattle age, sex and breed and so we are able to map the data to the categories required by the FSS.

When the UK was considering switching to an administrative system in 2005, we opted to collect data by both methods in 2006 to check the feasibility of switching methods. A considerable amount of background analysis was undertaken at the time1. The change of data source did introduce a step change into the series by identifying a higher number of cattle (6% or 360 thousand more in England in June 2006), but the trends were very similar to those of the June Survey.

 

 

 

 

 
- coverage:      
  over-coverage Organic data:When compiling the final organic data for FSS, the organic crop and livestock data is checked against total organic and inorganic crop and livestock data that was collected as part of the main FSS data collection.  This is done at the holding level. Organic data: For organic data, not all of the organic data can be matched to a FSS record and some of the organic data is on holdings that are below the threshold for inclusion in FSS2. Organic data: In such cases, the data are amended to prevent this issue.   Thus the organic data supplied in the FSS might differ from that provided in the annual returns made to Eurostat for some variables.
  under-coverage Cattle Tracing System: The registration of cattle on CTS is compulsory by law and so the coverage is likely to be almost universal and the acceptance of animals at slaughterhouses and livestock markets requires the appropriate CTS documentation. Thus the administrative data are believed to provide more reliable information than surveys – especially as we now rarely conduct a full census. Additional confidence in the reliability of tracing data is provided by the mechanisms in place for cross checking and correcting anomalies. Cattle: The level of unreported cattle movements is likely to be minimal.  
  misclassification   Cattle: For cattle data, the register does not make a distinction between dairy cows and beef. Cattle: We therefore assign the main herds using females aged at least two years with offspring and assign them as dairy or beef on the basis of their breed3.
  multiple listings   Rural development payments: An agreement might span across more than one holding.  Consider a situation where a father and a son each have a holding (with its own identification number) on adjacent parcels of land.  Suppose that if they each submit a claim on their own and the son has an excess of points4 but the father does not have enough points, only the son would receive payments on his hectarage.  If however they complete one application across the two holdings they can achieve enough points to receive a payment based on the combined hectarage without needing to undertake any additional measures.  In this situation matching the data to the holdings within FSS becomes more difficult.   Bearing in mind the number of holdings (and their total UAA) that have been captured in this way we do not believe that this approach has lead to significant losses of agri-environment recipients. Rural development payments: The dataset does include a main, maximum and minimum CPH reference and an indicator of whether the claim is from an individual or a group.  We can use this additional information to assign agri-environment payments to additional holdings. Of course in situations where there is a complex claim involving more than 3 holdings5 we will not be able to assign a payment marker to all holdings.
- missing data   No missing data.  
- errors in data Crop areas: The overall quality of the majority of the Scottish land data is very high, as the SAF data is under-pinned by cross-compliance and is subject to audit and inspection. There are financial penalties for incorrect SAF submissions, so the farmers have a much greater incentive to supply accurate data than for a survey form.    
- processing errors   No detected shortcomings.  
- comparability   No detected shortcomings.  
- other (if any)   No detected shortcomings.  

1 A report entitled “Request from the UK to Use the Bovine Registers of Great Britain and Northern Ireland in Replacement of Statistical Surveys” is available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/182225/defra-stats-foodfarm-landuselivestock-june-results-BovineRegisters.pdf

2 Largely due to the differing data collection periods.

3 Around 2% of all female cattle do not have an assigned breed or are of dual breed.  These cattle have been allocated to either dairy or beef at the holding level based on the other cattle on the holding or the national split between dairy and beef in that age band if there are no other cattle on the holding.

4 The current schemes rely on farmers undertaking a number of specific practices on their farm.  Each of these practices (or options) earns a number of points.  Farmers need to achieve a given average number of points per hectare across their area within the scheme.

5 Which we would expect to be a rare scenario.

 

4.5 Management of metadata
Organic data, Cattle data, Rural development payments, Crop area:

When the admin data source was first used, the metadata was seen and examined for consistency with the Regulation 1166/2008. The admin data source is responsible for storing and recording the metadata but the metadata can be requested by Defra when needed.

4.6 Reporting units and matching procedures
The same definition of holdings are used for these datasets.

Organic data from the certification bodies is supplied at individual operator level.  The certification bodies provide name and address details for all of their organic operators, and a County Parish Holding (CPH) number is also requested. A valid CPH is the best way of linking this organic data to the rest of the FSS dataset.
There are incomplete or incorrect County Parish Holding (CPH) numbers. Incomplete or incorrect CPH numbers are checked manually to see if they can be amended to valid and complete, CPH numbers6.  When this approach fails, attempts are made to match the contact details for the organic operators against names, addresses and telephone numbers on our register.   Where a match can be found this then yields a valid CPH number.
In Northern Ireland, a register of all organic producers is held by a specialist unit at Greenmount Campus (College of Agriculture, Food and Rural Enterprise). This consists of the name and address – including postcode – of the participants, coupled with the area currently considered organic or under conversion plus the types of enterprises conducted there. A sub-list of poultry producers is also held where the actual area of production may be registered as zero. This data was merged with the FSS dataset using both names and address as key variables.

Cattle:
Where a holding appears in both CTS and our register it is a straightforward task of capturing this data in the FSS dataset.  Analysis of data from the CTS and the 2015 June survey found that these holdings account for 97% of the total number of cattle.
There are a number of holdings where the same farmer will choose to use a different identifier for their cattle movements to the one they use on our survey register.
In these cases we can use name and address matching to assign the cattle data to the correct holding but there remains a small number of cattle on holdings which we cannot assign to a holding in our database (analysis of data from the CTS and the 2015 June survey found that this accounts for approximately 3% of the total number of cattle).  In these cases, these additional cattle are smeared across the other holdings with the appropriate cattle type in the same county as the unidentified holding.  This ensures that the national and local cattle estimates are correct in publications.

Rural development payments:
In the case of the agri-environment data, the only recipients are farmers and the data systems hosting the agri-environment payments data, for example the Natural England GenRep system, includes a country parish holding (CPH) reference number and sometimes additional identifiers like a single business identifier (SBI) and Business Reference Number (BRN). These numbers are unique and allow us to link the data directly to our FSS dataset.  Where a holding has an agri-environment payment approved between 1 June 2013 and 1 June 2016 the dataset can be amended to ‘Y’ indicating yes for the appropriate variable. Determining whether these payments are organic or not is straightforward as all organic payments are made through an organic scheme and not the standard agri-environment scheme.

The slight problem with agri-environment schemes is that a farmer need not (or possibly cannot) enter their entire farm into the scheme under one agreement.  The current generation of agri-environment agreements in the UK tend to run for 5 or 10 years.  When the latest generation of schemes were introduced a number of farmers had land within “classic schemes7” and could not therefore include all of their land within these new schemes otherwise there would be issues of double funding.  Such farmers would make a claim under the new scheme for land that was not covered by any existing schemes and then once their classic agreements come to an end make a second application.  Thus there can be situations where a given holding has a number of different agri-environment agreements logged within the database.  

For the remaining measures, the data are downloaded from the systems of the appropriate payment body.  For example, in England the data are downloaded from the CMEF on-line system8.  On this English system a registered user can download a list of all of the projects funded under a given rural development measure between point X and Y – in our case 1 June 2013 and 1 June 2016.  The slight problem with this system is that it does not include the CPH reference9. The data was matched to our farm register on the basis of names, addresses and postcodes.  Whilst this matching was quite a manual process it was possible because of the small number of projects claimed upon over the reference period.  The devolved administrations used a similar approach to England although often they had the benefit of a CPH or business identifier to aid the matching and weed out the non-agricultural claimants.

Crop area:
In Scotland, any holdings that were in-scope for FSS2016 who submitted a Single Farm Payment (SFP) claim had their land data from the SAF dataset automatically integrated into the 2016 FSS dataset. These farmers could then receive a simplified survey form.  

6 CPH numbers are of the form cc/ppp/hhhh and it is common for leading zeros on the parish or holding part to be omitted.

7 These are the suite of older schemes, like Countryside Stewardship, that have been replaced by the current generation of Environmental Stewardship Schemes.

8 A system for monitoring rural development programme projects.

9 The reason is that some of the recipients of funding under options such as the encouragement of tourism do not actually need to be farmers.

4.7 Difficulties using additional administrative sources not currently used
Nothing to report.
3.2. Frequency of data collection
Frequency of data collection
Annual.
3.3. Data collection
1. Data collection modes
Data collection varies slightly between each of the four countries in accordance with what administrative systems they have access to.  In general terms, the organic data fields, cattle information, rural development payments and common land data are all collected from administrative systems. For all other items on the main FSS items most of data is collected via a postal survey10.

In England farmers were also offered the chance to complete the survey online.  These farmers received an email inviting them to take part instead of a survey form11.  The farmers were then able to log into the website and enter their data.  The system uses shaping questions to ensure that the farmer only see questions relevant to them. Links to the online system are included on the paper form and reminder cards so even farmers who received a paper survey form could opt to log in and complete the form online.  Similarly farmers who received the email invite but did not want to complete an online return could contact us and request a paper form.  


10 Scotland has a significant quantity of land-use data available from administrative systems.

11 The numbers targeted in this way were limited by the number of holdings for which we had captured an email address from previous correspondence.

 

2. Data entry modes
These are professionally printed and dispatched. All of the forms are returned to a professional data capture company who either key or scan the data.  Each of the four countries uses their own service supplier who then returns the electronic data to the statistics teams.

 

3. Measures taken to increase response rates
Partially completed forms were treated in the same manner as inconsistent / incorrect forms.  They were placed under query and finalised by telephone contact with the farmer.  Repeat calls were made if we were not able to contact the farmer initially but of course some gaps remained that we were unable to fill in this manner and ended up being imputed.   

The UK does not use face to face interviews for any component of the FSS due to the costs for government and the burden placed upon the farmer involved in collecting such data.  Although a number of respondents answered full survey questions over the telephone we would not formally constitute this as an “interview”.

One of our key tools to improve response rates is through sending reminders to farmers.  The exact nature and timing of these varies slightly between the four countries but the overall process is similar.  For the main survey form there were typically two reminders sent in the form of a reminder card/email.  The first is sent two or three weeks after the survey day and the second in mid July.  In some instances these were followed up with a third reminder.  In Northern Ireland, these included a duplicate survey form and were targeted towards larger holdings and/or minority sectors (e.g., horticulture) to maximise their impact.  Wales targeted larger non-responders through telephone calls instead of a third reminder whilst Scotland did not need one because of the quantity of data that they can access through administrative systems.

Larger farms that are part of composite units (primarily pig and poultry farms) are issued with separate special survey forms to ensure that maximum coverage is achieved.  This is a routine operational procedure that we run each year for our regular June Survey and it generates good data.  The strategy used is to send the forms to the head office for the company rather than the individual farms.  They then collate the information and send it back to us.  Some of the larger farming businesses, particularly those involved in horticulture, have multiple holding numbers and often a significant number of staff who work across all of their units.  This can make it hard for them to complete the labour data for a 12 month period.  To encourage responses we allow them to record all of their farm labour data under a single holding number and not complete the labour section on their other forms.  The farm then indicates to us all of the holdings within their group and on which one they have recorded their labour data.  We then use our point in time estimates of worker numbers and the activity on the holding to apportion these workers between the holdings that the farmers have not supplied data for.      

Our mailing lists and contact details are derived from the live agricultural holdings database in each of the four countries.  These are updated on a daily basis.12 All staff, and in particular those recruited on a temporary basis specifically to deal with the survey receive a significant amount of training in advance of the survey.  This includes techniques on how to obtain information from difficult farmers and how they can use other information that we already hold about the farm to resolve issues with the supplied data.


12 The updates come from both other government registers / administrative systems, direct contact from the farmer (either comments on our survey forms or telephone calls) and undelivered mail that is returned to us.

 

4. Monitoring of response and non-response
1 Number of holdings in the survey frame plus possible (new) holdings added afterwards

In case of a census 1=3+4+5

185 867 (excluding common land units)
2 Number of holdings in the gross sample plus possible (new) holdings added to the sample

Only for sample survey, in which case 2=3+4+5

127 544 (excluding common land units)
3 Number of ineligible holdings 2 043 (including 42 ineligible for national purposes and excluding common land units)
3.1 Number of ineligible holdings with ceased activities

This item is a subset of 3.

 0
4 Number of holdings with unknown eligibility status

4>4.1+4.2

 0
4.1 Number of holdings with unknown eligibility status – re-weighted
4.2 Number of holdings with unknown eligibility status – imputed
5 Number of eligible holdings

5=5.1+5.2

 125 501 (excluding common land units)
5.1 Number of eligible non-responding holdings

5.1>=5.1.1+5.1.2

 58 403 (excluding common land units)
5.1.1 Number of eligible non-responding holdings – re-weighted 36 540 (excluding common land units)
5.1.2 Number of eligible non-responding holdings – imputed

21 863 (England only and excluding common land units -
we also imputed an additional 50 314 holdings in England which were not included in the gross sample)

5.2 Number of eligible responding holdings 67 098 (excluding common land units)
6 Number of the records in the dataset 

6=5.2+5.1.2+4.2

139 275 (excluding common land units)

 

5. Questionnaire(s) - in annex
See annexes.


Annexes:
3.3-5 Questionnaire_England_2016
3.3-5 Questionnaire_NorthernIreland_2016
3.3-5 Questionnaire_NorthernIreland_2016_2
3.3-5 Questionnaire_Scotland_2016
3.3-5 Questionnaire_Scotland_2016_2
3.3-5 Questionnaire_Wales_2016
3.4. Data validation
Data validation
For the data collected from the farmer, survey forms were professionally printed, dispatched and electronically captured.  Once the data has been returned to the institutions a number of validation checks are carried out.  Our survey support teams work to correct issues with the data by contacting farmers and/or using additional data that we store about the farm collected from other sources.

When loaded onto their systems the statisticians run a series of validation checks against this incoming data.  These will be things like checking the components sum to the total and subtotals, comparing the data against the return from the previous year to flag up large changes and highlighting inconsistent responses in categorical questions.  

All of these basic checks were run whilst the survey was still operational, additional checks were subsequently run.

A validation database was built that mimics all of the Eurostat rules and this highlighted other records needing checking, mainly comparing the organic administrative data against the conventional land/livestock data collected in the FSS.      

Once a complete dataset was achieved with suitable source data for every FSS item the data were transferred from our data collection format to that required for FSS.  In many cases this was converting numeric data to the Eurostat categorical variables or summing data items together.

The tools used for data validation were IT system, charts for erroneous values at analysis stage, calculated influential statistics to assess influence of individual data points.

There is validation built into the online data collection system which prevents farmers from moving on to the next section if the response they have given is not appropriate (for example they have specified a greater area of crops than their UAA). The validation is carried out separately by each UK country, then the overall validation is carried out at the UK level by Defra.

3.5. Data compilation
Methodology for determination of weights (extrapolation factors)
1. Design weights
All of the holdings that responded to the survey have an extrapolation factor that is a basic survey weight. Thus each holding in the dataset received a weight based on the inverse sampling fraction for the stratum the holding was in. This approach ensures that when the weights are summed for the records they sum to the population total.
2. Adjustment of weights for non-response
For land-use and livestock the imputation is done on an annual basis using a ratio raising process.  The data are stratified according to farm size.  For non-responders, farm size is based on the last recorded response to DEFRA’s annual June survey.  For all data items, a strata level ratio is derived between the 2016 responses for the given item and the base data.  The base data is usually the 2015 (actual or imputed) response, but equally might be something else that has a good correlation with the variable to be imputed in the case of a new item.  This ratio is then multiplied by the base value for all holdings that require an imputed value in that strata.  The process then moves on through the strata and items in sequence.
3. Adjustment of weights to external data sources
No.
4. Any other applied adjustment of weights
The data were not post stratified for analytical purposes, which in some cases, notably in Wales, can lead to some large survey weights due to low numbers of responses in these strata.
3.6. Adjustment

[Not requested]


4. Quality management Top
4.1. Quality assurance

[Not requested]

4.2. Quality management - assessment

[Not requested]


5. Relevance Top
5.1. Relevance - User Needs
Main groups of characteristics surveyed only for national purposes 
The United Kingdom has farms that cover the full range of farm type and sizes. As a result, most items are collected along with a number of additional items that are purely for national interest. The UK does survey a number of items for domestic purposes: 
  • Estimates for farm labour as at 1 June (not those who carried out farm work on the holding during the 12 months ending on the reference day of the survey) are collected each year.
  • In the livestock categories there are a number of instances where we collect more detail than required by the Regulation. For example, domestically sheep are quite important and therefore we have additional data categories such as lambs and three different categories for ewes.
  • In the vegetable and soft fruit categories, we collect more detail than required by the Regulation.  For example, we collect raspberries, blackcurrants and other small fruit as three separate categories when the regulation only calls for “berry species”.

These characteristics are requested by the UK Government to meet its need for evidence to support the making of Government policy on agriculture.

5.2. Relevance - User Satisfaction

[Not requested]

5.3. Completeness
Non-existent (NE) and non-significant (NS) characteristics - link to the file. Characteristics possibly not collected for other reasons
Please find the information at the link: (link available as soon as possible)
5.3.1. Data completeness - rate

[Not requested]


6. Accuracy and reliability Top
6.1. Accuracy - overall
Main sources of error
As with all sample surveys, the main limitation on the survey is that it is subject to sampling errors. There is also a degree of non-response which may potentially cause a bias in the results. The bias is unquantifiable but the response rate is reasonably high and how the response differs between farm types and size is monitored to try and avoid this possibility. The data are also subject to the vagaries of farmers’ interpretation of the categories on the form. The paper and online forms are made as clear as possible, including notes on how to complete the sections, to try and minimise any confusion. A data validation exercise to clean the data prior to processing is carried out to keep the data as accurate as possible.

For the main FSS items probably the biggest error results from non-response. 

6.2. Sampling error
Method used for estimation of relative standard errors (RSEs)
See attached.


Annexes:
6.2 Method_for_RSE_UK_2016
6.2.1. Sampling error - indicators

1. Relative standard errors (RSEs) - in annex

  

2. Reasons for possible cases where precision requirements are applicable and estimated RSEs are above the thresholds
See attached. The problems in achieving the desired level of accuracy for breeding sows, other pigs and poultry are due to the volatile nature of the data. Rapid turnover of pigs and birds means point in time estimates are not ideal. The pig and poultry industries are both dominated by a small number of very large units. These can have a strong influence on the overall results - particularly at lower geographical levels.


Annexes:
6.2.1-1 Relative standard errors_UK_2016
6.3. Non-sampling error

See below

6.3.1. Coverage error
1. Under-coverage errors
Under-coverage errors are likely to be minimal for most farm characteristics. Whilst it is not compulsory for farmers to register a holding number, a farmer will need one to conduct much of their agricultural business, for example buying, selling or moving livestock and claiming agricultural subsidies. We are therefore aware of most farms. 

Coverage of the poultry sector is difficult because the rapid turnover on the industry and its dominance by a few very large companies. The survey questions are designed to be a snapshot of the industry at 1 June. It is possible that on the day of the survey a number of producers may have no birds on their farm and be disinfecting their premises. To try and help with coverage, data is collected directly from the head office of the larger companies in a “special poultry exercise”.

  

2. Over-coverage errors
As the farm register is kept up to date, we only survey farms with activity above threshold levels. We only receive a small number of ineligible, for national purposes, responses (42 in 2016). In addition to this there were 2001 holdings which did not meet the Eurostat thresholds and so also classified as ineligible. Ineligible holdings are removed from our population before the final dataset is created. They are therefore not part of the raising factors and the weights are produced after the removal of the ineligible holdings.
2.1 Multiple listings 
Duplicates can occur where the same land parcel has been assigned two holding identification numbers either with the same farmer or different farmers in the case of land that has been subject to short term rental agreements. Where we identify such units in the survey, we contact the farmer to decide which to remove. The survey weights are calculated at the end of the survey so are only based on the eligible responses with duplicates removed.

 

3. Misclassification errors
Very low extent. The annual surveys cover a substantial proportion of holdings so information is relatively up to date. We kept the original strata as built in the sampling stage.

 

4. Contact errors
Comparisons to other departmental registers ensure contact details are accurate.

 

5. Other relevant information, if any
Not available.
6.3.1.1. Over-coverage - rate
Over-coverage - rate
1.5%
6.3.1.2. Common units - proportion

[Not requested]

6.3.2. Measurement error
Characteristics that caused high measurement errors
In terms of crop areas and livestock numbers measurement errors are negligible.  The larger and more important producers are familiar with our surveys – a number of them are sampled every year for the June Survey.  This familiarity means that their forms are filled in with a good degree of accuracy. It tends to be the smaller farms, whose occupiers are less familiar of the requirements of our surveys, that produce more errors in our validation. There is a well-established set of validation rules for these items that make use of past data to detect errors. The survey support team can then contact the farmer to resolve issues.  In Scotland the land area data now comes from subsidy claims and is therefore subject to inspection leading to increases in data quality.  Similarly a significant portion of the English data is now filled in by online self-completion and the system will not allow the farmer to move to the next section if the data they supply is inconsistent.

Our validation rate of checks is around 30% on land and livestock characteristics and around 50% on labour characteristics as farmers find it difficult to understand the complex requirements. The main source of data error is farmers incorrectly completing the questionnaire. We carry out validation checks for these.

A number of data items were collected from administrative data rather than the farmer. Whilst this improves the coverage there are some issues in matching this data to the FSS register and fitting the data to the FSS categories.

6.3.3. Non response error
1. Unit non-response: reasons, analysis and treatment
Non-response is considered to be forms that are not returned at all. We are not certain of the reasons for non-response but some farmers have provided feedback that the detail and length of the survey form is offputting, that the survey falls at a busy time of year for farmers as well as the deadline for BPS claims. Response rates this year were consistent with previous years and therefore we believe there are no additional factors in the non-response to this year's survey.

Thus far none of the UK administrations have pursued legal action in relation to non-response on FSS because legal advice indicated that a successful prosecution would be unlikely and it was considered that such actions are more likely to lower response to subsequent surveys rather than improve them and would lead to a very significant increase in the costs of the survey.  The administrations would prefer to work together with farmers and farming industry to improve survey response. Non-responses are imputed into the results.

For the main FSS items probably the biggest error results from non-response. Non-response affects all farm types and whilst this varies slightly with farm type, UK level records of non-response by farm type are not compiled.

 

2. Item non-response: characteristics, reasons and treatment
There were a number of farmers who were not prepared to complete the questions on farm labour.  They returned a form with completed land use and livestock data but found the level of detail required for farm labour to be an excessive burden. As well as the detail some found certain questions intrusive (such as age information) and struggled to understand the reasons why the information was required – particularly the other gainful activity information.  The item non-response was corrected for by contacting the farmer or by estimating unit values based on auxiliary information.
6.3.3.1. Unit non-response - rate
Unit non-response - rate
Non-response rate is 46.5%.
6.3.3.2. Item non-response - rate
Item non-response - rate
Of those who should have provided spouse data, 37% provided no spouse data (non-response rates for individual spouse data items ranged from 50% to 52%). Some of this will be down to the principal holder not having a spouse but it is impossible to ascertain where this is the case.
6.3.4. Processing error
1. Imputation methods
Ratios of respondents data applied to non-respondents previous year's data. See item 3.5-2 for more information.

 

2. Other sources of processing errors
Our data scanning and keying is of very high quality so we do not see many errors from data keying.

Any records that are flagged with issues (or are partially complete) are contacted via telephone using our own bespoke Computer Aided Telephone Interview (CATI) technology.

For data items collected from administrative data they are considered to offer complete coverage and the data are used in the supplied form.  The only changes applied to this data are those to map the data to the correct categories or in the case of the organic data to constrain the organic data to the total organic and inorganic data supplied from the survey.

For the surveyed items when the data is returned a series of validation checks are run against the data, for example, checking the components sum to the total and subtotals, comparing the data against the return from the previous year to flag up large changes and highlighting inconsistent responses in categorical questions. Any records that are flagged with issues (or are partially complete) are investigated by our survey support team. They use additional information such as comments farmers have written on the form, data from other surveys/admin data systems to try to resolve these issues – including data from the previous year (base data). Where they cannot use existing data the farmers are contacted via telephone to resolve the issues. Where a common problem arises, global updates can be applied to streamline the process, for example many farmers omit the section totals so we can automatically set the section total to be the sum of the components. In general less information is available to resolve issues with labour and diversification data than the land area and livestock data hence the former group usually require more telephone calls to farmers to clarify. 

Despite our best efforts we do not get responses from every farmer.  In addition, despite our call back strategy not all of the responses are fully complete and correct1. The methods used to complete missing or incorrect sections and deal with non-response changes depending on the data group (labour / diversification and land-use / livestock). For the land-use and livestock categories, there is a well established method of dealing with the non-response and the returned forms that are partially complete or in error following the actions of our survey support team. The data for each holding is broken down into chunks that represent a group of data items such as sheep, grassland, arable crops2. If there was an error within the group which could not be resolved by the survey support team, the data items for that group are imputed. 


1 In some cases we make numerous unsuccessful attempts to contact the farmer or the information that the farmer supplies will not resolve the issue.

2 Note no imputation is required for cattle as these come from the Cattle Tracing System (CTS) administrative system.  The Cattle Tracing System is a bovine register that records births, movements and deaths of cattle.

 

3. Tools used and people/organisations authorised to make corrections
Statistical teams in the administrations for Scotland, Wales and Northern Ireland, and Defra for England data.
6.3.4.1. Imputation - rate
Imputation - rate
36.1% of records were imputed to give the full population for England only, for the land and livestock characteristics. No imputation was required in Scotland, Wales or Northern Ireland as they only supplied response data.
6.3.5. Model assumption error

[Not requested]

6.4. Seasonal adjustment

[Not requested]

6.5. Data revision - policy
Data revision - policy
The UK has a Code of Practice for Official Statistics 13 developed for all Official Statistics, which covers the first release of many of the components of FSS. As part of this Code of Practice, each institution publishing Official Statistics must also publish their revisions policy (see hyperlinks below).

Data revision policy for the 4 institutions producing statistics that form the FSS dataset.


13 http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html
6.6. Data revision - practice
Data revision - practice
So far as the FSS dataset is concerned, it is subject to validation by Eurostat and revisions may be made to the dataset until it is approved by Eurostat. Once the dataset has passed Eurostat validation, we do not intend to make any further revisions unless a significant error is found.  
6.6.1. Data revision - average size

[Not requested]


7. Timeliness and punctuality Top
7.1. Timeliness

See below

7.1.1. Time lag - first result
Time lag - first result
Provisional crop areas and livestock populations for the United Kingdom were published on 13 October 2016, 4.5 months from the last day of the reference period. This is not an FSS publication but a routine annual statistical release for the UK June survey of agriculture.
7.1.2. Time lag - final result
Time lag - final result
Final crop areas, livestock populations and agricultural workforce for the United Kingdom were published on 15 December 2016, 6.5 months from the last day of the reference period. This is not an FSS publication but a routine annual statistical release for the UK June survey of agriculture.
7.2. Punctuality

See below

7.2.1. Punctuality - delivery and publication
Punctuality - delivery and publication
Both provisional and final results were released on pre-announced dates - provisional four months after the survey and final six months after the survey.


8. Coherence and comparability Top
8.1. Comparability - geographical
1. National vs. EU definition of the agricultural holding
None.

 

2.National survey coverage vs. coverage of the records sent to Eurostat
The UK totals from the national surveys will be slightly higher than the totals from the FSS (though not by much in the majority of cases) because Scotland, Wales and Northern Ireland use slightly different thresholds in their national surveys (see section 2.6 Statistical population for full details of these).

 

3. National vs. EU characteristics
Eurofarm manual for data suppliers Farm Structure Survey 2016. Handbook on implementing the FSS definitions was used.

There are no differences between national and EU definitions of characteristics and classifications of characteristics.

1800 hours are taken to be the minimum annual working hours for a full-time employee, equivalent to 225 working days of eight hours each.

 

4. Common land
4.1 Current methodology for collecting information on the common land
The UK methodology for reporting common land is the same as in 2013. Common land information is only available at the regional (NUTS3) level and is reported as 139 special “common land” units. Only 106 of them are included in the final dataset, having utilised agricultural area in 2016. They can be identified using FSS category A_2=6 (Holding is a common land unit). In the UK common land is always permanent grassland. Much of this common land is found in remote upland areas and in many instances the land has at least one special designation that prevents agricultural improvement of the land. Thus UK common land is (almost) exclusively rough grazing and not pastures or meadows. We do not survey the common land as registers are held in England and Scotland of common land areas (in Scotland the common grazing area is used as a reasonable proxy) and in Wales and Northern Ireland, statisticians use data from administrative systems to capture the area of common land upon which subsidy payments were made and this is aggregated to NUTS3 level estimates. The UK common land areas are carried forward as unchanged from 2013 on the basis that no common land has ceased to exist and no new common land has been created.

All the UK common land holdings are tenure classified as common land.

4.2 Possible problems encountered in relation to the collection of information on common land and possible solutions for future FSS surveys
None
4.3 Total area of common land in the reference year
1 195 246 hectares.
4.4 Number of agricultural holdings making use of the common land or Number of (especially created) common land holdings in the reference year
139 common land units. Only 106 of them are included in the final dataset, having utilised agricultural area in 2016.

 

5. Differences across regions within the country
See items 2.6-2 and 3.1-4.1.

 

6. Organic farming. Possible differences between national standards and rules for certification of organic products and the ones set out in Council Regulation No.834/2007
None. The only standards used in the UK, i.e. the official UK standards, are those in EU Regulations.
8.1.1. Asymmetry for mirror flow statistics - coefficient

[Not requested]

8.2. Comparability - over time
1. Possible changes of the definition of the agricultural holding
There have been no changes.

 

2. Possible changes in the coverage of holdings for which records are sent to Eurostat
There have been no changes.

 

3. Changes of definitions and/or reference time and/or measurements of characteristics
There have been no changes.

 

4. Changes over time in the results as compared to previous FSS, which may be attributed to sampling variability
The 2010 FSS was carried out in the form of a census. The 2013 and 2016 surveys were carried out in the form of sample surveys (other than where administrative data was used) and are thus subject to sampling variability.

 

5. Common land
5.1 Possible changes in the decision or in the methodology to collect common land
There have been no changes.
5.2 Change of the total area of common land and of the number of agricultural holdings making use of the common land / number of common land holdings
None.

 

6. Major trends on the main characteristics compared with the previous FSS survey
Main characteristic Current FSS survey Previous FSS survey Difference in % Comments
Number of holdings 183 919 183 699 0%  
Utilised agricultural area (ha) 16 393 799 17 096 166  -4%  
Arable land (ha) 6 027 342 6 268 770  -4%  
Cereals (ha) 3 154 805 3 048 920  4%  
Industrial plants (ha)  622 985 766 130  -19% This decrease has in fact been a gradual decrease from year to year, as shown in our annual June survey published time series. These year on year decreases have also been in line with industry expectations.
Plants harvested green (ha)  1 340 112 1 619 021  -17% This decrease has in fact been a gradual decrease from year to year, as shown in our annual June survey published time series. These year on year decreases have also been in line with industry expectations.
Fallow land (ha)  251 442 236 286 6%   
Permanent grassland (ha) 10 328 553 10 791 518 -4%   
Permanent crops (ha)  37 904 35 514 7%  This increase has in fact been a small change from year to year, as shown in our annual June survey published time series. These year on year changes have also been in line with industry expectations.
Livestock units (LSU)  13 251 820 13 282 320 0%   
Cattle (heads)  9 816 271 9 804 945 0%   
Sheep (heads)  33 133 796 32 352 109 2%   
Goats (heads)  99 820 95 215 5%   
Pigs (heads)  4 544 904 4 824 724 -6%   
Poultry (heads)  164 378 924 155 506 583 6%   
Family labour force (persons) 327 071 321 115 2%   
Family labour force (AWU) 181 613 182 248 0%   
Non family labour force regularly employed (persons) 99 540 110 144 -10%  Although we are not certain we believe this decrease can be explained by an increase in the use of casual labour as farm businesses move towards requiring a more flexible labour force.
Non family labour force regularly employed (AWU) 61 740 73 598 -16%  Although we are not certain we believe this decrease can be explained by an increase in the use of casual labour as farm businesses move towards requiring a more flexible labour force.
8.2.1. Length of comparable time series

[Not requested]

8.3. Coherence - cross domain
1. Coherence at micro level with other data collections
None. Data is not collected in such detail elsewhere.  

 

2. Coherence at macro level with other data collections
Comparisons have been made between FSS results and annual crop and animal statistics and all are consistent. They are very similar to those transmitted in the annual crop and livestock statistics but not identical.

The data compiled for the FSS are not collected elsewhere in a suitable form with sufficient coverage or a large enough sample to permit widespread comparisons. Generally the best method of comparison is against previously compiled data. Land, livestock and point in time estimates for labour are collected annually on 1 June, thus land use and livestock data compiled for FSS 2016 can be compared to data compiled in June 2015 and earlier years to monitor year-on-year changes.

8.4. Coherence - sub annual and annual statistics

[Not requested]

8.5. Coherence - National Accounts

[Not requested]

8.6. Coherence - internal

[Not requested]


9. Accessibility and clarity Top
9.1. Dissemination format - News release

[Not requested]

9.2. Dissemination format - Publications
1. The nature of publications
Provisional crop areas and livestock populations for the United Kingdom were published in October 2016 in the form of a statistical release (PDF) and dataset (XLS). Final crop areas, livestock populations and agricultural workforce for the United Kingdom were published in December 2016 also  in the form of a statistical release (PDF) and dataset (XLS). These are not FSS publications but routine annual statistical releases for the UK June survey of agriculture. Information on data uses and users, other survey results and publications, and methodology are included in the statistical release.

 

2. Date of issuing (actual or planned)
The provisonal release was published on 13 October 2016, the final release was published on 15 December 2016.

 

3. References for on-line publications
All releases, datasets and background information may be found at https://www.gov.uk/government/collections/structure-of-the-agricultural-industry
9.3. Dissemination format - online database
Dissemination format - online database
Results are disseminated as MS Excel spreadsheets at https://www.gov.uk/government/statistical-data-sets/structure-of-the-agricultural-industry-in-england-and-the-uk-at-june
9.3.1. Data tables - consultations
Data tables - consultations
Not known.
9.4. Dissemination format - microdata access
Dissemination format - microdata access
Data collected under the auspices of the Agricultural Statistics Act 1979, the Agriculture Act 1947 and the Agricultural Statistics (Northern Ireland) Order 2004 (where applicable) are protected by these legislation. They are also protected by the Data Protection Act 1998 and by the United Kingdom's Code of Practice for Official Statistics. In general, private information about individual persons (including bodies corporate) compiled in the production of official statistics is confidential and should be used for statistical purposes only. The legislation permits some limited use of micro-data for research purposes under well-defined criteria. This does not permit Eurostat to share micro-data with external users.
9.5. Dissemination format - other

[Not requested]

9.6. Documentation on methodology
1. Available documentation on methodology
No documentation on the methodology of the compilation of FSS dataset per se is published. However, information on data uses and users, other survey results and publications, and methodology of the annual June survey of agriculture are included in the statistical releases described at 9.2- item 1. A methodology document for the annual survey of agriculture and horticulture may be found at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/182206/defra-stats-foodfarm-landuselivestock-june-junemethodology-20120126.pdf

 

2. Main scientific references
None.
9.7. Quality management - documentation
Quality management - documentation
No other documentation on the quality of the FSS dataset is published.
9.7.1. Metadata completeness - rate

[Not requested]

9.7.2. Metadata - consultations

[Not requested]


10. Cost and Burden Top
Co-ordination with other surveys: burden on respondents
Care is taken not to duplicate surveys. Additional questions required by the FSS are incorporated into existing, regular surveys.


11. Confidentiality Top
11.1. Confidentiality - policy
Confidentiality - policy
The legislation contains restrictions on the disclosure of information, which may only be used for statistical purposes and for a limited number of non-statistical purposes. In addition, personal data is processed in accordance with the Data Protection Act 1998.

Confidentiality policy for the four institutions producing statistics that form the FSS dataset:

11.2. Confidentiality - data treatment
Confidentiality - data treatment
Results from all of our surveys are disseminated according to legislation and the United Kingdom's Code of Practice for Official Statistics.  In any tabular publications, all cells where there are less than five contributors are to be suppressed (usually represented by #), although where there are zero contributors this is allowed. If a table contains both holding counts and a variable specific estimate (e.g. wheat area or number of pigs) both values must be suppressed.  Further where tables have subtotals there is a need to suppress an additional record within the same group in the table to prevent users from deriving the suppressed data through simple differencing. 

An additional level of protection is applied if the tables are for spatial scales of NUTS4 or finer. This additional level involves calculating the proportion of the cell total contributed by the highest contributing farm. Where this value exceeds 85%, the cell value is suppressed to protect the identity of this dominant contributor.


12. Comment Top
1. Possible improvements in the future
Not available.

 

2. Other annexes
Not available.


Related metadata Top


Annexes Top